example of analysis in research paper

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

Primary research involves collecting data about a given subject directly from the real world. This section includes information on what primary research is, how to get started, ethics involved with primary research and different types of research you can do. It includes details about interviews, surveys, observations, and analysis.

Analysis is a type of primary research that involves finding and interpreting patterns in data, classifying those patterns, and generalizing the results. It is useful when looking at actions, events, or occurrences in different texts, media, or publications. Analysis can usually be done without considering most of the ethical issues discussed in the overview, as you are not working with people but rather publicly accessible documents. Analysis can be done on new documents or performed on raw data that you yourself have collected.

Here are several examples of analysis:

• Recording commercials on three major television networks and analyzing race and gender within the commercials to discover some conclusion.
• Analyzing the historical trends in public laws by looking at the records at a local courthouse.
• Analyzing topics of discussion in chat rooms for patterns based on gender and age.

Analysis research involves several steps:

• Finding and collecting documents.
• Specifying criteria or patterns that you are looking for.
• Analyzing documents for patterns, noting number of occurrences or other factors.

• Skip to main content
• Skip to ChatBot Assistant
• Academic Writing
• What is a Research Paper?
• Steps in Writing a Research Paper
• Critical Reading and Writing
• Punctuation
• Writing Exercises
• ELL/ESL Resources

Analysis in Research Papers

To analyze means to break a topic or concept down into its parts in order to inspect and understand it, and to restructure those parts in a way that makes sense to you. In an analytical research paper, you do research to become an expert on a topic so that you can restructure and present the parts of the topic from your own perspective.

For example, you could analyze the role of the mother in the ancient Egyptian family. You could break down that topic into its parts--the mother's duties in the family, social status, and expected role in the larger society--and research those parts in order to present your general perspective and conclusion about the mother's role.

Need Assistance?

If you would like assistance with any type of writing assignment, learning coaches are available to assist you. Please contact Academic Support by emailing [email protected].

Questions or feedback about SUNY Empire's Writing Support?

Contact us at [email protected] .

Smart Cookies

They're not just in our classes – they help power our website. Cookies and similar tools allow us to better understand the experience of our visitors. By continuing to use this website, you consent to SUNY Empire State University's usage of cookies and similar technologies in accordance with the university's Privacy Notice and Cookies Policy .

Research Paper Writing: 6. Results / Analysis

• 1. Getting Started
• 2. Abstract
• 3. Introduction
• 4. Literature Review
• 5. Methods / Materials
• 6. Results / Analysis
• 7. Discussion
• 8. Conclusion
• 9. Reference

Writing about the information

There are two sections of a research paper depending on what style is being written. The sections are usually straightforward commentary of exactly what the writer observed and found during the actual research. It is important to include only the important findings, and avoid too much information that can bury the exact meaning of the context.

The results section should aim to narrate the findings without trying to interpret or evaluate, and also provide a direction to the discussion section of the research paper. The results are reported and reveals the analysis. The analysis section is where the writer describes what was done with the data found.  In order to write the analysis section it is important to know what the analysis consisted of, but does not mean data is needed. The analysis should already be performed to write the results section.

Written explanations

How should the analysis section be written?

• Should be a paragraph within the research paper
• Consider all the requirements (spacing, margins, and font)
• Should be the writer’s own explanation of the chosen problem
• Thorough evaluation of work
• Description of the weak and strong points
• Discussion of the effect and impact
• Includes criticism

How should the results section be written?

• Show the most relevant information in graphs, figures, and tables
• Include data that may be in the form of pictures, artifacts, notes, and interviews
• Clarify unclear points
• Present results with a short discussion explaining them at the end
• Include the negative results
• Provide stability, accuracy, and value

How the style is presented

Analysis section

• Includes a justification of the methods used
• Technical explanation

Results section

• Purely descriptive
• Easily explained for the targeted audience
• Data driven

Example of a Results Section

Publication Manual of the American Psychological Association Sixth Ed. 2010

• << Previous: 5. Methods / Materials
• Next: 7. Discussion >>
• Last Updated: Jun 27, 2019 2:33 PM
• URL: https://wiu.libguides.com/researchpaperwriting

Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

Definition and Introduction

Journal article analysis assignments require you to summarize and critically assess the quality of an empirical research study published in a scholarly [a.k.a., academic, peer-reviewed] journal. The article may be assigned by the professor, chosen from course readings listed in the syllabus, or you must locate an article on your own, usually with the requirement that you search using a reputable library database, such as, JSTOR or ProQuest . The article chosen is expected to relate to the overall discipline of the course, specific course content, or key concepts discussed in class. In some cases, the purpose of the assignment is to analyze an article that is part of the literature review for a future research project.

Analysis of an article can be assigned to students individually or as part of a small group project. The final product is usually in the form of a short paper [typically 1- 6 double-spaced pages] that addresses key questions the professor uses to guide your analysis or that assesses specific parts of a scholarly research study [e.g., the research problem, methodology, discussion, conclusions or findings]. The analysis paper may be shared on a digital course management platform and/or presented to the class for the purpose of promoting a wider discussion about the topic of the study. Although assigned in any level of undergraduate and graduate coursework in the social and behavioral sciences, professors frequently include this assignment in upper division courses to help students learn how to effectively identify, read, and analyze empirical research within their major.

Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535.

Benefits of Journal Article Analysis Assignments

Analyzing a scholarly journal article is intended to help students obtain the reading and critical thinking skills needed to develop and write their own research papers. There are two broadly defined ways that analyzing a scholarly journal article supports student learning:

Improve Reading Skills

Conducting research requires an ability to review, evaluate, and synthesize prior research studies. Reading prior research requires an understanding of the academic writing style , the type of epistemological beliefs or practices underpinning the research design, and the specific vocabulary and technical terminology [i.e., jargon] used within a discipline. Reading scholarly articles is important because academic writing is unfamiliar to most students; they have had limited exposure to using peer-reviewed journal articles prior to entering college or students have yet to gain exposure to the specific academic writing style of their disciplinary major. Learning how to read scholarly articles also requires careful and deliberate concentration on how authors use specific language and phrasing to convey their research, the problem it addresses, its relationship to prior research, its significance, its limitations, and how authors connect methods of data gathering to the results so as to develop recommended solutions derived from the overall research process.

Improve Comprehension Skills

In addition to knowing how to read scholarly journals articles, students must learn how to effectively interpret what the scholar(s) are trying to convey. Academic writing can be dense, multi-layered, and non-linear in how information is presented. In addition, scholarly articles contain footnotes or endnotes, references to sources, multiple appendices, and, in some cases, non-textual elements [e.g., graphs, charts] that can break-up the reader’s experience with the narrative flow of the study. Analyzing articles helps students practice comprehending these elements of writing, critiquing the arguments being made, reflecting upon the significance of the research, and how it relates to building new knowledge and understanding or applying new approaches to practice. Comprehending scholarly writing also involves thinking critically about where you fit within the overall dialogue among scholars concerning the research problem, finding possible gaps in the research that require further analysis, or identifying where the author(s) has failed to examine fully any specific elements of the study.

In addition, journal article analysis assignments are used by professors to strengthen discipline-specific information literacy skills, either alone or in relation to other tasks, such as, giving a class presentation or participating in a group project. These benefits can include the ability to:

• Effectively paraphrase text, which leads to a more thorough understanding of the overall study;
• Identify and describe strengths and weaknesses of the study and their implications;
• Relate the article to other course readings and in relation to particular research concepts or ideas discussed during class;
• Think critically about the research and summarize complex ideas contained within;
• Plan, organize, and write an effective inquiry-based paper that investigates a research study, evaluates evidence, expounds on the author’s main ideas, and presents an argument concerning the significance and impact of the research in a clear and concise manner;
• Model the type of source summary and critique you should do for any college-level research paper; and,
• Increase interest and engagement with the research problem of the study as well as with the discipline.

Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students make the most of Scholarly Articles." Library Management 33 (2012): 525-535; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946.

Structure and Organization

A journal article analysis paper should be written in paragraph format and include an instruction to the study, your analysis of the research, and a conclusion that provides an overall assessment of the author's work, along with an explanation of what you believe is the study's overall impact and significance. Unless the purpose of the assignment is to examine foundational studies published many years ago, you should select articles that have been published relatively recently [e.g., within the past few years].

Since the research has been completed, reference to the study in your paper should be written in the past tense, with your analysis stated in the present tense [e.g., “The author portrayed access to health care services in rural areas as primarily a problem of having reliable transportation. However, I believe the author is overgeneralizing this issue because...”].

Introduction Section

The first section of a journal analysis paper should describe the topic of the article and highlight the author’s main points. This includes describing the research problem and theoretical framework, the rationale for the research, the methods of data gathering and analysis, the key findings, and the author’s final conclusions and recommendations. The narrative should focus on the act of describing rather than analyzing. Think of the introduction as a more comprehensive and detailed descriptive abstract of the study.

Possible questions to help guide your writing of the introduction section may include:

• Who are the authors?
• What was the research problem being investigated?
• What type of research design was used to investigate the research problem?
• What theoretical idea(s) and/or research questions were used to address the problem?
• What was the source of the data or information used as evidence for analysis?
• What methods were applied to investigate this evidence?
• What were the author's overall conclusions and key findings?

Critical Analysis Section

The second section of a journal analysis paper should describe the strengths and weaknesses of the study and analyze its significance and impact. This section is where you shift the narrative from describing to analyzing. Think critically about the research in relation to other course readings, what has been discussed in class, or based on your own life experiences. If you are struggling to identify any weaknesses, explain why you believe this to be true. However, no study is perfect, regardless of how laudable its design may be. Given this, think about the repercussions of the choices made by the author(s) and how you might have conducted the study differently. Examples can include contemplating the choice of what sources were included or excluded in support of examining the research problem, the choice of the method used to analyze the data, or the choice to highlight specific recommended courses of action and/or implications for practice over others. Another strategy is to place yourself within the research study itself by thinking reflectively about what may be missing if you had been a participant in the study or if the recommended courses of action specifically targeted you or your community.

Possible questions to help guide your writing of the analysis section may include:

Introduction

• Did the author clearly state the problem being investigated?
• What was your reaction to and perspective on the research problem?
• Was the study’s objective clearly stated? Did the author clearly explain why the study was necessary?
• How well did the introduction frame the scope of the study?
• Did the introduction conclude with a clear purpose statement?

Literature Review

• Did the literature review lay a foundation for understanding the significance of the research problem?
• Did the literature review provide enough background information to understand the problem in relation to relevant contexts [e.g., historical, economic, social, cultural, etc.].
• Did literature review effectively place the study within the domain of prior research? Is anything missing?
• Was the literature review organized by conceptual categories or did the author simply list and describe sources?
• Did the author accurately explain how the data or information were collected?
• Was the data used sufficient in supporting the study of the research problem?
• Was there another methodological approach that could have been more illuminating?
• Give your overall evaluation of the methods used in this article. How much trust would you put in generating relevant findings?

Results and Discussion

• Were the results clearly presented?
• Did you feel that the results support the theoretical and interpretive claims of the author? Why?
• What did the author(s) do especially well in describing or analyzing their results?
• Was the author's evaluation of the findings clearly stated?
• How well did the discussion of the results relate to what is already known about the research problem?
• Was the discussion of the results free of repetition and redundancies?
• What interpretations did the authors make that you think are in incomplete, unwarranted, or overstated?
• Did the conclusion effectively capture the main points of study?
• Did the conclusion address the research questions posed? Do they seem reasonable?
• Were the author’s conclusions consistent with the evidence and arguments presented?
• Has the author explained how the research added new knowledge or understanding?

Overall Writing Style

• If the article included tables, figures, or other non-textual elements, did they contribute to understanding the study?
• Were ideas developed and related in a logical sequence?
• Were transitions between sections of the article smooth and easy to follow?

Overall Evaluation Section

The final section of a journal analysis paper should bring your thoughts together into a coherent assessment of the value of the research study . This section is where the narrative flow transitions from analyzing specific elements of the article to critically evaluating the overall study. Explain what you view as the significance of the research in relation to the overall course content and any relevant discussions that occurred during class. Think about how the article contributes to understanding the overall research problem, how it fits within existing literature on the topic, how it relates to the course, and what it means to you as a student researcher. In some cases, your professor will also ask you to describe your experiences writing the journal article analysis paper as part of a reflective learning exercise.

Possible questions to help guide your writing of the conclusion and evaluation section may include:

• Was the structure of the article clear and well organized?
• Was the topic of current or enduring interest to you?
• What were the main weaknesses of the article? [this does not refer to limitations stated by the author, but what you believe are potential flaws]
• Was any of the information in the article unclear or ambiguous?
• What did you learn from the research? If nothing stood out to you, explain why.
• Assess the originality of the research. Did you believe it contributed new understanding of the research problem?
• Were you persuaded by the author’s arguments?
• If the author made any final recommendations, will they be impactful if applied to practice?
• In what ways could future research build off of this study?
• What implications does the study have for daily life?
• Was the use of non-textual elements, footnotes or endnotes, and/or appendices helpful in understanding the research?
• What lingering questions do you have after analyzing the article?

NOTE: Avoid using quotes. One of the main purposes of writing an article analysis paper is to learn how to effectively paraphrase and use your own words to summarize a scholarly research study and to explain what the research means to you. Using and citing a direct quote from the article should only be done to help emphasize a key point or to underscore an important concept or idea.

Business: The Article Analysis . Fred Meijer Center for Writing, Grand Valley State University; Bachiochi, Peter et al. "Using Empirical Article Analysis to Assess Research Methods Courses." Teaching of Psychology 38 (2011): 5-9; Brosowsky, Nicholaus P. et al. “Teaching Undergraduate Students to Read Empirical Articles: An Evaluation and Revision of the QALMRI Method.” PsyArXi Preprints , 2020; Holster, Kristin. “Article Evaluation Assignment”. TRAILS: Teaching Resources and Innovations Library for Sociology . Washington DC: American Sociological Association, 2016; Kershaw, Trina C., Jennifer Fugate, and Aminda J. O'Hare. "Teaching Undergraduates to Understand Published Research through Structured Practice in Identifying Key Research Concepts." Scholarship of Teaching and Learning in Psychology . Advance online publication, 2020; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Reviewer's Guide . SAGE Reviewer Gateway, SAGE Journals; Sego, Sandra A. and Anne E. Stuart. "Learning to Read Empirical Articles in General Psychology." Teaching of Psychology 43 (2016): 38-42; Kershaw, Trina C., Jordan P. Lippman, and Jennifer Fugate. "Practice Makes Proficient: Teaching Undergraduate Students to Understand Published Research." Instructional Science 46 (2018): 921-946; Gyuris, Emma, and Laura Castell. "To Tell Them or Show Them? How to Improve Science Students’ Skills of Critical Reading." International Journal of Innovation in Science and Mathematics Education 21 (2013): 70-80; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36; MacMillan, Margy and Allison MacKenzie. "Strategies for Integrating Information Literacy and Academic Literacy: Helping Undergraduate Students Make the Most of Scholarly Articles." Library Management 33 (2012): 525-535.

Writing Tip

Not All Scholarly Journal Articles Can Be Critically Analyzed

There are a variety of articles published in scholarly journals that do not fit within the guidelines of an article analysis assignment. This is because the work cannot be empirically examined or it does not generate new knowledge in a way which can be critically analyzed.

If you are required to locate a research study on your own, avoid selecting these types of journal articles:

• Theoretical essays which discuss concepts, assumptions, and propositions, but report no empirical research;
• Statistical or methodological papers that may analyze data, but the bulk of the work is devoted to refining a new measurement, statistical technique, or modeling procedure;
• Articles that review, analyze, critique, and synthesize prior research, but do not report any original research;
• Brief essays devoted to research methods and findings;
• Articles written by scholars in popular magazines or industry trade journals;
• Pre-print articles that have been posted online, but may undergo further editing and revision by the journal's editorial staff before final publication; and
• Academic commentary that discusses research trends or emerging concepts and ideas, but does not contain citations to sources.

Journal Analysis Assignment - Myers . Writing@CSU, Colorado State University; Franco, Josue. “Introducing the Analysis of Journal Articles.” Prepared for presentation at the American Political Science Association’s 2020 Teaching and Learning Conference, February 7-9, 2020, Albuquerque, New Mexico; Woodward-Kron, Robyn. "Critical Analysis and the Journal Article Review Assignment." Prospect 18 (August 2003): 20-36.

• << Previous: Annotated Bibliography
• Next: Giving an Oral Presentation >>
• Last Updated: Sep 15, 2023 9:37 AM
• URL: https://libguides.usc.edu/writingguide/assignments

How to Write an Analysis Essay: Examples + Writing Guide

An analysis / analytical essay is a standard assignment in college or university. You might be asked to conduct an in-depth analysis of a research paper, a report, a movie, a company, a book, or an event. In this article, you’ll find out how to write an analysis paper introduction, thesis, main body, and conclusion, and analytical essay example.

Our specialists will write a custom essay on any topic for 13.00 10.40/page

So, what is an analytical essay? This type of assignment implies that you set up an argument and analyze it using a range of claims. The claims should be supported by appropriate empirical evidence. Note that you need to explore both the positive and negative sides of the issue fully.

Analytical skills are the key to getting through your academic career. Moreover, they can be useful in many real-life situations. Keep reading this article by Custom-writing experts to learn how to write an analysis!

❓ What Is an Analytical Essay?

• 🤔 Getting Started

📑 Analytical Essay Outline

• 📔 Choosing a Title
• 💁 Writing an Introduction
• 🏋 Writing a Body
• 🏁 Writing a Conclusion

🔗 References

Before you learn how to start an analysis essay, you should understand some fundamentals of writing this type of paper. It implies that you analyze an argument using a range of claims supported by facts . It is essential to understand that in your analysis essay, you’ll need to explore the negative sides of the issue and the positive ones. That’s what distinguishes an analytical essay from, say, a persuasive one.

These are the steps to write an academic paper :

• Review the literature . Before starting any paper, you should familiarize yourself with what has already been written in the field. And the analytical essay is no exception. The easiest way is to search on the web for the information.
• Brainstorm ideas. After you’ve done your search, it is time for a brainstorm! Make a list of topics for your analysis essay, and then choose the best one. Generate your thesis statement in the same way.
• Prepare an outline . Now, when you’ve decided on the topic and the thesis statement of your analytical essay, think of its structure. Below you will find more detailed information on how your paper should be structured.
• Write the first draft. You’ve done a lot of work by now. Congratulations! Your next goal is to write the first version of your analysis essay, using all the notes that you have. Remember, you don’t need to make it perfect!
• Polish your draft. Now take your time to polish and edit your draft to transform it into the paper’s final version.

You are usually assigned to analyze an article, a book, a movie, or an event. If you need to write your analytical essay on a book or an article, you’ll have to analyze the style of the text, its main points, and the author’s purported goals.

🤔 Analytical Essay: Getting Started

The key to writing an analysis paper is to choose an argument that you will defend throughout it. For example: maybe you are writing a critical analysis paper on George Orwell’s Animal Farm The first and imperative task is to think about your thesis statement. In the case of Animal Farm , the argument could be:

In Orwell’s Animal Farm , rhetoric and language prove to be more effective ways to keep social control than physical power.

The University of North Carolina at Chapel Hill gives a great explanation of the thesis statement , how to create one, and what its function is.

But that’s not all. Once you have your thesis statement, you need to break down how you will approach your analysis essay to prove your thesis. To do this, follow these steps:

• Define the main goal(s) of your analysis . Remember that it is impossible to address each and every aspect in a single paper. Know your goal and focus on it.
• Conduct research , both online and offline, to clarify the issue contained within your thesis statement.
• Identify the main parts of the issue by looking at each part separately to see how it works.
• Try to clearly understand how each part works.
• Identify the links between the various aspects of the topic .
• By using the information you found, try to solve your main problem .

At this point, you should have a clear understanding of both the topic and your thesis statement. You should also have a clear direction for your analysis paper firmly planted in your mind and recorded in writing.

This will give you what you need to produce the paper’s outline.

Receive a plagiarism-free paper tailored to your instructions.

An outline is the starting point for your work. A typical analytical essay features the usual essay structure. A 500-word essay should consist of a one-paragraph introduction, a three-paragraph body, and a one-paragraph conclusion. Find below a great analytical essay outline sample. Feel free to use it as an example when doing your own work!

Analysis Essay: Introduction

• Start with a startling statement or provocative question.

“All animals are equal, but some animals are more equal”. Animal Farm abounds in ironic and provocative phrases to start an analytical essay.

• Introduce the work and its author.
• Give background information that would help the reader understand your opinion.
• Formulate a thesis statement informing the reader about the purpose of the essay. Essay format does not presuppose telling everything possible on the given topic. Thus, a thesis statement tells what you are going to say, implying what you will not discuss, establishing the limits.

In Animal Farm, Orwell uses different irony types to ridicule totalitarianism to manifest its inability to make every member of society equal and happy.

Analysis Essay: Body

The analytical essay structure requires 2-3 developmental paragraphs, each dedicated to one separate idea confirming your thesis statement. The following template should be used for each of the body paragraphs.

• Start with a topic sentence that supports an aspect of your thesis.

Dramatic irony is used in Animal Farm to point out society’s ignorance.

• Continue with textual evidence (paraphrase, summary, direct quotations, specific details). Use several examples that substantiate the topic sentence.

Animals are unaware of the fact that Boxer was never sent to the hospital. He was sent to the slaughterhouse. However, the reader and writer understand that this is a lie.

• Conclude with an explanation.

By allowing the readers to learn some essential facts before the characters, dramatic irony creates suspense and shows how easy it is to persuade and manipulate the public.

Analysis Essay Conclusion

The next four points will give you a short instruction on how to conclude an analytical essay.

• Never use new information or topics here.
• Restate your thesis in a different formulation.
• Summarize the body paragraphs.
• Comment on the analyzed text from a new perspective.

📔 Choosing a Title for Your Analysis Essay

Choosing a title seems like not a significant step, but it is actually very important. The title of your critical analysis paper should:

• Entice and engage the reader
• Be unique and capture the readers’ attention
• Provide an adequate explanation of the content of the essay in just a few carefully chosen words

In the Animal Farm example, your title could be:

Just 13.00 10.40/page , and you can get an custom-written academic paper according to your instructions

“How Do the Pigs Manage to Keep Social Control on Animal Farm?”

Analysis Essay Topics

• Analyze the media content.
• Analyze the specifics and history of hip-hop culture.
• Sociological issues in the film Interstellar .
• Discuss the techniques M. Atwood uses to describe social issues in her novel The Handmaid’s Tale .
• Compare and analyze the paintings of Van Gogh and George Seurat.
• Analysis of Edgar Allan Poe’s The Black Cat .
• Examine the juvenile crime rates.
• Describe the influence of different parenting styles on children’s mind.
• Analyze the concept of the Ship of Theseus .
• Compare and analyze the various views on intelligence .
• Analysis of The Yellow Wallpaper by Charlotte Perkins Gilman .
• Discuss the techniques used by W. Shakespeare in A Midsummer Night’s Dream .
• Analyze the biography of Frederic Chopin .
• Manifestation of the Chicano culture in the artwork An Ofrenda for Dolores del Rio .
• Similarities and differences of Roman, Anglo-Saxon, and Spanish Empires .
• Describe the problem of stalking and its impact on human mental health.
• Examine the future of fashion .
• Analyze the topicality of the article Effectiveness of Hand Hygiene Interventions in Reducing Illness Absence .
• Discuss Thomas Paine’s impact on the success of American revolution.
• Meaningful messages in Recitatif by Toni Morrison .
• Explore the techniques used by directors in the film Killing Kennedy .
• Compare the leadership styles of Tang Empress Wu Zetian and the Pharaoh Cleopatra .
• Evaluate the credibility of Kristof’s arguments in his article Remote Learning Is Often an Oxymoron .
• Analyze genetically modified food .
• Examine the influence of Europeans on Indian tribes in The Narrative of the Captivity and Restoration of Mrs. Mary Rowlandson .
• Describe the rhetoric techniques used in The Portrait of Dorian Gray by Oscar Wilde .
• The importance of fighting against violence in communities in the documentary film The Interrupters .
• Analyze indoor and outdoor pollution .
• Analyze the issue of overprotective parenthood .
• Explore the connection between eating habits and advertisement.
• Discuss the urgence of global warming issue .
• Influence of sleep on people’s body and mental health.
• Analyze the relationship between Christianity and sports .
• Discuss the concept of leadership and its significance for company efficiency.
• Analyze the key lessons of the book Rich Dad Poor Dad by Robert Kiyosaki .
• Examine the specifics of nursing ethic .
• The theme of emotional sufferings in the short story A Rose for Emily .
• Analysis of bias in books for children .
• Analyze the rhetoric of the article Public Monuments .
• Describe the main messages in Jean-Paul Sartre’s Nausea .
• Explore the problem of structural racism in healthcare .
• The reasons of tango dance popularity.
• The shortcomings of the American educational system in Waiting for Superman.
• Analyze and compare Erin’s Law and Megan’s Law .
• Analyze the James Madison’s essay Federalist 10 .
• Examine symbols in the movie The Joker .
• Compare the thematic connection and stylistic devices in the poems The Road Not Taken and Find Your Way .
• Describe and analyze the life of Eddie Bernice Johnson .
• Explore the social classes in America .
• Crucial strengths and weaknesses of the main translation theories .

💁 Writing Your Analytical Essay Introduction

You must understand how to compose an introduction to an analysis paper. The University of Wollongong describes the introduction as a “map” of any writing. When writing the introduction, follow these steps:

• Provide a lead-in for the reader by offering a general introduction to the topic of the paper.
• Include your thesis statement , which shifts the reader from the generalized introduction to the specific topic and its related issues to your unique take on the essay topic.
• Present a general outline of the analysis paper.

Watch this great video for further instructions on how to write an introduction to an analysis essay.

Example of an Analytical Essay Introduction

“Four legs good, two legs bad” is one of the many postulates invented by George Orwell for his characters in Animal Farm to vest them with socialist ideology and control over the animal population. The social revolution on Manor Farm was built on language instruments, first for the collective success of the animals, and later for the power consolidation by the pigs. The novel was written in 1945 when the transition from limitless freedoms of socialist countries transformed into dictatorship. Through his animal protagonists, the author analyzes the reasons for peoples’ belief in the totalitarian regime. In Orwell’s Animal Farm , rhetoric and language prove to be more effective ways to keep social control than physical power.

🏋 Writing Your Analytical Essay Body

The body of the paper may be compared to its heart. This is the part where you show off your talent for analysis by providing convincing, well-researched, and well-thought-out arguments to support your thesis statement. You have already gathered the information, and now all you may start crafting your paper.

To make the body of an analytical essay, keep the following in mind:

• Discuss one argument per paragraph , although each argument can relate to multiple issues
• Strike a balance between writing in an unbiased tone, while expressing your personal opinion
• Be reasonable when making judgments regarding any of the problems you discuss
• Remember to include the opposing point of view to create a balanced perspective

The bottom line is: you want to offer opposing views, but you must pose your arguments so they will counter those opposing views and prove your point of view. Follow these steps when constructing each body paragraph:

• Choose the main sentence. The main or topic sentence will be the first line in your essay. The topic sentence is responsible for presenting the argument you will discuss in the paragraph and demonstrate how this argument relates to the thesis statement.
• Provide the context for the topic sentence , whether it relates to a quote, a specific incident in society, or something else. Offer evidence on who, what, where, when, why, and how.
• Give your analysis of the argument and how it adequately proves your thesis.
• Write a closing sentence that sums up the paragraph and provides a transition to the following paragraph.

Example of an Analytical Essay Body

Literacy can grant power, provided that there are animals who cannot read or write. In the beginning, the animals’ literacy and intellect are relatively the same. Old Major is the cleverest pig; he is the kind old philosopher, like Karl Marx or Vladimir Lenin. During his retirement, he develops a theory that all humans are the root of evil. His speech was the foundation for the pigs’ assumption of power. They refined his ideas into a new ideology and called it Animalism. They also learned how to read. It allowed the pigs to declare themselves the “mind workers.” Therefore, the pigs’ literacy assured the illiterate animals in their objective superiority.

Meanwhile, as the pigs were the intellectual elite, they were not supposed to work, which raised their social status by itself. Snowball tried to promote education among all the animals, but most of them failed to master the alphabet. This is a metaphor for the general public being predominantly ignorant and easy to manipulate. At the same time, Boxer and other animals that spend most of the day in hard work merely have no time to develop their intellect. Thus, the pigs’ intention to build a school for pig children was highly efficient. Unequal access to education and unequal ability to express one’s thoughts in perspective reinforce the social divide, making the pigs smarter and more powerful and undermining other animals’ self-esteem.

At this point, the pigs resort to propaganda and rhetoric. Squealer uses his oratorical gift to refine the pigs’ message to the other animals. Upon Napoleon’s order, he breaks the Seven Commandments of farm governance. At night, he climbs the ladder to change them, and once even falls from the ladder trying to change the commandment on alcohol. The “proletarian” animals soon forget what the Seven Commandments were like in the first place and are unsure if they have ever been altered. Further on, Minimus writes a poem praising Napoleon. Finally, Squealer replaces the Commandments with a single assertion: “All animals are equal, but some animals are more equal than others.” Language is no longer used to convince. It is used to control and manipulate.

🏁 Writing Your Analytical Essay Conclusion

The conclusion is short and sweet. It summarizes everything you just wrote in the essay and wraps it up with a beautiful shiny bow. Follow these steps to write a convincing conclusion:

• Repeat the thesis statement and summarize your argument. Even when using the best summary generator for the task, reread it to make sure all the crucial points are included.
• Take your argument beyond what is simply stated in your paper. You want to show how it is essential in terms of the bigger picture. Also, you may dwell on the influence on citizens of the country.

Example of an Analytical Essay Conclusion

Because of everything mentioned above, it becomes clear that language and rhetoric can rise to power, establish authority, and manipulate ordinary people. Animal Farm is the simplified version of a communist society. It shows how wise philosophers’ good intentions can be used by mean leaders to gain unopposed power and unconditional trust. Unfortunately, this can lead to the death of many innocent animals, i.e., people, as totalitarianism has nothing to do with people’s rule. Therefore, language and oratory are potent tools that can keep people oppressed and weak, deprive them of any chance for improvement and growth, and make them think that there is no other possible existence.

Now you are ready to write an analysis essay! See, it’s easier than you thought.

Of course, it’s always helpful to see other analysis essay examples. The University of Arkansas at Little Rock provides some great examples of an analytical paper .

✏️ Analysis Essay FAQ

A great analytical paper should be well-structured, cohesive, and logically consistent. Each part of the essay should be in its place, creating a smooth and easy-to-read text. Most importantly, the statements should be objective and backed by arguments and examples.

It is a paper devoted to analyzing a certain topic or subject. An analysis essay is all about reviewing certain details of the subject and interpreting them. For example, such an analysis for a poem includes a description of artistic means that helped the poet convey the idea.

Writing an analytical essay on a book/movie/poem start with an outline. Point out what catches the eye when reviewing the subject. See how these details can be interpreted. Make sure that you refer to the main idea/message. Add an appropriate introduction and a logical conclusion.

Being more analytical in writing can be essential for a student. This is a skill that can be self-taught: try to start noticing subtle details and describe them. As you write, interpret the facts and strive to draw conclusions. Try to be as objective as possible.

• Elements of Analysis
• How Can I Create Stronger Analysis?
• How to Write a Literary Analysis Essay: Bucks.edu
• Essay Structure | – Harvard College Writing Center
• Analytical Writing: Looking Closely (Colostate.edu)
• Analytical Thesis Statements – University of Arizona
• Writing an analytic essay – UTSC – University of Toronto
• Organizing Your Analysis // Purdue Writing Lab
• How to Write an Analytical Essay: 15 Steps (with Pictures)
• Share to Facebook
• Share to Twitter
• Share to LinkedIn
• Share to email

This resource helps me a lot. Thanks! You guys have great information. Do you think I can use these steps when taking a test? Could it be known as plagiarized if I just copy and paste the information?

Glad to help, Hazel! You can use it in your test but you should cite it accordingly

Thanks, very good information.

Thank you for your attention, Jaweria🙂!

Thanks for learning how to critique research papers in a proper way! This is what I need to cope with this task successfully! Thanks!

How much is an essay, and is there a chance it can be plagiarized?

You have to remember that the price for our services depends on a lot of factors. You can find the detailed price quote here: https://custom-writing.org/prices (the page will be opened in a new window). You can check out the prices depending on the subjects and deadlines that you choose. No – it can’t be plagiarized: the papers are written from scratch according to your instructions. We also stress the importance of the fact that you CAN’T, under any circumstances, use our final product as your own work – the papers, which we provide, are to be used for research purposes only!

Recommended for You

Good Book Report: How to Write & What to Include

Reading books is pleasurable and entertaining; writing about those books isn’t. Reading books is pleasurable, easy, and entertaining; writing about those books isn’t. However, learning how to write a book report is something that is commonly required in university. Fortunately, it isn’t as difficult as you might think. You’ll only...

How to Write a Critique Paper: Tips + Critique Essay Examples

A critique paper is an academic writing genre that summarizes and gives a critical evaluation of a concept or work. Or, to put it simply, it is no more than a summary and a critical analysis of a specific issue. This type of writing aims to evaluate the impact of...

Short Story Analysis: How to Write It Step by Step [New]

Have you ever tried to write a story analysis but ended up being completely confused and lost? Well, the task might be challenging if you don’t know the essential rules for literary analysis creation. But don’t get frustrated! We know how to write a short story analysis, and we are...

How to Write a Literary Analysis Essay Step by Step

Some students find writing literary analysis papers rather daunting. Yet, an English class cannot go without this kind of work. By the way, writing literary analysis essays is not that complicated as it seems at a glance. On the contrary, this work may be fascinating, and you have a chance...

How to Write a Dissertation Critique: Examples & Guide 2023

Dissertation critique writing develops the students’ critical and logical thinking abilities. When composing, the students learn to analyze the works conducted by other researchers. To critique a dissertation, you should: Thoroughly read the paper.Take notes and summarize the text (you can even try and use auto summarizer for that).Interpret and...

How to Write an Art Critique: Examples & Strategies

An art critique paper involves a comprehensive analysis and assessment of an artwork. Though this looks a bit complicated, the task doesn’t require a lot of time if you have sufficient critique writing skills. It’s an interesting assignment for students of art colleges as well as high schoolers. All you...

Research Paper Guide

Research Paper Example

Research Paper Example - APA and MLA Format

12 min read

Published on: Nov 27, 2017

Last updated on: Oct 25, 2023

On This Page On This Page

Do you spend time staring at the screen and thinking about how to approach a monstrous  research paper ?

If yes, you are not alone.

Research papers are no less than a curse for high school and college students.

It takes time, effort, and expertise to craft a striking research paper.

Every other person craves to master the magic of producing impressive research papers.

Continue with the guide to investigate the mysterious nature of different types of research through examples.

Research Paper Example for Different Formats

An academic paper doesn't have to be boring. You can use an anecdote, a provocative question, or a quote to begin the introduction.

Learning from introductions written in professional college papers is the best strategy.

Have a look at the expertise of the writer in the following example.

Social Media and Social Media Marketing: A Literature Review

APA Research Paper Example

While writing research papers, you must pay attention to the required format.

Follow the example when the instructor mentions the  APA format .

Effects of Food Deprivation of Concentration and Preserverance

Research Paper Example APA 7th Edition

Research Paper Example MLA

Once you are done with APA format, let’s practice the art of writing quality MLA papers.

Found Voices: Carl Sagan

We have provided you with a top-notch research paper example in  MLA format  here.

Research Paper Example Chicago

Chicago style  is not very common, but it is important to learn. Few institutions require this style for research papers, but it is essential to learn. The content and citations in the research paper are formatted like this example.

Chicago Research Paper Sample

Research Paper Example Harvard

To learn how a research paper is written using the  Harvard citation style , carefully examine this example. Note the structure of the cover page and other pages.

Harvard Research Paper Sample

Examples for Different Research Paper Parts

A research paper has different parts. Each part is important for the overall success of the paper. Chapters in a research paper must be written correctly, using a certain format and structure.

The following are examples of how different sections of the research paper can be written.

Example of Research Proposal

What is the first step to starting a research paper?

Submitting the research proposal!

It involves several sections that take a toll on beginners.

Here is a detailed guide to help you  write a research proposal .

Are you a beginner or do you lack experience? Don’t worry.

The following example of a research paper is the perfect place to get started.

View Research Proposal Example Here

Research Paper Example Abstract

After submitting the research proposal, prepare to write a seasoned  abstract  section.

The abstract delivers the bigger picture by revealing the purpose of the research.

A common mistake students make is writing it the same way a summary is written.

It is not merely a summary but an analysis of the whole research project. Still confused?

Read the abstract mentioned in the following research to get a better idea.

Affirmative Action: What Do We Know? - Abstract Example

Literature Review Research Paper Example

What if a novice person reads your research paper?

He will never understand the critical elements involved in the research paper.

To enlighten him, focus on the  literature review  section. This section offers an extensive analysis of the past research conducted on the paper topics.

It is relatively easier than other sections of the paper.

Take a closer look at the paper below to find out.

Methods Section of Research Paper Example

While writing research papers, excellent papers focus a great deal on the methodology.

Yes, the research sample and methodology define the fate of the papers.

Are you facing trouble going through the methodology section?

Relax and let comprehensive sample research papers clear your doubts.

View Methods Section of Research Paper Here

Research Paper Conclusion Example

The conclusion leaves the last impression on the reader.

“Who cares for the last impression? It’s always the first.”

Don’t be fooled!

The conclusion sets the tone of the whole research paper properly.

A key list of elements must be present in conclusion to make it crisp and remarkable.

The Conclusion: Your Paper's Final Impression

View the sample paper and identify the points you thought were never a part of the conclusion.

Get Quick AI Research Help!

Research Paper Examples for Different Fields

Research papers can be about any subject that needs a detailed study. The following examples show how research papers are written for different subjects.

History Research Paper Sample

Many Faces of Generalisimo Fransisco Franco

Sociology Research Paper Sample

A Descriptive Statistical Analysis within the State of Virginia

Science Fair Research Paper Sample

What Do I Need To Do For The Science Fair?

Psychology Research Paper Sample

The Effects of Food Deprivation on Concentration and Preserverance

Art History Research Paper Sample

European Art History: A Primer

Scientific Research Paper Example

We have discussed several elements of research papers through examples.

Research Proposal!

Introduction in Research Paper!

Read on to move towards advanced versions of information.

Scientific research paper

Let's have a look at the template and an example to elaborate on concepts.

It includes:

• Introduction
• Related Work
• Research Methodology
• Experiments
• Results and Discussion
• Conclusion & Future Work
• Acknowledgment

The name itself sounds terrifying to many students. Make no mistake; it sure is dangerous when touched without practice.

Students become afraid and hence aspire to locate an outstanding essay paper writer to get their papers done.

Detailed, high-quality, and credible sources and samples are a must to be shared here.

Science Fair Paper Format

Example of Methodology in Research Paper

The words methodology, procedure, and approach are the same. They indicate the approach pursued by the researcher while conducting research to accomplish the goal through research.

The methodology is the bloodline of the research paper.

A practical or assumed procedure is used to conduct the methodology.

The Effects of Immediate Feedback Devices in High School Chemistry Classes

See the way the researcher has shared participants and limits in the methodology section of the example.

Research Paper Example for Different Levels

The process of writing a research paper is based on a set of steps. The process will seem daunting if you are unaware of the basic steps. Start writing your research paper by taking the following steps:

• Choose a Topic
• Create a thesis statement
• Do in-depth research for the research study
• Create an outline

You will find writing a research paper much easier once you have a plan.

No matter which level you are writing at, your research paper needs to be well structured.

Research Paper Example Outline

Before you plan on writing a well-researched paper, make a rough draft.

Brainstorm again and again!

Pour all of your ideas into the basket of the outline.

What will it include?

A standard is not set but follow the  research paper outline  example below:

View Research Paper Outline Example Here

This example outlines the following elements:

• Thesis Statement
• Methodology

Utilize this standard of outline in your research papers to polish your paper. Here is a step-by-step guide that will help you write a research paper according to this format.

Good Research Paper Examples for Students

Theoretically, good research paper examples will meet the objectives of the research.

Always remember! The first goal of the research paper is to explain ideas, goals, and theory as clearly as water.

Yes, leave no room for confusion of any sort.

Fiscal Research Center - Action Plan

Qualitative Research Paper Example

Research Paper Example Introduction

How to Write a Research Paper Example?

Research Paper Example for High School

When the professor reads such a professional research paper, he will be delighted.

High scores!

Grant of funds for the project!

Appreciation in Class!

You'll surely be highly rewarded.

Research Paper Conclusion

“Who cares for the last impression? It's always the first.”

Don't be fooled!

A key list of elements must be present in the conclusion to make it crisp and remarkable.

Critical Research Paper

To write a research paper remarkably, include the following ingredients in it:

• Justification of the Experimental Design
• Analysis of Results
• Validation of the Study

How to Write the Methods Section of a Research Paper

Theoretical Framework Examples

The theoretical framework is the key to establish credibility in research papers.

Read the purpose of the theoretical framework before following it in the research paper.

The researcher offers a guide through a theoretical framework.

• Philosophical view
• Conceptual Analysis
• Benefits of the Research

An in-depth analysis of theoretical framework examples research paper is underlined in the sample below.

View Theoretical Framework Example Here

Now that you have explored the research paper examples, you can start working on your research project. Hopefully, these examples will help you understand the writing process for a research paper.

If you're facing challenges with your writing requirements, think about hiring an online custom paper writing service .

MyPerfectWords.com is your trusted solution for obtaining a custom research paper and assisting students with their unique writing needs.

Don't hesitate – Hire our writing service now.

Nova A. (Literature, Marketing)

Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

People also read

Research Paper Writing - A Step by Step Guide

Guide to Creating Effective Research Paper Outline

Interesting Research Paper Topics for 2023

Research Proposal Writing - A Step-by-Step Guide

How to Start a Research Paper - 7 Easy Steps

How to Write an Abstract - A Step by Step Guide

Learn How To Write A Literature Review In Simple Steps

Qualitative Research - Methods, Types, and Examples

8 Types of Qualitative Research - Overview & Examples

Qualitative vs Quantitative Research - Learning the Basics

Psychology Research Topics - 220+ Ideas

How to Write a Hypothesis In 7 simple Steps: Examples and Tips!

20+ Types of Research With Examples - A Detailed Guide

Understanding Quantitative Research - Types & Data Collection Techniques

230+ Sociology Research Topics & Ideas for Students

How to Cite a Research Paper - A Complete Guide

Excellent History Research Paper Topics- 300+ Ideas

How to Write a Research Methodology for a Research Paper

Share this article

Keep reading

We value your privacy

We use cookies to improve your experience and give you personalized content. Do you agree to our cookie policy?

Website Data Collection

We use data collected by cookies and JavaScript libraries.

Are you sure you want to cancel?

Your preferences have not been saved.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• How to write a literary analysis essay | A step-by-step guide

How to Write a Literary Analysis Essay | A Step-by-Step Guide

Published on January 30, 2020 by Jack Caulfield . Revised on August 14, 2023.

Literary analysis means closely studying a text, interpreting its meanings, and exploring why the author made certain choices. It can be applied to novels, short stories, plays, poems, or any other form of literary writing.

A literary analysis essay is not a rhetorical analysis , nor is it just a summary of the plot or a book review. Instead, it is a type of argumentative essay where you need to analyze elements such as the language, perspective, and structure of the text, and explain how the author uses literary devices to create effects and convey ideas.

Before beginning a literary analysis essay, it’s essential to carefully read the text and c ome up with a thesis statement to keep your essay focused. As you write, follow the standard structure of an academic essay :

• An introduction that tells the reader what your essay will focus on.
• A main body, divided into paragraphs , that builds an argument using evidence from the text.
• A conclusion that clearly states the main point that you have shown with your analysis.

Table of contents

Step 1: reading the text and identifying literary devices, step 2: coming up with a thesis, step 3: writing a title and introduction, step 4: writing the body of the essay, step 5: writing a conclusion, other interesting articles.

The first step is to carefully read the text(s) and take initial notes. As you read, pay attention to the things that are most intriguing, surprising, or even confusing in the writing—these are things you can dig into in your analysis.

Your goal in literary analysis is not simply to explain the events described in the text, but to analyze the writing itself and discuss how the text works on a deeper level. Primarily, you’re looking out for literary devices —textual elements that writers use to convey meaning and create effects. If you’re comparing and contrasting multiple texts, you can also look for connections between different texts.

To get started with your analysis, there are several key areas that you can focus on. As you analyze each aspect of the text, try to think about how they all relate to each other. You can use highlights or notes to keep track of important passages and quotes.

Language choices

Consider what style of language the author uses. Are the sentences short and simple or more complex and poetic?

What word choices stand out as interesting or unusual? Are words used figuratively to mean something other than their literal definition? Figurative language includes things like metaphor (e.g. “her eyes were oceans”) and simile (e.g. “her eyes were like oceans”).

Also keep an eye out for imagery in the text—recurring images that create a certain atmosphere or symbolize something important. Remember that language is used in literary texts to say more than it means on the surface.

Narrative voice

Ask yourself:

• Who is telling the story?
• How are they telling it?

Is it a first-person narrator (“I”) who is personally involved in the story, or a third-person narrator who tells us about the characters from a distance?

Consider the narrator’s perspective . Is the narrator omniscient (where they know everything about all the characters and events), or do they only have partial knowledge? Are they an unreliable narrator who we are not supposed to take at face value? Authors often hint that their narrator might be giving us a distorted or dishonest version of events.

The tone of the text is also worth considering. Is the story intended to be comic, tragic, or something else? Are usually serious topics treated as funny, or vice versa ? Is the story realistic or fantastical (or somewhere in between)?

Consider how the text is structured, and how the structure relates to the story being told.

• Novels are often divided into chapters and parts.
• Poems are divided into lines, stanzas, and sometime cantos.
• Plays are divided into scenes and acts.

Think about why the author chose to divide the different parts of the text in the way they did.

There are also less formal structural elements to take into account. Does the story unfold in chronological order, or does it jump back and forth in time? Does it begin in medias res —in the middle of the action? Does the plot advance towards a clearly defined climax?

With poetry, consider how the rhyme and meter shape your understanding of the text and your impression of the tone. Try reading the poem aloud to get a sense of this.

In a play, you might consider how relationships between characters are built up through different scenes, and how the setting relates to the action. Watch out for  dramatic irony , where the audience knows some detail that the characters don’t, creating a double meaning in their words, thoughts, or actions.

Prevent plagiarism. Run a free check.

Your thesis in a literary analysis essay is the point you want to make about the text. It’s the core argument that gives your essay direction and prevents it from just being a collection of random observations about a text.

If you’re given a prompt for your essay, your thesis must answer or relate to the prompt. For example:

Essay question example

Is Franz Kafka’s “Before the Law” a religious parable?

Your thesis statement should be an answer to this question—not a simple yes or no, but a statement of why this is or isn’t the case:

Thesis statement example

Franz Kafka’s “Before the Law” is not a religious parable, but a story about bureaucratic alienation.

Sometimes you’ll be given freedom to choose your own topic; in this case, you’ll have to come up with an original thesis. Consider what stood out to you in the text; ask yourself questions about the elements that interested you, and consider how you might answer them.

Your thesis should be something arguable—that is, something that you think is true about the text, but which is not a simple matter of fact. It must be complex enough to develop through evidence and arguments across the course of your essay.

Say you’re analyzing the novel Frankenstein . You could start by asking yourself:

Your initial answer might be a surface-level description:

The character Frankenstein is portrayed negatively in Mary Shelley’s Frankenstein .

However, this statement is too simple to be an interesting thesis. After reading the text and analyzing its narrative voice and structure, you can develop the answer into a more nuanced and arguable thesis statement:

Mary Shelley uses shifting narrative perspectives to portray Frankenstein in an increasingly negative light as the novel goes on. While he initially appears to be a naive but sympathetic idealist, after the creature’s narrative Frankenstein begins to resemble—even in his own telling—the thoughtlessly cruel figure the creature represents him as.

Remember that you can revise your thesis statement throughout the writing process , so it doesn’t need to be perfectly formulated at this stage. The aim is to keep you focused as you analyze the text.

Finding textual evidence

To support your thesis statement, your essay will build an argument using textual evidence —specific parts of the text that demonstrate your point. This evidence is quoted and analyzed throughout your essay to explain your argument to the reader.

It can be useful to comb through the text in search of relevant quotations before you start writing. You might not end up using everything you find, and you may have to return to the text for more evidence as you write, but collecting textual evidence from the beginning will help you to structure your arguments and assess whether they’re convincing.

To start your literary analysis paper, you’ll need two things: a good title, and an introduction.

Your title should clearly indicate what your analysis will focus on. It usually contains the name of the author and text(s) you’re analyzing. Keep it as concise and engaging as possible.

A common approach to the title is to use a relevant quote from the text, followed by a colon and then the rest of your title.

If you struggle to come up with a good title at first, don’t worry—this will be easier once you’ve begun writing the essay and have a better sense of your arguments.

“Fearful symmetry” : The violence of creation in William Blake’s “The Tyger”

The introduction

The essay introduction provides a quick overview of where your argument is going. It should include your thesis statement and a summary of the essay’s structure.

A typical structure for an introduction is to begin with a general statement about the text and author, using this to lead into your thesis statement. You might refer to a commonly held idea about the text and show how your thesis will contradict it, or zoom in on a particular device you intend to focus on.

Then you can end with a brief indication of what’s coming up in the main body of the essay. This is called signposting. It will be more elaborate in longer essays, but in a short five-paragraph essay structure, it shouldn’t be more than one sentence.

Mary Shelley’s Frankenstein is often read as a crude cautionary tale about the dangers of scientific advancement unrestrained by ethical considerations. In this reading, protagonist Victor Frankenstein is a stable representation of the callous ambition of modern science throughout the novel. This essay, however, argues that far from providing a stable image of the character, Shelley uses shifting narrative perspectives to portray Frankenstein in an increasingly negative light as the novel goes on. While he initially appears to be a naive but sympathetic idealist, after the creature’s narrative Frankenstein begins to resemble—even in his own telling—the thoughtlessly cruel figure the creature represents him as. This essay begins by exploring the positive portrayal of Frankenstein in the first volume, then moves on to the creature’s perception of him, and finally discusses the third volume’s narrative shift toward viewing Frankenstein as the creature views him.

Some students prefer to write the introduction later in the process, and it’s not a bad idea. After all, you’ll have a clearer idea of the overall shape of your arguments once you’ve begun writing them!

If you do write the introduction first, you should still return to it later to make sure it lines up with what you ended up writing, and edit as necessary.

The body of your essay is everything between the introduction and conclusion. It contains your arguments and the textual evidence that supports them.

Paragraph structure

A typical structure for a high school literary analysis essay consists of five paragraphs : the three paragraphs of the body, plus the introduction and conclusion.

Each paragraph in the main body should focus on one topic. In the five-paragraph model, try to divide your argument into three main areas of analysis, all linked to your thesis. Don’t try to include everything you can think of to say about the text—only analysis that drives your argument.

In longer essays, the same principle applies on a broader scale. For example, you might have two or three sections in your main body, each with multiple paragraphs. Within these sections, you still want to begin new paragraphs at logical moments—a turn in the argument or the introduction of a new idea.

Robert’s first encounter with Gil-Martin suggests something of his sinister power. Robert feels “a sort of invisible power that drew me towards him.” He identifies the moment of their meeting as “the beginning of a series of adventures which has puzzled myself, and will puzzle the world when I am no more in it” (p. 89). Gil-Martin’s “invisible power” seems to be at work even at this distance from the moment described; before continuing the story, Robert feels compelled to anticipate at length what readers will make of his narrative after his approaching death. With this interjection, Hogg emphasizes the fatal influence Gil-Martin exercises from his first appearance.

Topic sentences

To keep your points focused, it’s important to use a topic sentence at the beginning of each paragraph.

A good topic sentence allows a reader to see at a glance what the paragraph is about. It can introduce a new line of argument and connect or contrast it with the previous paragraph. Transition words like “however” or “moreover” are useful for creating smooth transitions:

… The story’s focus, therefore, is not upon the divine revelation that may be waiting beyond the door, but upon the mundane process of aging undergone by the man as he waits.

Nevertheless, the “radiance” that appears to stream from the door is typically treated as religious symbolism.

This topic sentence signals that the paragraph will address the question of religious symbolism, while the linking word “nevertheless” points out a contrast with the previous paragraph’s conclusion.

Using textual evidence

A key part of literary analysis is backing up your arguments with relevant evidence from the text. This involves introducing quotes from the text and explaining their significance to your point.

It’s important to contextualize quotes and explain why you’re using them; they should be properly introduced and analyzed, not treated as self-explanatory:

It isn’t always necessary to use a quote. Quoting is useful when you’re discussing the author’s language, but sometimes you’ll have to refer to plot points or structural elements that can’t be captured in a short quote.

In these cases, it’s more appropriate to paraphrase or summarize parts of the text—that is, to describe the relevant part in your own words:

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

The conclusion of your analysis shouldn’t introduce any new quotations or arguments. Instead, it’s about wrapping up the essay. Here, you summarize your key points and try to emphasize their significance to the reader.

A good way to approach this is to briefly summarize your key arguments, and then stress the conclusion they’ve led you to, highlighting the new perspective your thesis provides on the text as a whole:

If you want to know more about AI tools , college essays , or fallacies make sure to check out some of our other articles with explanations and examples or go directly to our tools!

• Ad hominem fallacy
• Post hoc fallacy
• Appeal to authority fallacy
• False cause fallacy
• Sunk cost fallacy

College essays

• Choosing Essay Topic
• Write a College Essay
• Write a Diversity Essay
• College Essay Format & Structure
• Comparing and Contrasting in an Essay

 (AI) Tools

• Grammar Checker
• Paraphrasing Tool
• Text Summarizer
• AI Detector
• Plagiarism Checker
• Citation Generator

By tracing the depiction of Frankenstein through the novel’s three volumes, I have demonstrated how the narrative structure shifts our perception of the character. While the Frankenstein of the first volume is depicted as having innocent intentions, the second and third volumes—first in the creature’s accusatory voice, and then in his own voice—increasingly undermine him, causing him to appear alternately ridiculous and vindictive. Far from the one-dimensional villain he is often taken to be, the character of Frankenstein is compelling because of the dynamic narrative frame in which he is placed. In this frame, Frankenstein’s narrative self-presentation responds to the images of him we see from others’ perspectives. This conclusion sheds new light on the novel, foregrounding Shelley’s unique layering of narrative perspectives and its importance for the depiction of character.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Caulfield, J. (2023, August 14). How to Write a Literary Analysis Essay | A Step-by-Step Guide. Scribbr. Retrieved October 31, 2023, from https://www.scribbr.com/academic-essay/literary-analysis/

Is this article helpful?

Jack Caulfield

Other students also liked, how to write a thesis statement | 4 steps & examples, academic paragraph structure | step-by-step guide & examples, how to write a narrative essay | example & tips, what is your plagiarism score.

analysis paper

An analysis essay requires the student to look at a work, idea, situation or event and use his or her critical thinking skills to offer an informed opinion about it. Analysis papers typically focus on how to accomplish a goal such as solving a problem or improving your skill at a sport, but they can also be used to explore the meaning of something through analysis.

This guide will show you how to do an analysis essay fast and score a better grade. If you need professional help in writing an analysis paper, click here to ask your question and hire a professional writer to do your analysis essay fast and secure.

What is an analysis paper?

Define analysis paper: An analysis paper is a type of essay that specifically requires the writer to analyze their subject and then make an insightful statement about it . The best analysis papers will also include facts from their research as well as examples, evidence and details to support their analysis.

formal essay vs informal essay

• Different types of essays
• Ethnographic Essay: how to write an ethnography paper
• Diagnostic essay
• How to Write a Current Event Essay | Paper Outline, Topics, Examples
• How to write a book title in an essay

An important part of writing an effective analysis paper is deciding on your thesis statement. A good way to get started is to write a short paragraph identifying the topic and saying what you will be analyzing.

A good analysis essay should begin with an introductory sentence that offers some information about your subject and then moves on to the body of paragraphs offering your analysis, supporting evidence and details. The concluding paragraph brings everything together by restating the thesis statement and providing a brief summary or overview of the points that have been made in the paper.

Analysis essay is not just a piece of writing to show how much you know but also requires writer’s personal insight and stand on the issue. It means that analysis should be based on your own understanding, feelings and experiences if possible or from any reliable sources and references. Analysis papers do not involve just citing some other opinions and arguments but requires student’s own point of view expressed in a well-written way.

Writing an analysis essay that is well written, insightful originally is difficult for students as it requires detailed knowledge and experience on the subject, hard work and deep concentration. There are many information sources dedicated to writing about certain subjects so that you can get some ideas and examples on how to write an excellent analysis essay.

A good way for students to start writing their paper is by reading books and articles, watching movies or listening to music related to the subject they are analyzing. It will give them a better understanding of what they want to say as well as help them with details and examples.

Instruction and reference books related to writing analysis papers are also available on the internet so that students can read them free of charge in their own time.

Analysis essay offers many benefits for students whose goal is improving their academic success. It increases student’s critical thinking skills, teaches how to analyse different issues and topics and improves your ability to write your own original thoughts and opinions.

What does analyze mean in academic writing?

The word “analyze” is most commonly it’s used as a verb, meaning to break something into its component parts in order to better understand it . When you analyze an issue or problem, you examine all of its components and are able to form a judgement on the whole based on comprehensive information.

The purpose of analysis is understanding a situation or object rather than simply observing it. Analysis also means to break something into its components. This can show how a whole system fits together, and it can help us identify the causes of our problems.

The definition of analyze is words or ideas arranged for inspection or consideration in order to discover their meaning or importance; examine closely.

The root of analyze is the Greek word ánalysis, defined as “a breaking up, a dissolving” from ana-, meaning “up,” and lysis, which means “loosen.” The closest synonym for this word would be dissect.

Analysis can mean to carefully study and evaluate something. In psychology, it means observing how someone thinks or acts in order to find out why they behave this way. It can also refer to separating complex matter into its basic parts for examination or analysis. This is usually used when speaking about chemistry or biology.

Analyze : Examines closely; separates into constituent parts; makes an investigation of (something) in order to discover its nature or cause, etc.; employ analysis in determining the chemical composition of a substance.

In analysis essay writing, you make an argument by showing that your view is superior to others’. You can do this in two ways:

• clearly laying out the reasons why you hold your view and supporting it with evidence or examples; and
• carefully explaining the weaknesses of opposing views—their assumptions and evidence—and showing how they are inadequate compared to yours.

Essays are useful tools for examining and analyzing issues, exploring topics, thinking critically about them, and deciding upon a point of view.

This handout will give you some starting points for essays that attempt to analyze what has been said or written by someone else. Analysis involves looking at an issue more deeply than might be done through reading alone. It may result in a complete rethinking of the material or it may simply be an expansion upon, or application of, what is already known.

If you get stuck on your essay or can’t figure out how to organize your thoughts, see our handout for writing an analytical essay .

Still wondering “how do you write an analysis paper”? Let see how to write an analysis as a part of an academic writing exercise.

How to write an analysis paper – step by step guide on how to set up an analysis paper

Now that you have decided to write an analysis paper or a college analysis essay, you might be wondering how to start or where do you begin. There are many different ways on how to start off an analysis essay, but the best approach involves answering a certain number of questions on your topic. Some instructors prefer that you explicitly state these questions in the introduction. However, others require that they be implicit – available for readers to discover within the text of the paper itself.

An analysis essay is centered about an issue being discussed by academic communities and/or societies and it consists of two parts: a presentation of information and discussion about this information with reference to some cognitive tools (for example: statistics ) from professional literature and practical experience. This kind of writing does not tell people what to think about the issue; instead, it invites them to consider what evidence they have, what they already know about the subject and how this evidence compares to other information they might possess. 

An analysis paper should approach a topic from different angles of thinking: for example, psychological or sociological perspectives. It is also advisable to use some outside sources in your analysis essay, if you feel that they are appropriate for the particular situation. You can find these resources on the Internet as well as at your school library. You may even want to consult with an instructor when unsure about whether a resource will be considered appropriate by your peers.

The purpose of writing an analysis essay is two-fold: (1) to formulating provisional (provisional) conclusions and/or (2) add new ideas into academic discussions.

Your analysis essay should present a positive statement about your topic and offer an objective summary of the argument. The purpose of analysis papers is to explain why you agree or disagree with a specific point of view on your topic by analyzing three major elements of any argument: claims, evidence, and reasoning. 

An analysis essay is a way in which students can demonstrate their understanding of certain texts (articles, books or even lyrics). According to some teachers’ opinions this type of academic writing allows a student to have an opportunity to make his own opinion about the particular subject. This type of academic essay presents the author’s attitude towards material he analyses – whether it is written by someone else or by him-/herself.

For example, while studying different sociological theories of crime, a student can select one theory and show what evidence this theory has to support it; which positive sides and negative sides of this theory exist; how other sociologists who study the same issue respond to that theory.

In real life, writing analysis papers could be related to some professional practice when a manager, for example, needs to make decision about something based on certain information he received from someone else. According to some literature, an analysis essay can develop core critical thinking skills which are very important for professionals in every area.

For example, while studying different approaches toward human personality development you can compare them using argumentation method developed by Aristotle over 2 thousand years ago – counter argumentation.

Counter argumentation is a method of formal argumentation whereby one party (the proponent) makes an assertion and the second party (the opponent) replies, attacking the argument with a counter-claim that invalidates it.

In your analysis essay you can describe both parties’ arguments in detail and then state conclusion what approach to human personality development is more appropriate for nowadays or why there isn’t such thing as “best approach” and why we need both approaches to study acceptable level of human development.

Presenting your ideas using this method will not only help you to formulate solid thesis statement but also will take less time “to do something” than if you would write everything without any plan. It can also help you to expand thinking skills.

In some cases, writing an analysis paper is the only way to show how you can actually understand what you are studying. Some teachers’ opinion is that those students who have difficulties with analyzing information are not going to be able to write research papers or dissertations and therefore they will never get admitted in graduate schools.

And now let’s look at how this type of academic writing is different from other types:

A research paper consists of several facts, observations and arguments which support thesis statement. It differs from a literary review essay because it focuses on original ideas derived from first-hand research, rather than secondary sources such as books or articles. Research papers may contain elements of literature reviews but their main purpose is quite different; however these types of academic papers often have similar organizational and formatting styles.

A dissertation or thesis, on the other hand, is largely based on evidence, research and results of experiments performed by the author or his/her team. It is usually written in such a manner that it can be used to support further research into a particular subject. A dissertation generally contains more technical language than an average essay because its primary purpose is to formally establish a new area of knowledge for future researchers to build upon and learn from.

In fact writing any type of academic paper requires some skills – not only understanding what you are going to write but also ability to accurately express your thoughts using words as well as knowledge of grammar rules so that you would not make any mistakes. At the same time, writing an analysis essay requires different skills than other types of papers. This is a kind of paper where your opinion matters most but at the same time it has to be well-founded and supported by some arguments.

If you are going to write an analysis essay about current events or describe what social problems exists right now in your country consider following advice:

• Find some information on this topic – for example from TV news, internet etc;
• Try to think how someone else can argue against this statement – maybe somebody would say that something completely opposite happens? Think about counter arguments! ;
• After doing that try to formulate your opinion about that topic or issue.
• Find some arguments and facts that would support this opinion. It is better to find more than two arguments because if you choose one strong argument you can easily be attacked with counter-argumentation which might make your whole suggestion look not very good;
• Now it’s time to formulate your thesis statement – do it before writing any further! Try to think how big problem is in fact considered, what are the causes of these problems etc (do remember we’re talking about analysis essay here so try to provide as much information as possible!).
• Start using all gathered resources – maybe some statistics, maybe quotes from TV news or books, maybe opinions of famous people. Just use everything you have to support your opinion and try to be as logical as possible.
• It is very important to provide credentials for each statement you have made. This kind of paper requires different style of writing from other papers because it needs some evidence in order to show that this analysis is not just author’s own point-of-view but actually well-founded claim supported by facts (or at least, strong opinions backed up with some arguments). The majority of students make a mistake when they simply add “I think” or “some researchers believe” into their sentences – this essay does not need these phrases. You have to substantiate your claims! If there are no proofs provided all readers will assume primary source;
• Make sure to cite all sources of information you have used otherwise the readers will mark your paper as plagiarism. However if in most cases this type of essay is rather similar to research papers there are some differences between them. Having some experience in writing analysis essays I want to say that these two types of papers differ not only according to their formatting style but also due to analysis essay outline structure!

References: Analysis Paper Writing Sources

Here are some of the best resources that you can use together with this guide to write a good analysis paper for college writing assignments.

• Business The Article Analysis
• Writing a Literary Analysis Paper- Germanna Community College
• Purdue – Organizing your analysis
• A Process Approach to Writing Research Papers – UC Berkeley
• Sourtherneastern edu – Critical analysis

Related analysis resources include:

• Public health policy analysis essay
• Literary analysis essay
• Rhetorical analysis essay
• Process analysis essay
• Critical analysis essay
• Statistical analysis essay
• Character analysis essay
• ad-analysis essay
• Argument analysis essay
• Poem analysis essay
• How to write an analytical essay
• How to write a personal analysis essay
• cultural analysis essay
• causal analysis essay
• financial statement analysis paper

and many more kinds of analysis papers. Feel free to reachout for professional analysis writing services – Contact our write my essay for me cheap or do my homework for cheap services for faster and cheap online homework writing help .

Good analysis essay structure – analysis paper format example 

If we take a look at typical format for writing college/university analytical paper it would be the following:

In order to write a good analysis essay following steps should be fulfilled:

• Introduction – here you need to formulate thesis statement, provide some background information, main idea and provide objective for the essay.
• Body paragraphs – each body paragraph represents different argument or idea that supports your essay thesis statement . Each paragraph should have its own topic sentence and a few sentences with explanations and reasons why these arguments are relevant to the main idea of this paper. It is not necessary to write introduction for every single paragraph but it would be wise if you do because then readers will understand where your author’s thoughts go; Remember, stick to the topic sentence! It is often considered as a mistake when in fact it is not so! For example consider following passage: “A lot of people think that smoking can cause lung cancer but other scientists say that besides genetic predisposition there are no further factors contributing to tumor formation.” First thing first, this is not a very good example of “paragraph” discussion because there is only one sentence that talks about the paragraph topic and this sentence, besides having no logical connection to the previous passage, has nothing to do with the essay topic. This sentence had been written as an addition which is why we consider it to be an extra part in the text;
• Conclusion – here you should sum up all your thoughts and draw some final conclusions. You can also make recommendation what should happen next or how things could be improved. And that would be all! If you need any further help on writing analysis essay ordered by experts just contact us and we’ll try our best to fulfill your needs!

That is a simple analysis paper format example, another example will be shared below with the appropriate links to analytical essay outline and analytical essay examples .

Analysis essay introduction: how to write an introduction for an analysis paper

If you are a student in high school, college or university writing your first analysis essay is something that may be quite confusing for you.

As an academic analysis paper is bit different than other ones and requires some practical experience of working with it.

It would be good if our service helps you to avoid some mistakes while learning how to write an introduction for an analysis essay.

Here I’m going to suggest several rules which will help you to compose an outstanding introduction for your analysis paper;

• Determining the purpose of this type of paper – when students learn how to write an introduction for study analysis essay they often make mistake by trying to look at it as another regular term paper. Well, it’s not! The main difference between any term paper and essay lies in the purpose of writing them. Analysis paper has one goal – analysis of qualitative or quantitative data. The main purpose of analysis papers is to find out some conclusion based on this analysis. That’s why this type of essay requires an introduction which will provide the reader with enough information about what kind of research were used, the way you came to your conclusions and last but not least additional information about how reliable those conclusions are;
• Providing enough background for your topic – in order to write a good analytical introduction it would be wise if you describe as many sources as possible. For example if you have already read multiple books concerning the same subject or if there are several researches published online that could shed some light on your topic, then it would be good if you mentioned them right from the beginning;
• Showing how this research can be useful – analysis essay is different than any other type of essay i.e. compare & contrast essay , narrative essay , reaction paper , and others. In most cases when students write their analysis papers they want to find out some conclusion based on the analysis which will help them or someone else in making better decisions in future;
• Introducing an overall idea of your research – when you work on your analysis essay introduction make sure to include all of the above mentioned information.

Analysis essay structure – How to format an analysis paper outline

At this stage we recommend using some kind of outline as it will help you to keep everything in its proper place while writing an analysis essay. Here is a basis structure of an analysis essay paper.

Please note that this analysis paper outline might be different from your professor’s.

Make sure you follow your teacher’s guide for a higher mark. This is an example analysis paper outline:

• Introduction – It is the essay introduction where where you sum up all your thoughts and come to a conclusion what are the key points that must be discussed later;
• Materials & Methods – these lines are required when doing experimental researches, whereas for other types of research such as descriptive or explanatory you may skip this part;
• Results – any type of research requires results which must be described in one section only! Don’t mix data with conclusions drawn from them otherwise it will not only confuse your reader but it may also lower the value of your work;
• Discussion – this is the place where you describe why you come to those conclusions or what could be done better. It’s recommended that you should use some kind of outline to prevent rambling, leaving some points out and keeping everything ordered and clear for your reader;
• Conclusion – don’t forget to leave a short essay conclusion here where you tell about main key ideas mentioned earlier in your analysis essay.

Conclusion: how to write an analysis essay conclusion

Students often have problems with how to end their essays. Here you will find some useful tips on how to finish writing an analysis paper:

• Make sure that your conclusions are supported by the information provided earlier in the introduction;
• Try to avoid using phrases or sentences which repeat what is already said;
• Use attractive and expressive words when concluding your essay, e.g. “in my opinion” or “on the other hand” etc.;
• Never leave out a short conclusion as it’s always good if a reader can read one final paragraph before he puts down your paper for ever;

If you want to write efficient analysis essay then follow our step-by-step instructions mentioned above! They will help you to not only finish your paper but also write a well-structured work with clear argumentation and nice flow of ideas.

Don’t forget that it’s quite easy to get stuck on any stage from writing an introduction to conclusion.

If you’re unable to figure out what is going wrong or how to make your essay better simply use our instructions above which are based on years of experience in writing analysis essays for college students!

Essay Writing Tips: How to write an issue analysis essay 

If you have been asked to write an issue analysis essay, then you may find it hard to plan and write your paper. Therefore, if you want to understand how to do a good analysis essay, here are several essay writing tips that will help you:

Step 1 – Plan first what type of issue analysis essay you will need

First of all, create an outline for your paper. You should have strong introduction followed by paragraphs that discuss the topic at hand. If you don’t know how to start your paper or where to begin from, then there is nothing strange about it because many students face such problem when writing a new kind of work. But if you still can’t cope with creating new ideas or putting them into words, make use of our assistance! Click here to place your order there !

Step 2 – Use a lot of support examples

It is one thing to know the subject. However, it is quite another to understand what you will be writing about in your issue analysis essay. It means that if you want to write an ideal paper, you have to take some time thinking how all information in your head can be used properly . You may ask yourself questions such as: “What other example from my life or reading could illustrate this point?” Example will show that through case study/s we can easily see what happens when something goes wrong. Or also, as well as showing what could happen if things go right with an idea or method. And so on. This shows the reader how relevant the topic is to their own life/ studies.

Step 3 – Be persuasive, and try not to get bogged down by the details

If you want your issue analysis essay to be perfect, then it has to convince your reader that the side you are taking in the argument is right and correct . You can do it depending on what kind of paper you have been assigned with. For example, for a persuasive essay, provide facts and statistics to back up every assertion made in the body paragraphs. This will allow readers to see that your ideas logically follow from each other as well as supporting each other . If you were asked for analytical paper instead – just look deeper into an issue using different kinds of sources such as books, journals or interviews. And don’t forget to use direct quotes and statistics if you can.

Step 4 – Use examples that will support your point of view, but without sounding biased

People who are not familiar with the topic may find it hard to understand what a particular example is trying to prove and why would they need to understand with all details of an issue. Avoid using general statements like “This problem is terrible” or “All students must know better.” Such phrases don’t help much in writing a good paper . Although there are those who do it on purpose, this won’t get you far in academic writing either. If you want your issue analysis essay to be perfect, then it has to convince your reader that the side you are taking in the argument is right and correct. You can do it depending on what kind of paper you have been assigned with. 

Step 5 – Try not to overdo your issue analysis essay

Your reader may get confused when you include too much information in one paragraph or even a paper. So if you want to learn how to write an issue analysis essay, then don’t try to put everything that comes into your mind! Make sure to make all the important points connected so there are no holes in the argumentation. If necessary, use sub-headings, bullet point lists or bolded phrases to help readers distinguish between different points more clearly. The result should be an easy-to-follow and understand essay that will impress the grader.

Step 6 – Use sources to support your arguments

If you want to write a good issue analysis essay, then do not forget about referencing your sources correctly at the end of the paper. If there is no need in citation, don’t use it . This shows the reader how relevant the topic is to their own life/ studies. You should include quotes from “academic” books, journals or reputable newspapers if possible. And remember: always try to cite everything properly so it won’t be hard for anyone check what exactly you said and where you got this information from! If necessary, use sub-headings, bullet point lists or bolded phrases to help readers distinguish between different points more clearly.

Step 7 – Proofread your issue analysis essay and ask a trusted friend to proofread it as well

The last thing you should do before submitting your paper is read through the text again yourself . If there is no need in citation, don’t use it . Perhaps you’ll find a grammar mistake or decide that an example would be better somewhere else in the paper. Your reader may get confused when you include too much information in one paragraph or even a paper. So if you want to learn how to write an issue analysis essay, then don’t try to put everything that comes into your mind! Make sure to make all the important points connected so there are no holes in the argumentation. If necessary, use sub-headings, bullet point lists or bolded phrases to help readers distinguish between different points more clearly. The result should be an easy-to-follow and understand essay that will impress the grader.

Custom analysis essay help by professional writers online

Are you in need of expert opinion concerning your sample analysis essay topics? Then we can offer some assistance as we provide subject matter experts’ assistance via our online essay writing service ! It means that here at Tutlance you can order quality analysis essay writing help online, receive completed work within the shortest possible time and save your money!

Our analysis essay writing service gives a change to receive quick help with any of the steps followed when writing an analysis essay. Each step is essential for completion of your paper;

• Ordering – this stage is where you select what type of service (analysis essay sample or some other kind), length, deadline as well as level of quality required by you. All these factors will have significant impact on the price which you have to pay for your task;
• Starting work – after getting all information needed we start working with no delay regardless of whether it’s 3 am or 00:01am. Here our experts begin preparing analysis essay introduction, continue developing body paragraphs and end up writing conclusion in the shortest time possible;
• Delivery – we deliver papers via email or on our online tutoring website in a form of .doc, .docx for free;

The process to order an essay online is easy and simple as you should only fill in order form by clicking here .

Be sure to provide all necessary information correctly while placing an order to avoid any further inconveniences!

What to write an analysis paper on?

Wondering what to write an analysis paper on? Our tutors can help you discover great analysis paper topics depeding on your academic level. Whether you are looking for college analysis paper topics, high school analysis essay topics or even dissertation and thesis analysis ideas, we are the right team for the job. All you need to do is to connect with an analysis essay writer and get a great topic for your essay in the shortest time possible.

Guarantees you will get from us when ordering your analysis essay:

As an academic writing homework marketplace, All questions posted on our assignment writing help service comes with a couple of guarantees namely:

• We are native English speakers who can write analysis paper with flawless grammar;
• Our writers have deep knowledge of their subject plus they possess vast experience working with students from many countries around the world;
• When it comes to price we are undoubtedly among the most competitive services available at present.
• We are able to write any kind of paper no matter how difficult or unclear your idea is.
• Hardly anyone can compare with us when it comes to low prices, quality of work and friendly approach!

Now, if you have already read several analysis essays but still find it difficult to master this skill feel free to ask me all the questions and I will be more than happy to help you!

Stop struggling with guides on how to write an analysis while you can hire a professional essay writer or online writing tutors to write a perfect analysis essay sample for you.

Author: tutlance

• 250 word essay
• How to write a claim of value essay
• How to title an essay
• 200 Word Essay
• Write a business proposal cover letter
• 300 word essay

How to write an interview paper

How to write a film analysis essay with examples, related guides, writing effective essays: tips for students, how to write an effective essay in 5..., how to write a summative essay | definition,..., how to write an ethics essay, topics, outline,..., how to write a film analysis essay with..., background information essay, dialogue essay, short story essay, discussion essay, how to shorten an essay, how to write a photo essay – examples..., proper heading for essay, enduring issues essay, writing a commentary essay, attention grabbers for essays, essay draft: how to write a draft essay, how to polish an essay for a better..., peel paragraph, how to write a position paper essay |....

• Homework Help
• Online Tutors
• Essay Writing Services
• Do My Math Homework
• Assignment Help
• Take My Online Math Class
• Take My Exam
• Take My Test
• Take My Course
• Dissertation Services
• Essay Introduction
• Essay Thesis Statement
• Essay Hooks
• Essay Conclusion
• Essay Revision
• Essay Title
• Essay Format
• Essay Outline
• Essay Cover Page
• Essay Topics
• Classification Essay
• Analytical Essay
• Cause and Effect Essay
• Expository Essay
• Descriptive Essay
• Argumentative Essay
• Compare and Contrast Essay
• Definition essay
• Narrative essay
• Persuasive essay
• Reflective essay
• Proposal essay
• Process essay
• Reflection Paper
• Evaluation Essay
• Exemplification essay
• Illustration Essay
• Informative essay
• Review essay
• Scholarship essay
• Dissertation
• Annotated Bibliography
• Research Paper
• Research Paper Topics
• Position Paper
• Speech Writing
• Summary Writing
• Story writing
• Swot Analysis
• Resume Writing
• Business Plan
• Grant Writing
• Book Writing
• Personal Statement
• Writing Process
• Research Process
• Online Tutoring Subjects
• Become a Tutor
• Forgot Password?

Writing with MLA Style

Congratulations to the students whose essays were selected for the 2023 edition of Writing with MLA Style! Essays were selected as examples of excellent student writing that use MLA style for citing sources. Essays have been lightly edited. 

If your institution subscribes to MLA Handbook Plus , you can access annotated versions of the essays selected in 2022 and 2023. 

Writing with MLA Style: 2023 Edition

The following essays were selected for the 2023 edition of Writing with MLA Style. The 2023 selection committee was composed of Ellen C. Carillo, University of Connecticut (chair); Rachel Ihara, Kingsborough Community College, City University of New York; and Tarshia L. Stanley, Wagner College.

Caroline Anderson (Pepperdine University)

“ L’Appel du Vide : Making Spaces for Sinful Exploration in The Strange Case of Dr. Jekyll and Mr. Hyde ”

Hunter Daniels (University of South Carolina, Aiken)

“Biblical Legalism and Cultural Misogyny in The Tragedy of Mariam ”

Aspen English (Southern Utah University)

“Putting the ‘Comm’ in Comics: A Communication-Theory-Informed Reading of Graphic Narratives”

Raul Martin (Lamar University)

“The Book-Object Binary: Access and Sustainability in the Academic Library”

Grace Quasebarth (Salve Regina University)

“Finding a Voice: The Loss of Machismo Criticisms through Translation in Isabel Allende’s The House of the Spirits ”

Writing with MLA Style: 2022 Edition

The following essays were selected for the 2022 edition of Writing with MLA Style. The 2022 selection committee was composed of Ellen C. Carillo, University of Connecticut; Jessica Edwards, University of Delaware (chair); and Deborah H. Holdstein, Columbia College Chicago.

Kaile Chu (New York University, Shanghai)

“Miles Apart: An Investigation into Dedicated Online Communities’ Impact on Cultural Bias”

Sietse Hagen (University of Groningen)

“The Significance of Fiction in the Debate on Dehumanizing Media Portrayals of Refugees”

Klara Ismail (University of Exeter)

“Queering the Duchess: Exploring the Body of the Female Homosexual in John Webster’s The Duchess of Malfi ”

Yasmin Mendoza (Whittier College)

“Banning without Bans”

Niki Nassiri (Stony Brook University)

“Modern-Day US Institutions and Slavery in the Twenty-First Century”

Samantha Wilber (Palm Beach Atlantic University)

“‘Pero, tu no eres facil’: The Poet X as Multicultural Bildungsroman”

Writing with MLA Style: 2019 Edition

The following essays were selected for the 2019 edition of Writing with MLA Style. The 2019 selection committee was composed of Jessica Edwards, University of Delaware; Deborah H. Holdstein, Columbia College Chicago (chair); and Liana Silva, César E. Chavez High School, Houston, Texas.

Catherine Charlton (University of King’s College, Nova Scotia)

“‘Coal Is in My Blood’: Public and Private Representations of Community Identity in Springhill, Nova Scotia”

Alyiah Gonzales (California Polytechnic State University)

“Disrupting White Normativity in Langston Hughes’s ‘I, Too’ and Toni Morrison’s ‘Recitatif’”

Meg Matthias (Miami University, Ohio)

“Prescriptions of (Living) Historical Happiness: Gendered Performance and Racial Comfort in Reenactment”

Jennifer Nguyen  (Chaminade University of Honolulu)

“The Vietnam War, the American War: Literature, Film, and Popular Memory”

Emily Schlepp (Northwest University)

“A Force of Love: A Deconstructionist Reading of Characters in Dickens’s  Great Expectations ”

• Open access
• Published: 02 November 2023

A lowered threshold to partnerships: a mixed methods process evaluation of participants’ experiences of a person-centred eHealth intervention

• Matilda Cederberg 1 , 2 , 3 ,
• Emmelie Barenfeld 1 , 2 , 4 ,
• Lilas Ali 1 , 2 , 5 ,
• Inger Ekman 1 , 2 , 6 ,
• Anneli Goulding 3 , 7 &
• Andreas Fors 1 , 2 , 8  

BMC Health Services Research volume  23 , Article number:  1193 ( 2023 ) Cite this article

Metrics details

In order to understand pathways of complex interventions, the Medical Research Council has suggested that process evaluations should be conducted alongside randomised controlled trials (RCTs). This paper presents a mixed methods process evaluation of a complex, person-centred eHealth intervention for persons on sick leave with common mental disorders.

The aim of the study was to explore participants’ experiences of a person-centred eHealth intervention and illuminate meaningful activities and processes.

Participants were recruited from the intervention arm of an RCT (n = 102). Questionnaires on perceived meaningfulness of the overall intervention and intervention activities were sent to participants on two occasions, after 3 and 6 months, and semi-structured interviews were conducted with a purposeful sample of 15 participants in the intervention group. Questionnaire data were analysed using descriptive statistics, and interview data were analysed using qualitative content analysis. The quantitative and qualitative data strands were integrated at interpretation.

At both follow-ups, a majority of participants reported that the intervention was fully or partly meaningful and that the most meaningful activity was the phone calls with health care professionals working in the intervention. In the qualitative analysis, three categories describing participants’ experiences of the intervention were formed: Acknowledgment in a disconcerting situation , Finding ways forward and Unmet expectations . A synthesis of quantitative and qualitative findings resulted in the overarching theme of meaningfulness as constituted by a lowered threshold to partnerships: support within reach, when needed .

Experiences of meaningfulness of the intervention were constituted by a lowered threshold to forming care partnerships, in which support was within reach, when needed. If the content of the intervention was not in accordance with individuals’ needs or expectations, access alone did not suffice to constitute meaningfulness.

Trial registration

ClinicalTrials.gov; NCT03404583; 19/01/2018.

Peer Review reports

In Sweden and other high-income countries, the past decades have shown an increase in sick leave related to common mental disorders (CMDs) such as depression, anxiety syndromes and stress-related mental illness [ 1 , 2 , 3 ]. Due to their high prevalence in a general population, primary mental health care, where the majority of patients with these conditions seek help [ 4 ], has been struggling to allocate the necessary resources to give patients timely and effective care [ 5 ]. Developing eHealth alternatives has been one way of improving access to care, for example, in the form of digitalised self-guided treatments, telepsychology or as part of stepped-care programmes [ 6 , 7 ]. The use of mental health apps has also demonstrated the potential to improve health outcomes for persons with depression, anxiety disorder or substance abuse, and to improve treatment availability [ 8 ]. The majority of evaluated eHealth services for persons with CMDs build on cognitive behavioural therapy (CBT) and primarily focus on symptom improvement rather than outcomes related to sick leave, such as return to work [ 9 , 10 , 11 ]. By building on the premise of enabling patients to manage more of their condition on their own, it has been argued that eHealth services are also resource-effective [ 10 , 12 ].

Person-centred care (PCC) is an approach to health care advocating that care should be co-created in partnerships between healthcare professionals and patients, and if warranted, these partnerships should extend to include other persons of relevance to the patients’ care process, such as other professional contacts, family members and friends [ 13 , 14 ]. Partnerships are characterised by sharing of information and decision making, trust and mutuality. They are based on interpersonal and communicative processes in which patients’ experiences are essential [ 15 ]. In order for partnerships to be formed, patients need to be included in their care process and given the necessary space and means to participate [ 16 ]. This conviction is based in the ontological assumption that humans possess resources and that treating patients as persons entails recognising both the resourcefulness and vulnerability of each patient [ 17 , 18 , 19 ]. A defining feature of person-centred care is that the goal of health care interventions is not necessarily directed at managing the illness, but at understanding what constitutes a meaningful life for the patient and offer support in that direction [ 20 ]. This focus on a meaningful life is congruent with recovery-oriented initiatives in mental health care, which defines recovery as a deeply personal, individual process towards living a fulfilling and meaningful life even if there are limitations caused by illness [ 21 ].

PROMISE: a person-centred intervention for patients on sick leave with CMDs

A research project (PROMISE) was launched in 2018 in an eHealth setting with the aim of operationalising the ethics of PCC in an intervention for persons on sick leave with CMDs [ 22 , 23 ]. The intention was to evaluate whether the person-centred eHealth intervention offered in addition to usual care at the patients’ primary care centres could support patients in their sick leave process and influence self-efficacy by identifying and mobilising personal and social resources and support. Support can be conceptualised as an individual’s perception that supportive resources, such as others providing information, services or emotional reassurance, are available if needed [ 24 ].

In order to better understand the pathways of intervention programmes, especially when they entail levels of complexity, the Medical Research Council (MRC) has suggested the need to conduct process evaluations alongside effect studies [ 25 ]. Process evaluations are valuable when seeking to understand whether an intervention is working as expected and to explore potentially unexpected mechanisms, and to capture experiences of the intervention [ 25 , 26 ]. A few studies have reported on patients’ experiences of eHealth interventions for CMDs. For example, in a process evaluation of a web-based blended intervention for employees on sick leave with CMDs, patients reported overall satisfaction but needed more support from health care professionals (HCPs) [ 27 ]. A meta-synthesis on participants’ experiences of digital health interventions also found that personal support from HCPs was highly valued and seen as a component influencing the intervention’s overall successfulness, as it enabled personalisation of care [ 28 ]. Similar results were found in a study on experiences of an internet mediated CBT intervention for depression [ 29 ]. To our knowledge, no one has yet explored experiences of interventions for patients with CMDs grounded in person-centred ethics. In the PROMISE intervention, the anticipated core component was the partnership, whose potential as support lies in how it is experienced by the persons involved, not in the delivery of a certain procedure [ 14 ]. Therefore, the aim of the present study was to explore participants’ experiences of a person-centred eHealth intervention and illuminate meaningful activities and processes.

Study setting: the PROMISE intervention

The PROMISE project recruited patients on sick leave due to CMDs, including depression, anxiety syndromes or stress-related mental illness (adjustment disorder, acute stress reaction or exhaustion disorder) from nine primary health care centres in a larger city in Sweden. To be included, sick leave had to be issued by a physician and the duration of the sick leave should not have exceeded 30 days at the time of inclusion. The recruitment, randomisation and intervention processes were managed remotely from a research setting separate from the primary health care centres by dedicated health care professionals (HCPs). The final study sample included 209 participants (107 in the control group and 102 in the intervention group). Further details on the project and the RCT have been published elsewhere [ 22 ]. Participants in both groups received usual care at their primary health care centres. Usual care commonly involves meetings with a physician, and decisions on treatments and sick leave are based on individual assessment and evidence-based guidelines. This process differs somewhat for the different conditions within the CMD spectrum but often include advice on self-care, medication, CBT and meetings with a physiotherapist, rehab coordinator, occupational therapist or group treatments [ 30 , 31 ]. For participants in the intervention group, phone support from HCPs were offered on top of usual care during a period of 6 months, as well as unlimited access to a web-based platform. The intention of using a remote format for support was to enable a PCC process without requiring face-to-face meetings. See Table  1 for an overview of intervention content.

HCPs from different disciplines (nursing, psychology, physiotherapy and occupational therapy) with various experiences of working with CMDs and PCC conducted the intervention. They took part in a half-day education session on symptoms, treatment and care for CMDs led by psychologists and physicians, were introduced to the philosophical underpinnings of PCC by scholars in the area, and participated regularly in meetings where they together with each other and experts in PCC could discuss and practise person-centred communication.

During the scheduled phone conversations, HCPs encouraged the patients to narrate how they experienced their situation. With their experiences as a departure point, they discussed patient’s goals and a plan to reach them, and the HCPs were mindful of identifying personal and social resources of value in each patient’s recovery process. This agreement was documented in the form of a personal health plan, which was uploaded to the web-based platform and served as a personal plan guiding the subsequent intervention process. The conversations used a narrative approach in that the patients were encouraged to narrate their experiences related to their illness and sick leave period and collaborate actively in their care by providing the contextual information central to the health plan and tailored support. After the initial phone conversation, follow-up calls were scheduled in agreement.

The patients could access the platform using any device with an internet connection and a web browser. On the platform, patients could make daily ratings on symptoms and well-being, monitor their symptoms and keep private notes. They could seek information on their condition through links to other web pages. The platform was also intended to facilitate communication and sharing of information between the patient and the intervention HCPs as well as the patient’s extended network. Patients could engage their supportive network, such as other health care contacts, family members or workplace representatives, by inviting them to the platform in order to keep them informed. Patients could manage how much of the content each invitee could view, and they could allow or remove access independently.

Data collection

The present study builds on questionnaire data and semi-structured interviews. To explore participants’ experiences of the intervention, a concurrent quantitative + qualitative mixed methods design was used, with quantitative and qualitative strands integrated at interpretation [ 32 , 33 ].

Participants were recruited from the intervention arm of the RCT study (n = 102). Data were collected synchronously and consecutively. Quantitative data were gathered at 3 and 6 months after inclusion using questionnaires. The questionnaires contained three items on perceived meaningfulness of the support and intervention content, previously published by Barenfeld et al. [ 34 ]. In the questionnaire, meaningfulness is conceptualised as activities and processes perceived as meaningful in relation to a personal goal.

Participants were asked to rate whether they found the intervention overall to be a meaningful support on a 5-point Likert scale with the following answer options: fully agree, partly agree, partly disagree, fully disagree, do not know (item 1).

They were then presented with an 11-item list of the intervention’s content (Table  3 ) and asked to mark which, if any, of the content they found meaningful ( item 2 ).

An open-ended question on which, if any, content they found most meaningful ( item 3 ).

Qualitative interviews were used for in-depth exploration of experiences [ 25 , 35 ]. Semi-structured interviews were conducted with participants in the intervention arm of the RCT, recruited consecutively throughout the study period upon individual completion of the 6-month phase of active intervention. Eligible participants were contacted via phone by the first author. During the period of recruitment, 14 participants did not respond and 2 declined to participate; 17 agreed to participate, but at the time of the interview, 2 did not respond. A purposeful sampling procedure was conducted to ensure heterogeneity in gender, age, diagnosis and overall positive and negative experiences of the intervention, assessed through dichotomisation of item 1 in the post-intervention questionnaire. Responding that the intervention was fully or partly meaningful was considered an overall positive experience, whereas fully or partly disagreeing or not knowing were considered an overall negative experience. In the final sample of 15 participants, 4 had negative experiences of the intervention (fully, partly or did not know), and 11 had positive experiences (fully or partly). Of the 15 participants, 4 were men and 11 were women, and they were between 29 and 59 years of age. For further details, see Table  2 .

The first author conducted the interviews, each lasting between 25 and 64 min. Participants were invited to choose whether to be interviewed in person or via telephone. All but one participant chose the telephone option. A semi-structured interview guide was developed assessing experiences of the intervention as a whole as well as its content and composition (supplementary material). All interviews started with asking the participants to describe how they were doing at the time they got access to the intervention and how they felt about what the intervention offered. Thereafter, they were asked to describe what it was like for them to take part in the intervention, how they experienced the phone calls and the platform and their overall process of recovery.

Data analysis

For the questionnaire data, descriptive statistics were used to illustrate responses on the intervention’s meaningfulness after 3 and 6 months. The descriptive statistics were calculated by the first author using SPSS. Data on most meaningful content were gathered either from participants who had listed only one activity in the question containing multiple options (item 2) or through participants’ answers to the open-ended question on which activity they found most meaningful (item 3). As this item was open-ended, after all answers had been read through, they were sorted into one of the following five categories: phone communication; rating & monitoring symptoms; health plan; using links; or two or more activities. The ‘two or more activities’ category comprised answers where participants explicitly stated that both activity a and activity b were most meaningful, or answers where participants indicated that a combination of activities was most meaningful, for example, talking with the HCPs and making a health plan.

The interviews were analysed using qualitative content analysis according to Graneheim and Lundman [ 36 , 37 ]. An inductive approach was chosen to explore participants’ experiences of the intervention support. To begin, the first author read through all the transcripts several times to get an initial grasp of the content. Meaning units were then identified on a manifest level throughout all transcripts using NVivo and sorted into content areas. Thereafter, the meaning units were condensed, and the condensations were abstracted into codes. All codes were then compared in terms of differences and similarities and sorted into main categories and subcategories [ 36 , 37 ]. The first author conducted the initial categorisation, which was developed in collaboration with the last author. The categories were then discussed several times together with all authors, including excerpts from the transcripts to ensure transparency of and closeness to data. In the presentation of findings, quotes from the interviews are used to express the participants’ voices and to illustrate the categories. Each interview participant was allocated a number between 1 and 15 to which they are referred to in the result section.

The data from the questionnaires and the data from the interviews were analysed separately and the results were integrated at interpretation level [ 32 , 33 ]. The integration of findings was performed in a last step of the analytic procedure in a synthesis of both quantitative and qualitative findings. The synthesis was performed as an interpretation of the material as a whole in the form of an overarching theme on meaningful activities and processes in the intervention and what enabled or blocked participants’ experience of the intervention as meaningful.

Meaningfulness of the intervention

Altogether, 84 of the 102 participants in the intervention group responded to the questionnaire at the 3-month follow-up (n = 18 missing), and 81 responded at the 6-month follow-up (n = 21 missing).

At 3 months, 41% (n = 34) responded that the intervention overall was fully meaningful, and 43.4% (n = 36) responded that it was partly meaningful. Scheduled phone communication was reported as meaningful by 86.9% (n = 73), and 70.8% (n = 46) reported the phone communication to be the most meaningful part of the intervention overall. The second-most-common ‘meaningful’ rating was given to ‘Reading health plan’, as reported by 50% (n = 42) of respondents (Table  3 ).

At 6 months, the proportion of participants fully agreeing that the intervention overall was meaningful had decreased to 33.3% (n = 27), and the proportion of participants fully disagreeing that the overall intervention was meaningful had increased from 3.6% (n = 3) at 3 months to 6.2% (n = 5). A dominant majority of 77.7% (n = 63) still reported that they found the intervention fully or partly meaningful, and 80.2% (n = 65) found the phone communication to be a meaningful part of the intervention. The proportion of respondents rating ‘Reading health plan’ as meaningful had decreased from 50 to 38.3% (n = 31), but it was still the content second-most often rated as meaningful after the phone communication. ‘Inviting significant others’ was rated as meaningful by the fewest respondents, only 6% (n = 5) after 3 months and 2.5% (n = 2) after 6 months (Table  3 ).

Experiences of the intervention

In the qualitative analysis, three overarching categories of how the participants experienced the intervention were formed (Table  4 ). The first category, ‘Acknowledgment in a disconcerting situation’, and the second category, ‘Finding ways forward’, cover positive experiences of the intervention pertaining both to how participants perceived it and what meaning they attributed to the content and the mode of conduct in the eHealth setting. The third category, ‘Unmet expectations’, covers participants’ experiences of disappointment with and struggle to understand the intervention’s content and design.

Acknowledgement in a disconcerting situation

Intertwined with how the participants experienced the intervention was the situation they were in at the beginning and throughout the intervention period. Several described an unsettling situation where they were tired, confused, worried about the future and questioned themselves. By perceiving that their experiences were important in the phone calls with the HCPs and through receiving support which did not add to their burdens, the participants described an overall sense of acknowledgment through the intervention. This is further elaborated in two subcategories: Feeling heard and respected and Remote support as a prerequisite and relief.

Feeling heard and respected

The participants described the phone calls as conveying to them the status of someone who matters. Their thoughts and experiences were requested by the HCPs and they felt listened to, like there was time for them to finish their sentences without being interrupted or having colliding agendas steering the conversation in a particular direction. One participant described feeling like there were no ulterior motives to the conversations and that their well-being, in the long run, was the number one priority. Perceiving that their words and experiences mattered to the HCPs, and that they could express themselves freely without feeling judged, was an important recognition of the legitimacy of their needs, emotions and reactions. Being heard and respected mattered in a situation where one could otherwise feel alone and vulnerable, especially if this was their first experience of mental illness.

Talking to someone, having an extra pair of eyes on you, to me that’s what you need, and especially if it’s the first time it happens, I felt almost lost, I didn’t know what happened, what kind of illness this is, I didn’t know if there was any kind of limit, so these phone calls with the nurse, that’s really what I appreciated the most. (Participant 2)

Remote support as a prerequisite and relief

Many participants considered the remote format of support to be essential. It enabled them to participate in the intervention and to access support without having to go to appointments in person, which relieved them of significant stressors. They felt like the limited energy they experienced as a consequence of their condition was being taken seriously as the remote format removed the need for them to use scarce time and energy on the planning and travel that physical appointments required. The possibility to write a message to the HCPs through the platform between scheduled calls made it easy for them to reach out when they needed to reschedule or wanted a professional’s point of view on something, and receiving a phone call while at work, home or wherever they were lessened the demands on them and made them feel cared for and looked after.

It felt somehow like it was on my terms even if it, you have a phone appointment to attend, that’s completely fine, I don’t need to physically go somewhere and travel and be somewhere on time or take time off work or anything like that, so it’s been really nice and very good for me. (Participant 9)

Many of the participants also described how talking to the HCPs by phone instead of face-to-face made it easier for them to talk freely and lower their guard. The phone worked as a kind of shield, both against the reactions of the conversational partner and against the uncomfortable situation of putting one’s emotions on display. Seeing reactions to their words in face-to-face interactions could make them feel awkward, lose track or censor themselves. The participants also described how remaining in their own milieu made them feel less like they needed to perform and like they could more easily allow the conversation to unfold from where they were in that moment of time.

I didn’t need to focus on you [the HCP], we didn’t even need to look at each other, which I also think contributed a lot to making it much, much easier to talk, it’s just someone listening. (Participant 8)

Finding ways forward

The category ‘Finding ways forward’ covers participants’ experiences of the intervention as a support in a situation where their illness and the associated sick leave challenged them to reflect upon their lives, get an overview of their situation and to make decisions on how to act. This is further described in the subcategories: Increasing awareness, Recognising strategies to act and Making and maintaining changes.

Increasing awareness

Through the intervention, participants were provided with a forum in which to reflect upon how they were feeling and how they were progressing, something they might otherwise forget, avoid or struggle to find time to do. This reflection was encouraged in the phone calls but also in the self-rating and diary-like activities on the platform. The participants experienced that the intervention helped them untangle messy thoughts, get an overview of their situation or reflect more deeply on a particular concern. Their reflective processes were supported by the intervention HCPs, through their questions and reflections and through their mirroring of the participants’ words. The participants also described using the visualisation function of the self-ratings to keep track of how their symptoms evolved. They described how it could be difficult for them not to get carried away by their fluctuating feelings, and how seeing the progress they made allowed them to gain perspective on their feelings then and there. One participant described how she liked seeing the transformation in her graphs, starting at a low point at the beginning and moving up a notch as she started to feel better:

You made it up a notch or whatever you should call it, then I felt like you could see that in a graph. I like graphs; it suited me really well. And then maybe you went down again the next day but then at least you had… and then you could be reminded that, well, last week I was on the bottom of everything and now I’m not, so, you could, like, visualise that you were actually doing better. (Participant 4)

Recognising strategies to act

The participants described how they made use of their increased awareness through recognising actions they could take. They described how they could become aware of problems they needed to solve, imbalances in how they were prioritising their time and energy, ideas on how to organise life differently, or other directions they thought necessary to pursue as part of their recovery. When talking about such experiences, the participants mainly referred to discussions they had with HCPs during the phone calls. They described how they were encouraged to do most of the talking and how the HCPs followed up on their reflections by asking them to elaborate on their perspectives on a specific matter. They also described getting advice, information and encouragement on how to take action.

Somehow you realise, it felt like they helped you realise the questions that you had, they helped you realise the answers yourself. It wasn’t like ‘this is what we’ll do’ or ‘this is what I think you should do’ but… they helped you realise it yourself. (Participant 10)

Making and maintaining changes

The participants described how their situation required them to be active in a number of ways: active in getting the right treatment, active in making the workplace understand their situation, and active in changing their own attitudes and behaviours towards work or towards themselves. This was an ongoing process to most of them, something the intervention allowed them room to engage with. The participants described how the strategies laid out in the phone calls followed them into their everyday lives, and how an important aspect of the process was finding ways to maintain the changes, move forward and not to fall back into old habits.

I got the support I needed to move forward, otherwise you can get stuck on the same spot and, like, think you can’t manage and all that, but I felt like every time after every conversation I could take another step and it help me move forward, really. (Participant 7)

Unmet expectations

This category covers the participants’ unmet expectations of the intervention, in terms of what kinds of support they felt were lacking and what kinds of support they felt were offered but did not appreciate. Some were uncertain about the exact purpose of the intervention, and this lack of clarity confused them as to why they should engage with it and what they could expect. The category is structured into three subcategories: Expecting disease-specific guidance, Unexpected content and barriers in the design and Efforts outweighing the rewards.

Expecting disease-specific guidance

Participants described expecting the intervention to give them access to experts on mental illness who could provide them with tools, personalised advice and general knowledge about their condition. Instead, they found that they were expected to do most of the talking during the phone calls, and they received little in return from the HCPs. They felt that it was up to them to find solutions to their problems and that the phone calls offered little more than a listening ear. They also described having other needs than ‘just talking about it’, especially if they already had people around who they felt they could talk to. Some described expecting information, but they felt that they were not encouraged to ask, neither in the phone calls nor through the platform, or if they did receive information, it offered little more than they already knew. Having expected to get tools and ideas to help them deal with their problems, they were disappointed with the lack of guidance on symptom management or advice on how to deal with their condition.

I guess I experienced a lot during the conversations that there was sort of this idea that I should put my condition into words, but sometimes I could ask for tips. I wanted more guidance, but it felt like the whole idea which I understood from their answers was more like that I should talk about how I was feeling. (Participant 11)

Unexpected content and barriers in the design

Whether or not the participants found the intervention meaningful overall, they primarily associated the intervention with the phone calls and regarded the platform as an appendage whose function in the intervention was not entirely clear. They expressed that, to achieve greater unity and clarity in the intervention, the platform would benefit from changes to both content and design. Many participants indicated that they would have preferred the platform to be designed in an app format rather than as a web page. The log-in procedure was described as cumbersome and as a barrier when one had very limited energy. Some also experienced technical problems with logging in to the platform, and one participant never managed to access it. Issues with the design also pertained to particular functions of the platform. Participants wanted to use the self-rating function to track their progress, but because graphs were visualised weekly, tracking progress in a longer perspective was difficult.

And then I don’t think you could see it over a longer time period either, so this diagram could have been good or like what I figured was the primary purpose with it to, like, follow a curve where you could see that [in] the last couple of months your condition slowly got better and better, for example, but you couldn’t really do that or the diagram didn’t function that way; you couldn’t use it like I think it was intended. (Participant 5)

Some participants indicated that some aspects of the intervention were not exactly clear to them. They were unsure of what they were supposed to do and accomplish in the phone calls and on the platform, and what kind of personal gain they could expect from the intervention. For example, one participant described how she did not understand the logic behind the planning of the phone calls, which appeared to her as detached from her current needs and situation, making her question whether the planning was really intended to follow her needs or if there was another, hidden, structure:

In the beginning it was like every week and then all of a sudden it was thinned out. I think it was those kinds of things that made it feel detached because it wasn’t that anchored; I mean I was still feeling really bad. (Participant 11)

In hindsight, participants expressed that if they had understood more about the logic behind the different activities proposed in the intervention, perhaps they would have given them more of an effort. However, many felt unsure about inviting their extended network to their platform, and very few chose to do so. Either they described not seeing what good it could do, or they felt it would compromise their integrity, and they valued having a private forum in which to express their thoughts and feelings. Those who already had good support from family and workplace representatives and were communicating well with them, saw little benefit in inviting them to the platform. Equally, if they described lacking a supportive network, this also served as a barrier to inviting others as they either did not know whom to invite or did not feel safe letting people know how they were really doing.

Efforts outweighing the rewards

Some participants experienced that the intervention required more of them than it gave in return. Needing to prioritise their efforts towards what gave the greatest reward made them shy away from using parts of the intervention, or from engaging at all, when they felt that the efforts outweighed the rewards. For example, they felt discouraged from using the platform when they received so little feedback on those activities from the HCPs in the phone calls. One participant described how there was a kind of tunnel vision throughout the intervention, where so much focused on the phone calls, and that the use of the platform was forgotten by both the staff and the participant. Not receiving feedback on their ratings or other activities made some participants feel like there was no point in continuing to use the platform. Some participants also described an imbalance between their stake and the return in the phone calls with the HCPs. Talking to yet another person about their situation could be tiring, and they did not want to have to go through difficult subjects once again. Finding the time and energy to engage in yet another activity was also a source of stress for some of the participants, and they described how obstacles such as difficulty finding time for phone calls during working hours and feeling like they should take the chance to use the platform properly added to their stress.

Despite being on a level where you can barely, like I said, barely manage to wash your hair, there’s also this kind of need to be good. I have this good girl mentality which made me feel like now that I’ve been chosen, I got the chance to be a part of this, I felt, like, this pressure on myself to log in and use the platform. (Participant 8)

Interpretative synthesis: a lowered threshold to partnerships - support within reach, when needed

An interpretative synthesis of the quantitative and qualitative findings resulted in the overarching theme of meaningfulness as constituted by perceiving a partnership, characterised by the sensation of having the support of a professional within reach, when needed. While physical appointments in regular care required a lot from the participants, the remote format of the intervention was considered suitable to their needs, as it lowered the threshold to receiving professional support. Support within reach also covers the relief of evading face-to-face appointments without compromising the sense of being cared for and looked after by empathetic and competent professionals, mainly through the connection established and maintained in the phone calls. In the descriptive statistics, no other activity came near the meaningfulness of the phone calls with HCPs. This activity was regarded as meaningful by more than 80% of intervention participants at both follow-ups, and it was the activity reported as most meaningful when participants were asked to choose. Furthermore, the possibility of contacting HCPs through the platform and by phone, between scheduled calls, was also reported as meaningful by 20–30% of intervention participants, further strengthening the interpretation of ‘within reach, when needed’ as a central mechanism in the intervention.

However, it appears that easy access to HCPs only covers part of the experience of meaningfulness. If participants did not perceive the support as relevant in response to their particular expectations and needs, then access did not matter. We found that a key to meaningfulness was thus the establishment of partnerships, which both acknowledged the patient’s situation and involved the HCPs’ guidance and encouragement to find ways forward. Achieving partnerships which recognised the participants’ needs and met their expectations could thus be interpreted as central to the experience of meaningful support. Conversely, a failure to achieve proper recognition of and response to the patient’s needs could be understood as blocking meaningfulness.

This mixed methods analysis used questionnaires and interview data to explore participants’ experiences of a person-centred eHealth intervention. It is important to understand what constitutes meaningfulness for patients with CMDs, both in regard to recovery [ 20 , 21 ] and when designing health care support, also in order to avoid engaging patients in activities which add to their stress or are perceived as a burden. The results of the present study indicate that for a majority of the participants, the person-centred intervention was perceived as meaningful. In order to be a meaningful support, it is important to clarify expectations and needs, and to ensure that purposes of proposed activities are transparent and appreciated.

The identification of intervention processes recognised by participants as meaningful to their experience of the intervention, and beyond, in their recovery and sick leave process can contribute to understanding how PCC interventions work, or why they do not work as intended. The integration of data strands resulted in an overarching interpretation of the intervention’s meaningfulness as constituted by perceiving a partnership, characterised by the feeling of having the support of a professional within reach, when needed, through the eHealth format. Furthermore, we conclude that the most meaningful processes of the intervention took place in the phone calls, in which positive experiences of acknowledgment and reflective, change-oriented processes could occur. In accordance with literature describing partnerships in PCC, this could be understood as another testament to the importance of establishing an emotionally supportive, trusting relationship building on a common understanding [ 15 , 19 , 38 ]. Moreover, the findings of the study add to prior evidence that such relational qualities are not only possible in remote settings but are sometimes even facilitated outside of the traditional health care environment [ 39 ]. Our findings are also congruent with prior research suggesting that personalisation and access to professional support are valued features of eHealth interventions for CMDs [ 27 , 28 , 29 ].

However, despite the intention to co-create support according to each participant’s experiences and needs, some participants indicated that the intervention did not correspond to their expectations or met their needs. A recent study evaluating a related intervention among people diagnosed with chronic conditions highlighted similar challenges with unmet expectations due to unclarity of roles and unspoken expectations about what each partner can contribute to the partnership [ 34 ]. This suggests that in order for PCC interventions to be experienced as meaningful, it is important to make sure that patients understand why and how the intervention work and what they are intended to achieve, and to openly communicate expectations of both patient and HCPs to limit the risk of failing to meet needs because they are unrecognised. Additionally, it is worth considering that even if needs are recognised, they can be in collision with the intervention’s agenda or challenging to combine with the ethical principles of PCC. For example, if patients express a need to be taken care of, or that they are ill equipped to manage their illness, recognising their needs while also encouraging them to be active partners in care is a delicate task for the HCP. When the intention is to support capabilities and recognise needs, it is important to find a balance where patients are neither abandoned to self-management nor stripped of their agency [ 40 ].

Among the participants in this study, where the majority where on sick leave due to stress-related conditions, many participants described how meaningful and important it was to them that the HCPs encouraged and supported them in the importance to take a step back, which can be understood as a reminder of vulnerability and needs. Further, self-stigma is common among patients with mental illnesses, and self-stigmatising thoughts can be reinforced by having difficulties managing everyday life and work [ 41 , 42 ]. This was evident also in our material, expressed as a form of vulnerability where the HCPs’ expressions of recognising and taking the illness seriously were valued and important forms of acknowledgement. To patients with CMDs, a person-centred approach may thus aid in avoiding to push their recovery too fast or too hard.

Furthermore, in concluding that the most meaningful part of the intervention was the access to and provision of HCP support through the phone calls, it was also evident that the platform failed to assert any greater meaning as support to the intervention participants. Our interpretation is that the platform had potential to support reflective and recovery-oriented processes, but in its current form, the purpose was not sufficiently clear to the patients, and perhaps not to the HCPs either considering the lack of attention given to platform activities in the phone calls. As studies on acceptability and engagement in eHealth interventions clearly suggest that tailored content and feedback strengthen participants’ engagement [ 28 , 43 , 44 ], this could be important to address as an area of improvement.

An unexpected finding was the lack of willingness to invite family and professional contacts to the platform. The reasons given in the interviews highlight the value participants placed on having a private space in which to express themselves in the turbulent process of illness and sick leave, or that the participants felt that they already had adequate communication with others. The need to invite, inform and share information with an extended network was indeed smaller than anticipated from previous studies on the importance of support in RTW processes [ 45 , 46 , 47 ]. However, this finding is congruent with a study evaluating a person-centred eHealth support targeting people diagnosed with chronic conditions [ 34 ], which could suggest the need to seek new ways to include other kinds of support in the PCC process.

Strengths and limitations

A strength of the present study is the purposive sampling of intervention participants with both positive and negative experiences of the intervention, which was representative of the full intervention group (Table  2 ). In interviews, it can be difficult for informants to express unpleasant or negative views, especially if this can be read as critique. During the interviews, measures were taken to express the value of both positive and negative experiences of the intervention in relation to the aims of a process evaluation, and the interview data were considered rich, complex and full of nuances. The first author, who conducted the interviews, had no prior communication with the informants and had no significant role in delivering the intervention, which hampers the risk of social-desirability bias.

Using a concurrent mixed methods approach enabled the analysis to accommodate experiences at the group and individual levels, and to triangulate the different findings [ 32 ]. A further strength is the collaborative process in which the analysis was performed, while the construction of an intervention-specific questionnaire for the quantitative strand can be considered a limitation. While this was considered a feasible way to capture the processes and activities of this specific intervention, it impedes comparisons of experiences between different interventions.

Another limitation of the study is that meaningfulness has not been conceptualised as meaningful in relation to a certain outcome, but as a personal judgment of every participant’s own experience of the intervention [ 20 ]. However, it is precisely the individual attribution of what is meaningful to each and every one that constitutes the concept’s relevance in person-centred care. Furthermore, exploring participants’ experiences can help to guide the understanding of what happens in an intervention and capture unexpected pathways [ 25 ]. This is considered particularly relevant in understanding what enables or blocks perceiving an intervention as supportive, considering the experiential dimension of support.

The majority of participants reported that the person-centred eHealth intervention was meaningful to use. Participants’ experiences of meaningfulness of the intervention were constituted by a lowered threshold to forming care partnerships, in which support was within reach, when needed. However, if the content of the intervention was not in accordance with individuals’ needs or expectations, access alone did not suffice to constitute meaningfulness. The most meaningful processes and activities in the intervention occurred in the phone calls between patients and the intervention HCPs, and the platform failed to assert any greater supportive influence due to unclarities in the content and barriers in the design. If pitfalls in the design are addressed, the format of the intervention and the person-centred approach underpinning its content and design have potential to function as a valued and anticipated support for patients with CMDs.

Data availability

To maintain participant confidentiality, per information provided in the informed consent, study data is not publicly available. Reasonable requests to the corresponding author will be considered and a confidentiality assessment will be performed at each individual request.

Abbreviations

Cognitive behavioural therapy

Common Mental Disorder

Gothenburg Centre for Person-Centred Care

Health Care Professional

Medical Research Council

Person-Centred Care

Randomised Controlled Trial

Henderson M, Harvey SB, Øverland S, Mykletun A, Hotopf M. Work and common psychiatric disorders. J R Soc Med. 2011;104(5):198–207.

Article   CAS   PubMed   PubMed Central   Google Scholar  

OECD. Sick on the job? Myths and realities about mental health and work. Paris: OECD; 2012.

Book   Google Scholar  

Försäkringskassan. Sjukfrånvaro i psykiatriska diagnoser. 2020.

Sundquist J, Ohlsson H, Sundquist K, Kendler KS. Common adult psychiatric disorders in Swedish primary care where most mental health patients are treated. BMC Psychiatry. 2017;17(1):235.

Article   PubMed   PubMed Central   Google Scholar  

OECD. Fit mind, fit job: from evidence to practice in mental health and work. Paris: OECD Publishing; 2015.

Clark DM. Implementing NICE guidelines for the psychological treatment of depression and anxiety disorders: the IAPT experience. Int Rev Psychiatry. 2011;23(4):318–27.

van Straten A, Hill J, Richards DA, Cuijpers P. Stepped care treatment delivery for depression: a systematic review and meta-analysis. Psychol Med. 2015;45(2):231–46.

Article   PubMed   Google Scholar  

Donker T, Petrie K, Proudfoot J, Clarke J, Birch MR, Christensen H. Smartphones for smarter delivery of mental health programs: a systematic review. J Med Internet Res. 2013;15(11):e247.

Burger FV, Neerincx MA, Brinkman WP. Technological state of the art of electronic mental health interventions for major depressive disorder: systematic literature review. J Med Internet Res. 2020;22(1):e12599.

Andersson G. Internet-delivered psychological treatments. Ann Rev Clin Psychol. 2016;12(1):157–79.

Article   Google Scholar  

Sin J, Galeazzi G, McGregor E, Collom J, Taylor A, Barrett B, et al. Digital interventions for screening and treating common mental disorders or symptoms of common mental Illness in adults: systematic review and meta-analysis. J Med Internet Res. 2020;22(9):e20581–e.

Lindsäter E, Axelsson E, Salomonsson S, Santoft F, Ejeby K, Ljótsson B, et al. Internet-based cognitive behavioral therapy for chronic stress: a randomized controlled trial. Psychother Psychosom. 2018;87(5):296–305.

Ekman I, Swedberg K, Taft C, Lindseth A, Norberg A, Brink E, et al. Person-centered care—ready for prime time. Eur J Cardiovasc Nurs. 2011;10(4):248–51.

Britten N, Ekman I, Naldemirci Ö, Javinger M, Hedman H, Wolf A. Learning from Gothenburg model of person centred healthcare. BMJ. 2020;370.

Wolf A, Moore L, Lydahl D, Naldemirci Ö, Elam M, Britten N. The realities of partnership in person-centred care: a qualitative interview study with patients and professionals. BMJ Open. 2017;7(7):e016491.

Britten N, Moore L, Lydahl D, Naldemirci Ö, Elam M, Wolf A. Elaboration of the Gothenburg model of person-centred care. Health Expect. 2017;20(3):407–18.

Entwistle VA, Watt IS. Treating patients as persons: a capabilities approach to support delivery of person-centered care. Am J Bioeth. 2013;13(8):29–39.

Ricœur P. Oneself as another. Chicago: University of Chicago Press; 1994.

Google Scholar  

Ekman I. Practising the ethics of person-centred care balancing ethical conviction and moral obligations. Nurs Philos. 2022;n/a(n/a):e12382.

Håkansson Eklund J, Holmström IK, Kumlin T, Kaminsky E, Skoglund K, Höglander J, Sundler AJ, Condén E, Summer Meranius M. Same same or different? A review of reviews of person-centered and patient-centered care. Patient Educ Couns. 2019;102(1):3–11.

Slade M. Mental Illness and well-being: the central importance of positive psychology and recovery approaches. BMC Health Serv Res. 2010;10:26.

Cederberg M, Ali L, Ekman I, Glise K, Jonsdottir IH, Gyllensten H et al. Person-centred eHealth intervention for patients on sick leave due to common mental disorders: study protocol of a randomised controlled trial and process evaluation (PROMISE). BMJ Open. 2020;10(9).

Cederberg M, Alsén S, Ali L, Ekman I, Glise K, Jonsdottir IH, et al. Effects of a person-centered eHealth intervention for patients on sick leave due to common mental disorders (PROMISE study): open randomized controlled trial. JMIR Ment Health. 2022;9(3):e30966.

Taylor SE. Social support: a review. Oxford University Press; 2011.

Moore G, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ: Br Med J. 2015;350:h1258.

Richards D, Rahm Hallberg I, editors. Complex interventions in health: an overview of research methods. London and New York: Routledge; 2015.

Volker D, Zijlstra-Vlasveld MC, Brouwers EPM, van der Feltz-Cornelis CM. Process evaluation of a blended web-based intervention on return to work for sick-listed employees with common mental health problems in the occupational health setting. J Occup Rehabil. 2017;27(2):186–94.

Article   CAS   PubMed   Google Scholar  

Patel S, Akhtar A, Malins S, Wright N, Rowley E, Young E, Sampson S, Morriss R. The acceptability and Usability of Digital Health Interventions for adults with Depression, anxiety, and Somatoform disorders: qualitative systematic review and Meta-synthesis. J Med Internet Res. 2020;22(7):e16228.

Holst A, Nejati S, Björkelund C, Eriksson MC, Hange D, Kivi M, Wikberg C, Petersson EL. Patients’ experiences of a computerised self-help program for treating depression - a qualitative study of internet mediated cognitive behavioural therapy in primary care. Scand J Prim Health Care. 2017;35(1):46–53.

Socialstyrelsen. Nationella riktlinjer för vård vid depression och ångestsyndrom. 2017.

Petersson EL, Forsén E, Björkelund C, Hammarbäck L, Hessman E, Weineland S, Svenningsson I. Examining the description of the concept treatment as usual for patients with depression, anxiety and stress-related mental disorders in primary health care research - A systematic review. J Affect Disord. 2023;326:1–10.

Fetters MD, Curry LA, Creswell JW. Achieving integration in mixed methods designs: principles and practices. Health Serv Res. 2013.

Plano Clark V, Ivankova N. Mixed methods research: a guide to the field. Thousand Oaks, CA: SAGE Publications, Inc.; 2016.

Barenfeld E, Fuller JM, Wallström S, Fors A, Ali L, Ekman I. Meaningful use of a digital platform and structured telephone support to facilitate remote person-centred care - a mixed-method study on patient perspectives. BMC Health Serv Res. 2022;22(1):442.

Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ. 2021;374:n2061.

Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. 2004;24(2):105–12.

Graneheim UH, Lindgren B-M, Lundman B. Methodological challenges in qualitative content analysis: a discussion paper. Nurse Education Today. 2017;56:29–34.

Barenfeld E, Ali L, Wallström S, Fors A, Ekman I. Becoming more of an insider: a grounded theory study on patients’ experience of a person-centred e-health intervention. PLoS ONE. 2020;15(11):e0241801.

Irvine A, Drew P, Bower P, Brooks H, Gellatly J, Armitage CJ, et al. Are there interactional differences between telephone and face-to-face psychological therapy? A systematic review of comparative studies. J Affect Disord. 2020;265:120–31.

Entwistle VA, Cribb A, Owens J. Why health and social care support for people with long-term conditions should be oriented towards enabling them to live well. Health Care Anal. 2018;26(1):48–65.

Cruwys T, Gunaseelan S. Depression is who I am: mental Illness identity, stigma and wellbeing. J Affect Disord. 2016;189:36–42.

Millward LJ, Lutte A, Purvis RG. Depression and the perpetuation of an incapacitated identity as an inhibitor of return to work. J Psychiatr Ment Health Nurs. 2005;12(5):565–73.

Saleem M, Kühne L, De Santis KK, Christianson L, Brand T, Busse H. Understanding engagement strategies in digital interventions for mental health promotion: scoping review. JMIR Ment Health. 2021;8(12):e30000.

Knowles SE, Toms G, Sanders C, Bee P, Lovell K, Rennick-Egglestone S, et al. Qualitative meta-synthesis of user experience of computerised therapy for depression and anxiety. PLoS ONE. 2014;9(1):e84323.

Andersen MFM, Nielsen KMMP, Brinkmann SMP. Meta-synthesis of qualitative research on return to work among employees with common mental disorders. Scand J Work Environ Health. 2012;38(2):93–104.

Holmgren K, Ivanoff SD. Women on sickness absence—views of possibilities and obstacles for returning to work. A focus group study. Disabil Rehabil. 2004;26(4):213–22.

Ståhl C, Edvardsson Stiwne E. Narratives of sick leave, return to work and job mobility for people with common mental disorders in Sweden. J Occup Rehabil. 2014;24(3):543–54.

World Medical Association. World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–4.

Download references

Acknowledgments

The authors would like to thank the study participants for their contributions to this research and the professional health care workers Mahboubeh Goudarzi, Eva-Lena Andersson, Paula Johansson Tunås and Emma Vasell for their contributions to performing the study.

This work was supported by The Swedish Research Council for Health, Working Life and Welfare (reference number 2016–07418, 2017 − 00557 and 2019 − 01726). The funder has no role in the design of the study, data collection, analysis, or interpretation. The study was financed by grants from the Swedish state under the agreement between the Swedish government and the country councils, the ALF agreement (ALFGBG-772191 and ALFGBG-932659).

Open access funding provided by University of Gothenburg.

Author information

Authors and affiliations.

Institute of Health and Care Sciences, Sahlgrenska Academy, University of Gothenburg, Box 457, Gothenburg, 405 30, Sweden

Matilda Cederberg, Emmelie Barenfeld, Lilas Ali, Inger Ekman & Andreas Fors

Centre for Person-Centred Care (GPCC), University of Gothenburg, Gothenburg, Sweden

Psychosis Clinic, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden

Matilda Cederberg & Anneli Goulding

Institute of Neuroscience and Physiology, Section of Health and Rehabilitation, Occupational therapy, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

Emmelie Barenfeld

Department of Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden

Department of Internal Medicine and Geriatrics, Sahlgrenska University Hospital Östra, Gothenburg, Sweden

Inger Ekman

Department of Psychology, University of Gothenburg, Gothenburg, Sweden

Anneli Goulding

Education, Development and Innovation, Region Västra Götaland, Primary Health Care, Research, Gothenburg, Sweden

Andreas Fors

You can also search for this author in PubMed   Google Scholar

Contributions

All authors contributed to conceptualising the study. MC conducted the quantitative analysis and the initial categorisation of the qualitative analysis. MC, AF and EB developed the qualitative analysis. MC, EB, LA, IE, AG and AF contributed in refining and validating the qualitative and quantitative analyses and developing the synthesis. MC wrote the first draft and all authors participated in revising and approving the final draft.

Corresponding author

Correspondence to Matilda Cederberg .

Ethics declarations

Ethics approval and consent to participate.

The RCT obtained ethical approval from the Regional Ethical Review Board in Gothenburg, Sweden (DNr 497 − 17, T023-18 and T526‐18) also covering the present sub-study. All participants have received oral and written information about the study and their rights as study participants and provided informed consent prior to engaging in any study activities. They were informed that their decision on participation would not impact on their usual care or their possibility to continue in the RCT. The research was performed in accordance with the Declaration of Helsinki [ 48 ].

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Cite this article.

Cederberg, M., Barenfeld, E., Ali, L. et al. A lowered threshold to partnerships: a mixed methods process evaluation of participants’ experiences of a person-centred eHealth intervention. BMC Health Serv Res 23 , 1193 (2023). https://doi.org/10.1186/s12913-023-10190-7

Download citation

Received : 08 May 2023

Accepted : 20 October 2023

Published : 02 November 2023

DOI : https://doi.org/10.1186/s12913-023-10190-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Person-centred care
• Process evaluation
• Mixed methods

BMC Health Services Research

ISSN: 1472-6963

• Submission enquiries: [email protected]
• General enquiries: [email protected]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 30 October 2023

Dynamic simulation research on urban green transformation under the target of carbon emission reduction: the example of Shanghai

• Hua Shang 1 &
• Hailei Yin   ORCID: orcid.org/0000-0001-8929-5922 1  

Humanities and Social Sciences Communications volume  10 , Article number:  754 ( 2023 ) Cite this article

10 Accesses

Metrics details

• Environmental studies
• Social policy

This paper aimed to predict the trend of carbon emissions during the green transformation process in Shanghai, with a focus on the city’s urban system structure. Green development has become an inevitable trend in urban progress, as traditional urban development has led to severe environmental problems caused by the emissions of a large amount of carbon dioxide. This study was motivated by the need for cities to actively pursue green transformation and achieve carbon peaking targets. Through a literature analysis, it was found that urban green transformation is influenced by various factors such as economy, energy, population, technology, and policy. Furthermore, carbon dioxide emissions primarily arise from fossil fuels and are regulated by carbon emission trading (CET) policies. With this knowledge, the urban system was divided, and the flow of carbon was analyzed. Using the general methodology of the IPCC, the carbon production resulting from energy consumption in Shanghai from 2014 to 2019 is calculated to construct an urban system dynamic (SD) model, which is used to predict the carbon emissions expected during the green transformation from 2020 to 2025. The key findings of the study are as follows: (1) The dynamic model of the urban green transformation system proved to be effective in predicting carbon emissions. (2) Based on the current status of green transformation in Shanghai, the city is capable of achieving its expected carbon emission peaking target by 2025. (3) The progress and timing of green transformation and carbon peaking in Shanghai vary across different scenarios, highlighting the importance of collective adjustments to identify the most appropriate path for urban green transformation. These findings provide valuable insights for cities seeking to adopt green development measures, facilitating the acceleration of their green transformation efforts and early attainment of carbon peaking targets.

Introduction

During the process of traditional urban development, the overuse of resources and the disregard for green development made it challenging to limit carbon emissions. This created a situation where the economy and resources were hindered by each other (Dong et al., 2020 ). To meet carbon reduction obligations, China introduced a plan at the 75th United Nations General Assembly to peak carbon dioxide emissions and achieve carbon neutrality (Lu et al., 2022 ). Subsequently, the Opinions on Promoting Green Development of Urban and Rural Construction proposed the establishment of a green development system for urban and rural construction in China by 2025 (General Office of the State Council, 2021 ). This policy aims to make significant advancements in green transformation, carbon reduction, and the alleviation of “urban diseases”. In response to this policy, cities need to control CO 2 emissions and achieve coordinated improvements in economic restructuring and ecological quality (Guo et al., 2020 ). Therefore, developing a green transformation plan is of great importance as it can provide a theoretical and practical foundation for accelerating urban green development.

The concept of green transformation arose from the evolution of the green economy (Loiseau et al., 2016 ). In early developed countries, the focus of green transformation was on practicality (Table 1 ). Resource-based regions transformed and extended high-energy industries through green development planning and policy revisions (Labussière, 2021 ; Wang et al., 2022 ; Su et al., 2023 ; Herrador et al., 2023 ). In China, green transformation is guided by the concept of ecological civilization, which is based on a circular economy and supported by green management. The objective is to achieve resource conservation, environmental friendliness, ecological balance, and harmonious development of people, nature, and society (Feng et al., 2020 ). However, as scholars Wang et al. ( 2022 ) have noted, the level of urbanization has led to urban economic development playing an increasingly significant role in promoting carbon emissions. Moreover, the relationship between urban economic development and carbon emissions shows varying trends as urban income levels rise (Wang et al., 2023 ). This implies that China’s urban green transformation faces the challenge of balancing economic growth and carbon emissions, with different cities at different stages of development requiring diverse approaches to green transformation. Therefore, accurately predicting carbon emission trends and identifying suitable green transformation strategies based on the specific stage of urban development is a worthwhile research question (Wei et al., 2022 ).

Scholars have devoted their efforts to aligning urban development with the requirements of green transformation, focusing on designing strategies and evaluating the effects of transformation plans. These research endeavors aim to provide guidance for cities to expedite their transformation towards green development. Guo and Ma ( 2023 ) utilized efficiency analysis and entropy value method to measure the efficiency of urban digital development and carbon emissions. They also analyzed the spatial and temporal evolution characteristics of these factors, providing valuable insights for urban development planning. Wang et al. ( 2022 ) constructed a conceptual framework to examine how regional integration affects the efficiency of green urban development. Their study investigated the facilitation of factor mobility and optimization of industrial layout through regional integration, offering development plan from the perspective of regional integration of city clusters. Evaluating the effects of green transformation, Su et al. ( 2023 ) constructed an evaluation index system for the synergistic governance of pollution reduction and carbon emission reduction in urban agglomerations. By applying this system, they evaluated the level of synergistic governance in seven urban agglomerations in the Yellow River Basin, providing empirical references for high-quality green development paths. Song et al. ( 2022 ) leveraged the Low Carbon City Pilot (LCCP) policy as a quasi-natural experiment to assess its emission reduction effect, providing an empirical basis for accelerating the realization of the “peak carbon emission” and “carbon neutral” targets. These studies collectively emphasize the need for future urban development to break free from resource constraints and environmental pollution, urging the adoption of a green development path. Therefore, researching and exploring urban green transformation pathways and assisting cities in formulating green development plans hold significant implications.

Peaking carbon dioxide emissions represents a historical turning point in which CO 2 emissions shift from increasing to decreasing (Chen et al. 2022 ). Traditional economic development heavily relies on massive energy consumption, and CO 2 emissions serve as a direct indicator of the degree of urban green transformation (Du et al. 2021 ). Existing studies on urban carbon emissions concentrates on energy consumption and carbon trading policies. Energy consumption refers to the process through which carbon dioxide is produced by consuming fossil and non-fossil energy, representing the main source of CO 2 production. Various methods, such as LMDI (Peng and Liu, 2022 ), remote sensing measurement (Wu et al., 2022 ), and structural equations (Xue and Yao, 2022 ), can be employed to decompose the factors influencing CO 2 production. Through these approaches, factors such as economic level (Jia et al., 2023 ), human capital (Wang et al., 2023 ), industrial structure (Fang, 2023 ), technological level (Wang et al. 2023 ), and energy intensity (Wang and Xue, 2023 ) have been identified as crucial determinants of CO 2 emissions. Among these factors, economic structure has been proven to be the most significant negative factor affecting carbon emissions (Li et al., 2021 ), while energy efficiency improvements effectively inhibits carbon emission growth (Li et al., 2022 ). In addition, CO 2 emissions can be affected by CET, which involves converting carbon emissions into cost constraints (Zhang et al., 2020 ). Some studies incorporate low-carbon policies into urban construction evaluation (Ren and Liu, 2023 ) or employ simulation models to examine the impact of different carbon trading mechanisms (Yu et al., 2021 ). Zheng et al. ( 2023 ). explored whether and to what extent carbon markets function in developing countries. Their findings indicated that China’s pilot carbon trading policy effectively reduced carbon emissions by about 38.61% Tang et al. ( 2021 ) investigated the effectiveness and heterogeneity of emission trading schemes from regional and industrial perspectives. It is important to note that all these factors exhibit spatial characteristics that can be used to forecast trends in urban carbon emissions.

Existing research primarily focuses on elucidating the concept of urban green transformation and devising strategies for its attainment. However, there are some limitations that necessitate attention. Firstly, the analysis of cities’ dynamic development and intrinsic interconnectedness during the implementation process remains insufficient. While a few studies have undertaken phased transformation planning, it is imperative to consider cities as dynamic and complex systems that undergo economic and social evolution. Adopting a systemic perspective would furnish a more comprehensive understanding of the green transformation process. Secondly, the research on the factors that influence carbon emissions in cities often confines itself to energy consumption or CET at a singular level. This approach fails to adequately capture the interconnectedness of these factors. In addition, the prevalent reliance on empirical analysis using econometric models may not effectively depict long-term changes and nonlinear relationships in carbon emissions. Thirdly, while reducing carbon emissions is a crucial aspect of urban green transformation, many studies overlook the carbon flow underpinning it when examining economic, environmental, and resource systems. Consequently, the impact of carbon emissions on urban green transformation oftentimes goes unnoticed. In conclusion, further research should consider the dynamic nature of cities, delve into the interconnectedness of factors influencing carbon emissions, and pay attention to the role of carbon flow in the realization of urban green transformation.

In view of aforementioned research limitations, this study seeks to address these gaps through the following contributions: (1) Considering the developmental stage of Shanghai and taking into account factors that influence carbon emissions, such as energy consumption and carbon emission reduction policy, this study adopts a systemic perspective by dividing the urban system into sub-dimensions including industrial economy, environmental energy, social population, technological level, and carbon emission reduction policy. Through this analysis, the study aims to uncover the causal relationships and long-term dynamic changes in the process of urban green transformation within the context of carbon emission reduction targets. (2) This study also conducts a comprehensive assessment of carbon dioxide production from fossil energy sources in Shanghai, providing valuable insights into recent trends in the city. (3) To further examine the process of urban green transformation and carbon emissions reduction, this study develops a system dynamics model. Various scenarios are constructed based on different development objectives, allowing for a thorough exploration of the urban green transformation process and the achievement of carbon emissions peaks. The findings from these scenarios can serve as a scientific basis for future urban development planning. In summary, this study aims to overcome the limitations of previous research by providing a systemic and dynamic analysis of urban green transformation in Shanghai, with a particular focus on carbon emissions reduction. By utilizing a system dynamics model and conducting scenario analysis, this study intends to contribute to the field of urban planning and offer valuable insights for sustainable urban development.

The focus of this paper is to understand the causal relationships and dynamic changes in the process of urban green transformation, provide insights into carbon dioxide emissions in Shanghai, and provide a framework for exploring different scenarios of urban green transformation and carbon peak. The study is divided into the following sections: “Research method and system analysis” section presents the research design process including research framework and systemic factors analysis. “Model construction” section describes the process of constructing the system dynamics model. “Analysis and result” section provides the scenario design and results of simulation. Finally, in “Conclusion and implication” section, the conclusions and implications of the study are given.

Research method and system analysis

To comprehensively comprehend the intricacies of urban green transformation, adopting a systemic perspective to observe the holistic changes in the city is crucial. This entails considering the transformation of economic industries and energy utilization, as well as analyzing the nonlinear relationships and causal feedback between them using a systems thinking approach. One effective method for capturing the dynamic changes and nonlinear structural characteristics of systems is the system dynamics (SD) method. Specifically, urban carbon dioxide emissions, which are influenced by industrial energy consumption, are regulated by urban CET policies. Given the involvement of multiple urban subsystems, the application of system dynamics becomes a valuable tool for studying the process of urban green transformation. Scholars have begun to use SD model to predict the impact of different transformation conditions on future development. For instance, Lee et al. ( 2021 ) developed a SD model that considers the relationships between variables such as population, building area, industry, and the environment. Similarly, Wang et al. ( 2023 ) proposed a SD model of urban transportation system to examine the impacts of different strategies on CO 2 emission reduction as well as the economic benefits to the environment. By analyzing the feedback characteristics of causal relationships within the system, the evolution of carbon emissions in the context of urban green transformation can be effectively observed.

Professor Forrester ( 1961 ) laid the scientific foundations for SD in his seminal work, Industrial Dynamics , published in 1957, where he elucidated its principles and typical applications. This study follows the general steps of SD method, which involve determining the system boundary, delineating the internal structure and drawing a causal diagram, identifying system factors and their relationships, establishing a model in the form of a system flow chart, and conducting simulation analysis of future urban green transformation with respect to carbon emissions through parameter control (Bao et al. 2023 ).

System boundary determination of research areas

China’s vast territory encompasses cities with diverse resource endowments and levels of economic development. Green transformation must be tailored to local conditions. This study examines the process of urban green transformation under carbon emission reduction goals, using Shanghai as a case (Fig. 1 ). Shanghai is a core city in the Yangtze River Economic Belt and one of China’s national central cities. It has been continuously building an ecological civilization in recent years. The city’s 14th Five-Year Plan outlines its goal to reach carbon peaking five years ahead of the national target (Niu et al. 2022 ). To this end, Shanghai launched a pilot carbon emissions trading program in 2013 (Li and Wang, 2021 ). As a pioneer in urban green development in China, Shanghai’s early achievement of green development will position it as a trailblazing city that inspires and propels other cities towards green transformation.

It provides the geographical location and economic population situation.

Clarifying the urban system boundary excludes unrelated content. In terms of spatial boundaries, this study defines the urban system based on administrative divisions. By the end of 2022, Shanghai comprises 107 streets, 106 towns, and 2 townships, totaling 215 township-level divisions. In terms of temporal boundaries, this study focuses on key time points related to carbon emission reduction and green transformation in Shanghai. Since the study involves the participation of the CET policy subsystem, it is important to note that Shanghai became one of the pilot cities for urban CET in 2013, with steady development since the establishment of the carbon quota system in 2014. Therefore, the starting point of the study is set as 2014 and analyzes existing data from 2014 to 2019. Furthermore, one of the research objectives is to assess Shanghai’s achievement of the carbon peak target before 2025, as proposed in the 14th Five-Year Plan. To ensure the reliability of the predictive results, a large time span is avoided. Hence, the study sets 2025 as the end point and uses a yearly time step to observe the dynamic changes in Shanghai’s green transformation development from 2020 to 2025.

Research framework analysis

The literature on urban green transformation highlights the influence of the urban industrial economy, environmental energy, technological level, social population, and policy support. The industrial economy reflects the basic structure of urban economic development, while the environmental energy reflects the natural reserves and utilization in the city. Technological level acts as a means and tool, either promoting or inhibiting system development, while social population provides necessary support (Zheng et al. 2023 ). Policy support, on the other hand, provides external impetus (Luo et al. 2023 ). Meanwhile, the study of urban carbon reduction mainly focuses on energy consumption and carbon trading policies. Fossil energy consumption is the direct sources of carbon dioxide production, while CET policies establish carbon markets and facilitate the trading of carbon emission rights, providing important constraints to reduce actual carbon dioxide emissions. As shown in Fig. 2 , carbon reduction is a development requirement for urban green transformation, and green transformation is a vital approach to achieving carbon reduction. The two are connected through the carbon flow, promoting coordinated development and achieving the target of green development with carbon peaking.

It illustrates the relationship between green transformation influenced by factors such as industrial economy, environmental energy, technological level, social population, and policy support in the urban system, and carbon emissions reduction related to energy consumption and carbon trading policies. This relationship is achieved through carbon flow to attain carbon peak.

The causal diagram is a qualitative analysis tool for describing the causal relationship between factors. This study divides the urban system into the industrial economy, environmental energy, technological level, social population, and carbon trading policy. To capture the flow of factors in the process of carbon generation to emission as factors flow, we construct the system causal diagram and distinguish subsystems by color (Fig. 3 ). The causal diagram can be further categorized into positive and negative feedback loops based on the loops present. The curves in the diagram represent the interconnections between factors within each subsystem. “+“ represents a positive correlation, while “-“ represents a negative correlation. In this paper, the constructed causal diagram consists of a total of fifteen feedback loops that constitute the urban green transformation system. The major feedback loops are as follows.

It depicts the causal relationships between various factors influencing urban green transformation. Brown represents the industrial economy subsystem, green represents the environmental energy subsystem, purple represents the technological level subsystem, blue represents the social population subsystem, and pink represents the carbon trading policies subsystem.

(1) GDP → (+) Secondary industry output value → (+) Industrial energy consumption → (+) Production energy consumption → (+) Total energy consumption → (+) Carbon emissions → (+) Carbon emission cost → (-) Enterprise profit → (+) GDP

(2) GDP → (+) Primary and tertiary industry output value → (+) Non-industrial energy consumption → (+) Production energy consumption → (+) Total energy consumption → (+) Carbon emissions → (+) Carbon emission cost → (-) Enterprise profit → (+) GDP

Loops (1)–(2) highlight the impact of industrial structure on the system. GDP growth is linked to an increase in output values. The output value of primary and tertiary industries mainly depends on non-industrial energy consumption. The output value of the secondary industry mainly depends on industrial energy consumption. Under the common influence of domestic energy consumption, the total amount of energy consumption continues to increase. The enterprises’ cost of controlling carbon dioxide also increases accordingly, which has a negative impact on GDP.

(3) Total energy consumption → (+) Fossil fuel carbon emissions → (+) Carbon emissions → (+) Carbon emission cost → (-) GDP → (+) Industrial output value → (+) Total energy consumption

(4) Total energy consumption → (+) Non-fossil fuel carbon emissions → (+) Carbon emissions → (+) Carbon emission cost → (-) GDP → (+) Industrial output value → (+) Total energy consumption

Loops (3)–(4) highlight the impact of energy structure on the system. Total energy consumption is composed of fossil and non-fossil fuel consumption. Fossil fuels have strong pollution and high carbon emission coefficients. Clean energy such as natural gas and other renewable energies have smaller carbon emission coefficients and produce less carbon dioxide accordingly. Carbon dioxide of both types determine the level of carbon emission costs and extends to influencing urban GDP growth, acting on industrial output values and cycling back to energy consumption.

(5) Carbon emissions → (+) Environmental investment → (-) GDP → (+) Technological investment → (+) Emission reduction technology → (-) Carbon emissions

Loop (5) highlights the impact of carbon reduction technology on the system. In the face of increasing CO 2 emissions, the government invests more in environmental governance, leading to an increase cost and a negative impact on economic growth, while the cities’ scientific and technological level is closely related to GDP. Although enterprises produce a large volume of CO 2 during energy consumption, through the application of emission reduction technology, actual emissions are effectively reduced.

(6) Carbon emissions → (+) Excessive carbon dioxide emissions → (+) Punishment → (+) Carbon emission cost → (-) Enterprise profit → (+) GDP → (+) Industrial output value → (+) Total energy consumption → (+) Carbon emissions

Loop (6) highlights the impact of CET policies on the system. An important content of policies is to punish enterprises for excessive carbon dioxide emissions based on their carbon dioxide quota. The fines paid by enterprises can be regarded as part of their carbon emission costs. Increased costs reduce enterprise profits and affect regional economic growth, which in turn affects urban total carbon emissions through factors such as energy consumption and technological investment.

Research subjects and main factors

As shown in Fig. 3 , the causal relationships among industrial economy, environmental energy, social population, technological level, and CET policy constitute the urban green transformation system under carbon emission reduction goals. Drawing on the research by Du et al. ( 2018 ), the variable selection starts with urban GDP, which can be divided into primary, secondary, and tertiary industries based on the industrial structure. Each industry is then categorized into industrial and non-industrial energy consumption types, collectively constituting productive energy consumption. Combining with domestic energy consumption, the total urban energy consumption is obtained. The energy consumption is then subdivided according to the energy structure to calculate the carbon dioxide emissions for each fossil energy source. Taking into account technology utilization efficiency and forestry carbon sinks, the actual carbon emissions are derived. Moreover, the carbon emission quotas imposed by urban CET policies are applied to production enterprises. Measures are taken based on the quota ratio and excess carbon emissions to ensure compliance. Ultimately, these actions have feedback impacts on urban GDP. These variables have been discussed in the research by Ye et al. ( 2021 ). The system model depicts the interrelationships and causal feedback between different variables, thereby reflecting the influences on urban green transformation from carbon generation to emission. This model serves as a basis for the design of scenario plans in subsequent sections.

Table 2 presents the variables and equations of the Shanghai low-carbon green transformation system dynamics model. It provides a comprehensive overview of the units of the variables and categorizes them as L -state factors, R -rate factors, A -auxiliary factors, and exogenous factors. Regression analysis is employed to examine variables exhibiting significant linear correlations, such as industrial energy consumption and the technology investment ratio. For variables without significant linear correlation, a table function is used for analysis, such as birth rate and carbon trading price.

In order to know exactly the level of CO 2 production, a common accounting method is to use the carbon coefficients of energy sources in the IPCC National Greenhouse Gas Emissions Inventory Guidelines. According to the China Energy Statistical Yearbook , regional terminal energy consumption is classified into eight categories: coal, crude oil, coke, gasoline, kerosene, fuel oil, diesel, and natural gas. The amount of CO 2 produced by fossil energy in Shanghai is calculated as follows(Guo et al. 2012 ).

Where Q represents the total volume of CO 2 produced by energy consumption in Shanghai. The production of the i -th fossil energy is denoted by \(\alpha _i\) , the carbon emission coefficient of the i -th fossil energy is denoted by \(\beta _i\) , and the consumption of the i -th fossil energy is denoted by \(C_i\) . Table 3 displays the CO 2 emission coefficients for various types of energy.

Without taking into account the impact of technology and other factors on carbon emissions, Table 4 shows the CO 2 produced by energy consumption in Shanghai from 2014 to 2019.

Model construction

Data collection.

In this study, the data on economics, population, and energy are sourced from the China Urban Statistical Yearbook , China Energy Statistical Yearbook , and Shanghai Statistical Yearbook for the years 2015 to 2020. The environmental data, such as forestry area, are obtained from the Shanghai Municipal National Economic and Social Development Statistical Bulletin for each year. The data on total carbon trading quotas and free quota are obtained from the China Carbon Emissions Trading Network . The data on carbon trading amount, carbon trading price, and auction price are sourced from the Shanghai Environment and Energy Exchange . Variables that are not directly available in the statistical yearbooks are calculated indirectly. Furthermore, for variables with missing or abnormal original data, appropriate data processing techniques such as mean or regression methods are employed.

Flow chart drawing

The system flow chart is derived by analyzing the relationships between factors in the causality loop diagram, as described by Crielaard et al. ( 2022 ). As shown in Fig. 4 , the variables of industrial economy, environmental energy, social population, technological level, and CET policy together comprise the system. By incorporating the equations presented in Table 1 into the system flow chart and using VENSIM to run the urban system, we have constructed a SD model. This model forms the basis for designing scenarios in subsequent sections.

It illustrates the relationships between different types of variables. Brown represents the industrial economy subsystem, green represents the environmental energy subsystem, purple represents the technological level subsystem, blue represents the social population subsystem, and pink represents the carbon trading policies subsystem.

Validity test

The validity test of the SD model is assessed through a structure test and a historical test. The structure test verifies the reasonableness of the variables and equations in the model, and the VENSIM software has confirmed that the structure of the model is effective. The historical test involves comparing the simulation results with historical data and assessing the accuracy of the model based on the error range. Generally, if the absolute value of the error falls within 20%, the model is considered to be highly credible (Qian et al. 2023 ).

In this study, the selection of GDP, total energy consumption, technology investment, carbon emissions, and total population as observed variables within each subsystem reflects their fundamental importance. These variables have a significant influence on the accuracy of other variables within their respective subsystems. For example, the value added of each industry is derived by multiplying the GDP by a pre-determined industry proportion coefficient. Energy consumption in different sectors is determined by multiplying the total energy consumption by the energy proportion structure. The efficiency of emissions reduction and absorption is dependent on technological investment. Policies addressing excessive carbon dioxide emissions are constrained by regional carbon emission levels. The level of energy consumption in daily life is influenced by the total population. By ensuring the high accuracy of these observed variables, the potential errors of other variables in the subsystems can be, to some extent, controlled. The test results are shown in Table 5 .

The absolute errors for these five variables over the past six years are all below 5%, indicating that they fall within the acceptable error threshold. This demonstrates that the model is highly accurate and capable of effectively representing the actual system dynamics.

Analysis and result

Scenario design.

To assess changes in the system, it is necessary to identify the parameters from various variables that largely determine the operational state of Shanghai’s SD system and then make appropriate adjustments. Parameters are usually human-adjusted variables. In this study, parameters are identified through sensitivity analysis. We set the selected variable according to its value range while other variable values remained unchanged. If the simulated results varied greatly, then it indicates that the variable is sensitive and can be treated as a parameter for designed scenarios, calculated as follows.

Where S represents the sensitivity of factor y to x , \({\Delta}x\) and \({\Delta}y\) represent the changes in the variables. Then S can be expressed as the change magnitude of y when x changes by 1%, and a larger S indicating the higher sensitivity. Since more than one y is selected, the mean value of S is calculated for each x to make the sensitivity results more stable.

Where n is the number of y , the mean sensitivity \(\overline S\) of all selected y to a certain x is calculated. When \(\overline S\) is lower than 5%, the system is considered to be insufficiently sensitive to x . When \(\overline S\) is higher than 5%, x is considered to be a parameter affecting the system.

GDP, carbon emissions, total energy consumption, and carbon emission cost were chosen as y . The sensitivity results in Fig. 5 were obtained by calculating the independent parameters, except for the joint parameters such as industrial structure and energy structure, which have high sensitivities. It can be seen that \(\overline S\) is greater than 5%, and the parameters that have a greater impact on Shanghai’s green transformation system are, in order of importance: the proportion of technology investment, the carbon trading price, the punishment price, the proportion of free quota, and per capita domestic energy consumption.

It shows the impact of each parameter on Shanghai’s green transformation. Parameters with values higher than 5% have a significant impact, while those below 5% have a minor impact.

Under the 14th Five-Year Plan for Comprehensive Energy Conservation and Emission Reduction planning in Shanghai, we have developed six scenarios to compare the impact on urban green transformation. A natural development scenario is set based on the city’s current state. An industrial structure adjustment scenario is set to reduce the proportion of traditional high-energy-consuming industries, and increase the proportion of tertiary industries. An energy structure adjustment scenario is set to promote the transformation of fossil energy consumption to non-fossil energy consumption. An environmental technology advances scenario is set to accelerate technological innovation by increasing investment, and improve domestic energy efficiency. A CET policy adjustment scenario is set to reasonably regulate carbon quotas, and incentivize and constrain enterprise carbon dioxide emissions. Without considering the priority of each scenario, a coordinated development scenario is set by comprehensively considering the impact of industrial structure, energy structure, environmental technology and CET policy on Shanghai’s green transformation process.

Based on historical data from 2014 to 2019, this study conducted Logistic analysis to estimate the values of various parameters for the year 2025. However, it was observed that the linear trends of certain parameters, such as the proportion of tertiary industry and the proportion of coal energy consumption, did not align with the actual situation in Shanghai. Therefore, these parameters were treated as idealized states in Scenario II and Scenario III. To improve the realism of the results, a trend analysis of the industrial and energy structures was conducted after applying logarithmic transformations to the time variable. This analysis was combined with information from the Shanghai Clean Air Action Plan (2023–2025), the Shanghai Carbon Market Report, the Residential Energy Consumption Index (RECI), and predictions from domestic experts regarding the remaining parameters. These inputs were used to obtain adjusted values for the year 2025. Furthermore, the punishment price was determined based on relevant carbon trading policies in China and is simulated to be 3 or 4 times the carbon trading price. To facilitate a comparison within a reasonable range, this study used three times the carbon trading price as the predicted price under natural conditions, and four times as the adjusted price. The predicted and adjusted values for each parameter in 2025 are presented in Table 6 .

Simulation analysis

Based on the above scenarios, all parameters in the system change accordingly by adjusting the values of a specific scenario. The simulation results are shown in Fig. 6 . As GDP reflects the city’s overall economic development, carbon emission cost represents the economic impact on enterprises under carbon trading policy, total energy consumption corresponds to energy conservation, carbon emissions correspond to emission reduction, and carbon intensity is a critical indicator of the degree of balance, GDP, total energy consumption, carbon emissions, carbon intensity, and carbon emission cost are selected as the five variables for result analysis. The simulation results are summarized in Table 7 .

a Simulation results of GDP in Shanghai. b Simulation results of total energy consumption in Shanghai. c Simulation results of carbon emission in Shanghai. d Simulation results of carbon intensity in Shanghai. e Simulation results of carbon emission cost in Shanghai.

Scenario I: Natural development

Under Scenario I, the parameters maintain their current growth trends. From 2014 to 2025, Shanghai’s GDP is expected to increase from 2.527 trillion yuan to 4.5418 trillion yuan. Total energy consumption is projected to rise from 106.58 million tons of standard coal to 126.61 million tons of standard coal. Carbon emissions are estimated to reach their peak in 2023 at 27.31 million tons and gradually decline thereafter. This indicates a decoupling of economic development and carbon emissions, with carbon intensity decreasing from 0.6977 to 0.5928, aligning with Shanghai’s goal of peaking carbon emissions by 2025. In addition, the implementation of CET mechanism incurs corresponding emission costs. Since the reform of carbon trading products in 2016, the market has stabilized, with annual trading volume increasing and emission costs rising year after year.

Scenario II: Adjustment of industrial structure

Under Scenario II, the objective is to impact carbon dioxide emissions by altering the proportion of industries in Shanghai. Traditionally, resource-intensive heavy chemical industries have been the dominant drivers of economic growth and major energy consumers. As the share of the secondary industry increases, the energy consumption also rises. Following the adjustment, Shanghai’s GDP experiences a notable increase of 203.3 billion yuan compared to Scenario I. However, this economic growth is accompanied by a substantial rise in energy consumption, which is projected to reach 136.55 million tons of standard coal by 2025. Consequently, the carbon intensity, measured as the amount of carbon dioxide emitted per unit of GDP, remains similar to Scenario I at 0.5955 tons per 10,000 yuan. In this scenario, carbon emissions are expected to fluctuate rather than reach a peak during the forecast period. After reaching the first peak in 2022, carbon emissions initially decrease but then start to rise again. By 2025, carbon emissions will surpass the level of natural development by 13.32 million tons, resulting in carbon emission costs of 26.1 billion yuan. This situation occurs because the tertiary industry dominates Shanghai’s economy, and the rapid expansion of emerging industries has led to a swift increase in energy consumption. The shift towards the tertiary sector has also driven led to substantial growth in electricity and refined oil consumption, further contributing to higher carbon emissions. As shown in Fig. 7 , despite the industrial structure adjustment, total energy consumption for production actually increases, with non-industrial energy consumption rising more noticeably than industrial energy consumption. This becomes the primary driver of the increase in carbon emissions.

Production energy consumption before (left) and after (right) industrial structure adjustment.

Scenario III: Adjustment of energy structure

Scenario III impacts carbon emissions by altering the proportion of energy sources in Shanghai. Coal consumption is a major contributor to carbon emissions in the city’s urban development, while the consumption of natural gas and non-fossil energy is relatively low. After adjustment are made, it is projected that by 2025, Shanghai’s GDP will increase to 4.5409 trillion yuan, with a total energy consumption of 126.6 million tons of standard coal and a carbon intensity of 0.5951 tons/10,000 yuan. In 2022, carbon emissions are expected to reach a peak of 27.31 million tons, achieving an early peak in carbon emissions. This demonstrates that optimizing the energy structure can effectively reduce carbon emissions and expedite the attainment of the carbon emission peak. As depicted in Fig. 8 , increasing the proportion of clean energy has a noticeable substitution effect in reducing carbon dioxide emissions from coal use. The increase in the share of non-fossil energy does not lead to significant additional carbon emissions. Therefore, efforts should be made to promote the transition from fossil energy to non-fossil energy use, advocate for clean energy utilization, and effectively control the growth of carbon emissions.

Carbon emissions from energy consumption before (left) and after (right) energy structure adjustment.

Scenario IV: Advances of environmental technology

Scenario IV impacts carbon emissions by promoting emission reduction efficiency and domestic energy consumption. Following the adjustments, Shanghai’s GDP growth will not be hindered by increased costs and is projected to increase to 4.5524 trillion yuan by 2025. The total energy consumption will reach 126.03 million tons of standard coal, and carbon emissions will peak in 2021 at 26.989 million tons. The carbon intensity will decrease annually to 0.5807 tons/10,000 yuan. Technological advancements also reduce the burden of carbon emission on enterprises, and by 2025, carbon emission costs will be reduced to 22.5 billion yuan. As shown in Fig. 9 , the energy consumption and CO 2 directly generated by economic production activities will exceed 300 million tons. However, through the utilization of emission reduction technologies, the actual carbon emissions are reduced by almost one-fifth. Compared to natural development, the actual carbon emissions further decrease, highlighting the importance of investing in environmental technologies to reduce urban carbon dioxide. In this scenario, enterprises improve their carbon emission efficiency, reduce excess carbon emissions, increase profits, and offset the expenditure of environmental technology investment in GDP.

CO 2 production and emissions before (left) and after (right) technology investment adjustment.

Scenario V: Adjustment of CET policy

Scenario V impacts carbon emissions by adjusting carbon trading costs, punishment, and carbon trading quotas. Following the adjustment, it is projected that Shanghai’s GDP will be 4.0039 trillion yuan by 2025, with a total energy consumption of 124.07 million tons of standard coal, and a carbon emissions peak in 2023 at 27.041 million tons. Similar to Scenario II, although the total energy consumption and carbon emissions are restricted, the policy imposes a heavier burden on enterprises. Figure 10 shows that Shanghai’s excess carbon emissions still reach ~100 million tons, and the decrease in excess emissions is not significant after the reduction in quota ratio. Compared to natural development, the increase in punishment price results in a significant increase in fines imposed on enterprises. The cost burden slows down the decoupling between the economy and energy consumption, resulting in a carbon intensity of 0.66 tons/10,000 yuan. In this scenario, the decrease in total energy consumption is partly due to the increase in carbon emission costs and the decline in production capacity, rather than an improvement in energy-saving and emission reduction capabilities.

Excess carbon emissions and fines before and after policy adjustment.

Scenario VI: Coordinated development

Scenario VI focuses on energy conservation and emission reduction while maintaining stable economic development. Through coordinated adjustments, Shanghai’s GDP will reach 4.6276 trillion yuan by 2025, with a total energy consumption of 135.14 million tons of standard coal and a carbon intensity decrease to 0.5727 tons/10,000 yuan. The carbon emission costs will be 35.7 billion yuan. In this Scenario, Shanghai’s carbon emissions will peak in 2022 at 27.952 million tons and then decline. Under the coordinated development plan, although the adjustment of industrial structure and the implementation of the Carbon Emission Trading (CET) policy may increase carbon dioxide emissions and the cost of emissions, technological progress will also enable enterprises to improve energy efficiency and reduce emission costs. Due to the high degree of optimization of Shanghai’s industrial structure, the increasing proportion of the tertiary industry, such as the service industry, will lead to higher energy consumption compared to the reduced energy consumption in the secondary industry. Therefore, in the short term, the total energy consumption and carbon emissions required for Shanghai’s coordinated development show an increasing trend, which needs to be balanced by long-term technical support provided by energy-saving and emission reduction measures in high-tech industries within the tertiary sector.

Based on predictive results, Shanghai can achieve carbon emissions peaking in 2023 under the premise of sustained economic growth and stable energy consumption, with Scenario I as the benchmark and Scenario VI as the development trend. While previous studies have made predictions about carbon emissions in Shanghai (Zhou et al. 2023 ), this paper is more aligned with the actual policy requirements of Shanghai and provides a more focused predictive result compared to the conclusion that carbon peaking can be achieved before 2030. In contrast to the isolated adjustment of subsystems, scenario VI emphasizes the joint action of different influencing factors. It is observed that under scenario VI, although Shanghai achieves carbon peaking one year earlier, GDP, energy consumption as well as carbon emissions all rise, which can be seen as a double-edged sword. The reasons for this can be identified in scenarios II–V. For instance, previous predictions showed a small fluctuation in Shanghai’s decoupling index, indicating strong decoupling (Wu and Xu, 2022 ). However, this study found that adjusting the industrial structure alone seems to increase carbon emissions. Further investigation revealed that Shanghai’s economic development highly relies on the tertiary industry, particularly finance and trade, and the actual improvement of emission reduction technology primarily relies on the support of high-tech industries. In addition, energy structure adjustment and environmental technology advances face challenges such as lengthy implementation cycles and high difficulty. In contrast, the implementation effect of policies is evident and can be seen immediately, albeit at a considerable cost. Therefore, considering the characteristics of various scenarios, the study suggests that Shanghai should focus on developing high-tech industries to enhance its economic strength; use technology to optimize carbon emission efficiency; employ energy transformation to optimize energy structure; and utilize policy guidance to constrain enterprise behaviors. Coordinated development in all aspects can accelerate the green transformation process as soon as possible.

Conclusion and implication

Conclusions.

This study simulates the green transformation process of Shanghai under the goal of carbon emission reduction using the methods of system dynamics. The process includes three main steps: Firstly, the IPCC general method is used to calculate the carbon dioxide production of Shanghai’s main fossil energy from 2014 to 2019. Secondly, the urban system is divided into subsystems. Main factors of the system are identified and a SD model is constructed. Then, parameters are screened and combined through sensitivity analysis. Finally, through scenario simulation, the green transformation situation and carbon emission peaking time of Shanghai are explored. The results provide a reference for low-carbon green transformation in Shanghai. Specifically, the following conclusions can be drawn:

(1) The feasibility of conducting research on urban low-carbon green transformation based on system dynamics (SD) has been established. This study focuses on Shanghai as a case study and divides the urban system into various subsystems, including industrial economy, environmental energy, technology level, social population, carbon trading policy subsystems and uses SD methods to explore the urban green transformation process with the target of carbon emission reduction. The model’s validity has been tested and confirmed, providing methodological support for the research.

(2) The main factors influencing the urban green transformation system under the target of carbon emission reduction have been identified. Sensitivity analysis results reveal that, in addition to industrial structure and energy structure, system control parameters include the proportion of technology investment, the carbon trading price, the punishment price, the proportion of free quota, and per capita domestic energy consumption. Therefore, when designing scenarios, emphasis should be placed on optimizing industrial structure, transforming energy sources, improving trading policies, and advancing environmental technologies to enhance the effectiveness of the transformation.

(3) Shanghai is expected to achieve its carbon emission peaking target under its current green transformation status. Assuming no sudden changes occur in the system, Shanghai’s total carbon emissions during the green transformation process will peak at 27.31 million tons in 2023 and begin to decline in 2024, achieving its goal by 2025.

(4) Different scenarios have varying impacts on the urban green transformation process and carbon emission peaking. The industrial structure adjustment scenario exhibits a trend of expanding Shanghai’s carbon emissions, necessitating continuous optimization to promote the development of high-tech industries. The energy structure adjustment scenario has the most obvious reduction in Shanghai’s energy consumption and carbon emissions, emphasizing the promotion of the transformation from fossil energy to non-fossil energy and the adoption of clean energy. The environmental technology advances scenario has the most comprehensive impact on Shanghai, not only reducing emission costs but also lowering energy consumption levels. It serves as a major driver for urban green transformation. The improvement of the carbon trading polices directly affect enterprise behaviors and imposes cost burdens, providing certain auxiliary effect on low-carbon development.

(5) Through the joint adjustment of industrial structure, energy structure, technological level and policy guidance, cities can find suitable green transformation paths and strive to achieve carbon emission peaking as soon as possible. Shanghai should ta For Shanghai, it is crucial to prioritize the development of high-tech industries to enhance its economic strength; leverage environmental technology as a means to improve carbon emission efficiency; utilize energy transformation to optimize energy structure; and take policy guidance as an auxiliary to constrain enterprise behaviors. The results of Shanghai have practical implications for urban green transformation. Most cities in China still have heavily rely on the secondary industry and lack a sufficient level of greening. They should aim to achieve coordinated optimization across multiple aspects according to their development requirements and accelerate the process of urban green transformation.

Policy implications

The green transformation of cities is a crucial strategy for achieving carbon reduction targets. By promoting green transformation, carbon emissions can be effectively reduced, environmental quality can be improved, and urban sustainability can be enhanced. It is important to recognize that green transformation is not only an environmental protection action but also a new catalyst for economic development. Based on research findings from Shanghai, cities should prioritize the importance of green transformation and adopt appropriate policy measures to facilitate its comprehensive implementation.

First and foremost, promoting the development of high-tech industries in the context of green transformation is a key direction. The government should increase support for high-tech industries by providing financial assistance and tax incentives. This will encourage enterprises to innovate and develop in the field of green technology, thus accelerating the growth of high-tech industries. Simultaneously, it is crucial to strengthen the oversight of enterprises to ensure their compliance with environmental regulations and standards during green transformation. In addition, establishing a green technology innovation platform can facilitate technical exchange and collaborative research and development among high-tech enterprises. This will promote the innovation and application of green technology, as well as facilitate the integration of high-tech industries with traditional sectors. Furthermore, efforts should be made to enhance the cultivation of high-tech talent by establishing relevant training institutions and research centers. Attracting more talented individuals to engage in the development of green technology industries will contribute to reducing carbon emissions, enhancing resource utilization efficiency, and achieving sustainable urban development.

Secondly, proactive promotion of clean and renewable energy development is pivotal to achieving carbon peaking. In light of the carbon reduction targets, cities must urgently prioritize the development of clean energy. To achieve this objective, the government should increase financial support for clean energy projects and encourage enterprises and individuals to invest in this sector. A range of preferential policies, such as tax and fee reductions for clean energy enterprises, as well as land and electricity subsidies, can be implemented to attract more investment in clean energy.

Lastly, improving the CET mechanism is essential for achieving carbon reduction targets. Currently, carbon trading pilots are concentrated in a limited number of cities. Going forward, more cities should establish robust platforms that provide a fair and transparent trading environment for enterprises and institutions. Such platforms should have efficient trading systems and regulatory mechanisms to ensure fairness and compliance in transactions. Simultaneously, a carbon emission quota allocation mechanism should be established to equitably distribute carbon emission rights based on the production capacity and emission levels of enterprises, incentivizing them to reduce carbon emissions. The government can encourage enterprise participation in carbon trading by establishing incentive mechanisms and providing economic and policy support. For instance, rewards can be granted to enterprises that demonstrate advanced emission reduction practices in the form of carbon emission rights. In addition, tax incentives for carbon trading can be implemented. It is critical to strengthen the supervision and enforcement of the carbon trading market to address illegal trading and fraudulent activities related to carbon emission rights. Maintaining market order and stability is essential. By improving the carbon trading mechanism, cities can also identify new economic growth opportunities and stimulate green transformation.

To promote green transformation, it is imperative to emphasize coordinated progress within the urban system. Coordinated progress entails collaboration and coordination among various departments, industries, and sectors of society to achieve comprehensive advancement towards carbon reduction goals and green transformation. Government departments at all levels should enhance policy integration and coordination, while avoiding conflicts and duplications. In addition, close cooperation with pertinent departments and industries should be pursued to jointly formulate and implement policies and measures for carbon reduction and green transformation. This collaborative approach will generate synergistic effects.

In summary, promoting green transformation necessitates government support and supervision, the promotion of high-tech industry development, the advancement of clean and renewable energy, enhancements to the carbon trading mechanism, and coordinated progress within the urban system. The recommendations provided in this paper aim to assist cities in formulating relevant policy measures that promote the achievement of green transformation, carbon reduction, and mutual benefits through sustainable development.

Limitations and future recommendations

This study presents a model construction and scenario simulation of urban green transformation systems, using Shanghai as a case study to explore carbon reduction targets. The research aims to provide a systemic perspective on the carbon flow in cities, considering the constraints of energy consumption and carbon emission trading (CET) policies. However, several limitations should be considered in the interpretation of these findings. Firstly, it should be noted that the green transformation strategies and implementation may vary among different cities. The focus of this study on Shanghai limits the generalizability of the findings to other cities at different stages of economic development. Therefore, future research should expand the scope of cities and categorize them based on their development stages to explore and compare the various green transformation paths. Secondly, the calculation of CO 2 production in this study only considers major types of fossil fuels, neglecting other sources of emissions. In addition, the selection of variables and their interrelationships in the construction of the system dynamics model might not be sufficiently comprehensive, thus limiting the universality of the model. Future research should incorporate additional factors and variables into the urban system to create a more comprehensive green transformation system dynamics model. Lastly, the scenario settings in this study are based on existing literature or historical data for predicting adjustable variables, which may fluctuate over time and affect the accuracy of future urban development predictions. Therefore, future research should consider employing other methods to design more reliable scenarios to enhance the accuracy of projections.

Therefore, while this study sheds light on the model construction and scenario simulation of urban green transformation systems, there are several limitations that need to be addressed in future research. Expanding the scope of cities, incorporating more factors and variables, and employing alternative scenario design methods are important directions for future investigation.

Data availability

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request. The historical data and predicted results used for the study will be presented in the supplementary materials.

Bao K, He G, Ruan J et al. (2023) Analysis on the resource and environmental carrying capacity of coal city based on improved system dynamics model: a case study of Huainan, China. Environ Sci Pollut Res 30:36728–36743

Article   Google Scholar  

Chen M, Ma M, Lin Y et al. (2022) Carbon Kuznets curve in China’s building operations: Retrospective and prospective trajectories. Sci. Total Environ. 803:150104

Article   ADS   CAS   PubMed   Google Scholar  

Crielaard L, Uleman JF, Châtel BDL et al. (2022) Refining the causal loop diagram: A tutorial for maximizing the contribution of domain expertise in computational system dynamics modeling. Psychol Methods. https://doi.org/10.1037/met0000484

Dong Y, Jin G, Deng X (2020) Dynamic interactive effects of urban land-use efficiency, industrial transformation, and carbon emissions. J Clean Prod 270:122547

Du K, Cheng Y, Yao X (2021) Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities. Energy Econ 98:105247

Du L, Li X, Zhao H et al. (2018) System dynamic modeling of urban carbon emissions based on the regional National Economy and Social Development Plan: A case study of Shanghai city. J Clean Prod 172:1501–1513

Fang Z (2023) Assessing the impact of renewable energy investment, green technology innovation, and industrialization on sustainable development: A case study of China. Renew Energy 205:772–782

Feng Y, Dong X, Zhao X et al. (2020) Evaluation of urban green development transformation process for Chinese cities during 2005–2016. J Clean Prod 266:121707

Forrester JW (1961) Industrial dynamics . Cambridge, Massachusetts

General Office of the State Council (2021) Opinions on Promoting Green Development of Urban and Rural Construction. General Office of the State Council

Guo S, Ma H (2023) Can urban digitalization significantly improve carbon emission efficiency?Evidence from 282 cities in China. Environ Sci Pollut Res 30:55214–55236

Guo C, Shao C, Ju M (2012) Carbon emission accounting and decomposition analysis of energy consumption in the industrial sub-sectors of Tianjin City. Res Environ Sci 25:232–239

Google Scholar  

Guo Y, Tong L, Mei L (2020) The effect of industrial agglomeration on green development efficiency in Northeast China since the revitalization. J Clean Prod 258:120584

Herrador M, de Jong W, Nasu K et al. (2023) The rising phenomenon of circular cities in Japan. Case studies of Kamikatsu, Osaki and Kitakyushu. Sci Total Environ 894:165052

Jia J, Xin L, Lu C et al. (2023) China’s CO2 emissions: a systematical decomposition concurrently from multi-sectors and multi-stages since 1980 by an extended logarithmic mean divisia index. Energy Strategy Rev 49:101141

Labussière O (2021) A coalbed methane ‘stratum’ for a low-carbon future: a critical inquiry from the Lorraine Basin (France). Polit Geogr 85:102328

Lee J, Akashi Y, Takaguchi H et al. (2021) Forecasting model of activities of the city-level for management of CO 2 emissions applicable to various cities. J Environ Manag 286:112210

Article   CAS   Google Scholar  

Li R, Li L, Wang Q (2022) The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces. Sustain Cities Soc 82:103880

Li Z, Wang J (2021) Spatial emission reduction effects of China’s carbon emissions trading: quasi-natural experiments and policy spillovers. Chinese J Popul Resour Environ 19:246–255

Li R, Wang Q, Liu Y et al. (2021) Per-capita carbon emissions in 147 countries: the effect of economic, energy, social, and trade structural changes. Sustain Prod Consump 27:1149–1164

Loiseau E, Saikku L, Antikainen R et al. (2016) Green economy and related concepts: an overview. J Clean Prod 139:361–371

Lu X, Tong D, He K (2022) China’s carbon neutrality: an extensive and profound systemic reform. Front Environ Sci Eng 17:14

Luo X, Liu C, Zhao H (2023) Driving factors and emission reduction scenarios analysis of CO2 emissions in Guangdong-Hong Kong-Macao Greater Bay Area and surrounding cities based on LMDI and system dynamics. Sci Total Environ 870:161966

Niu Z, Xiong J, Ding X et al. (2022) Analysis of China’s Carbon Peak Achievement in 2025. Energies 15:5041

Peng D, Liu H (2022) Measurement and driving factors of carbon emissions from coal consumption in China based on the Kaya-LMDI Model. Energies 16:439

Qian, Wang L, Cao F et al. (2023) Ecological health assessment and sustainability prediction in coastal area: a case study in Xiamen Bay, China. Ecol Indic 148:110047

Ren F, Liu X (2023) Evaluation of carbon emission reduction effect and porter effect of China’s carbon trading policy. Environ Sci Pollut Res 30:46527–46546

Song J, Wang J, Chen Z (2022) How low-carbon pilots affect Chinese urban energy efficiency: an explanation from technological progress. Int J Environ Res Public Health 19:15563

Article   CAS   PubMed   PubMed Central   Google Scholar  

Su Y, Li J, Yin S et al. (2023) Spatial and temporal variation characteristics and driving mechanisms of multidimensional socio-economic development levels in resource-based cities. Sustainability 15:1573

Su Z, Yang Y, Wang Y et al. (2023) Study on spatiotemporal evolution features and affecting factors of collaborative governance of pollution reduction and carbon abatement in urban agglomerations of the yellow river basin. Int J Environ Res Public Health 20:3994

Tang K, Zhou Y, Liang X et al. (2021) The effectiveness and heterogeneity of carbon emissions trading scheme in China. Environ Sci Pollut Res 28:17306–17318

Wang Y, Mo S, Zhang C et al. (2023) Decomposition of drivers and identification of decoupling states for the evolution of carbon emissions from energy consumption in China. Environ Sci Pollut Res 30:75629–75654

Wang J, Rienow A, David M et al. (2022) Green infrastructure connectivity analysis across spatiotemporal scales: a transferable approach in the Ruhr Metropolitan Area, Germany. Sci Total Environ 813:152463

Wang H, Shi W, He W et al. (2023) Simulation of urban transport carbon dioxide emission reduction environment economic policy in China: an integrated approach using agent-based modelling and system dynamics. J Clean Prod 392:136221

Wang Q, Wang X, Li R (2022) Does urbanization redefine the environmental Kuznets curve? An empirical analysis of 134 Countries. Sustain Cities Soc 76:103382

Wang L, Xue W (2023) Analysis of carbon emission drivers and multi-scenario projection of carbon peaks in the Yellow River Basin. Sci Rep 13:13684

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Wang Q, Yang T, Li R (2023) Does income inequality reshape the environmental Kuznets curve (EKC) hypothesis? A nonlinear panel data analysis. Environ Res 216:114575

Article   CAS   PubMed   Google Scholar  

Wang Q, Zhang F, Li R (2023) Revisiting the environmental kuznets curve hypothesis in 208 counties: the roles of trade openness, human capital, renewable energy and natural resource rent. Environ Res 216:114637

Wang Z, Zhang X, Zhang C et al. (2022) How regional integration affects urban green development efficiency: evidence from urban agglomeration in the middle reaches of the Yangtze River. Int J Environ Res Public Health 19:7937

Article   PubMed   PubMed Central   Google Scholar  

Wei YM, Chen K, Kang JN et al. (2022) Policy and management of carbon peaking and carbon neutrality: a literature review. Engineering 14:52–63

Wu Y, Li C, Shi K et al. (2022) Exploring the effect of urban sprawl on carbon dioxide emissions: an urban sprawl model analysis from remotely sensed nighttime light data. Environ Impact Assess Rev 93:106731

Wu Y, Xu B (2022) When will China’s carbon emissions peak? Evidence from judgment criteria and emissions reduction paths. Energy Rep 8:8722–8735

Xue F, Yao E (2022) Impact analysis of residential relocation on ownership, usage, and carbon-dioxide emissions of private cars. Energy 252:124110

Ye F, Xiong X, Li L et al. (2021) Measuring the effectiveness of the Chinese Certified Emission Reduction scheme in mitigating CO 2 emissions: a system dynamics approach. J Clean Prod 294:125355

Yu X, Dong Z, Zhou D et al. (2021) Integration of tradable green certificates trading and carbon emissions trading: How will Chinese power industry do? J Clean Prod 279:123485

Zhang Y, Li S, Luo T et al. (2020) The effect of emission trading policy on carbon emission reduction: evidence from an integrated study of pilot regions in China. J Clean Prod 265:121843

Zheng Y, Tan R, Zhang B (2023) The joint impact of the carbon market on carbon emissions, energy mix, and copollutants. Environ Res Lett 18:045007

Article   ADS   Google Scholar  

Zhou X, Niu A, Lin C (2023) Optimizing carbon emission forecast for modelling China’s 2030 provincial carbon emission quota allocation. J Environ Manage 325:116523

Download references

Acknowledgements

This paper is supported by the grant of National Natural Science Foundation of China (71874021, 71974024), the 2023 Research Project for International Students Studying in China (DUTLHLX202322).

Author information

Authors and affiliations.

School of Economics and Management, Dalian University of Technology, No.2 Ling Gong Road, Dalian, 116024, China

Hua Shang & Hailei Yin

You can also search for this author in PubMed   Google Scholar

Contributions

The corresponding author made contributions to this article, including conceptualization, drafting, and finalization, as well as editing for style and clarity. The first author provided ideas and theoretical guidance for the article.

Corresponding author

Correspondence to Hailei Yin .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

Informed consent

Additional information.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary table s1, supplementary table s2, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and Permissions

About this article

Cite this article.

Shang, H., Yin, H. Dynamic simulation research on urban green transformation under the target of carbon emission reduction: the example of Shanghai. Humanit Soc Sci Commun 10 , 754 (2023). https://doi.org/10.1057/s41599-023-02283-9

Download citation

Received : 08 July 2023

Accepted : 18 October 2023

Published : 30 October 2023

DOI : https://doi.org/10.1057/s41599-023-02283-9

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

This paper is in the following e-collection/theme issue:

Published on 2.11.2023 in Vol 25 (2023)

Temporal and Emotional Variations in People’s Perceptions of Mass Epidemic Infectious Disease After the COVID-19 Pandemic Using Influenza A as an Example: Topic Modeling and Sentiment Analysis Based on Weibo Data

Authors of this article:

Original Paper

• Jing Dai 1 * , PhD   ; 
• Fang Lyu 1 * , MS   ; 
• Lin Yu 1   ; 
• Yunyu He 2 , MM  

1 Kunming University of Science and Technology, Kunming, China

2 The First People’s Hospital of Yunnan Province, Kunimg, China

*these authors contributed equally

Corresponding Author:

Yunyu He, MM

The First People’s Hospital of Yunnan Province

57 Jinbi Road

Kunimg, 650093

Phone: 86 18987253562

Email: [email protected]

Background: The COVID-19 pandemic has had profound impacts on society, including public health, the economy, daily life, and social interactions. Social distancing measures, travel restrictions, and the influx of pandemic-related information on social media have all led to a significant shift in how individuals perceive and respond to health crises. In this context, there is a growing awareness of the role that social media platforms such as Weibo, among the largest and most influential social media sites in China, play in shaping public sentiment and influencing people’s behavior during public health emergencies.

Objective: This study aims to gain a comprehensive understanding of the sociospatial impact of mass epidemic infectious disease by analyzing the spatiotemporal variations and emotional orientations of the public after the COVID-19 pandemic. We use the outbreak of influenza A after the COVID-19 pandemic as a case study. Through temporal and spatial analyses, we aim to uncover specific variations in the attention and emotional orientations of people living in different provinces in China regarding influenza A. We sought to understand the societal impact of large-scale infectious diseases and the public’s stance after the COVID-19 pandemic to improve public health policies and communication strategies.

Methods: We selected Weibo as the data source and collected all influenza A–related Weibo posts from November 1, 2022, to March 31, 2023. These data included user names, geographic locations, posting times, content, repost counts, comments, likes, user types, and more. Subsequently, we used latent Dirichlet allocation topic modeling to analyze the public’s focus as well as the bidirectional long short-term memory model to conduct emotional analysis. We further classified the focus areas and emotional orientations of different regions.

Results: The research findings indicate that, compared with China’s western provinces, the eastern provinces exhibited a higher volume of Weibo posts, demonstrating a greater interest in influenza A. Moreover, inland provinces displayed elevated levels of concern compared with coastal regions. In addition, female users of Weibo exhibited a higher level of engagement than male users, with regular users comprising the majority of user types. The public’s focus was categorized into 23 main themes, with the overall emotional sentiment predominantly leaning toward negativity (making up 7562 out of 9111 [83%] sentiments).

Conclusions: The results of this study underscore the profound societal impact of the COVID-19 pandemic. People tend to be pessimistic toward new large-scale infectious diseases, and disparities exist in the levels of concern and emotional sentiments across different regions. This reflects diverse societal responses to health crises. By gaining an in-depth understanding of the public’s attitudes and focal points regarding these infectious diseases, governments and decision makers can better formulate policies and action plans to cater to the specific needs of different regions and enhance public health awareness.

Introduction

Over the past century, COVID-19 has emerged as one of the most widespread and impactful diseases. During the COVID-19 pandemic, the rapid transmission and extensive reach of the novel coronavirus, as well as the potentially fatal symptoms of the disease, were a cause for great concern. This not only had a profound impact on people’s lives and economies but also triggered widespread panic, which could lead individuals to experience fear, anxiety, and panic-driven behaviors, such as hoarding supplies or avoiding public places. Therefore, effective risk communication and emotional management are of paramount importance in mitigating the panic effect. In the backdrop of the COVID-19 pandemic, studying people’s focus and emotional orientation when confronted with new large-scale infectious diseases becomes crucial.

Research has shown that effective information dissemination can alleviate people’s fear of infectious diseases. Consequently, public awareness and an understanding of large-scale infectious diseases play a pivotal role in alleviating panic and prompting individuals to take action against this challenge. Personal perceptions of risk are often influenced by emotions. Positive emotions can make people more attentive and inclined to take proactive protective measures. When individuals have a more positive attitude toward pandemics, the recovery rate and control tend to be higher [ 1 ]. Conversely, negative emotions may lead to avoidance or inaction. Therefore, discussing the public’s attention to outbreaks of contagious diseases and the emotional shifts after the COVID-19 pandemic not only provides insights into changes in public attention to contagious diseases but also helps identify positive and negative emotions, as well as provides a more comprehensive understanding of the public’s stance on large-scale infectious diseases.

Simultaneously, discussing the public’s focus on large-scale infectious diseases and emotional orientation can not only help clarify the public’s perspectives on this issue but also assist in identifying the factors influencing emotions, both positive and negative, toward infectious diseases. Social media platforms play a vital role in disseminating information and shaping public opinion. Governments, health organizations, and public intellectuals can use these platforms to convey accurate information, reduce the spread of false information, and actively engage the public’s attention and actions regarding large-scale infectious diseases.

People are now more willing to express their opinions web-based and there is an abundance of data on social media platforms. Because of the convergence of opinions on the web, researchers can explore the changes in public discussion during the time change and likewise can focus on the public’s changing emotions about it. Considering current trends in technology, especially the role of computer science, it must be acknowledged that computer technology has made a major contribution to medical decision-making with regard to, for example, infectious diseases and epidemics [ 2 , 3 ]. The accurate and logical access sources of these data include social media platforms, which provide more valuable data than ever.

Weibo is among the largest and most influential social media sites in China. Weibo users can share their opinions, discuss current events, and express their emotions via PC using text, share pictures, and upload videos. Therefore, Weibo is an ideal platform for obtaining data sources of popular opinion texts. In addition, the opinions expressed on social networks are highly emotionally oriented; therefore, it is essential to analyze the emotions in the texts and content posted by users. Positive emotions are critical for motivation, perseverance, and prosocial behavior [ 4 , 5 ].

The existing literature on influenza sentiment orientation is mainly about COVID-19; for example, the study by Yin et al [ 6 ] is based on 13 million posts related to COVID-19 pneumonia collected over 2 weeks on Twitter (subsequently rebranded X), and the study by Harba et al [ 7 ] investigated how consumer sentiment evolved during the COVID-19 outbreak through content analysis and sentiment analysis of the texts of web-based restaurant reviews. Other mass infectious diseases have been studied to a lesser extent. Ng et al [ 8 ] studied public sentiment on the global outbreak of monkeypox on Twitter and analyzed 352,182 posts via unsupervised machine learning.

However, it is rare for an analysis of emotional orientation to analyze people’s attitudes toward other mass infectious diseases after experiencing the COVID-19 pandemic. Therefore, analyzing the public’s sentiment and changing views on the currently prevalent mass infectious disease, influenza A, through content posted on Weibo can accurately reflect the importance of public opinion in promoting policies related to epidemic prevention, increasing public awareness and participation in protective actions against the epidemic, and advancing the epidemic management process.

In surveys about emotions (questionnaires or interviews), respondents or interviewees may be influenced by the content of the questions or consider privacy issues and negative impacts, leading to difficulties in assessing emotions accurately and reasonably. Moreover, questionnaires do not allow access to, say, real-time influenza A sentiment, and data collection takes a long time and has high economic costs [ 9 ]. Therefore, we chose text mining as the research method to ensure the spatial and temporal diversity of data. Moreover, text mining applications have been used in various areas, including tourism [ 10 , 11 ], business [ 12 , 13 ], education [ 14 , 15 ], and health care [ 16 - 18 ] for a variety of beneficial purposes.

On the basis of the analysis described in the previous subsection, this study used a web crawler approach to obtain people’s opinions about influenza A. Thematic model analysis and sentiment analysis were used to explore people’s attention, concerns, and sentiments about the recent epidemic of the mass infectious disease. The topic analysis used latent Dirichlet allocation (LDA) to extract latent topics from comment text data. For comment text sentiment analysis, deep learning, that is, the bidirectional long short-term memory (BiLSTM) model, was chosen to classify sentiment. This study attempts to answer the following questions:

• How concerned are people about the recently prevalent infectious disease, influenza A, after experiencing the COVID-19 pandemic? How does the concern differ from province to province?
• What are the spatiotemporal differences between the total number of blog posts and the public’s attention to influenza A?
• What are the changes in the public’s attitude toward infectious diseases after experiencing the COVID-19 outbreak? What are the most critical concerns of the people when a new infectious disease is spreading?
• What is the public sentiment toward epidemic infectious diseases? How does it vary by region?
• What are the drivers of positive and negative emotions?

We primarily used web crawling techniques to acquire data. After preprocessing the data, we further explored and analyzed the data using 2 models, LDA and BiLSTM, and obtained some meaningful conclusions, as shown in Figure 1 .

Preprocessing

We used web crawling techniques to collect 9351 posts on Weibo related to “influenza A” from November 1, 2022, to March 31, 2023. These data were used to create a data set that included user names, locations, posting times, content, repost counts, comments, likes, user types, and more.

To ensure the validity and stability of the data set, we removed duplicate data, deleted posts with <6 characters, and eliminated meaningless stop words, expressions, punctuation marks, and numbers. We also conducted semantic integration by summarizing words with similar meanings in the vocabulary.

Text Mining Analysis

Lda topic model.

The standard topic models are latent semantic analysis, probabilistic latent semantic analysis, LDA, and hierarchical Dirichlet process. On the basis of text features and research needs, this study used LDA to extract latent topics from comment text data. LDA is an unsupervised machine learning technique that can identify potential topic information in large document sets or corpora. It uses a bag-of-words approach that treats each document as a vector of word frequencies, thereby converting textual information into numerical information that can be easily modeled. The model was first proposed by Blei et al [ 19 ] in 2003, along with the concepts and ideas of the LDA model. It is a 3-level Bayesian probabilistic model containing words, topics, and documents, and the document generation process is shown in Figure 2 . In this study, the LDA model was used to investigate public attention to potential topics and understand the focus of public attention.

Sentiment Analysis

Comment text data are typically categorized into positive and negative sentiments for comment text sentiment analysis. There are 3 approaches to text sentiment analysis: sentiment analysis based on sentiment lexicon, sentiment analysis based on machine learning, and sentiment parsing based on deep knowledge. However, when it comes to sentiment analysis of medical service reviews, using a sentiment dictionary constructed based on electronic commerce reviews may lead to significant errors. Deep learning methods have shown clear advantages in sentiment analysis, breaking free from complex rule-based setups and demonstrating superior recognition performance, with the evaluation metrics and results significantly outperforming those achieved using traditional rule-based learning models. Research into deep learning models for sentiment recognition has primarily focused on the field of neural networks. However, owing to the large number of parameters in deep neural networks, they tend to overfit on limited data sets. To address this challenge, Vaswani et al [ 20 ] introduced the transformer deep learning model, which combines self-attention mechanisms, achieving fast and parallelized training and effectively addressing the issues of slow training and overfitting. Pretrained models have found extensive application in natural language processing tasks, particularly in domain-specific sentiment analysis. Nevertheless, regular corpora often fail to cover various domain-specific terminologies, resulting in certain limitations in the application of pretrained models such as bidirectional encoder representations from transformers in sentiment analysis research within the field of web-based sentiment. Research results indicate that, compared with other traditional sentiment analysis methods such as long short-term memory (LSTM), recurrent neural network, convolutional neural network, and naïve Bayes, BiLSTM models exhibit higher efficiency because they can effectively capture semantic information, achieving >90% accuracy in context understanding [ 21 ]. In sentiment analysis, positive and negative sentiments are typically the core focus because they directly relate to emotional polarity, which is crucial for many applications, such as sentiment trend analysis. Although some sentiment analysis tasks may include the classification of neutral sentiments, this choice often depends on specific application scenarios. Nevertheless, to maintain the research’s focus and clarity, we opted to solely concentrate on positive and negative sentiments. After careful consideration, we selected deep learning, specifically the BiLSTM model, for sentiment classification and categorized sentiment values into positive and negative emotions.

BiLSTM is a bidirectional recurrent neural network that takes the entire sentence’s words as input and considers the contextual information of the text. This allows information to be processed in both forward and backward directions [ 22 , 23 ]. As illustrated in Figure 3 , BiLSTM combines forward LSTM and backward LSTM. Compared with convolutional neural network and LSTM, the BiLSTM model demonstrates superior performance, achieving an accuracy rate of >90% [ 21 ]. The internal structure of LSTM is depicted in Figure 4 .

Ethical Considerations

This study was approved by the medical ethics committee of the First People’s Hospital of Yunnan province (2022ZYFB001). The study used open-access social media data and excluded all personal information; therefore, informed consent was not required.

Basic Information About Blog Posts and Public Attention

Trends in the number of blog posts and public attention over time.

First, a fundamental descriptive statistical analysis of blog post volume was conducted to analyze the trend in public concern about influenza A. As seen in Figure 5 , the public concern about the change in influenza A showed a significant increasing trend over time. In November 2022, there were 231 posts on Weibo related to the influenza A. In December, this number increased significantly to 1073 posts. Moving into January 2023, there were 194 posts, and in February, the number surged to 1703 posts. By March, the conversation intensified further, with a total of 5910 posts on the topic. After the COVID-19 pandemic, influenza A is a recent epidemic that has received much attention.

Spatial Difference Analysis of Blog Posts and Public Attention

There are considerable regional variations in the levels of concern about influenza A among Chinese provinces. This paper investigated the correlation between the number of blog posts and concerns about a potential mass epidemic in different areas of China, revealing some intriguing findings.

The study involved calculating the number of blog posts and the level of worry about influenza A for each of the 34 provinces. The findings, as depicted in Figure 6 , highlight a substantial disparity in the number of blog posts between China’s eastern and western regions. Specifically, the Yellow River basin (including the provinces of Henan, Shandong, Hebei, and Shanxi) exhibits a relatively high number of blog posts, whereas the northwest region demonstrates the lowest. This pattern corresponds to the trapezoidal downward development trend observed in China, where the number of blog posts gradually diminishes from the eastern coastal areas to the western inland regions. Furthermore, the analysis identifies Beijing as the province with the highest number of published blog posts. In terms of ranking, Beijing, Zhejiang, Jiangsu, Shandong, and Sichuan occupy the top 5 positions. This indicates that these provinces expressed greater concern about influenza A than the others.

Comparative Analysis of Influenza A Attention Among Different Genders and User Types

Among different genders, there are 2122 male users and 5997 female users. It is evident that the number of posts made by female users surpasses that of male users. This observation suggests that women exhibit a higher level of concern about influenza A and actively engage in discussions on the internet regarding this topic. Their willingness to participate indicates a significant interest in the subject matter. Furthermore, Weibo classifies its users into 4 categories: blue V users, yellow V users, red V users, and regular users (the “V” label is akin to a verification symbol). Blue V users typically represent businesses or departments affiliated with certified institutions. These entities are required to undergo certification processes involving recognized organizations such as governments, businesses, schools, and media. Yellow V users, by contrast, are certified accounts belonging to renowned individuals in fields such as entertainment, sports, media, finance and economics, science and technology, literature and publishing, humanities and arts, games, military aviation, animation, tourism, and fashion, as well as government officials. Finally, red V users are certified accounts that achieve a minimum of 10 million monthly reads, granting them the red V certification. This distinction is a testament to the users’ popularity and influence on the platform.

Among all users, regular users make up the majority, accounting for 83% (7562/9111); following them are yellow V users at 10% (911/9111); blue V users at 5% (455/9111); while red V users comprise only 2% (183/9111). This observation implies that the topic of influenza A holds significant importance and captures the interest of the general public. The fact that ordinary users, who represent the majority of users on Weibo, display the greatest interest in this topic further emphasizes its relevance and the widespread concern among the public. It suggests that discussions and information related to influenza A are highly valued and sought after by ordinary individuals, highlighting the significance of this topic in the public discourse.

Influenza A Topic Analysis

Word frequency analysis.

The word frequency analysis, shown in Textbox 1 , is used to analyze the concerns that people have about influenza A. The textbox shows that the words “Covid-19,” “infection,” “virus,” “influenza,” “flu,” and “feeling” are the main focus of people’s attention. This indicates that people will compare influenza, fever, and COVID-19 when concerned about influenza A and that the symptoms after falling sick are the most important. In addition to the aforementioned words, words such as “hospital,” “mask,” and “vaccine” appear more frequently. This indicates that people are also very worried about the related protective and treatment measures and the distribution of medical resources when concerned about influenza A.

• Covid-19: 4445
• Infection: 3437
• Virus: 2946
• Influenza: 2447
• Fever: 2107
• Symptoms: 1843
• Hospitals: 1537
• Schools: 1324
• Student: 1324
• Children: 1273
• Vaccine: 1206
• Outbreak: 1122
• Feeling: 1003
• Health: 904

Hot Topic Analysis

In this study, the LDA topic model was used for topic mining. The hyperparameters α and β were set as symmetric Dirichlet priors with values of 50/T and .01, respectively. The number of iterations for Gibbs sampling was set to 100, and the document contribution threshold ε was set to 1/k. The LDA model plays a crucial role in determining the number of potential topics and assigning meaningful labels to these topics. We used perplexity values to identify the optimal number of topics for the LDA model.

To determine the optimal number of topics, we conducted experiments with topic values ranging from 1 to 25 and generated a consistency curve fit, as depicted in Figure 7 . On the basis of the results, 23 topics were identified as the most suitable for analysis. The right-hand section of Figure 8 illustrates the top 30 words with the highest frequency associated with each of the 23 topics.

From Figure 8 , it is evident that there is a high degree of overlap among topics 1, 5, and 8. Textbox 2 reveals that these topics share common keywords such as “school,” “students,” and “classes.” The topics discussed revolve around the suspension of classes at primary and secondary schools owing to a rise in influenza A cases. In addition, topics 7 and 21 also exhibit a significant overlap. Moreover, there is a substantial crossover between topics 7 and 21, as well as among topics 6, 9, and 17. In Figure 8 , the larger the circle in the left-hand section, the more critical the topic. Therefore, the blog posts with the highest attention paid to influenza A are topics 1, 2, 3, 4, 6, and 7. These highly discussed topics will be further analyzed.

Topics and content

• Covid-19, school, students, class, prevention, control, outbreak, command, primary school, virus, symptoms, children, testing, antigens, and precautions
• granules, Pfizer medicine, western medicine, clinical, price, efficacy, Covid-19, national, Pfizer, pharmaceuticals, pharmacy, treatment, protocol, drug, and patients
• pneumonia, epidemic, patient, patients, research, immunity, disease, symptoms, virus, situation, capsules, clinical, methods, traditional Chinese medicine, and time
• influenza, symptoms, influenza virus, oseltamivir, drugs, antiviral, population, general, high Incidence, virus, dosing, patients, video, taking, and influenza vaccine
• parents, students, Covid-19, positive, children, symptoms, virus, antigen, news, outbreak, school, class, test, virus infection, and elementary school
• virus, influenza, Covid-19, human, transmission, everyone, virus strain, medical, nucleic acid, variant, positive, data, avian influenza, general, and mortality
• company, pharmaceuticals, vaccines, limited company, pharmaceutical industry， national, work, Chinese Yuan, center, products, market, projects, production, sales, and hospitals
• school, student, Covid-19, class, influenza, infectious disease, outbreak, primary school, symptoms, education bureau, situation, part, oral disease, and parents
• vaccine, Covid-19, link, web page, biological, cell, protein, population, antibody, virus, variant, level, elderly, research, and antigen
• feeling, throat, symptoms, sore throat, runny nose, slight, headache, body, body aches all over, stuffy nose, snot, whole body, pharynx, dizziness, and taste
• hospital, viral, infection, influenza, patients, reporters, symptoms, disease, people, virus, situation, feelings, antigen, Covid-19, people’s daily, and nausea
• sickness, infection, home, friends, teacher, classmates, school, exam, record, dormitory, colleague, good night, infection to, and almost
• hospital, doctor, nucleic acid, test, check, outpatient, home, negative, symptoms, oseltamivir, community, queue, Covid-19 reinfection, daughter, and influenza
• mom, son, dad, sister, adult, world, child, brother, life, diarrhea, family members, school, family, medicine, and housemate
• body temperature, a little bit, all over the body, mental, state, bed, oseltamivir, hour, special medicine, antipyretic, day, affect, appetite, weakness, and aunt
• child, fever medicine, hour, cooling, wave influenza A, All, warm water, disinfection, temperature, physical, everyone, situation, parents, moisture, and children
• mask, month, personnel, ventilation, work, Covid-19, subtype, home, everyone, mobile, personal, time, first wave, and diligent hand washing
• Covid-19, video, influenza B, school, aftermath, news, experiences, experts, positive rate, prevention, help, national, infectiousness, large number, and events
• body, people, antigen, race, licorice, cold medicine, problem, situation, outrageous, advice, acute, magic, medicine, weight, ingredients, and pharyngitis
• symptoms, soreness, general, advice, whole body, food nourishment, muscle, nasal congestion, infection period, inflammation, healthy, sore throat, throat, runny, and stomach
• start school, infectious disease, basic, epidemic, family, spread, awareness, times, infectiousness, unable, probability, eyes, task, period, and science
• life, kids, roommates, resistance, exercise, experts, parent, programs, moms, professors, gym, nutrition, dad, chief, physician, good, and news
• kids, colleague, throat, influenza, vaccine, nose, infusion, go out, play, leader, thing, diary, neighborhood, oseltamivir, cake, care, and what

In topic 1, the keywords include “Covid-19,” “school,” “students,” “class,” “prevention and control,” “outbreak,” “command,” “primary school,” “virus,” “symptoms,” “children,” and “testing.” This topic focuses on the outbreak of influenza A in primary and secondary schools. Because of the gathering of people and the relative vulnerability of children, who are more susceptible to influenza A than adults, there is heightened societal concern about large-scale infections.

On social media platforms, individuals often express their concerns when their children contract influenza A. Parents who have not been infected themselves are worried about what preventive measures they can take against influenza A. These prevention efforts encompass a range of measures, including enhancing hygiene management and supervision at educational institutions; implementing disinfection and ventilation protocols; promptly identifying and isolating patients who have fallen ill and providing necessary treatment; raising awareness about protection measures among teachers, students, and parents; and reinforcing virus and antibody testing. Overall, the outbreak of influenza A at primary and secondary schools poses a significant public health challenge that necessitates collaborative efforts from the government, schools, parents, and the community to prevent and control its spread. Given the impact of the COVID-19 pandemic, there is heightened societal concern regarding mass infectious diseases, emphasizing the need for increased attention toward prevention and response to safeguard the health and safety of our children.

Compared with topic 1, topic 2 places more emphasis on the drugs used for combating influenza A, including their prices, efficacy, and the pharmaceutical manufacturers involved. Keywords associated with this topic include “Chinese medicine,” “Western medicine,” “clinical,” “treatment,” “Pfizer,” and “pharmacy.” The scarcity of drugs during the COVID-19 pandemic made it imperative to focus on drug-related aspects when addressing a new large-scale epidemic. Simultaneously, people want the pharmaceutical industry to develop specific drugs for contagious diseases, aiming to help individuals avoid illness. As is evident from the keywords, traditional Chinese medicine (TCM) holds a significant role in addressing the recent outbreaks of contagious diseases, garnering appreciation from the public. However, the issue of antibiotic misuse persists, particularly among patients with respiratory infections. Although various studies have been conducted to address the reduction of irrational antibiotic use, only a few have been multicenter or randomized trials. Exploring novel and innovative methods of administering medications is crucial to achieving the societal objectives of reducing irrational antibiotic use and eliminating unreasonable drug use. Therefore, providing education on the appropriate use of antibiotics during large-scale epidemic outbreaks is critical. Moreover, attention should be directed toward the drugs used to treat influenza A and their pricing to ensure that the public can access effective treatment promptly. This focus also aims to promote the research, development, and production efforts of pharmaceutical manufacturers in this field.

As depicted in Figure 8 , topic 3 exhibits overlap with topic 2, sharing common areas of focus such as clinical aspects, methodologies, and TCM. Topic 3 specifically concentrates on the rational use of medications for managing influenza A symptoms. In light of the recent outbreak of the novel coronavirus, there has been heightened interest in mass infectious diseases, leading to a deeper understanding of the influenza A virus. This includes comprehending the symptoms caused by the virus, the human immune system’s response, and making comparisons with the novel coronavirus. Furthermore, individuals are likely to express concerns regarding the transmission of the influenza A virus, the efficacy of herbal treatments, and available clinical treatment options. Consequently, the outbreak of the novel coronavirus has significantly elevated the public’s awareness and comprehension of epidemic infectious diseases.

The topic 4 keywords encompass “influenza,” “symptoms,” “influenza virus,” “oseltamivir “ “drugs,” “antiviral,” “population,” “general,” “high incidence,” “virus,” “dosing,” “patients,” “video,” “taking,” and “influenza vaccine,” highlighting the focus on influenza A itself. Simultaneously with rapid ecological changes, accelerated urbanization, the impact of influenza A, and increased risks associated with travel and globalization, epidemics are becoming more frequent, complex, and challenging to prevent and control. In recent years, the general public has become increasingly aware of the health implications of epidemics, as evidenced by the appearance of keywords such as “antiviral,” “high incidence,” and “influenza vaccine” in topic 4. In conclusion, effectively responding to large-scale infectious diseases such as influenza A necessitates collaborative efforts among the government, medical institutions, pharmaceutical manufacturers, academia, and the public. By enhancing public education, improving preventive measures, and promoting rational drug use, the incidence and transmission risks of epidemics can be reduced, thereby ensuring public health and safety. In addition, it is crucial to learn from the experiences of the COVID-19 pandemic, enhance the public’s awareness and understanding of mass infectious diseases, and drive continual improvement and progress in epidemic prevention and control.

Keywords for topic 6 include “virus,” “influenza,” “Covid-19,” “human,” “transmission,” “everyone,” “viral strain,” “medical,” “nucleic acid,” “variant,” “positive,” “data,” “avian influenza,” “general,” and “mortality.” The focus is on the discussion of viruses. Influenza A is an influenza virus that belongs to the family Orthomyxoviridae, a different family of viruses than the novel coronavirus. The virulence of the influenza A virus is relatively low, but it spreads quickly and is easily disseminated among the population. The main symptoms of influenza A include fever, cough, sore throat, muscle pain, fatigue, and headache, which usually appear within 2 to 3 days after infection. The mortality rate of the influenza A virus is low. However, it may cause more severe complications in specific populations, such as older adults, young children, pregnant women, and people with weakened immune systems. It is important to note that the influenza A virus and the novel coronavirus have different characteristics and impacts on public health. It is worth noting that topic 6 mentions comparisons with previous major infectious viruses when discussing influenza A viruses, including the ones responsible for COVID-19 and avian influenza.

Under topic 7, the keywords include “company,” “pharmaceuticals,” “vaccines,” “limited company,” “pharmaceutical industry,” “national,” “work,” “Chinese Yuan” “center,” “products,” “market,” and “projects.” This topic focuses on the public’s interest in pandemic vaccines. Influenza viruses are classified into 3 serotypes: A, B, and C. Type A has the potential to cause large-scale epidemics owing to the variation in the structure of its antigens, which occurs approximately once every 10 to 15 years. Type B epidemics are typically milder and more limited in scope, whereas type C generally causes milder epidemics. Humans are universally susceptible to all 3 types, and all 3 types can cause various respiratory conditions such as laryngitis, bronchitis, bronchiectasis, capillary bronchitis, and pneumonia.

In Figure 9 , the left-hand side represents the 4 provinces with the highest posting activity, whereas the right-hand side shows the number of posts corresponding to negative emotional themes. The research findings indicate that the topic of greatest concern among users is topic 12, which revolves around infections in schools. This is primarily because of the closure of schools after the influenza A outbreak, and the susceptibility of children in school environments to infection. The next topic of interest is topic 10, which includes keywords such as “feeling,” “throat,” “symptoms,” “sore throat,” “runny nose,” “slight headache,” “body aches over all,” “stuffy nose,” “snot,” “whole body,” “dizziness,” and “taste.” This topic pertains to postinfection symptoms because the symptoms associated with influenza A infections are prominent, leading individuals to experience physical and emotional distress, thereby contributing to more negative sentiment.

Influenza A Change Sentiment Orientation Analysis

Spatial difference analysis.

Emotional distribution can reflect the public’s attitude and sentiment toward relevant issues. In this paper, we categorized emotional orientation as positive or negative. According to our analysis, the public’s emotional exposure toward influenza is mainly negative, with negative emotions accounting for 83% (7562/9111), whereas positive emotions account for only 17% (1549/9111). This indicates that although the COVID-19 pandemic has brought many adverse effects, the public’s attitude toward influenza still needs to be more optimistic. We also analyzed the emotional orientation of different provinces toward influenza A. Figure 10 shows that each region holds a negative attitude toward influenza A, and there is little difference in the ratio of positive and negative emotions. We mainly focused on 3 regions—Qinghai, Yunnan, and Tibet—and found that they have a stronger negative emotional orientation than other sites.

The Factors Influencing Sentiment Orientation

On the basis of the study’s analysis, further exploration was conducted to understand the reasons behind positive and negative emotions among the public regarding influenza A. In the word frequency analysis concerning positive emotions, the following terms hold significance within the data set: “COVID-19” appears 1863 times, “influenza A” is documented 1768 times, “Infection” occurs 1596 times, “Virus” is mentioned 1033 times, “Influenza” is noted 1008 times, “Symptoms” is found 1001 times, “Control” is used 909 times, “Prevention” appears 854 times, “Outbreak” is mentioned 829 times, “Vaccine” occurs 818 times, “Fever” is referenced 719 times, “Children” is included 709 times, “Hospital” appears 706 times, “Malaise” is used 681 times, and “Classes” is seen 622 times. In addition to the high-frequency term “influenza A,” the public often discussed terms such as “prevention,” “control,” and “vaccine,” an indication of their concern and focus on influenza A. This suggests that the positive sentiment toward the influenza A epidemic primarily stems from effective prevention and control measures and the availability of a reliable vaccine. Furthermore, discussions about antiviral drugs and treatment reflect the public’s trust and expectation of scientific treatment options.

In the word frequency analysis pertaining to negative emotions, the following terms play a significant role in the data: “influenza A” appears 6069 times, “COVID-19” occurs 1729 times, “fever” is found 1373 times, “infection” appears 903 times, “myself” is present 820 times, “today” is mentioned 816 times, “influenza” is documented 778 times, “symptoms” is noted 759 times, “cold” is mentioned 730 times, “feeling” appears 721 times, “virus” occurs 679 times, “hospital” is seen 616 times, “uncomfortable” is used 599 times, and “child” is included 527 times. Finally, “cough” is listed 522 times. The common words associated with negative sentiment in blog posts, including “infection,” “fever,” and “symptoms” reflect the negative emotions stemming from public concern about the influenza A outbreak and the discomfort experienced by those who fall sick. In addition, inaccurate rumors and misunderstandings can contribute to negative emotions among the public. Therefore, it is crucial to disseminate scientific and accurate information while implementing timely epidemic prevention and control measures. These actions can effectively alleviate negative emotions, enhance public confidence and resilience, and collectively address the challenges posed by the influenza A epidemic.

Principal Findings

The level of concern regarding the recently prevalent infectious disease, influenza A, has shown variations across Chinese provinces, influenced by the experience of the COVID-19 pandemic. Notably, the central region of China seems to display a heightened level of concern, whereas the northwest region exhibits a lower level of attention. This geographic disparity is reflected in both the total number of blog posts and the public’s attention to influenza A, demonstrating fluctuations over time. These fluctuations underscore the dynamic nature of public attention to infectious diseases and emphasize the necessity for region-specific communication strategies. Furthermore, the research findings suggest that individuals become more sensitized with regard to infectious diseases and exhibit increased levels of concern, especially in the face of the spread of a new infectious disease.

Interpretation

Spatiotemporal differences between blog posts and public attention.

From November 1, 2022, to March 31, 2023, there was an increase in the number of posts related to influenza A, indicating a growing concern among the public regarding this issue. Figure 6 illustrates that the number of posts is relatively lower in the western region and higher in the eastern part of the country, with a concentration in the central area. This pattern may be attributed to the higher population density and greater mobility in the eastern part, leading to a faster spread of influenza A and prompting more people to pay attention to the topic and discuss it. In addition, the central region, characterized by a more densely populated area, facilitates frequent information exchange among its residents, resulting in an increased number of posts on Weibo. Notably, Beijing has the highest number of posts among all provinces. This can be attributed to Beijing being a region with high population density and significant mobility, which may contribute to a faster spread of influenza A and generate more attention and discussion on the topic. Moreover, Beijing’s advanced internet infrastructure and the widespread adoption of social media platforms also contribute to the higher number of posts.

Difference Analysis of Influenza A Attention Among Different Genders and User Types

This study of the genders and types of users shows that female users are much more concerned about influenza A than men. This can be explained in several ways. First, women are more concerned about health and personal hygiene issues [ 24 ], which makes them more worried about the influenza A outbreak. Second, more women than men work in medical and nursing professions [ 25 ], which means that diseases such as influenza A are top of mind for them. This also contributes to their higher level of concern about influenza A. In addition, information about influenza A is usually more widely disseminated by women in the family [ 26 ]. Women typically play more active roles in the family as primary family caregivers, guardians of children, and so on [ 27 ]. Therefore, they are more likely to spread information about influenza A within the family. In addition, some studies show that women are better at expressing emotions and empathy [ 28 ]. Women’s risk perception ability is sharper when faced with a public health event [ 29 ], and they are more likely to pay attention to information about influenza A. From another perspective, there is a reason why there are many Weibo users with posts related to influenza A. First, influenza A is a prevalent infectious disease that can affect most people. Therefore, many people are concerned about information related to influenza A. Second, the symptoms of influenza A are similar to those of some common diseases, such as cold and influenza, which makes many people search for influenza A–related information when they have similar symptoms.

Building from previous studies that focus on influenza [ 30 - 32 ], this study highlights that the health topic of greatest public concern in China is influenza A and its characteristics. As a highly contagious disease, influenza A, which shares similarities with influenza, is known to be more painful than influenza and prone to severe complications, including death. Consequently, the public is eager to acquire more information about influenza A to safeguard their health and that of their families. Furthermore, both the novel coronavirus and the influenza A virus are respiratory viruses, prompting comparisons between the two. Consequently, understanding the differences and similarities between influenza A and COVID-19 can empower the public to comprehend both diseases better and adopt more effective preventive and control measures.

The next topic of interest is viruses. As influenza A is a virus-transmitted disease, it is essential to understand its virulence, symptoms, mortality rate, and transmission rate to understand the disease. This is also because the spread of the virus directly affects public health and social stability; therefore, naturally, the public is concerned about the virus.

Another topic is the public’s concern about preventing mass epidemic infectious diseases through the use of vaccines. The reasons for this are easy to understand. First, as vaccines are one of the most effective measures to prevent disease [ 33 , 34 ], the public began to pay more attention to the development of a vaccine in the hope that reliable preventive measures would be available early. Considering the role played by vaccines during the COVID-19 pandemic, we can see the importance of vaccines in controlling the spread of diseases and providing the public with effective measures to prevent the spread of epidemics. Second, public concern is also related to the safety and efficacy of vaccines [ 35 , 36 ] because vaccinating oneself is a significant decision involving everyone’s health and life. Finally, the public’s concern about epidemic vaccines is also related to health care systems and policies [ 36 , 37 ]. Vaccine development, production, and distribution require the support and regulation of health care systems and policies.

In addition to prevention, people are also concerned about the drugs used to treat influenza A, the price and efficacy of the drugs, and the drug manufacturers. This may be related to the COVID-19 outbreak. As the COVID-19 outbreak continues to pose a threat to people’s physical and mental health, there is still concern among the public about contracting the virus. In addition, people are also worried about the efficacy and side effects of antiviral medications and want to know details about their safety and applicability to make the proper treatment choice [ 38 ]. Pharmaceutical manufacturers have also become the focus of public attention because they are essential players in producing influenza A treatment drugs. Many TCM institutions and physicians actively responded during the COVID-19 pandemic and achieved some significant treatment results [ 39 - 41 ]. This also drew public attention to TCM’s role during the epidemic, and people increasingly value TCM; in fact, the treatment of influenza A by TCM has received much attention [ 42 - 45 ].

The next concern is the rational use of medication after contracting influenza A. This may be related to the COVID-19 outbreak, in the sense that the public is more concerned now about using the correct medications to relieve influenza A symptoms. In this context, the public is more concerned about using medications to relieve influenza A symptoms correctly. In addition, owing to the popularity of the internet and social media, public health awareness is gradually increasing, and people are more willing now to actively seek health information and treatment advice [ 46 - 48 ]. At the same time, the continuous advancement of medical technology has made the treatment methods for influenza A more and more diversified and precise, making the public more concerned about the rational use of medication to treat influenza A.

One fascinating topic was the influenza A outbreak in primary and secondary schools. This relates to the closure of primary and secondary schools in China during the COVID-19 pandemic when the government took several measures to prevent the spread of the disease. This resulted in students being unable to attend school, and many students began to study independently or receive distance learning at home. This situation has led to an increase in parents’ concerns about the safety and hygiene standards prevalent in schools and other educational institutions [ 49 - 51 ]. Besides, it is known that schools can become a source of mass infections among children.

Sentiment Orientation Analysis

Understanding public sentiment regarding the influenza A epidemic in light of the COVID-19 outbreak is crucial because it reflects public perceptions and attitudes toward health and disease, as well as their level of confidence and trust in outbreak prevention and control measures. The results of our study indicate that 83% (7357/9111) of Chinese individuals hold negative attitudes toward influenza A. These negative emotions are not primarily directed at the government or official institutions but rather stem from people’s psychological distress and anxiety regarding physical discomfort because influenza A can cause physical pain, fever, cough, and weakness, leading to individuals feeling unwell and physically burdened; in addition, given the recent experience of the COVID-19 pandemic, the emergence of influenza A exacerbates people’s psychological exhaustion and weariness.

At the same time, there are also positive emotions associated with confronting influenza A; for example, the efforts of the Chinese government in implementing various measures to address the influenza A outbreak, including vaccination programs, have helped the public to better cope with the outbreak and instilled confidence in the government’s response.

Limitations

Data source limitations.

It is important to acknowledge the limitations of our data source. Weibo users, primarily composed of the younger demographic, may not provide a comprehensive representation of society as a whole. Furthermore, the attitudes and sentiments expressed on Weibo may not be entirely reflective of the broader societal attitude. It is crucial to recognize that Weibo users’ opinions may not necessarily encompass the perspectives of the entire community.

Spatiotemporal Analysis Constraints

Our study’s spatiotemporal analysis is subject to certain constraints. Specifically, we focused on analyzing people’s attitudes toward influenza A during a specific time frame after the COVID-19 pandemic. Unfortunately, we did not conduct a comparative analysis of attitudes before and during the COVID-19 pandemic. This limitation restricts our ability to provide insights into how the pandemic might have influenced changes in attitudes over time. In future research, comparing prepandemic and pandemic-era attitudes could yield valuable additional insights.

Conclusions

The COVID-19 pandemic has significantly increased public awareness of mass infections and the importance of preventive and control measures. In this context, this study on influenza A and its analysis of public sentiment provide valuable insights into the changing attitudes and concerns of the public. These findings can positively affect epidemic prevention and control efforts in the following ways.

Effective Communication Policies

Understanding public sentiment regarding the influenza A epidemic empowers the government and health organizations to devise communication policies tailored to the public’s perceptions and concerns. By addressing these, they can enhance the public’s comprehension of the outbreak and encourage the adoption of suitable protective measures. This proactive communication strategy plays a pivotal role in effectively curbing the spread of the epidemic; for instance, the government may implement a comprehensive communication plan, including daily updates on infection rates, guidelines for mask wearing, and information on vaccination centers, all designed to keep the public well informed.

Promoting Vigilance and Preventive Awareness

Positive public attitudes toward the influenza A epidemic can heighten public vigilance and awareness of preventive measures. A positive outlook encourages individuals to proactively engage in protective behaviors such as regular handwashing, consistent mask use, and avoidance of crowded areas. These actions reduce the risk of infection and contribute significantly to slowing down the transmission of the virus. To promote this, public health campaigns can emphasize the role of these behaviors in reducing transmission rates and saving lives.

Promptly Addressing Public Concerns

Understanding public attitudes and concerns about the influenza A epidemic equips health organizations and government authorities to promptly respond to public inquiries and address worries. By strengthening public information campaigns and educational initiatives focused on influenza A, they can bolster the public’s confidence and willingness to cooperate with recommended control and prevention measures; for example, they may establish hotlines or web-based forums where experts provide real-time answers to common questions, alleviating public concerns and building trust in official guidance.

Risk Assessment and Adaptive Policies

Negative public sentiment regarding influenza A in China indicates the necessity for a comprehensive risk assessment. Understanding public opinion allows health organizations and government entities to swiftly adapt prevention and control measures. This includes the development of targeted policies and guidelines that align with the evolving public sentiment; for instance, if negative sentiment arises owing to perceived vaccine shortages, authorities can swiftly adjust vaccine distribution strategies and communicate these changes transparently to rebuild trust.

Enhancing Management Capacity and Public Cooperation

A profound understanding of public sentiment helps enhance the management capacity of health organizations and government bodies. It strengthens communication channels and cooperation with the public, fostering a more robust social collaboration mechanism. This, in turn, facilitates the seamless implementation of epidemic prevention and control measures; for example, regular public engagement forums can be established, allowing citizens to voice concerns and provide input into decision-making processes, ultimately leading to more effective and inclusive policies.

By actively considering public sentiment, health organizations and the government can not only engage the public more effectively but also tailor their strategies and policies to better address the challenges presented by the influenza A epidemic.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (71764014).

Data Availability

The data sets generated and analyzed during this study are available from the corresponding author on reasonable request.

Authors' Contributions

JD and FL contributed equally to this work. JD acquired funding, provided a mock peer review, and supervised the investigation. FL analyzed the data and wrote the original draft. LY performed a mock peer review and helped write the Discussion section. YH provided a mock peer review and supervised the investigation.

Conflicts of Interest

None declared.

• Singh R, Singh R, Bhatia A. Sentiment analysis using machine learning techniques to predict outbreaks and epidemics. Int J Adv Sci Res 2018 Mar;3(2):19-24 [ https://www.researchgate.net/publication/332819639_Sentiment_analysis_using_machine_learning_techniques_to_predict_outbreaks_and_epidemics ]
• Guo JY, Bhat CR. Population synthesis for microsimulating travel behavior. Transport Res Record 2007 Jan 01;2014(1):92-101 [ CrossRef ]
• Soliman HA, Tabak F. Deep learning framework for RDF and knowledge graphs using fuzzy maps to support medical decision. J Int Res Med Pharm Sci 2019;14(3):92-97 [ https://www.researchgate.net/publication/338676727_DEEP_LEARNING_FRAMEWORK_FOR_RDF_AND_KNOWLEDGE_GRAPHS_USING_FUZZY_MAPS_TO_SUPPORT_MEDICAL_DECISION_Journal_of_International_Research_in_Medical_and_Pharmaceutical_Sciences ]
• Zelenski JM, Desrochers JE. Can positive and self-transcendent emotions promote pro-environmental behavior? Curr Opin Psychol 2021 Dec;42:31-35 [ CrossRef ] [ Medline ]
• Schneider CR, Weber EU. Reducing discrimination and fostering prosociality towards ex-prisoners in Nigeria and the United States. J Soc Issues 2020 Mar 03;76(1):172-199 [ CrossRef ]
• Yin H, Yang S, Li J. Detecting topic and sentiment dynamics due to COVID-19 pandemic using social media. In: Proceedings of the 16th International Conference, ADMA 2020. 2020 Presented at: 16th International Conference, ADMA 2020; November 12-14, 2020; Foshan, China [ CrossRef ]
• Harba JN, Tigu G, Davidescu AA. Exploring consumer emotions in pre-pandemic and pandemic times. A sentiment analysis of perceptions in the fine-dining restaurant industry in Bucharest, Romania. Int J Environ Res Public Health 2021 Dec 17;18(24):13300 [ https://www.mdpi.com/resolver?pii=ijerph182413300 ] [ CrossRef ] [ Medline ]
• Ng QX, Yau CE, Lim YL, Wong LK, Liew TM. Public sentiment on the global outbreak of monkeypox: an unsupervised machine learning analysis of 352,182 twitter posts. Public Health 2022 Dec;213:1-4 [ https://europepmc.org/abstract/MED/36308872 ] [ CrossRef ] [ Medline ]
• Kolyshkina I, van Rooyen M. Text mining for insurance claim cost prediction. In: Williams GJ, Simoff SJ, editors. Data Mining. Berlin, Germany: Springer; 2006.
• Li M. Research on extraction of useful tourism online reviews based on multimodal feature fusion. ACM Trans Asian Low Resour Lang Inf Process 2021 Sep 01;20(5):1-16 [ CrossRef ]
• Zhou J, Wu S, Wu X, Xia X. Cultural landscape perception of the Chinese traditional settlement: based on tourists' online comments. PLoS One 2023 Apr 13;18(4):e0283335 [ https://dx.plos.org/10.1371/journal.pone.0283335 ] [ CrossRef ] [ Medline ]
• Zhang C, Jiang J, Jin H, Chen T. The impact of COVID-19 on consumers' psychological behavior based on data mining for online user comments in the catering industry in China. Int J Environ Res Public Health 2021 Apr 15;18(8):4178 [ https://www.mdpi.com/resolver?pii=ijerph18084178 ] [ CrossRef ] [ Medline ]
• Liu Y, Gan WX, Zhang Q. Decision-making mechanism of online retailer based on additional online comments of consumers. J Retail Consum Serv 2021 Mar;59:102389 [ CrossRef ]
• Krishnamurthy S. The future of business education: a commentary in the shadow of the Covid-19 pandemic. J Bus Res 2020 Sep;117:1-5 [ https://europepmc.org/abstract/MED/32501309 ] [ CrossRef ] [ Medline ]
• Khalili H. Online interprofessional education during and post the COVID-19 pandemic: a commentary. J Interprof Care 2020;34(5):687-690 [ CrossRef ] [ Medline ]
• Lei Y, Pereira JA, Quach S, Bettinger JA, Kwong JC, Corace K, et al. Examining perceptions about mandatory influenza vaccination of healthcare workers through online comments on news stories. PLoS One 2015 Jun 18;10(6):e0129993 [ https://dx.plos.org/10.1371/journal.pone.0129993 ] [ CrossRef ] [ Medline ]
• Barteit S, Sié A, Yé M, Depoux A, Louis VR, Sauerborn R. Lessons learned on teaching a global audience with massive open online courses (MOOCs) on health impacts of climate change: a commentary. Global Health 2019 Aug 22;15(1):52 [ https://globalizationandhealth.biomedcentral.com/articles/10.1186/s12992-019-0494-6 ] [ CrossRef ] [ Medline ]
• Peng Z, Ma X, Yang D, Tsang KW, Guo Q. Effects of support-seekers’ community knowledge on their expressed satisfaction with the received comments in mental health communities. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 2021 Presented at: CHI '21: CHI Conference on Human Factors in Computing Systems; May 8-13, 2021; Yokohama, Japan [ CrossRef ]
• Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. J Mach Learn Res 2003;3:993-1022 [ CrossRef ]
• Vaswani V, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AL, et al. Attention is all you need. In: Proceedings of the 31st Annual Conference on Neural Information Processing Systems. 2017 Presented at: NIPS '17; December 4-7, 2017; Long Beach, CA URL: https:/​/proceedings.​neurips.cc/​paper_files/​paper/​2017/​file/​3f5ee243547dee91fbd053c1c4a845aa-Paper.​pdf
• Xu G, Meng Y, Qiu X, Yu Z, Wu X. Sentiment analysis of comment texts based on BiLSTM. IEEE Access 2019 Apr 9;7:51522-51532 [ CrossRef ]
• Hochreiter S, Schmidhuber J. Long short-term memory. Neural Comput 1997 Nov 15;9(8):1735-1780 [ https://dl.acm.org/doi/abs/10.5555/870541 ] [ CrossRef ] [ Medline ]
• Graves A, Schmidhuber J. Framewise phoneme classification with bidirectional LSTM and other neural network architectures. Neural Netw 2005;18(5-6):602-610 [ CrossRef ] [ Medline ]
• Vaidya V, Partha G, Karmakar M. Gender differences in utilization of preventive care services in the United States. J Womens Health (Larchmt) 2012 Feb;21(2):140-145 [ CrossRef ] [ Medline ]
• Feith HJ. [Female roles and conflicts in health care professions]. Orv Hetil 2009 Jun 07;150(23):1089-1095 [ CrossRef ] [ Medline ]
• Huang CE, Tai DW. Family-friendly policies and work-family balance: the gender perspective. In: Proceedings of the Fourth International Conference on Computer Sciences and Convergence Information Technology. 2009 Presented at: Fourth International Conference on Computer Sciences and Convergence Information Technology; November 24-26, 2009; Seoul, South Korea [ CrossRef ]
• Swinkels J, Tilburg TV, Verbakel E, Broese van Groenou M. Explaining the gender gap in the caregiving burden of partner caregivers. J Gerontol B Psychol Sci Soc Sci 2019 Jan 10;74(2):309-317 [ https://europepmc.org/abstract/MED/28379560 ] [ CrossRef ] [ Medline ]
• Brody LR. Gender differences in emotional development: a review of theories and research. J Personality 1985 Jun;53(2):102-149 [ CrossRef ]
• Rana IA, Bhatti SS, Aslam AB, Jamshed A, Ahmad J, Shah AA. COVID-19 risk perception and coping mechanisms: does gender make a difference? Int J Disaster Risk Reduct 2021 Mar;55:102096 [ https://europepmc.org/abstract/MED/33777688 ] [ CrossRef ] [ Medline ]
• Mutanga MB, Abayomi A. Tweeting on COVID-19 pandemic in South Africa: LDA-based topic modelling approach. Afr J Sci Technol Innov Dev 2020 Oct 08;14(1):163-172 [ CrossRef ]
• Zhu B, Zheng X, Liu H, Li J, Wang P. Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics. Chaos Solitons Fractals 2020 Nov;140:110123 [ https://europepmc.org/abstract/MED/32834635 ] [ CrossRef ] [ Medline ]
• Puri N, Coomes EA, Haghbayan H, Gunaratne K. Social media and vaccine hesitancy: new updates for the era of COVID-19 and globalized infectious diseases. Hum Vaccin Immunother 2020 Nov 01;16(11):2586-2593 [ https://europepmc.org/abstract/MED/32693678 ] [ CrossRef ] [ Medline ]
• Swayne DE. Impact of vaccines and vaccination on global control of avian influenza. Avian Dis 2012 Dec;56(4 Suppl):818-828 [ CrossRef ] [ Medline ]
• Watson OJ, Barnsley G, Toor J, Hogan AB, Winskill P, Ghani AC. Global impact of the first year of COVID-19 vaccination: a mathematical modelling study. Lancet Infect Dis 2022 Sep;22(9):1293-1302 [ https://linkinghub.elsevier.com/retrieve/pii/S1473-3099(22)00320-6 ] [ CrossRef ] [ Medline ]
• Wagner AL, Huang Z, Ren J, Laffoon M, Ji M, Pinckney LC, et al. Vaccine hesitancy and concerns about vaccine safety and effectiveness in Shanghai, China. Am J Prev Med 2021 Jan;60(1 Suppl 1):S77-S86 [ https://linkinghub.elsevier.com/retrieve/pii/S0749-3797(20)30402-5 ] [ CrossRef ] [ Medline ]
• Siciliani L, Wild C, McKee M, Kringos D, Barry MM, Barros PP, et al. Strengthening vaccination programmes and health systems in the European Union: a framework for action. Health Policy 2020 May;124(5):511-518 [ CrossRef ] [ Medline ]
• Ozawa S, Stack ML. Public trust and vaccine acceptance--international perspectives. Hum Vaccin Immunother 2013 Aug 27;9(8):1774-1778 [ https://europepmc.org/abstract/MED/23733039 ] [ CrossRef ] [ Medline ]
• Signorini A, Segre AM, Polgreen PM. The use of Twitter to track levels of disease activity and public concern in the U.S. during the influenza A H1N1 pandemic. PLoS One 2011 May 04;6(5):e19467 [ https://dx.plos.org/10.1371/journal.pone.0019467 ] [ CrossRef ] [ Medline ]
• Lyu M, Fan G, Xiao G, Wang T, Xu D, Gao J, et al. Traditional Chinese medicine in COVID-19. Acta Pharm Sin B 2021 Nov;11(11):3337-3363 [ https://linkinghub.elsevier.com/retrieve/pii/S2211-3835(21)00350-6 ] [ CrossRef ] [ Medline ]
• Luo H, Gao Y, Zou J, Zhang S, Chen H, Liu Q, et al. Reflections on treatment of COVID-19 with traditional Chinese medicine. Chin Med 2020 Sep 03;15(1):94 [ https://cmjournal.biomedcentral.com/articles/10.1186/s13020-020-00375-1 ] [ CrossRef ] [ Medline ]
• Xu J, Zhang Y. Traditional Chinese medicine treatment of COVID-19. Complement Ther Clin Pract 2020 May;39:101165 [ https://europepmc.org/abstract/MED/32379692 ] [ CrossRef ] [ Medline ]
• Ge H, Wang YF, Xu J, Gu Q, Liu HB, Xiao PG, et al. Anti-influenza agents from traditional Chinese medicine. Nat Prod Rep 2010 Jan;27(12):1758-1780 [ CrossRef ] [ Medline ]
• Xiong Y, Li NX, Duan N, Liu B, Zhu H, Zhang C, et al. Traditional Chinese medicine in treating influenza: from basic science to clinical applications. Front Pharmacol 2020 Sep 15;11:575803 [ https://europepmc.org/abstract/MED/33041821 ] [ CrossRef ] [ Medline ]
• Li J, Wang RQ, Guo WJ, Li JS. Efficacy and safety of traditional Chinese medicine for the treatment of influenza A (H1N1): a meta-analysis. J Chin Med Assoc 2016 May;79(5):281-291 [ https://linkinghub.elsevier.com/retrieve/pii/S1726-4901(16)00008-3 ] [ CrossRef ] [ Medline ]
• Chen H, Jie C, Tang LP, Meng H, Li XB, Li YB, et al. New insights into the effects and mechanism of a classic traditional Chinese medicinal formula on influenza prevention. Phytomedicine 2017 Apr 15;27:52-62 [ CrossRef ] [ Medline ]
• Cline RJ, Haynes KM. Consumer health information seeking on the internet: the state of the art. Health Educ Res 2001 Dec;16(6):671-692 [ CrossRef ] [ Medline ]
• Escoffery C, Miner KR, Adame DD, Butler S, McCormick L, Mendell E. Internet use for health information among college students. J Am Coll Health 2005;53(4):183-188 [ CrossRef ] [ Medline ]
• Bilgin N, Kesgin M, Gucuk S, Ak B. Assessment of internet usage for health-related information among clients utilizing primary health care services. Niger J Clin Pract 2019 Nov;22(11):1467-1474 [ http://www.njcponline.com/article.asp?issn=1119-3077;year=2019;volume=22;issue=11;spage=1467;epage=1474;aulast=Bilgin ] [ CrossRef ] [ Medline ]
• Wyse AE, Stickney EM, Butz D, Beckler A, Close CN. The potential impact of COVID‐19 on student learning and how schools can respond. Educ Measure 2020 Jul 23;39(3):60-64 [ CrossRef ]
• Rundle AG, Park Y, Herbstman JB, Kinsey EW, Wang YC. COVID-19-related school closings and risk of weight gain among children. Obesity (Silver Spring) 2020 Jun 18;28(6):1008-1009 [ https://europepmc.org/abstract/MED/32227671 ] [ CrossRef ] [ Medline ]
• Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, Iosifidis C, et al. The socio-economic implications of the coronavirus pandemic (COVID-19): a review. Int J Surg 2020 Jun;78:185-193 [ https://linkinghub.elsevier.com/retrieve/pii/S1743-9191(20)30316-2 ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by A Mavragani; submitted 24.05.23; peer-reviewed by R Gore, P Brzustewicz; comments to author 01.09.23; revised version received 20.09.23; accepted 11.10.23; published 02.11.23

©Jing Dai, Fang Lyu, Lin Yu, Yunyu He. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.11.2023.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.