is abstract and thesis statement the same

• How to Write an Abstract for a Dissertation or Thesis
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What is a Thesis or Dissertation Abstract?

The Cambridge English Dictionary defines an abstract in academic writing as being “ a few sentences that give the main ideas in an article or a scientific paper ” and the Collins English Dictionary says “ an abstract of an article, document, or speech is a short piece of writing that gives the main points of it ”.

Whether you’re writing up your Master’s dissertation or PhD thesis, the abstract will be a key element of this document that you’ll want to make sure you give proper attention to.

What is the Purpose of an Abstract?

The aim of a thesis abstract is to give the reader a broad overview of what your research project was about and what you found that was novel, before he or she decides to read the entire thesis. The reality here though is that very few people will read the entire thesis, and not because they’re necessarily disinterested but because practically it’s too large a document for most people to have the time to read. The exception to this is your PhD examiner, however know that even they may not read the entire length of the document.

Some people may still skip to and read specific sections throughout your thesis such as the methodology, but the fact is that the abstract will be all that most read and will therefore be the section they base their opinions about your research on. In short, make sure you write a good, well-structured abstract.

How Long Should an Abstract Be?

If you’re a PhD student, having written your 100,000-word thesis, the abstract will be the 300 word summary included at the start of the thesis that succinctly explains the motivation for your study (i.e. why this research was needed), the main work you did (i.e. the focus of each chapter), what you found (the results) and concluding with how your research study contributed to new knowledge within your field.

Woodrow Wilson, the 28th President of the United States of America, once famously said:

The point here is that it’s easier to talk open-endedly about a subject that you know a lot about than it is to condense the key points into a 10-minute speech; the same applies for an abstract. Three hundred words is not a lot of words which makes it even more difficult to condense three (or more) years of research into a coherent, interesting story.

What Makes a Good PhD Thesis Abstract?

Whilst the abstract is one of the first sections in your PhD thesis, practically it’s probably the last aspect that you’ll ending up writing before sending the document to print. The reason being that you can’t write a summary about what you did, what you found and what it means until you’ve done the work.

A good abstract is one that can clearly explain to the reader in 300 words:

• What your research field actually is,
• What the gap in knowledge was in your field,
• The overarching aim and objectives of your PhD in response to these gaps,
• What methods you employed to achieve these,
• You key results and findings,
• How your work has added to further knowledge in your field of study.

Another way to think of this structure is:

• Introduction,
• Aims and objectives,
• Discussion,
• Conclusion.

Following this ‘formulaic’ approach to writing the abstract should hopefully make it a little easier to write but you can already see here that there’s a lot of information to convey in a very limited number of words.

How Do You Write a Good PhD Thesis Abstract?

The biggest challenge you’ll have is getting all the 6 points mentioned above across in your abstract within the limit of 300 words . Your particular university may give some leeway in going a few words over this but it’s good practice to keep within this; the art of succinctly getting your information across is an important skill for a researcher to have and one that you’ll be called on to use regularly as you write papers for peer review.

Keep It Concise

Every word in the abstract is important so make sure you focus on only the key elements of your research and the main outcomes and significance of your project that you want the reader to know about. You may have come across incidental findings during your research which could be interesting to discuss but this should not happen in the abstract as you simply don’t have enough words. Furthermore, make sure everything you talk about in your thesis is actually described in the main thesis.

Make a Unique Point Each Sentence

Keep the sentences short and to the point. Each sentence should give the reader new, useful information about your research so there’s no need to write out your project title again. Give yourself one or two sentences to introduce your subject area and set the context for your project. Then another sentence or two to explain the gap in the knowledge; there’s no need or expectation for you to include references in the abstract.

Explain Your Research

Some people prefer to write their overarching aim whilst others set out their research questions as they correspond to the structure of their thesis chapters; the approach you use is up to you, as long as the reader can understand what your dissertation or thesis had set out to achieve. Knowing this will help the reader better understand if your results help to answer the research questions or if further work is needed.

Keep It Factual

Keep the content of the abstract factual; that is to say that you should avoid bringing too much or any opinion into it, which inevitably can make the writing seem vague in the points you’re trying to get across and even lacking in structure.

Write, Edit and Then Rewrite

Spend suitable time editing your text, and if necessary, completely re-writing it. Show the abstract to others and ask them to explain what they understand about your research – are they able to explain back to you each of the 6 structure points, including why your project was needed, the research questions and results, and the impact it had on your research field? It’s important that you’re able to convey what new knowledge you contributed to your field but be mindful when writing your abstract that you don’t inadvertently overstate the conclusions, impact and significance of your work.

Thesis and Dissertation Abstract Examples

Perhaps the best way to understand how to write a thesis abstract is to look at examples of what makes a good and bad abstract.

Example of A Bad Abstract

Let’s start with an example of a bad thesis abstract:

In this project on “The Analysis of the Structural Integrity of 3D Printed Polymers for use in Aircraft”, my research looked at how 3D printing of materials can help the aviation industry in the manufacture of planes. Plane parts can be made at a lower cost using 3D printing and made lighter than traditional components. This project investigated the structural integrity of EBM manufactured components, which could revolutionise the aviation industry.

What Makes This a Bad Abstract

Hopefully you’ll have spotted some of the reasons this would be considered a poor abstract, not least because the author used up valuable words by repeating the lengthy title of the project in the abstract.

Working through our checklist of the 6 key points you want to convey to the reader:

• There has been an attempt to introduce the research area , albeit half-way through the abstract but it’s not clear if this is a materials science project about 3D printing or is it about aircraft design.
• There’s no explanation about where the gap in the knowledge is that this project attempted to address.
• We can see that this project was focussed on the topic of structural integrity of materials in aircraft but the actual research aims or objectives haven’t been defined.
• There’s no mention at all of what the author actually did to investigate structural integrity. For example was this an experimental study involving real aircraft, or something in the lab, computer simulations etc.
• The author also doesn’t tell us a single result of his research, let alone the key findings !
• There’s a bold claim in the last sentence of the abstract that this project could revolutionise the aviation industry, and this may well be the case, but based on the abstract alone there is no evidence to support this as it’s not even clear what the author did .

This is an extreme example but is a good way to illustrate just how unhelpful a poorly written abstract can be. At only 71 words long, it definitely hasn’t maximised the amount of information that could be presented and the what they have presented has lacked clarity and structure.

A final point to note is the use of the EBM acronym, which stands for Electron Beam Melting in the context of 3D printing; this is a niche acronym for the author to assume that the reader would know the meaning of. It’s best to avoid acronyms in your abstract all together even if it’s something that you might expect most people to know about, unless you specifically define the meaning first.

Example of A Good Abstract

Having seen an example of a bad thesis abstract, now lets look at an example of a good PhD thesis abstract written about the same (fictional) project:

Additive manufacturing (AM) of titanium alloys has the potential to enable cheaper and lighter components to be produced with customised designs for use in aircraft engines. Whilst the proof-of-concept of these have been promising, the structural integrity of AM engine parts in response to full thrust and temperature variations is not clear.

The primary aim of this project was to determine the fracture modes and mechanisms of AM components designed for use in Boeing 747 engines. To achieve this an explicit finite element (FE) model was developed to simulate the environment and parameters that the engine is exposed to during flight. The FE model was validated using experimental data replicating the environmental parameters in a laboratory setting using ten AM engine components provided by the industry sponsor. The validated FE model was then used to investigate the extent of crack initiation and propagation as the environment parameters were adjusted.

This project was the first to investigate fracture patterns in AM titanium components used in aircraft engines; the key finding was that the presence of cavities within the structures due to errors in the printing process, significantly increased the risk of fracture. Secondly, the simulations showed that cracks formed within AM parts were more likely to worsen and lead to component failure at subzero temperatures when compared to conventionally manufactured parts. This has demonstrated an important safety concern which needs to be addressed before AM parts can be used in commercial aircraft.

What Makes This a Good Abstract

Having read this ‘good abstract’ you should have a much better understand about what the subject area is about, where the gap in the knowledge was, the aim of the project, the methods that were used, key results and finally the significance of these results. To break these points down further, from this good abstract we now know that:

• The research area is around additive manufacturing (i.e. 3D printing) of materials for use in aircraft.
• The gap in knowledge was how these materials will behave structural when used in aircraft engines.
• The aim was specifically to investigate how the components can fracture.
• The methods used to investigate this were a combination of computational and lab based experimental modelling.
• The key findings were the increased risk of fracture of these components due to the way they are manufactured.
• The significance of these findings were that it showed a potential risk of component failure that could comprise the safety of passengers and crew on the aircraft.

The abstract text has a much clearer flow through these different points in how it’s written and has made much better use of the available word count. Acronyms have even been used twice in this good abstract but they were clearly defined the first time they were introduced in the text so that there was no confusion about their meaning.

The abstract you write for your dissertation or thesis should succinctly explain to the reader why the work of your research was needed, what you did, what you found and what it means. Most people that come across your thesis, including any future employers, are likely to read only your abstract. Even just for this reason alone, it’s so important that you write the best abstract you can; this will not only convey your research effectively but also put you in the best light possible as a researcher.

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An abstract is a summary of a longer written document. It is written with the same organization as the original document, usually without “review” or comment. Abstract lengths vary by discipline and purpose of the project; generally, they are 50-100 words for a short paper and 150-200 for a longer one. Abstracts are typically placed prior to the manuscript. Abstracts fall into two categories: indicative and informative.

The  indicative  abstract covers a less structured document (like a book, essay or editorial). It helps readers to understand the focus, arguments and conclusions of the larger document so that they can determine whether to read it more thoroughly.

An  informative  abstract is used for more strictly structured documents (like scientific experiments or investigations) and includes the elements of the original research report: its objective, methods, results, and conclusions.

Whichever type of abstract you write, it should be able to stand alone as a statement separate from the larger document.

Components of an Abstract

Abstracts, at heart, are decision-making documents. Based on the abstract, readers decide whether to read your article, support your proposal, grant your funding, or accept you to a conference. To write a successful abstract, you need to include these three components:  Context ,  Problem , and  Response  (CPR).

By definition, context is essentially what surrounds a thing. In other words, in order to understand a snippet of conversation, we often ask, “He said that in what context?” When we provide context for our readers, we are establishing a comfortable common ground, a shared understanding that provides an entry point into the larger or more specific ideas of our project. Common ground might take the form of a shared belief, a kind of truism, or a basic principle of the field. Frequently this takes the form of a brief survey of the field or an overview of a current situation. This might include what those in the discipline already know to be true, a point of conventional wisdom, something we’ve all seen and heard, a primary text, a case study, or an anecdote of some kind. 

The problem is essentially establishing a deficit. A deficit in this sense refers to a gap in knowledge or what might be misunderstood or overlooked. The problem is what our research question or project is trying to solve. This might be, for example, a practical question (how can we best distribute H1N1 vaccine?) or it can be a theoretical or conceptual question (to what degree is marital behavior determined by intergenerational influences?). As researchers, we begin with the problem, but often by the time we are ready to write our abstracts, introductions, or proposals, the problem has moved into the background, obscured by the details of our work. However, in terms of meeting the reader’s needs, the problem is an essential and necessary feature. The reader’s level of investment, and thus the grade, the acceptance, the funding for your project hinges upon how successfully you articulate the problem. 

This is generally your summary or description of your paper or project, which you position in dialogue with the problem as you’ve established it. Depending on the nature of your project, in your response you might explicitly state your main point or thesis, or you might present your hypothesis and generalize your results. In addition, research that relies on primary data often includes an abbreviated description of the methodology used. 

The ABCs of a Good Abstract

• Accuracy:  Include only information included in the original document.
• Brevity:  Get straight to the point, use precise language, and do not include superfluous adjectives.
• Clarity:  Do not use unnecessary technical jargon, colloquialisms or obscure vocabulary and detail and always explain any acronyms.

Abstracts are challenging because they require decisions about what constitutes that essence of a document full of important information. Here are some tips to help you:

• Write the final version of your abstract after your paper is completed so the organization and development of the two documents match.
• Begin with a topic sentence: what is this paper about?
• Use an outline to confirm that you are summarizing the most important information.
• Incorporate keywords for electronic retrieval into the text. (They may also be listed at the end of the abstract text.) Bibliographic references and graphics are typically excluded from an abstract.

Keep your readers in mind as you develop the abstract:

• Assume that they are generally familiar with the information being abstracted but are interested in evaluating the usefulness of the entire document for their research.
• Write in a concise and readable style so that they can read through the abstract quickly to ascertain the essence of the larger document.
• Provide information in each sentence; for example, if it is important enough to include, “a cost was given,” it is appropriate to give the specifics: “The cost was $5.25 per gallon.”

Sample Abstracts

Variation Among Isolates of Fusarium Circinatum in Tolerance of the Anti-fungal Metabolite   BOA

Amir Begovic

Fusarium circinatum is a fungal pathogen responsible for a disease affecting pines known as pitch canker. Although this is what F. circinatum is notorious for, recent work has shown that this fungus also can colonize grasses. However, the importance of grasses as a resource in the life history of F. circinatum is unknown. To learn more about how well adapted F. circinatum is to exploitation of grass hosts, the present study was undertaken to determine how well this fungus can tolerate anti-fungal compounds produced by corn, a member of the grass family. To this end, plates of PDA (potato dextrose agar) were amended with various concentrations of BOA (2-benzoxazolinone), and inoculated with a colonized agar plug of F. circinatum. All tested strains failed to grow at concentrations of 0.75 and 1.0 mg of BOA per ml of medium. Colonized plugs transferred from plates containing BOA to PDA without BOA did not grow, indicating the fungus was killed by exposure to this anti-fungal compound. The same strains were able to survive exposure to 0.5 mg of BOA per ml, although growth was strongly inhibited. The next step will be to test for heritable variation in tolerance of BOA in F. circinatum. (197 words)

Source: University of California, Davis 2013 Undergraduate Research Symposium  

Connecting the U.S. Media: A Network Analysis of Mutual Fund Ownership in Communication Corporations

Grace A. Benefield

Social scientists have long been interested in the ever increasing concentration and effects of computer, telecommunication and media corporations, such as Google, Apple and Verizon. By gathering statistics on mutual fund and individual stock owners, the study compares the proportion of institutional investment across communication corporations, which are service or technology corporations responsible for the exchange of information. The research incorporates network analysis software to identify outliers and central players in this web of media owners. The study seeks to measure centrality as a connection between two companies and their investors' similar interest investments, such as a similarity in size, expectations for growth, company values, or industrial interests. Surprisingly, the study finds that market capitalization did not result in centrality, such as IBM's peripheral status. The results find that smaller telecommunications companies, such as Sprint and Comcast, share a large portion of the same mutual funds. In contrast, other industries appear to have intermixed and varietal institutional owners. There are also indications of mutual fund interest groupings based on geography, as in west coast companies Disney, HP, and Qualcomm. Further research is needed to compare the individual stock owners who control large interests in various companies. (196 words)

Source: University of California, Davis 2013 Undergraduate Research Symposium

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An abstract summarizes, usually in one paragraph of 300 words or less, the major aspects of the entire paper in a prescribed sequence that includes: 1) the overall purpose of the study and the research problem(s) you investigated; 2) the basic design of the study; 3) major findings or trends found as a result of your analysis; and, 4) a brief summary of your interpretations and conclusions.

Writing an Abstract. The Writing Center. Clarion University, 2009; Writing an Abstract for Your Research Paper. The Writing Center, University of Wisconsin, Madison; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-first Century . Oxford, UK: Chandos Publishing, 2010;

Importance of a Good Abstract

Sometimes your professor will ask you to include an abstract, or general summary of your work, with your research paper. The abstract allows you to elaborate upon each major aspect of the paper and helps readers decide whether they want to read the rest of the paper. Therefore, enough key information [e.g., summary results, observations, trends, etc.] must be included to make the abstract useful to someone who may want to examine your work.

How do you know when you have enough information in your abstract? A simple rule-of-thumb is to imagine that you are another researcher doing a similar study. Then ask yourself: if your abstract was the only part of the paper you could access, would you be happy with the amount of information presented there? Does it tell the whole story about your study? If the answer is "no" then the abstract likely needs to be revised.

Farkas, David K. “A Scheme for Understanding and Writing Summaries.” Technical Communication 67 (August 2020): 45-60;  How to Write a Research Abstract. Office of Undergraduate Research. University of Kentucky; Staiger, David L. “What Today’s Students Need to Know about Writing Abstracts.” International Journal of Business Communication January 3 (1966): 29-33; Swales, John M. and Christine B. Feak. Abstracts and the Writing of Abstracts . Ann Arbor, MI: University of Michigan Press, 2009.

Structure and Writing Style

I.  Types of Abstracts

To begin, you need to determine which type of abstract you should include with your paper. There are four general types.

Critical Abstract A critical abstract provides, in addition to describing main findings and information, a judgment or comment about the study’s validity, reliability, or completeness. The researcher evaluates the paper and often compares it with other works on the same subject. Critical abstracts are generally 400-500 words in length due to the additional interpretive commentary. These types of abstracts are used infrequently.

Descriptive Abstract A descriptive abstract indicates the type of information found in the work. It makes no judgments about the work, nor does it provide results or conclusions of the research. It does incorporate key words found in the text and may include the purpose, methods, and scope of the research. Essentially, the descriptive abstract only describes the work being summarized. Some researchers consider it an outline of the work, rather than a summary. Descriptive abstracts are usually very short, 100 words or less. Informative Abstract The majority of abstracts are informative. While they still do not critique or evaluate a work, they do more than describe it. A good informative abstract acts as a surrogate for the work itself. That is, the researcher presents and explains all the main arguments and the important results and evidence in the paper. An informative abstract includes the information that can be found in a descriptive abstract [purpose, methods, scope] but it also includes the results and conclusions of the research and the recommendations of the author. The length varies according to discipline, but an informative abstract is usually no more than 300 words in length.

Highlight Abstract A highlight abstract is specifically written to attract the reader’s attention to the study. No pretense is made of there being either a balanced or complete picture of the paper and, in fact, incomplete and leading remarks may be used to spark the reader’s interest. In that a highlight abstract cannot stand independent of its associated article, it is not a true abstract and, therefore, rarely used in academic writing.

II.  Writing Style

Use the active voice when possible , but note that much of your abstract may require passive sentence constructions. Regardless, write your abstract using concise, but complete, sentences. Get to the point quickly and always use the past tense because you are reporting on a study that has been completed.

Abstracts should be formatted as a single paragraph in a block format and with no paragraph indentations. In most cases, the abstract page immediately follows the title page. Do not number the page. Rules set forth in writing manual vary but, in general, you should center the word "Abstract" at the top of the page with double spacing between the heading and the abstract. The final sentences of an abstract concisely summarize your study’s conclusions, implications, or applications to practice and, if appropriate, can be followed by a statement about the need for additional research revealed from the findings.

Composing Your Abstract

Although it is the first section of your paper, the abstract should be written last since it will summarize the contents of your entire paper. A good strategy to begin composing your abstract is to take whole sentences or key phrases from each section of the paper and put them in a sequence that summarizes the contents. Then revise or add connecting phrases or words to make the narrative flow clearly and smoothly. Note that statistical findings should be reported parenthetically [i.e., written in parentheses].

Before handing in your final paper, check to make sure that the information in the abstract completely agrees with what you have written in the paper. Think of the abstract as a sequential set of complete sentences describing the most crucial information using the fewest necessary words. The abstract SHOULD NOT contain:

• A catchy introductory phrase, provocative quote, or other device to grab the reader's attention,
• Lengthy background or contextual information,
• Redundant phrases, unnecessary adverbs and adjectives, and repetitive information;
• Acronyms or abbreviations,
• References to other literature [say something like, "current research shows that..." or "studies have indicated..."],
• Using ellipticals [i.e., ending with "..."] or incomplete sentences,
• Jargon or terms that may be confusing to the reader,
• Citations to other works, and
• Any sort of image, illustration, figure, or table, or references to them.

Abstract. Writing Center. University of Kansas; Abstract. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Abstracts. The Writing Center. University of North Carolina; Borko, Harold and Seymour Chatman. "Criteria for Acceptable Abstracts: A Survey of Abstracters' Instructions." American Documentation 14 (April 1963): 149-160; Abstracts. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Hartley, James and Lucy Betts. "Common Weaknesses in Traditional Abstracts in the Social Sciences." Journal of the American Society for Information Science and Technology 60 (October 2009): 2010-2018; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-first Century. Oxford, UK: Chandos Publishing, 2010; Procter, Margaret. The Abstract. University College Writing Centre. University of Toronto; Riordan, Laura. “Mastering the Art of Abstracts.” The Journal of the American Osteopathic Association 115 (January 2015 ): 41-47; Writing Report Abstracts. The Writing Lab and The OWL. Purdue University; Writing Abstracts. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-First Century . Oxford, UK: 2010; Writing an Abstract for Your Research Paper. The Writing Center, University of Wisconsin, Madison.

Writing Tip

Never Cite Just the Abstract!

Citing to just a journal article's abstract does not confirm for the reader that you have conducted a thorough or reliable review of the literature. If the full-text is not available, go to the USC Libraries main page and enter the title of the article [NOT the title of the journal]. If the Libraries have a subscription to the journal, the article should appear with a link to the full-text or to the journal publisher page where you can get the article. If the article does not appear, try searching Google Scholar using the link on the USC Libraries main page. If you still can't find the article after doing this, contact a librarian or you can request it from our free i nterlibrary loan and document delivery service .

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Thesis and Purpose Statements

Use the guidelines below to learn the differences between thesis and purpose statements.

In the first stages of writing, thesis or purpose statements are usually rough or ill-formed and are useful primarily as planning tools.

A thesis statement or purpose statement will emerge as you think and write about a topic. The statement can be restricted or clarified and eventually worked into an introduction.

As you revise your paper, try to phrase your thesis or purpose statement in a precise way so that it matches the content and organization of your paper.

Thesis statements

A thesis statement is a sentence that makes an assertion about a topic and predicts how the topic will be developed. It does not simply announce a topic: it says something about the topic.

Good: X has made a significant impact on the teenage population due to its . . . Bad: In this paper, I will discuss X.

A thesis statement makes a promise to the reader about the scope, purpose, and direction of the paper. It summarizes the conclusions that the writer has reached about the topic.

A thesis statement is generally located near the end of the introduction. Sometimes in a long paper, the thesis will be expressed in several sentences or an entire paragraph.

A thesis statement is focused and specific enough to be proven within the boundaries of the paper. Key words (nouns and verbs) should be specific, accurate, and indicative of the range of research, thrust of the argument or analysis, and the organization of supporting information.

Purpose statements

A purpose statement announces the purpose, scope, and direction of the paper. It tells the reader what to expect in a paper and what the specific focus will be.

Common beginnings include:

“This paper examines . . .,” “The aim of this paper is to . . .,” and “The purpose of this essay is to . . .”

A purpose statement makes a promise to the reader about the development of the argument but does not preview the particular conclusions that the writer has drawn.

A purpose statement usually appears toward the end of the introduction. The purpose statement may be expressed in several sentences or even an entire paragraph.

A purpose statement is specific enough to satisfy the requirements of the assignment. Purpose statements are common in research papers in some academic disciplines, while in other disciplines they are considered too blunt or direct. If you are unsure about using a purpose statement, ask your instructor.

This paper will examine the ecological destruction of the Sahel preceding the drought and the causes of this disintegration of the land. The focus will be on the economic, political, and social relationships which brought about the environmental problems in the Sahel.

Sample purpose and thesis statements

The following example combines a purpose statement and a thesis statement (bold).

The goal of this paper is to examine the effects of Chile’s agrarian reform on the lives of rural peasants. The nature of the topic dictates the use of both a chronological and a comparative analysis of peasant lives at various points during the reform period. . . The Chilean reform example provides evidence that land distribution is an essential component of both the improvement of peasant conditions and the development of a democratic society. More extensive and enduring reforms would likely have allowed Chile the opportunity to further expand these horizons.

For more tips about writing thesis statements, take a look at our new handout on Developing a Thesis Statement.

Writing Process and Structure

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Getting Started with Your Paper

Interpreting Writing Assignments from Your Courses

Generating Ideas for Your Paper

Creating an Argument

Thesis vs. Purpose Statements

Developing a Thesis Statement

Architecture of Arguments

Working with Sources

Quoting and Paraphrasing Sources

Using Literary Quotations

Citing Sources in Your Paper

Drafting Your Paper

Introductions

Paragraphing

Developing Strategic Transitions

Conclusions

Revising Your Paper

Peer Reviews

Reverse Outlines

Revising an Argumentative Paper

Revision Strategies for Longer Projects

Finishing Your Paper

Twelve Common Errors: An Editing Checklist

How to Proofread your Paper

Writing Collaboratively

Collaborative and Group Writing

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How To Write An Abstract

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Inhaltsverzeichnis

• 1 Definition: Abstract
• 4 Abstract in Different Languages
• 5 Abstract vs. Conclusion
• 6 In a Nutshell

Definition: Abstract

An abstract is a short summary of a research paper. It is not part of the actual text and must be included at the very beginning of your work. It does not show up in the structure and the table of contents of your thesis.

You write an abstract to give a brief account of the most important information relating to the research background, structure, method, data analysis, and results of your research paper. The abstract should not create suspense: Making it very clear early on what your results are will help the reader evaluate the relevance of your paper.

What is an abstract?

An abstract is a short summary written at the beginning of a research paper . It highlights the main ideas of your academic project. Your research methods, data analysis, results plus any background information relating to your research should be included in the abstract.

Why do I need an abstract?

An abstract is nescessary, as it helps the reader to decide whether the results and methods of a particular paper are relevant to them or whether it is worthwhile for them to read the whole paper. It effectively creates the first impression of the thesis or essay. It is also very useful for fellow researchers in the academic community, as they can decide upon first glance whether or not the paper can be useful or relevant to their personal research project.

Where does the abstract belong?

The abstract is to be put at the beginning of your writing project. It should appear between the title page and the table of contents page of the research paper. If you’re writing a thesis with an acknowledgements page, then the abstract is placed after the acknowledgements.

When do I write the abstract?

The abstract should be the very last thing you write during the academic writing process. This is because it is only possible to come up with a precise summary of your work once you have written the whole research paper . Using this same logic, the conclusion should also be one of the very last paragraphs that you write.

How long should an abstract be?

The abstract should be between one third of a page and one full page in length. However, this depends on the length of the paper that you’re writing. For a smaller research paper, 100 words is sufficient. For a bachelor’s thesis, or a master’s thesis, the abstract should be between 1 or 2 pages. But it should definitely not exceed 2 pages!

Tip: Take a look at some abstract examples for inspiration!

What is included in an abstract?

A top-quality abstract will include a brief explanation of the following aspects:

1. Background and purpose 2. Overarching research question 3. Gap in literature and methods used to address the gap in literature 4. Main results of the writing project 5. Interpretation or conclusion of the thesis statement Each of these points should be addressed in only a few sentences.

Is an abstract international?

It doesn’t matter which language you write your abstract in, an English translation of your abstract is often required. The reason for this is so that the results of your research paper can be reviewed by an international audience.

Also useful: What is plagiarism?

How to Write an Abstract: The Content

There is one thing you must understand about how to write an abstract:

The abstract should contain important aspects of the paper, like the

• research question ,
• limitations,
• study design,
• main results,
• main idea or message,
• key interpretations,
• implications,
• and validity (cf. Schnur 2005, as quoted in Theisen 2013: 101).

How to Write an Abstract: Structure

The abstract follows the same structure as your paper:

(cf. Kruse 2007: 186)

How to Write an Abstract: Goal

“An abstract is a very precise summary of your whole paper”

You might have heard the term ‘summary’ referring to an abstract of a research paper (cf. Oertner, St. John, & Thelen 2014: 93). However, do not make the mistake of assuming that an abstract is something rather general. You would be on the wrong track. When asked to write an abstract for your bachelor’s or master’s thesis, you are expected to deliver a very precise summary of your whole paper.

An abstract’s right to exist is founded in its purpose of helping a potential reader to quickly find out if it is worthwhile to read the whole paper (cf. Rossig & Prätsch 2005: 89). For this reason, an abstract has to offer everything the reader needs in order to evaluate the relevance of a research paper for their own work. It is the ultimate way of advertising your research.

You can save yourself a lot of work and trouble if you concentrate on reading the abstracts of published papers first; most papers these days provide abstracts (cf. Oertner, St. John, & Thelen 2014: 80). If you take your time to thoroughly read the abstracts, you will be able to judge whether a particular article will help you to support your line of argumentation. If not, then just move on the next article. You can check out the sample abstracts in this blog entry to get a better idea of how to write an abstract and what an abstract looks like.

“Through reading an abstract, you can find out if a paper arouses your interest or is relevant for your studies.”

How to Write an Abstract: Length 

An abstract is a summary of a publication or an article on one third of a DIN-A4 page (cf. Kruse 2007: 185). Stickel-Wolf & Wolf provide a rough guideline for the word count: They say that an abstract should not contain more than 100 words (cf. 2013: 249).

Note: Generally speaking, an abstract for a bachelor’s or master’s thesis should not exceed one page, and the absolute maximum is two pages (cf. Rossig & Prätsch 2005: 89). The reason for this is self-explanatory: The purpose of the abstract is to offer a quick overview of, for example, a 60- or 80-page paper.

Abstract Example 1: English abstract addressing the main points of your paper

Abstract Example 2: English abstract of a master’s thesis with keywords

Recommended: Harvard Referencing

When to Write the Abstract and Where to Put It

You are probably wondering where the abstract should be placed in your research paper: at the beginning or towards the end? It is common to include the abstract right at the beginning (cf. Rossig & Prätsch 2005: 89; Samac, Prenner, & Schwetz 2009: 56). As we have established, it is a helpful tool for the reader to get an overview of the whole paper as early as possible. It is good to know what will follow. So, it would not be logical to put it at the end, right? Stickel-Wolf and Wolf recommend embedding the abstract in between the title page and the table of contents (cf. 2013: 249).

The next question about ‘How to write an abstract’ is a bit trickier. When is the right time to write the abstract? Given that it is to be added at the very beginning, before the actual text, you might think it is the first thing you are supposed to write. However, you will not be able to write a clear-cut and precise summary at a stage when you do not even know what you are summarizing. Therefore, you can only write the abstract after you have written the whole paper. How else would you know enough about your results to give a complete record of your whole work (cf. Rossig & Prätsch 2005: 89)?

Note: You can draw essential information to write your abstract from your conclusion, as this part briefly repeats the research questions and provides an evaluative summary of the results (cf. Stickel-Wolf 2013: 249).

Abstract in Different Languages

The question of how to write an abstract is popular not just in an English-speaking context.

It increasingly concerns international students as well. Nowadays, it is becoming more and more important to write the whole paper in English, rather than in the native language of the country a student studies in. Indeed, many papers are still written in the native language of the country.

But your research paper not being written in English does not mean that this also holds true for the abstract. Often, the student needs to write an abstract in not only German, Spanish, or French (depending on the country you study in) but also English.

An English abstract (in addition to, say, a German abstract) is necessary to ensure that a research paper will be accessible to an international market.

Sometimes, only an English abstract is required. Also, as Samac, Prenner, and Schwetz point out, an English translation of the German text (if your thesis is in German) must be provided on the very same page to meet international standards (2009: 56).

Example of an abstract in German and English

Note: Academic English is quite a bit different from academic German, Spanish, and other languages. We recommend that you read research papers in English to get a feel for the differences in style and structure (cf. Karmasin & Ribing 2014: 45).

Abstract vs. Conclusion

Caution: The abstract is NEVER a conclusion of your research paper and it differs from the conclusion in many aspects. Make sure to read the sample abstracts provided on this page to get a good grasp on the major differences between the abstract and the conclusion.

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You are already done writing your assignment and need a high quality printing & binding service? Then you are right to choose BachelorPrint! Check out our 24-hour online printing service. For more information click the button below :

In a Nutshell

• An abstract is a short summary of a research paper. It is embedded between the title page and the table of contents , and appears before the actual text.
• The abstract should not exceed one page (at the most, two pages). Ideally, it should fit on a single page.
• An abstract is a brief account of your paper. It provides information about the structure, argumentation, method, and results of your research paper (cf. Oertner, St. John, & Thelen 2014: 93).
• The aim of writing an abstract is to make it possible for the reader to quickly evaluate the relevance of your work without having to read much. Also, reading abstracts makes your life easier when you are doing research. You can decide which paper is worth reading and which one is not, just based on the abstract.
• There is a clear difference between the abstract and the conclusion. The abstract is shorter, can be read independently of the text, and does not contain evaluations of the author which are not already part of the text (cf. Kruse 2007: 186).
• Writing an English abstract or providing an English translation of your abstract is becoming increasingly important and popular. In this way, your research can be made internationally accessible.

Works cited

Karmasin, Matthias, & Rainer Ribing. 2014. Die Gestaltung wissenschaftlicher Arbeiten . 8th Edition. Vienna: Facultas.

Kruse, Otto. 2007. Keine Angst vor dem leeren Blatt – Ohne Schreibblockaden durchs Studium . 12th Edition. Frankfurt: Campus.

Oertner, Monika, Illona St. John, & Gabriele Thelen. 2014. Wissenschaftlich Schreiben – Ein Praxisbuch für Schreibtrainer und Studierende. Paderborn: Wilhelm Fink.

Rossig, Wolfram E., & Joachim Prätsch. 2005. Wissenschaftliche Arbeiten . 5th Edition. Weyhe: PRINT-TEC.

Samac, Klaus, Monika Prenner, & Herbert Schwetz. 2009. Die Bachelorarbeit an Universität und Fachhochschule. Vienna: Facultas.

Stickel-Wolf, Christine, & Joachim Wolf. 2013. Wissenschaftliches Arbeiten und Lerntechniken – Erfolgreich studieren – gewusst wie! 7th Edition. Wiesbaden: Springer Gabler.

Theisen, Manuel René. 2013. Wissenschaftliches Arbeiten – Erfolgreich bei Bachelor- und Masterarbeit . Munich: Franz Vahlen.

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How do I Write a Literature Review?: #5 Writing the Review

• Step #1: Choosing a Topic
• Step #2: Finding Information
• Step #3: Evaluating Content
• Step #4: Synthesizing Content
• #5 Writing the Review
• Citing Your Sources

WRITING THE REVIEW 

You've done the research and now you're ready to put your findings down on paper. When preparing to write your review, first consider how will you organize your review.

The actual review generally has 5 components:

Abstract  -  An abstract is a summary of your literature review. It is made up of the following parts:

• A contextual sentence about your motivation behind your research topic
• Your thesis statement
• A descriptive statement about the types of literature used in the review
• Summarize your findings
• Conclusion(s) based upon your findings

Introduction :   Like a typical research paper introduction, provide the reader with a quick idea of the topic of the literature review:

• Define or identify the general topic, issue, or area of concern. This provides the reader with context for reviewing the literature.
• Identify related trends in what has already been published about the topic; or conflicts in theory, methodology, evidence, and conclusions; or gaps in research and scholarship; or a single problem or new perspective of immediate interest.
• Establish your reason (point of view) for reviewing the literature; explain the criteria to be used in analyzing and comparing literature and the organization of the review (sequence); and, when necessary, state why certain literature is or is not included (scope)  - 

Body :  The body of a literature review contains your discussion of sources and can be organized in 3 ways-

• Chronological -  by publication or by trend
• Thematic -  organized around a topic or issue, rather than the progression of time
• Methodical -  the focusing factor usually does not have to do with the content of the material. Instead, it focuses on the "methods" of the literature's researcher or writer that you are reviewing

You may also want to include a section on "questions for further research" and discuss what questions the review has sparked about the topic/field or offer suggestions for future studies/examinations that build on your current findings.

Conclusion :  In the conclusion, you should:

Conclude your paper by providing your reader with some perspective on the relationship between your literature review's specific topic and how it's related to it's parent discipline, scientific endeavor, or profession.

Bibliography :   Since a literature review is composed of pieces of research, it is very important that your correctly cite the literature you are reviewing, both in the reviews body as well as in a bibliography/works cited. To learn more about different citation styles, visit the " Citing Your Sources " tab.

• Writing a Literature Review: Wesleyan University
• Literature Review: Edith Cowan University
• << Previous: Step #4: Synthesizing Content
• Next: Citing Your Sources >>
• Last Updated: Aug 22, 2023 1:35 PM
• URL: https://libguides.eastern.edu/literature_reviews

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Published by Nicolas at March 19th, 2024 , Revised On March 27, 2024

Intro Vs Abstract – Are They The Same?

Scholarly writing serves as a cornerstone for the dissemination of knowledge and the exploration of new ideas. Two crucial elements that play a pivotal role in framing the structure of academic papers are the introduction and abstract. While often used interchangeably, these components serve distinct purposes, each contributing to a scholarly work’s overall coherence and effectiveness.

Table of Contents

Understanding The Introduction

The introduction serves as the gateway to a scholarly work, setting the stage for what lies ahead. It is not merely a perfunctory beginning but a strategic piece that aims to engage readers, provide context, and establish the groundwork for the research to follow. The primary functions of an introduction can be delineated into several key aspects.

Contextualization

The introduction contextualizes the research by presenting the broader field of study. It provides a backdrop against which the specific research question or problem statement can be understood.

This involves reviewing relevant literature, highlighting gaps in existing knowledge, and justifying the need for the current study.

Statement Of The Problem Or Research Question

One of the critical elements of an introduction is the formulation of a clear and concise research question or problem statement. This sets the trajectory for the entire paper, guiding readers on what to expect and why the study is significant.

Objectives And Scope

The introduction outlines the objectives of the research and delineates the scope of the study. This helps readers understand the boundaries within which the research is conducted and what specific aspects will be addressed.

Hypotheses Or Research Hypothesis

In scientific research, the introduction may present hypotheses that the study aims to test. These hypotheses are formulated based on existing knowledge and are critical for guiding the research methodology and analysis.

Thesis Statement

In some academic disciplines, particularly in humanities and social sciences, the introduction may encapsulate the thesis statement —a concise summary of the main argument or position taken in the paper.

Understanding The Abstract

While the introduction sets the stage, the abstract serves as a concise summary that encapsulates the entire research paper. Positioned at the beginning of the paper, the abstract acts as a standalone piece, providing readers with a snapshot of the research without requiring them to delve into the full text. The abstract has its own distinct set of functions and characteristics.

Summary Of Key Elements

The abstract encapsulates the essential elements of the research, including the research question, methodology, key findings, and conclusions. It serves as a condensed version of the entire paper, offering readers a quick overview.

Conciseness And Clarity

Unlike the introduction, the abstract is highly condensed and should be succinct. It demands clarity and precision in conveying the main points of the research without unnecessary details.

A well-crafted abstract can stand alone, providing readers with a clear understanding of the study even if they choose not to read the full paper.

Keywords And Indexing

Abstracts often include keywords that are relevant to the research. These keywords are essential for indexing and categorizing the paper in databases, making it easier for researchers to locate relevant literature.

No Citations Or References

Unlike the introduction, the abstract typically does not include citations or references in APA or MLA to other works. It is a self-contained unit that focuses solely on summarizing the research conducted in the paper.

Structural Alignment

The abstract should mirror the structure of the paper, summarizing each section in a logical sequence. It typically includes brief statements about the introduction, methodology, results, and conclusion.

What Is The Difference Between Intro Vs Abstract

While the introduction and abstract share the common goal of providing readers with a roadmap to the research, they differ significantly in their depth, scope, and functions. Understanding these distinctions is crucial for crafting a well-rounded and impactful research paper.

While an abstract is a tightrope walker, restricted to a concise space, the introduction enjoys the freedom of expansiveness. It can stretch across paragraphs, weaving a tapestry of context and intrigue.

An abstract concentrates on the “what” and the “how” – highlighting the research question, methodology, and results. The introduction delves deeper, exploring the “why” – establishing the importance of your work and engaging the reader emotionally.

An abstract primarily caters to specialists and peer reviewers and needs technical accuracy and jargon. The introduction speaks to a broader audience, using accessible language and captivating storytelling to pique their interest.

An abstract follows a rigid format, typically outlining the research question, methodology, results, and conclusion. The introduction offers greater flexibility, allowing for creative storytelling and engaging transitions.

Depth Of Detail

The introduction provides a comprehensive overview of the background, context, and rationale for the study. It delves into existing literature, establishes the research question, and outlines the objectives. In contrast, the abstract is a condensed summary, offering a snapshot of the entire paper without the depth of detail found in the introduction.

Inclusion Of Citations

The introduction extensively cites relevant literature reviews to provide a foundation for the research. It establishes the scholarly context and justifies the study’s significance. On the other hand, the abstract typically avoids citations and focuses on presenting the research’s key elements without reference to external works.

Readability And Accessibility

The introduction is designed to be read sequentially, guiding readers from the general to the specific. It is an integral part of the paper’s narrative, contributing to the overall flow. In contrast, the abstract is a standalone piece that should be easily understandable on its own. It serves as a quick reference for researchers scanning multiple papers to determine their relevance.

Function Within The Paper

The introduction serves as a foundation for the entire paper, providing the necessary context for readers to understand the study’s purpose and significance.

It invites readers into the research narrative, guiding them through the subsequent sections. On the other hand, the abstract is a succinct summary that allows readers to quickly assess the paper’s content, methodology, and findings without delving into the full text.

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Strategies For Crafting Effective Introductions And Abstracts

Crafting compelling introductions and abstracts is a skill that evolves with practice and a nuanced understanding of the research process. Here are some strategies to enhance the effectiveness of these key components:

Clarity And Precision

Both the introduction and abstract benefit from clarity and precision. Use clear language to convey ideas and avoid unnecessary jargon. Ensure that each sentence serves a specific purpose and contributes to the overall coherence of the text.

Engaging The Reader

The introduction should engage the reader from the outset. Consider using anecdotes, thought-provoking questions, or relevant statistics to capture attention. Create a narrative flow that seamlessly leads readers from the general context to the specific research question.

Conciseness In The Abstract

Given its condensed nature, the abstract requires a careful selection of words to convey maximum information in a limited space. Avoid unnecessary details and focus on presenting the core elements of the research. Aim for brevity without sacrificing clarity.

Both the introduction and abstract should align with the overall structure of the paper. Ensure that the abstract provides a coherent summary of each section, mirroring the paper’s organization. Similarly, the introduction should seamlessly transition into subsequent sections.

Highlighting Significance

Clearly articulate the significance of the research in both the introduction and abstract. Explain why the study is relevant, what gaps it addresses, and how

Proofreading And Editing

Thoroughly proofread and edited both the introduction and abstract to eliminate grammatical errors, typos, and inconsistencies. Pay attention to the overall flow of the text, ensuring that ideas are presented logically and coherently.

Frequently Asked Questions

What is an abstract vs introduction.

An abstract is a concise summary of a research paper, providing an overview of key elements. An introduction contextualizes the study, presents the research question, and outlines objectives, serving as the entry point to the paper.

How to write an abstract vs introduction?

Write a clear, concise abstract by summarizing key research elements: objectives, methodology, findings, and conclusions. Craft an engaging introduction by providing context, stating the research question, and justifying its significance, leading readers into the study seamlessly.

Is introduction and abstract the same?

No, introduction and abstract serve distinct purposes in academic writing. The introduction provides context, states the research question, and justifies the study’s significance. The abstract is a concise summary of the entire paper, presenting key elements independently for quick reference.

Is The introduction on the same page as the abstract?

Yes, in academic papers, the introduction and abstract typically appear on the same page. The abstract precedes the introduction, providing a brief summary of the paper’s key elements, while the introduction introduces the study in more detail on the same page.

What is the difference between abstract and background?

The abstract is a concise summary of a research paper’s key elements. The background provides context in the introduction, detailing the broader field of study, and existing literature, and establishing the foundation for the specific research question or problem.

What is the difference between abstract and overview?

An abstract is a concise summary of a research paper, highlighting key elements. An overview is a broader term, encompassing a brief explanation or review of a subject, topic, or process, providing a general understanding without the depth of detail found in an abstract.

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• How to Write a Thesis Statement for Your Research: Tips + Examples

Every research paper builds on a central argument that reflects the position of the researcher—this is known as the thesis statement. More than defining the researcher’s central argument, a good thesis statement tells the reader how to interpret the subject matter being discussed. 

Without any doubt, writing a good thesis statement is an important step in developing an effective research paper. In this article, we’ll show you how to create different types of thesis statements plus examples you can learn from. Ready? Let’s get started! 

What is a Thesis Statement?  

A thesis statement is a single sentence or assertion that captures the core argument of your research. In other words, it summarizes the claim or primary idea that you want to pass across in the dissertation. 

A good thesis statement helps you achieve two major things. First, it gives the reader a clear idea of what your research is about; that is, what the paper is saying about the topic. Next, it asserts your unique position for or against the argument at hand. 

Typically, you’d find the thesis statement at the conclusion of your research paper’s introductory paragraph. So when next you’re reading a research paper, look out for that ONE sentence that ties together the main idea of the research paper’s argument. 

Explore: 21 Chrome Extensions for Academic Researchers in 2021

Importance of a Thesis Statement

Since you have an abstract and research proposal, why should you bother writing a thesis statement? The first thing you need to know is that the abstract and thesis statement work differently. An abstract summarizes your research paper, highlighting its key points while a thesis statement communicates the core idea of your paper. 

Let’s go through a few reasons why you need a thesis statement in research. 

• A good thesis statement establishes the core idea behind your research paper. It introduces readers to the core idea of your work. 
• After reading your thesis statement, your professor would understand your unique position on the argument at hand. In other words, a thesis statement declares the position of the researcher on the specific subject. 
• It serves as an “accountability check”. When you make a claim in research, you’d have to provide supporting arguments and points that confirm this claim. 
• A good thesis helps the reader to focus on the main idea of your research paper. 
• A thesis statement sets the pace for your essay and helps you to organize your ideas neatly. 
• It tells the audience what comes next by presenting the writer’s point of view. The rest of your paper is about reinforcing this statement with supporting facts or case studies.
• A good thesis statement helps you achieve cohesion and coherence in your essay. 

Read: Writing Research Proposals: Tips, Examples & Mistakes

Categories of Thesis Statements

1. informative thesis .

You’d find an informative thesis statement in essays and research papers that do not argue for or against a topic. In other words, an informative thesis is one that simply communicates the purpose of an essay, without making any arguments or claims that can be true or false. 

When writing an informative thesis, your primary focus should be communicating the purpose of your research in a clear and concise manner. Be careful not to steer up any arguments or make any claims that you need to provide evidence for. 

Examples of Informative Thesis Statements 

• The first wave of feminism focused on securing women’s rights to vote and other legal issues. 
• Diabetes is a major cause of medical conditions like blindness, kidney failure, and stroke. 

Important Read: Research Questions: Definitions, Types + [Examples]

2. Persuasive Thesis  

A persuasive thesis statement is one that makes a claim and goes on to show why that claim is true. Unlike an informative thesis, a persuasive thesis sets out to make a bold argument that forms the core idea of your research process. 

Persuasive statements have two parts. In the first part, the researcher makes an assertion that she believes to be true. In the second part of the statement, the researcher provides some evidence to back up this claim. The goal is to provide a solid backing that convinces the reader to agree with the researcher’s position. 

Let’s look at a few examples of a persuasive thesis statement. 

Learn About: How to Write a Problem Statement for your Research

Examples of a Persuasive Thesis Statement

• Students who sleep early perform better in the classroom because they have higher levels of concentration. 
• Peanut butter and jelly sandwiches are the best types of sandwiches because they are versatile, easy to make, and taste good.

Many research papers adopt persuasive thesis statements because it allows the researcher to highlight major discoveries from their systematic investigation. 

Learn More: Cross-Sectional Studies: Types, Pros, Cons & Uses

Types of Thesis Statements 

Now that you’re familiar with the major categories of thesis statements, let’s discuss some common types of thesis in academic research. 

1. Analytical Thesis Statement 

An analytical statement is a logical presentation of the researcher’s stance in a systematic investigation. Here, the researcher breaks down an idea into different parts, evaluates these parts closely, and clearly presents the order of the analysis to the reader. This means that your thesis needs to mention the specific aspect that you’ll focus on and state what insight it gives us into the text’s meaning or purpose.

How to Formulate an Analytical Thesis Statement

• Break down your main idea into its key components.
• Discover the logical relationship among the parts.
• Discover the motives, causes, and underlying assumptions. 
• Make the required inferences and lay out evidence to support your claims. 

Examples of Analytical Thesis Statement 

Sample 1: Purdue.edu (Source)

An analysis of the college admission process reveals one challenge facing counselors: accepting students with high test scores or students with strong extracurricular backgrounds.

Sample 2: Study.com (Source) 

Though World War I had many different causes, burgeoning nationalism fomented the sense of aggression that ultimately led to the War’s beginning and proliferation.

Read: Double Blind Studies in Research: Types, Pros & Cons

2. Expository Thesis Statement 

The purpose of an expository thesis statement is to get the reader acquainted with your research paper. In other words, it sets the expectations for your essay by stating your research topic plus the key areas you will touch on in the paper. 

Because of its nature, an expository thesis doesn’t have to give a strong opinion. Rather, it should clearly communicate the theme of your essay, and hint at supporting arguments that you will touch on. After reading your expository thesis, the reader should have a clear idea of what they’ll learn from your essay. 

Examples of an Expository Thesis Statement 

Sample 1: Scribbr.com (Source)

The invention of Braille transformed the lives of blind people in the nineteenth century, but its success depended on mainstream acceptance by sighted teachers, and this process was shaped by debates about disabled people’s place in society.

Although there are different causes of world war 1, Militarism, Nationalism, Alliances, Imperialism, and Assassination led to the war’s beginning.

Read: Hypothesis Testing: Definition, Uses, Limitations + Examples

3. Argumentative Thesis Statement

This is the most common type of thesis you’d find in research papers. Basically, the purpose of an argumentative thesis is to make a claim that people can agree or disagree with. Throughout the research paper, you’d have to provide facts, figures, and data that convince the audience to agree with your position.  

Examples of an Argumentative Thesis Statement 

• Children who have single parents find socialization more challenging compared to their counterparts. 
• Junk food can help you become healthier and get rid of excess calories. 

Elements of a Good Thesis Statement

How do you know you’ve written an excellent thesis statement? The simple way to do this is to match your thesis statement against the features on this list. 

In this section, we’d go through some of the elements of a good thesis statement. 

• Interpretation: More than regurgitating facts, a good thesis statement must explain these facts and show their significance.
• Precision: Your thesis statement should highlight specific facts, and create a logical relationship among these facts. it states that two ideas were similar or different, without explaining how they were similar or different, it is too vague.
• Element of Surprise: Do you have any information that can catch the reader’s attention and convince them to agree with your position? Now is a good time to highlight them and win the reader over to your side. 
• Evidence: A thesis statement should contain an opinion or point of view that can be supported with evidence.
• Demonstrability : Any claims you’ve made in your statement must be backed by reasons and examples for your opinion. 

Read: Research Report: Definition, Types + [Writing Guide]

Steps for Writing a Thesis Statement

Step 1: Start with a Question 

Ask yourself a simple question concerning what you’d like to explore or find out regarding a topic. 

Step 2: Write an Answer to this Question

After conducting your initial research, string all the information you gather to form a tentative answer to this question. The purpose of this temporary response is to guide your research. 

Step 3: Develop Your Answer

This is the point where you flesh out your answer with new and supporting evidence. You need to consider why this is your answer and how you will convince your reader to agree with you.

Examples of a Strong Thesis Statement

Sample 1 : Schools should provide educational resources for low-income students so that they can perform better in the classroom. 

Sample 2 : Prioritizing diversity and inclusion in the workplace can lead to richer ideas, better employee collaboration, and more empathy among people from different backgrounds. 

Sample 3 : Countries with high poverty levels record higher incidences of violence.   

Sample 4: Because half of all American elementary school children consume nine times the recommended daily allowance of sugar, schools should be required to replace the beverages in soda machines with healthy alternatives.

Examples of a Weak Thesis Statement 

A weak thesis statement is too broad or ambiguous, making it difficult for the reader to understand your position. Weak thesis statements may also lack evidence. Here are a few samples. 

Sample 1: Technology has its advantages and disadvantages. 

This statement is weak because it doesn’t point to the type of technology you’re referring to. Also, it attempts to argue two points in a single sentence. 

Sample 2 : Taking affirmative action is a way to reduce gender-based violence. 

This is a statement of fact that doesn’t pique the interest of the reader. Instead, you should establish a thesis that is arguable, and state the how or why of your position. 

Although a thesis statement is just a single sentence, you should take your time to formulate one. Before you develop an argument on any topic, you have to collect and organize evidence, look for possible relationships between known facts (such as surprising contrasts or similarities), and think about the significance of these relationships.

When you have a well-rounded understanding of the data, you can build a strong thesis statement that captures the core of your research.

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Q. What is the difference between a thesis statement and a hypothesis statement?

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Answered By: APUS Librarians Last Updated: Apr 15, 2022     Views: 127656

Both the hypothesis statement and the thesis statement answer a research question. 

• A hypothesis is a statement that can be proved or disproved. It is typically used in quantitative research and predicts the relationship between variables.  
• A thesis statement is a short, direct sentence that summarizes the main point or claim of an essay or research paper. It is seen in quantitative, qualitative, and mixed methods research. A thesis statement is developed, supported, and explained in the body of the essay or research report by means of examples and evidence.

Every research study should contain a concise and well-written thesis statement. If the intent of the study is to prove/disprove something, that research report will also contain a hypothesis statement.

NOTE: In some disciplines, the hypothesis is referred to as a thesis statement! This is not accurate but within those disciplines it is understood that "a short, direct sentence that summarizes the main point" will be included.

For more information, see The Research Question and Hypothesis (PDF file from the English Language Support, Department of Student Services, Ryerson University).

How do I write a good thesis statement?

How do I write a good hypothesis statement?

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Neurobiology-based Cognitive Biotypes Using Multi-scale Intrinsic Connectivity Networks in Psychotic Disorders

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Objective Understanding the neurobiology of cognitive dysfunction in psychotic disorders remains elusive, as does developing effective interventions. Limited knowledge about the biological heterogeneity of cognitive dysfunction hinders progress. This study aimed to identify subgroups of patients with psychosis with distinct patterns of functional brain alterations related to cognition (cognitive biotypes).

Methods B-SNIP consortium data (2,270 participants including participants with psychotic disorders, relatives, and controls) was analyzed. Researchers used reference-informed independent component analysis and the NeuroMark 100k multi-scale intrinsic connectivity networks (ICN) template to obtain subject-specific ICNs and whole-brain functional network connectivity (FNC). FNC features associated with cognitive performance were identified through multivariate joint analysis. K-means clustering identified subgroups of patients based on these features in a discovery set. Subgroups were further evaluated in a replication set and in relatives.

Results Two biotypes with different functional brain alteration patterns were identified. Biotype 1 exhibited brain-wide alterations, involving hypoconnectivity in cerebellar-subcortical and somatomotor-visual networks and worse cognitive performance. Biotype 2 exhibited hyperconnectivity in somatomotor-subcortical networks and hypoconnectivity in somatomotor-high cognitive processing networks, and better preserved cognitive performance. Demographic, clinical, cognitive, and FNC characteristics of biotypes were consistent in discovery and replication sets, and in relatives. 70.12% of relatives belonged to the same biotype as their affected family members.

Conclusions These findings suggest two distinctive psychosis-related cognitive biotypes with differing functional brain patterns shared with their relatives. Patient stratification based on these biotypes instead of traditional diagnosis may help to optimize future research and clinical trials addressing cognitive dysfunction in psychotic disorders.

Competing Interest Statement

PAC has received travel support from Neuraxpharm and ROVI. CDC has received honoraria or travel support from Angelini and Janssen. JC, RB, VC, and AI report no financial relationships with commercial interests.

Funding Statement

PAC has received grant support from Programa Intramural de Impulso a la I+D+i 2023 (Instituto de Investigacion Sanitaria Gregorio Maranon). CDC has received grant support from Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation (PI20/00721, JR19/00024) and the European Commission (grant 101057182, project Youth-GEMs). VC has received grant support from the National Institutes of Health (R01MH123610). AI has received grant support from the National Institutes of Health (R01MH123610).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The storage and management of the data and access procedures are overseen by the National Institute of Mental Health (NIMH) through the National Data Archive (NDA). The Institutional Review Board approved the project at each participating institution: Athens, GA (University of Georgia, B-SNIP2 only); Baltimore, MD (University of Maryland School of Medicine, B-SNIP1 only); Boston, MA (Harvard Medical School), Chicago IL (University of Illinois-Chicago for B-SNIP1 and University of Chicago for B-SNIP2); Dallas, TX (University of Texas Southwestern Medical Center), Detroit MI (Wayne State University, B-SNIP1 only); and Hartford, CT (Yale University School of Medicine).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

The storage and management of the data and access procedures are overseen by the National Institute of Mental Health (NIMH) through the National Data Archive (NDA).

https://nda.nih.gov/

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• Vibration of effects resulting from treatment selection in mixed-treatment comparisons: a multiverse analysis on network meta-analyses of antidepressants in major depressive disorder
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• http://orcid.org/0000-0002-6899-1838 Constant Vinatier 1 ,
• http://orcid.org/0000-0001-5440-1860 Clement Palpacuer 2 ,
• Alexandre Scanff 1 ,
• http://orcid.org/0000-0003-3760-3801 Florian Naudet 1 , 3
• 1 Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, Centre d’investigation clinique de Rennes (CIC1414), F-35000 , Rennes , France
• 2 Groupe Hospitalier de la Region de Mulhouse et Sud Alsace , Mulhouse , France
• 3 Institut Universitaire de France , Paris , France
• Correspondence to Constant Vinatier, University of Rennes, Rennes, 35000, France; constant.vinatier1{at}gmail.com

Objective It is frequent to find overlapping network meta-analyses (NMAs) on the same topic with differences in terms of both treatments included and effect estimates. We aimed to evaluate the impact on effect estimates of selecting different treatment combinations (ie, network geometries) for inclusion in NMAs.

Design Multiverse analysis, covering all possible NMAs on different combinations of treatments.

Setting Data from a previously published NMA exploring the comparative effectiveness of 22 treatments (21 antidepressants and a placebo) for the treatment of acute major depressive disorder.

Participants Cipriani et al explored a dataset of 116 477 patients included in 522 randomised controlled trials.

Main outcome measures For each possible treatment selection, we performed an NMA to estimate comparative effectiveness on treatment response and treatment discontinuation for the treatments included (231 between-treatment comparisons). The distribution of effect estimates of between-treatment comparisons across NMAs was computed, and the direction, magnitude and statistical significance of the 1st and 99th percentiles were compared.

Results 4 116 254 different NMAs concerned treatment response. Among possible network geometries, 172/231 (74%) pairwise comparisons exhibited opposite effects between the 1st and 99th percentiles, 57/231 (25%) comparisons exhibited statistically significant results in opposite directions, 118 of 231 (51%) comparisons derived results that were both significant and non-significant at 5% risk and 56/231 (24%) treatment pairs obtained consistent results with only significant differences (or only non-significant differences) at 5% risk. Comparisons based on indirect evidence only were associated with greater variability in effect estimates. Comparisons with small absolute values observed in the complete NMA more frequently obtained statistically significant results in opposite directions. Similar results were observed for treatment discontinuation.

Conclusion In this multiverse analysis, we observed that the selection of treatments to be included in an NMA could have considerable consequences on treatment effect estimations.

Trial registration https://osf.io/mb5dy .

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Data availability statement

Data are available in a public, open access repository. The data and code are openly shared on the OSF ( https://osf.io/hb7uj/ ) and the dataset is shared by the original authors on Mendeley ( https://data.mendeley.com/datasets/83rthbp8ys/2 ).

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjebm-2024-112848

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WHAT IS ALREADY KNOWN ON THIS TOPIC

It is frequent to find contradictory network meta-analyses on the same topic, although these studies are currently considered to possess among the best evidential standards.

Analytical and methodological flexibility in pairwise meta-analyses, pooled analyses and indirect comparisons can lead to vibration of effects (measuring how far an effect estimate can change across multiple distinct analyses).

WHAT THIS STUDY ADDS

Our multiverse analysis based on a large network meta-analysis exploring antidepressant efficacy in major depressive disorder suggests that network meta-analyses are prone to considerable vibration of effects, if only via the choice of treatments to be included in the network. Whether amitriptyline is more effective than other drugs—as the conclusion of the original meta-analysis—strongly depends on the drugs and comparisons considered.

Vibration of effects can be greater for treatment comparisons based solely on indirect evidence. Statistically significant results pointing in opposite directions are more readily generated when differences between treatments are small.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Results from network meta-analyses should be critically appraised.

Introduction

Network meta-analyses (NMAs) are influential evidence synthesis tools often considered to dominate the hierarchy of evidence supporting clinical decision-making. 1 By evaluating connected networks of randomised control trials (RCTs), NMAs draw inferences on the comparative effectiveness of many interventions that may or may not have been compared directly. NMAs provide some answers to practical questions in day-to-day clinical practice, for instance. which treatment should be prioritised when many treatments are available for the same condition. 2 This information is all the more important in fields such as psychopharmacology where ‘blockbuster’ drugs (eg, fluoxetine for major depressive disorders) co-exist with ‘me-too’ drugs, marketed despite uncertain added value. Direct evidence for comparative effectiveness is indeed all too often lacking from regulatory approvals. 3 For these reasons, NMAs have become very popular tools in Evidence-Based Medicine.

NMAs are, however, victims of their own success, as their number is rapidly expanding with extensive overlap and potential redundancy. Too often, NMAs present an incomplete and fragmented picture of the total available evidence, with certain potential reproducibility issues. It has been observed that conclusions on comparative effectiveness can vary across overlapping NMAs on the same topic, 4 suggesting that NMAs are prone to vibration of effects (VoE), which measures how far an effect estimate can vary across multiple distinct analyses. 4 The study of VoE is possible by running an extreme range of sensitivity analysis. It enables assessment of the impact of a methodological choice on results by testing all of them. Various indicators exist to assess the presence of VoE, 5 such as the Janus effect (ie, when the 1st percentile and the 99th percentiles of all possible effect estimates are in different directions) or the relative OR (ROR, which is the ratio between the 1st percentile and the 99th percentile of all possible effect estimates). Several multiverse analyses have highlighted how VoE resulting from different methodological and analytical choices can lead to divergent and antagonistic conclusions in meta-analyses, for example, for pairwise meta-analyses, 6 7 for pooled analyses of individual patient data 8 and for indirect comparisons. 7 Similar reproducibility issues are expected with NMAs since they rely on strong assumptions—for example, transitivity (similarity across the studies included) and consistency (homogeneity between direct and indirect evidence)—which are quite difficult to ascertain. 9 Because of the numerous interventions compared in NMAs, they are also prone to multiplicity issues. 9 Even basic choices such as the consideration of eligible nodes to be included in an NMA can yield different effect estimates and treatment rankings. 10 We aimed to quantify and visualise VoE arising from all possible network geometries, that is, all possible combinations of treatments included in a network meta-analysis, using a multiverse analysis approach. For this purpose, we based our investigation on a widely known NMA by Cipriani et al exploring the comparative effectiveness and acceptability of 21 antidepressant drugs and placebo for the treatment of adults with acute major depressive disorder. 11

Protocol, registration and reporting

The protocol was registered on 3 August 2020, on the Open Science Framework before the start of the study (available at: https://osf.io/mb5dy ). The results are presented according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis checklist 12 and its extension for network meta-analyses. 13

Data retrieval and study selection

We re-used the dataset used in Cipriani et al . NMA which is openly shared on Mendeley (available at: https://data.mendeley.com/datasets/83rthbp8ys/2 ). Data collection has been comprehensively detailed previously. 11 Briefly, this dataset was collected up to 8 January 2016 and includes published and unpublished placebo-controlled and head-to-head double blind RCTs on 21 antidepressants (agomelatine, amitriptyline, bupropion, citalopram, clomipramine desvenlafaxine, duloxetine, escitalopram, fluoxetine, fluvoxamine, levomilnacipran, milnacipran, mirtazapine, nefazodone, paroxetine, reboxetine, sertraline, trazodone venlafaxine, vilazodone and vortioxetine) used for the acute treatment of adults with major depressive disorder. Quasi-randomised trials, incomplete trials or trials that included 20% or more participants with bipolar disorder, psychotic depression or treatment-resistant depression, or patients with a serious concomitant medical condition were not included. The dataset includes 522 RCTs involving 116 477 patients in 1199 different study arms, conducted between 1979 and 2016. All study arms evaluating the efficacy of antidepressants within the licensed dose range and the accepted/recommended dose range in the main clinical guidelines 11 were considered.

Study outcome

We explored VoE for the two different outcomes used in the NMA by Cipriani et al . The primary outcome was efficacy assessed using the response rate (treatment response defined by a reduction of ≥50% in the total score on a standardised observer-rated scale for depression). The secondary outcome was treatment discontinuation measured by the proportion of patients who withdrew for any reason. These outcomes were recorded as close to 8 weeks after initiation of treatment as possible and computed for all randomised patients. The response rate was imputed for 292 (24.3%) study arms, and dropouts were imputed as non-responders. In the case of multi-arm studies evaluating several doses of the same treatment for which the outcome was available, these arms were pooled.

Assessment of VoEs

NMAs were performed for each possible treatment selection derived from the 21 antidepressants and placebo (ie, we constructed all possible networks with 2, 3, etc up to 22 treatments). Among these possible networks, combinations that led to non-connected networks were excluded.

For all networks included, NMAs were performed. We collected network geometry (names of treatments, number of comparisons, number of participants treated), treatment comparisons (OR and p value) and two other metrics (Cochran’s Q and I² index). We computed the distribution of point estimates by effect sizes (ESs) and their corresponding p values under the various analytical scenarios defined by the different network geometries. Comparisons were considered statistically significant if the ES was associated with a p value <0.05. For each comparison pair, the presence of a ‘Janus effect’ was investigated by calculating the 1st and 99th percentiles of the distribution of the ES. 5 A Janus effect is defined as an ES that is in the opposite direction between the 1st and 99th percentiles of the meta-analysis. It demonstrates the presence of substantial VoE. In addition, we computed the distribution of the I 2 indices, and the p values on Cochran’s Q test calculated for each network meta-analysis. Heterogeneity was considered statistically significant if the p value for the Q test was <0.10.

The network meta-analyses were performed with R software (V.4.2.2 (2022-10-31)) 14 netmeta package (V.2.8.2), which uses a frequentist method to perform NMAs, 15 the doParallel package (V.1.0.17) 16 and the tidyverse language (V.2.0.0). 17 A random-effect model was considered for all NMAs.

Changes to the initial protocol

In addition to the Janus effect, we described two additional parameters in order to have a more comprehensive understanding of VoE in this dataset: (1) an extreme form of the Janus effect where the two extremes exhibit statistically significant results and (2) the RORs as described by Patel et al , 5 calculated as the ratio of ORs at the 1st and 99th percentile, which enables quantification of variations in point estimates, even when no Janus effect is observed. An ROR value of 1 suggests the absence of VoE, whereas higher ROR values indicate a more pronounced level of vibration. 18 We explored the correlation between the ROR for treatment response and the ROR for treatment discontinuation using Spearman’s rank correlation.

As an exploratory analysis using our assessment of VoE for all treatment comparisons, we decided to investigate, using either a logistic or a linear model, the associations for (1) the Janus effect, (2) the existence of statistically significant results in opposite directions and (3) the RORs with the following explanatory variables considered as possible sources of VoE in NMAs: (1) a categorial variable describing the type of available evidence for the comparison in the full network and (2) the ES of the comparison in question. The type of available evidence was defined either as the presence of direct comparison without inconsistency, the presence of direct comparison with inconsistency or indirect comparisons only. A threshold for the p value <0.10 was used to define inconsistency, from a two-sided z test comparing direct and indirect evidence determined on the most complete network. 15 In this exploratory analysis, we defined the ES of the comparison in question as the absolute value of the log OR of the most complete NMA. With this last parameter, we aimed to explore whether null results were more likely to induce a Janus effect. Because of the lack of normality of residuals in the linear model for ROR, a log transformation was applied. Following a reviewer’s comment, we decided to explore whether the number of treatments included in a given network impacted the presence of VoE. This was explored by computing separately the percentage of treatment comparisons that exhibited a Janus effect (among the 231 comparisons) by subgroups of NMAs with fixed numbers of treatments (ie, NMAs of 3, NMAs of 4, NMAs of 5, …, NMAs of 21 treatments). Additionally, we plotted VoE for comparisons between the treatments exhibiting the highest and lowest VoE (clomipramine and placebo, respectively) depending on the number of treatments in the NMA. Following another reviewer’s comment, we carried out sensitivity analyses using percentiles of 10%–90% and 25%–75% to define the Janus effect.

Patient and public involvement

Patients and the public were not involved in the design, conduct, reporting, or dissemination plans for this research. This was a methodological study, and we had no established contacts with specific patient groups who might be involved in this project.

Primary outcome: treatment response

Among the 4 194 281 possible NMAs, 78 027 (2%) non-connected networks were excluded, resulting in a total of 4 116 254 NMAs (see online supplemental e-Table 1 ). The percentage of non-connected networks decreased as the number of treatments per network increased, falling from 57% for networks of two treatments to 0% for networks with 18–22 treatments. Figure 1 and online supplemental e-Table 2 summarise the distribution of the network geometries observed for all 4 116 254 NMAs included. All treatments except milnacipran and clomipramine had direct comparisons with placebo which was the most widely represented arm (with 35 721 patients). The most frequent direct comparisons were those for paroxetine versus placebo (46 studies) and fluoxetine versus placebo (40 studies). Levomilnacipran was the only treatment represented in the network by a single comparison (vs placebo). Among the 231 pairs across the 22 treatments, 99 had direct evidence and 132 relied only on indirect evidence.

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Distribution of network geometry for NMAs on treatment response. The size of each dot represents the number of patients allocated to the respective treatments. For each treatment, the blue circles indicate the NMAs with the largest number of patients included, the green circles represent the NMAs with the median number of patients included and the orange circles show the NMAs with the smallest number of patients included. The width of the lines is proportional to the number of trials comparing pairs of treatments in the complete NMA. NMA, network meta-analyses.

Figure 2A summarises VoE observed across the 231 treatment comparisons. After computing the 4 116 254 NMAs, we observed the presence of the Janus effect in 172/231 (74%) treatment comparisons. There were statistically significant results pointing in opposite directions for 57/231 (25%) of the comparisons, suggesting the presence of substantial VoE; 56/231 (24%) comparisons obtained consistent results with only significant differences (or only non-significant differences) at the 5% level and 118/231 (51%) comparisons obtained results with both significant and non-significant results at the 5% level across NMAs. RORs ranged from 1.01 to 5.96 with a median ROR of 1.72 (IQR: 1.03–4.83) indicating significant VoE.

VoE in the 231 comparisons across the 22 treatments, classified according to their degree of VoE. (A) For treatment response. (B) For treatment discontinuation. For each dot, the centre indicates the existence of a Janus effect (green=no, orange=yes), the outline indicates the existence of statistically significant results in two opposite directions (green=comparisons that obtained consistent results with only significant differences (or only non-significant differences) at the 5% level, orange: comparison that yielded both significant and non-significant results at the 5%, red: significant results observed in opposite directions). Numbers correspond to the relative ORs which are ratios quantifying the ratios of ORs at the 1st and 99th percentile. The higher the relative OR, the greater the variability of results arising from the network geometries considered. VoE, vibration of effects.

Clomipramine ( figure 3 ) was the treatment with the highest level of VoE with a Janus effect present in all comparisons except the comparison with placebo. NMAs showing statistically significant results in opposite directions were present for 10 different comparisons.

Vibration of effects for treatment response for the comparisons of clomipramine with the 20 remaining antidepressants and placebo (with the number of patients included in the most complete network for this comparison). An OR >1 favours clomipramine. The colours indicate the log densities of network meta-analyses (yellow: high, green: moderate, blue: low). Dotted red lines show the 1st and 99th percentiles.

Placebo ( figure 4 ) was the treatment with the lowest level of VoE. No Janus effect was identified for any comparisons. All NMAs identified a statistically significant superiority of antidepressants over placebo, except for clomipramine and milnacipran for which 16% and 11% of the NMAs respectively failed to identify statistically significant results.

Vibration of effects for treatment response for the comparisons of placebo with the 21 antidepressants (with the number of patients included in the most complete network for this comparison). An OR >1 favours placebo. The colours indicate the log densities of network meta-analyses (yellow: high, green: moderate, blue: low). Dotted red lines show the 1st and 99th percentiles.

Results for other treatments are presented in online supplemental e-Figures 1–20 .

Post-hoc analysis. (A) RORs for treatment response and treatment discontinuation. The colour of the dots indicates the presence of a Janus effect for both outcomes (green: no Janus effect, yellow: Janus effect for one of the outcomes and red: Janus effect for both). (B) Percentage of treatment comparisons exhibiting a Janus effect (among the possible comparisons) by subgroups of NMAs with fixed number of treatments (ie, NMAs of 3, NMAs of 4, NMAs of 5, …, NMAs of 21 treatments). NMA, network meta-analyses; ROR, relative OR.

Across all NMAs assessing treatment response, the median I 2  was 31% (IQR=22%–36%) and the p value for Cochran’s Q test was < 0.10 for 3 353 881/4 116 254 (81%) of the NMAs. Online supplemental e-Figure 21 details vibration for these two parameters.

Secondary outcome: treatment discontinuation

For these analyses, we had to exclude six studies corresponding to 145 patients randomised in seven arms because of the absence of an event. Of the 4 194 281 possible NMAs, 72 691 (2%) non-connected networks were not included, resulting in a total of 4 121 590 NMAs (see online supplemental e-Table 1 ), that is, 5336 more than for treatment response. Online supplemental e-Figure 22 and e-Table 2 summarise the distribution of the network geometries observed for the 4 121 590 NMAs included. Four direct comparisons that were available for treatment response were missing for treatment discontinuation (clomipramine vs milnacipran, clomipramine vs trazodone, fluoxetine vs vilazodone and reboxetine vs venlafaxine). Conversely, there were two direct comparisons for treatment discontinuation that were absent for treatment response (amitriptyline vs bupropion and clomipramine vs placebo). Among the 231 comparisons of the 22 treatments, 97 had direct evidence and 134 relied only on indirect evidence. Figure 2B summarises VoE observed across the 231 treatment comparisons. After computing the 4 194 281 NMAs, we observed a Janus effect in 180/231 (78%) treatment comparisons. We also observed statistically significant results pointing in opposite directions for 45/231 (19%) of the comparisons; 46/231 (20%) of the comparisons were able to obtain consistent results with only significant differences (or only non-significant differences) at the 5% level, and 140/231 (61%) comparisons obtained results with both significant and non-significant results at the 5% level. RORs ranged from 1.01 to 10.17 with a median ROR of 1.95 (IQR: 1.33–2.50) indicating significant VoE. Results observed for all treatments are detailed in online supplemental e-Figures 23–44 . Among the NMAs assessing treatment discontinuation, the median I 2  was 24% (IQR=11%–30%) and the p value on Cochran’s Q test was < 0.10 for 2 539 033/4 121 590 (61%) of the NMAs. Online supplemental e-Figure 45 details vibration for these two parameters. RORs observed for treatment discontinuation were correlated with RORs observed for treatment response (Spearman’s ρ=0.86, p value <0.001, figure 5A ).

Exploratory analysis of characteristics associated with VoE

Levomilnacipran was only studied against placebo, making it impossible to provide indirect evidence, which is why this comparison was left out for the exploratory analysis. The results based on the remaining 230 comparisons are presented in table 1 . Regarding treatment response, indirect evidence was associated with a more frequent Janus effect, more results in opposite directions and greater RORs, while the ES observed in the most comprehensive meta-analysis (expressed as an absolute value of the log ORs) was only found to be associated with the Janus effect and statistically significant results in opposite directions. Quite similar results were observed for treatment discontinuation.

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Association between vibration of effects indices and various characteristics of treatment comparisons

Exploratory analysis according to number of treatments in each network

Figure 5B details the percentage of treatment comparisons that exhibited a Janus effect (among the 231 comparisons) by subgroups of NMAs with fixed numbers of treatments. This percentage was in general above 50% for most subgroups with a maximum of 80% (180/231) for networks including nine treatments, with a gradual reduction to 30% (69/231) for meta-analyses with 21 treatments. The VoE plot for comparisons between the treatments exhibiting the highest and lowest VoE (clomipramine and placebo, respectively) according to the number of treatments in the NMA are presented in the online supplemental e-Figures 46–87 .

Sensitivity analysis regarding the definition of the Janus effect

A Janus effect was identified in 58.9% (136/231) and in 35.1% (81/231) of comparisons for definitions using percentiles of 10%–90% and 25%–75%, respectively.

Statement of principal findings

In this multiverse analysis, we performed 4 116 254 NMAs evaluating the comparative treatment response of 21 antidepressants and placebo. Depending on treatment selection, we identified substantial VoE with the presence of a Janus effect in 172/231 (74%) comparisons. For 57/231 comparisons (25%), VoE yielded statistically significant results in opposite directions. In more concrete terms, whether amitriptyline is more effective than other drugs, as suggested by Cipriani et al , strongly depends on the drugs and comparisons considered. Similar results were observed among the 4 121 590 NMAs evaluating treatment discontinuation. RORs for treatment response and treatment discontinuation were highly correlated. Comparisons relying on indirect evidence alone were associated with all three indices of VoE (Janus effect, significant results in opposite directions and RORs). Having an ES close to zero (as assessed in the most comprehensive meta-analysis) was associated with the Janus effect, with significant results in opposite directions, but not with RORs.

In other terms, variations in estimated effects are greater for comparisons relying on indirect evidence only. When the actual differences between treatments are small, this can lead to effect estimates in opposite directions, and occasionally to statistically significant results in both directions. It is not surprising to see these results in this very specific multiverse analysis focused on antidepressants. Many of the drugs studied are me-too drugs from a few therapeutic classes, resulting in small difference between treatments. In addition, VoE could be expected in this corpus, as a previous re-analysis of the Cipriani et al dataset was able to identify differences among antidepressant placebos although all are composed of sucrose, 19 to some extent suggesting violations of the main assumption of NMAs.

Strengths and weaknesses of the study

We used a well-known NMA with 22 different treatments (including placebo), making it possible to study a large number of network geometries. As this was a multiverse analysis performed in a very specific field (the use of antidepressants to treat major depressive disorder), different results could be observed in a different context, for example, for networks of different size or in different fields. In addition, estimating VoE related to treatment selection could be difficult to conduct for NMAs exploring smaller networks of RCTs. Smaller networks could be less prone to VoE because of the treatment selection, as the contribution of indirect comparisons is associated with the number of treatments included in the NMA. 20 On the other hand, studies of VoE related to treatment selection can be challenging in larger networks, since performing a large number of NMAs requires a lot of computing time. It took us almost 3 months on a personal computer to compute the near 8 million NMAs needed for this specific case study.

In addition, we considered only treatment selection as a source of VoE for this study. Although it seems to be a relevant choice, as differences in treatment selection are frequently observed for overlapping NMAs on the same topic, 4 complementary methodological choices could have been made, for example, the exhaustiveness of the evidence base (related both to the selection criteria and to the quality of the literature searches) or the risk of bias in the RCTs included. In addition, for treatment selection, additional VoE could be related to decisions made to merge or not to merge different doses of the same treatment in a given node. Lastly, the exploratory analysis of the characteristics associated with VoE includes results on various treatments that are in fact correlated, meaning that uncertainty is greater than that reflected by the 95% CIs. Great caution is therefore warranted when interpreting these exploratory results.

Strengths and weaknesses in relation to other studies, discussion of important differences in results

After our previous multiverse analysis, which made several methodological choices for indirect comparison meta-analyses to compare nalmefene and naltrexone in the reduction of alcohol consumption, 7 this new study, in a more complex network, corroborates VoE arising from indirect comparisons. VoE was also found to influence the results in a head to head meta-analysis in the case of acupuncture for smoking cessation, a domain that is known for its clinical and methodological heterogeneity. 21 Similarly, marked VoE was observed in a meta-analysis comparing operative with non-operative treatments for proximal humerus fractures. 6 While the domain of antidepressant research is probably more standardised with less variability in interventions and study designs than acupuncture or surgery, we were still able to find evidence for VoE. In addition, VoE has been observed in pooled analyses of individual participant data from 12 RCTs comparing canagliflozin and placebo for type 2 diabetes mellitus. 8 All these multiverse analyses were useful to investigate reproducibility issues and controversies arising from redundant and overlapping meta-analyses. 22 Nevertheless, these studies converge to point to the existence of VoE in meta-analyses, and we recommend further research to systematically explore VoE and its determinants (eg, ESs, heterogeneity, inconsistency, risk of bias in studies included and random sampling) in a large set of meta-analyses before any systematic implementation in routine practice. It might help to understand better the strengths and limitations of the approach, even if computational time can be a source of difficulties.

Meaning of the study: possible explanations and implications for clinicians and policymakers

Our results show that effect estimates in NMAs can be impacted by the network structure. In other words, NMAs allow for a certain amount of analytical flexibility, which can lead to divergent results, and NMAs can therefore be easily hijacked to a desired conclusion. This is all the more important since NMAs have particular importance for clinical decision-making: since direct evidence of comparative effectiveness is all too often lacking in regulatory approvals, 23 indirect evidence is often required for guideline development. 24 Concerning the conduct of NMAs, analytical flexibility can be partly addressed by pre-registration in Prospero, 25 a practice that is encouraged but not enforced by most journals, as there is no policy for meta-analyses similar to the 2005 ICMJE policy on clinical trials. 26 Still, because meta-analyses are almost always retrospective studies that gather existing evidence, the possibility of an a posteriori registration is often very difficult to rule out. The constitution of systematic, permanent, living NMAs could also help to reduce reporting bias of this sort. Regarding interpretation of NMAs, our results highlight the importance of considering uncertainties in NMA results, and corroborate the widespread idea that indirect comparisons can lead to biased conclusions. 27 28 This is all the more important since empirical evidence suggests that in NMAs, most of the information often comes from indirect evidence. 20 NMAs results are considered as an important source of evidence for clinical practice guidelines, 24 for instance, in mental health disorders. 29 However, our results raise doubts about the relevance of indirect comparisons as a decision-making tool, and provide empirical support for the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach for NMAs, which considers the certainty of evidence for all direct, indirect and NMA estimates between interventions included in the network, 30 and downgrades certainty of the evidence in case of absence of direct comparisons. In the case of antidepressants for major depressive disorder, achieving a precise classification of antidepressants is challenging. Only 18% of the clinical trials were rated by Cipriani et al as having a low risk of bias. 11 Our multiverse analysis suggests that the inclusion of different treatments in the network adds even more uncertainty and that particular caution should be exercised when ranking treatments.

Unanswered questions and future research

In this multiverse analysis, we explored the VoE arising from the treatment selection in a large NMA on 21 antidepressants and placebo in the treatment of major depressive disorders. We found substantial variations in the magnitude, direction and statistical significance of the effects estimated. These findings suggest that when conducting NMAs on RCTs, the selection of treatments to be included in the network could have considerable consequences on treatment effect estimations. More comprehensive studies on VoE across the medical literature are needed to gain better understanding of these reproducibility issues and to define safeguards to limit their impact on clinical decision-making.

Ethics statements

Patient consent for publication.

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Ethics approval

Acknowledgments.

We thank Angela Verdier for revising the English, and Karima Hammas for her help for the protocol. We would like to express our gratitude to the FABrique du Loch for granting us access to a calculation server, which has contributed to our efforts to reduce computation time.

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X @NaudetFlorian

Contributors CP initiated and designed the study. FN initiated and designed the study, interpreted the results and drafted the manuscript. CV cleaned the data, performed the analysis, interpreted the results and drafted the manuscript. AS contributed to the data analysis. All authors have critically revised the manuscript for important intellectual content and approved the manuscript. FN acts as guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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