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Know How to Structure Your PhD Thesis

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In your academic career, few projects are more important than your PhD thesis. Unfortunately, many university professors and advisors assume that their students know how to structure a PhD. Books have literally been written on the subject, but there’s no need to read a book in order to know about PhD thesis paper format and structure. With that said, however, it’s important to understand that your PhD thesis format requirement may not be the same as another student’s. The bottom line is that how to structure a PhD thesis often depends on your university and department guidelines.

But, let’s take a look at a general PhD thesis format. We’ll look at the main sections, and how to connect them to each other. We’ll also examine different hints and tips for each of the sections. As you read through this toolkit, compare it to published PhD theses in your area of study to see how a real-life example looks.

Main Sections of a PhD Thesis

In almost every PhD thesis or dissertation, there are standard sections. Of course, some of these may differ, depending on your university or department requirements, as well as your topic of study, but this will give you a good idea of the basic components of a PhD thesis format.

• Abstract : The abstract is a brief summary that quickly outlines your research, touches on each of the main sections of your thesis, and clearly outlines your contribution to the field by way of your PhD thesis. Even though the abstract is very short, similar to what you’ve seen in published research articles, its impact shouldn’t be underestimated. The abstract is there to answer the most important question to the reviewer. “Why is this important?”
• Introduction : In this section, you help the reviewer understand your entire dissertation, including what your paper is about, why it’s important to the field, a brief description of your methodology, and how your research and the thesis are laid out. Think of your introduction as an expansion of your abstract.
• Literature Review : Within the literature review, you are making a case for your new research by telling the story of the work that’s already been done. You’ll cover a bit about the history of the topic at hand, and how your study fits into the present and future.
• Theory Framework : Here, you explain assumptions related to your study. Here you’re explaining to the review what theoretical concepts you might have used in your research, how it relates to existing knowledge and ideas.
• Methods : This section of a PhD thesis is typically the most detailed and descriptive, depending of course on your research design. Here you’ll discuss the specific techniques you used to get the information you were looking for, in addition to how those methods are relevant and appropriate, as well as how you specifically used each method described.
• Results : Here you present your empirical findings. This section is sometimes also called the “empiracles” chapter. This section is usually pretty straightforward and technical, and full of details. Don’t shortcut this chapter.
• Discussion : This can be a tricky chapter, because it’s where you want to show the reviewer that you know what you’re talking about. You need to speak as a PhD versus a student. The discussion chapter is similar to the empirical/results chapter, but you’re building on those results to push the new information that you learned, prior to making your conclusion.
• Conclusion : Here, you take a step back and reflect on what your original goals and intentions for the research were. You’ll outline them in context of your new findings and expertise.

Tips for your PhD Thesis Format

As you put together your PhD thesis, it’s easy to get a little overwhelmed. Here are some tips that might keep you on track.

• Don’t try to write your PhD as a first-draft. Every great masterwork has typically been edited, and edited, and…edited.
• Work with your thesis supervisor to plan the structure and format of your PhD thesis. Be prepared to rewrite each section, as you work out rough drafts. Don’t get discouraged by this process. It’s typical.
• Make your writing interesting. Academic writing has a reputation of being very dry.
• You don’t have to necessarily work on the chapters and sections outlined above in chronological order. Work on each section as things come up, and while your work on that section is relevant to what you’re doing.
• Don’t rush things. Write a first draft, and leave it for a few days, so you can come back to it with a more critical take. Look at it objectively and carefully grammatical errors, clarity, logic and flow.
• Know what style your references need to be in, and utilize tools out there to organize them in the required format.
• It’s easier to accidentally plagiarize than you think. Make sure you’re referencing appropriately, and check your document for inadvertent plagiarism throughout your writing process.

PhD Thesis Editing Plus

Want some support during your PhD writing process? Our PhD Thesis Editing Plus service includes extensive and detailed editing of your thesis to improve the flow and quality of your writing. Unlimited editing support for guaranteed results. Learn more here , and get started today!

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How to write the perfect design dissertation

Tutors and students from top design colleges share their advice.

Studying design is about crafting a great design portfolio that will wow potential employers, right? Well, yes. But don't discount the importance of astute creative thinking, and expressing yourself eloquently through the written word. In short, your design dissertation matters.

"I don't believe that design students should be focused entirely on portfolio work," argues Myrna MacLeod , programme leader for Graphic Design at Edinburgh Napier University. "They should also be able to demonstrate an interest in the contexts that underpin their work, and the histories and connections that have informed our practice."

• 5 top tips for graduate designers

"Think of a dissertation as an opportunity, not a burden," urges Craig Burston , Graphic and Media Design course leader at London College of Communication (LCC). "It gives us visually-minded people an opportunity to demonstrate that we too can construct arguments and distil complex notions." 

As Burston points out, this is not just an academic exercise: the power of persuasion is often key to success as a commercial designer. "Clients seek clarity, and project concepts or proposals need to be put into context," he says.

Read on to discover some top tips from leading tutors and their students for nailing your design dissertation…

01. Treat it like a design brief

"A great dissertation should be a designed artefact, and portfolio-worthy in its own right," says Burston. And like a design brief, it should be about solving a problem: "Make sure it has clearly stated aims, strong focus, and doesn't lack opinion or rhetoric," he adds.

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"The value of a designed dissertation as a portfolio piece is that it's a holistic view of the individual," agrees Sarah James , senior lecturer in Visual Communication at Arts University Bournemouth (AUB). 

"It shows, type, editorial, research and aesthetic skill, as well as the personal interests and convictions of the individual."

James identifies AUB student Maarit Koobas , who investigated responsive type in both her dissertation and final project, as a particularly strong example of this. "Her design version was one of the most authentic, restrained and elegantly expressive I have ever received," she enthuses.

Koobas conducted a huge amount of initial research into both the contexts in which responsive type can be seen – such as advertising, product design, science and material cultures – and the theories behind its analysis, including semiotics, philosophy and politics. "Creating and analysing ideas, before they end up in your portfolio, is what design is all about," argues Koobas.

• 5 must-read books for design students

02. Write about your passion

"To develop essay questions, AUB students are asked to consider what they love, hate or are puzzled by in their practice – essentially, what moves them," says James. 

"A poor dissertation is inauthentically chosen for ease as opposed to interest," she adds. "It rambles and blusters, using complex language to mask insufficient research." 

"You can tell a mile off when the writer isn't interested," agrees Burston. "How can you expect the reader to care about it if you don't? Write about something that reflects your interests, focus and direction. I've read fascinating dissertations on topics as diverse as patterns in nature, and Brutalist car parks. Make me interested in what interests you."

For Edinburgh Napier graduate Fiona Winchester , this topic turned out to be typography in graphic novels. "I love reading them, but I think people still don't take them seriously as an art form, which is a shame," she says. For her dissertation, she conducted qualitative interviews using modified pages with and without imagery (shown above). 

Her advice is simple: "Narrow down your idea to be as precise as possible. The smaller your question, the easier it is to research and try to answer it."

If you're struggling to get the ball rolling on the actual writing process, Winchester advocates starting with whichever bit you have ideas for. "If you're stuck, it's so much easier to write in whatever order it comes to you, and then edit it into a dissertation, than to try write straight through from beginning to end," she insists.

03. Don't be afraid to talk to people

"I always think my students get the most out of the new streams of knowledge they find from talking to people," says McLeod. "It breaks down barriers and allows them to find answers to problems. Hopefully they will adopt that approach when designing for people also."

In some cases, this can involve interviewing your design heroes. "Students are very surprised when they send a question to Stefan Sagmeister , Milton Glaser or Michael Wolff and they reply with the most precious nugget of knowledge," smiles McLeod. 

But remember: it's your dissertation, so don't get lazy and expect your interview subject to do all the heavy lifting.

In other cases, it could be as simple as asking friends or family to help proofread. "It is quite daunting writing such a large body of text," admits Kaori Toh , a recent graduate from Central Saint Martins, whose dissertation explored the politics of design and technology.

"I often felt I'd get lost in all that text and research," she confesses. "Therefore, I would often send my drafts to a couple of friends to have them look through, and keep my writing cohesive."

04. Reflect on your design practice 

Most of all, dissertations are an opportunity to reflect on, and develop, your creative process as a designer. "Ultimately, it's your job to make your work relevant and credible, and the dissertation helps you learn how to do this," adds Burston. 

Of course, writing doesn't always come easily to visually minded people – and Burston highlights the fact that dyslexia is not uncommon amongst designers. 

"You're not on your own – in our profession, quite the opposite in fact – so do seek academic support, and just enjoy thinking and writing about 'stuff' that informs your practice," is his advice.

One of Burston's stand-out students from this year, Tom Baber , welcomed support from the university to help with his dyslexia. Baber's dissertation focused on type design, and particularly the extent to which the longwinded design process is worth the effort, compared to using an existing typeface.

"I saw it as an opportunity to approach other type designers and see what they thought. Turns out I'm not the first to ask the question," he smiles. "Writing my dissertation helped me change from a 'maker' mentality to a 'designer' mentality, and be more critical of my ideas."

Related articles:

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• A Guide to Writing a PhD Thesis

Written by Ben Taylor

A PhD thesis is a work of original research all students are requiured to submit in order to succesfully complete their PhD. The thesis details the research that you carried out during the course of your doctoral degree and highlights the outcomes and conclusions reached.

The PhD thesis is the most important part of a doctoral research degree: the culmination of three or four years of full-time work towards producing an original contribution to your academic field.

Your PhD dissertation can therefore seem like quite a daunting possibility, with a hefty word count, the pressure of writing something new and, of course, the prospect of defending it at a viva once you’ve finished.

This page will give you an introduction to what you need to know about the doctoral thesis, with advice on structure, feedback, submission and more.

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Beginning your PhD thesis

The first stage of your PhD thesis will usually be the literature review . We’ve already written a detailed guide to what the PhD literature review involves , but here’s what you need to know about this stage of your PhD:

• The literature review is a chance for you to display your knowledge and understanding of what’s already been written about your research area – this could consist of papers, articles, books, data and more
• Rather than simply summarising what other scholars have said about your subject, you should aim to assess and analyse their arguments
• The literature review is usually the first task of your PhD – and typically forms the first part or chapter of your dissertation

After finishing your literature review, you’ll move onto the bulk of your doctoral thesis. Of course, you’ll eventually return to the lit review to make sure it’s up-to-date and contains any additional material you may have come across during the course of your research.

PhD thesis research

What sets your PhD thesis apart from previous university work you’ve done is the fact that it should represent an original contribution to academic knowledge . The form that this original contribution takes will largely depend on your discipline.

• Arts and Humanities dissertations usually involve investigating different texts, sources and theoretical frameworks
• Social Sciences are more likely to focus on qualitive or quantitative surveys and case studies
• STEM subjects involve designing, recording and analysing experiments, using their data to prove or disprove a set theory

Depending on the nature of your research, you may ‘write up’ your findings as you go, or leave it until the dedicated ‘writing-up’ period, usually in the third year of your PhD. Whatever your approach, it’s vital to keep detailed notes of your sources and methods – it’ll make your life a lot easier when it comes to using references in your dissertation further down the line.

PhD thesis vs dissertation

It’s common to use the terms ‘thesis’ and ‘dissertation’ interchangeably, but strictly speaking there is a difference in meaning between them:

• Your thesis is your argument. It’s the conclusions you’ve arrived at through surveying existing scholarship in your literature review and combining this with the results of your own original research.
• Your dissertation is the written statement of your thesis. This is where you lay out your findings in a way that systematically demonstrates and proves your conclusion.

Put simply, you submit a dissertation, but it’s the thesis it attempts to prove that will form the basis of your PhD.

What this also means is that the writing up of your dissertation generally follows the formulation of your doctoral thesis (it’s fairly difficult to write up a PhD before you know what you want to say!).

However, it’s normal for universities and academics to use either (or both) terms when describing PhD research – indeed, we use both ‘thesis’ and ‘dissertation’ across our website.

Can I use my Masters research in my PhD thesis?

If you’re studying an MPhil, it’s normal to ‘ upgrade ’ it into a PhD. Find mroe information on our guide.

PhD thesis structure

Having completed your initial literature review and conducted your original research, you’ll move onto the next phase of your doctoral dissertation, beginning to sketch out a plan that your thesis will follow.

The exact structure and make-up of your doctoral thesis will vary between fields, but this is the general template that many dissertations follow:

• Introduction – This sets out the key objectives of your project, why the work is significant and what its original contribution to knowledge is. At this point you may also summarise the remaining chapters, offering an abstract of the argument you will go on to develop.
• Literature review – The introduction will generally lead into a write-up of your literature review. Here you’ll outline the scholarly context for your project. You’ll acknowledge where existing research has shaped your PhD, but emphasise the unique nature of your work.
• Chapters – After you’ve finished introducing your research, you’ll begin the bulk of the dissertation. This will summarise your results and begin explaining the argument you have based on them. Some PhDs will also include specific chapters on methodology and / or a recreation of the data you have developed. Others will develop your argument over a series of stages, drawing on sources and results as relevant.
• Conclusion – The dissertation will end with a final chapter that pulls together the different elements of your argument and the evidence you have provided for it. You’ll restate the significance of your project (and its all-important original contribution to knowledge). You may also take the opportunity to acknowledge the potential for further work or opportunities to apply your findings outside academia.
• Bibliography and appendices – At the end of your thesis, you’ll need to include a full list of the books, articles and data you’ve referenced in a bibliography. You may also need to provide additional information in the form of an appendix.

How long is a PhD thesis?

The length of a PhD thesis varies from subject to subject, but all are far longer than those for undergraduate or Masters degrees. Your university will usually set an upper limit – typically between 70,000 and 100,000 words, with most dissertations coming in at around 80,000 words.

Generally speaking, STEM-based theses will be a little shorter than those in the Arts, Humanities and Social Sciences.

Different universities (and departments) will have different policies regarding what counts towards the PhD thesis word count, so make sure you’re aware what is expected of you. Check with your supervisor whether references, the bibliography or appendices are included in the word count for your dissertation.

How many chapters should a PhD thesis have?

There’s no hard and fast rule for the numbers of chapters in a PhD thesis, but most will have four or five chapters (in addition to the introduction and conclusion). This is the sort of thing you’ll discuss with your supervisor when planning out your research.

Writing up your PhD thesis

Once you’ve conducted your research and settled upon your thesis, there’s only one thing left to do: get it down on paper. Appropriately enough, this final part of a PhD is often referred to as the ‘ writing up period ’.

This is when you produce the final dissertation, which will be submitted as the basis for your viva voce exam. The nature of this task can vary from PhD to PhD.

In some cases you may already have a large amount of chapter drafts and other material. ‘Writing up’ therefore becomes a process of re-drafting and assembling this work into a final dissertation. This approach is common in Arts and Humanities subjects where PhD students tend to work through stages of a project, writing as they go.

Alternatively, you may have spent most of your PhD collecting and analysing data. If so, you’ll now ‘write up’ your findings and conclusions in order to produce your final dissertation. This approach is more common in STEM subjects, where experiment design and data collection are much more resource intensive.

Whatever process you adopt, you’ll now produce a persuasive and coherent statement of your argument, ready to submit for examination.

PhD thesis feedback

Your supervisor will usually give you feedback on each chapter draft, and then feedback on the overall completed dissertation draft before you submit it for examination. When the thesis is a work-in-progress, their comments will be a chance for them to make sure your research is going in the right direction and for you to ask their advice on anything you’re concerned about. This feedback will normally be given in the form of a supervisory meeting.

Although your PhD supervisor will be happy to give you advice on your work, you shouldn’t expect them to be an editor – it’s not their responsibility to correct grammatical or spelling mistakes, and you should make sure any drafts you submit to them are as error-free as possible. Similarly, they won’t be willing to edit your work down to fit a particular word count.

Finishing your PhD thesis

When you’ve finished the final draft of your doctoral thesis and it’s been approved by your supervisor, you’ll submit it for examination. This is when it’s sent to the examiners who will conduct your viva.

Submitting your thesis involves printing enough copies for your examiners and the university’s repository. Don’t leave this until the last minute – printing multiple copies of a 300-page document is a substantial undertaking and you should always allow enough time to account for any possible glitches or issues with the printing process.

Your viva will usually take place within three months of submitting your thesis. You can find out more in our dedicated guide to the PhD viva . After your viva, your examiners will give you a report that confirms whether or not you need to make any changes to your thesis, with several different potential outcomes:

• Pass – You’ve received your doctoral qualification!
• Minor corrections – These are usually fairly small edits, tweaks and improvements to your thesis, which you’ll be given three months to implement
• Major corrections – For these substantial changes, you may have to rewrite part of your dissertation or complete extra research, with a six-month deadline

Most PhD students will need to fix some corrections with their thesis (hopefully not major ones). It’s very rare for a dissertation to be failed.

Once you’ve made any necessary changes to your thesis, you’ll submit it one last time (usually electronically).

If you have plans to publish all or part of your work, you may want to request an embargo so that it won’t be visible to the public for a certain time. 12 months is a fairly standard time period for this, although you may want to ask for a longer embargo if you know that you want to turn your thesis into a book or monograph.

Take a look at our programme listings and find the perfect PhD for you.

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The PhD is the most common variety of doctorate, but others are awarded in specific disciplines or sometimes particular countries.

Joint PhD programmes involve collaboration between two (or more) different universities. So how does that work? Who can apply? And what are the advantages (and disadvantages) of researching in this way?

Integrated PhD programmes consist of a one-year Masters followed by three years of PhD research. Find out more about what it's like to study an integrated PhD, how to apply and the funding options available.

Thinking of applying for the Doctor of Engineering (EngD)? Our guide covers everything you need to know about the qualification, including costs, applications, programme content, and how it differs from a PhD.

A PhD isn't the only option for postgraduate researchers. Our guides explain professional doctorates, joint degrees and compare other qualification types.

How does the value of an MPhil compare with a PhD, and why might you choose the Masters over the doctorate?

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Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.

By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019

So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.

To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .

*The Caveat *

In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).

So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.  

Overview: S tructuring a dissertation or thesis

• Acknowledgements page
• Abstract (or executive summary)
• Table of contents , list of figures and tables
• Chapter 1: Introduction
• Chapter 2: Literature review
• Chapter 3: Methodology
• Chapter 4: Results
• Chapter 5: Discussion
• Chapter 6: Conclusion
• Reference list

As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:

• The introduction chapter presents the core research question and aims .
• The literature review chapter assesses what the current research says about this question.
• The methodology, results and discussion chapters go about undertaking new research about this question.
• The conclusion chapter (attempts to) answer the core research question .

In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.

To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.

Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.

The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:

• Succinct (not overly lengthy or verbose)
• Specific (not vague or ambiguous)
• Representative of the research you’re undertaking (clearly linked to your research questions)

Typically, a good title includes mention of the following:

• The broader area of the research (i.e. the overarching topic)
• The specific focus of your research (i.e. your specific context)
• Indication of research design (e.g. quantitative , qualitative , or  mixed methods ).

For example:

A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].

Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).

Acknowledgements

This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.

So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:

• Your dissertation supervisor or committee.
• Any professors, lecturers or academics that helped you understand the topic or methodologies.
• Any tutors, mentors or advisors.
• Your family and friends, especially spouse (for adult learners studying part-time).

There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.

Abstract or executive summary

The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .

For it to stand alone, your abstract should cover the following key points (at a minimum):

• Your research questions and aims – what key question(s) did your research aim to answer?
• Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
• Your findings – following your own research, what did do you discover?
• Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?

So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.

In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .

Need a helping hand?

Table of contents

This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:

If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.

Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…

It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:

• What will you be investigating (in plain-language, big picture-level)?
• Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
• What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
• What is the scope of your study? In other words, what will and won’t you cover ?
• How will you approach your research? In other words, what methodology will you adopt?
• How will you structure your dissertation? What are the core chapters and what will you do in each of them?

These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.

If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.

Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:

• What does the literature currently say about the topic you’re investigating?
• Is the literature lacking or well established? Is it divided or in disagreement?
• How does your research fit into the bigger picture?
• How does your research contribute something original?
• How does the methodology of previous studies help you develop your own?

Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.

Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.

Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…

In this chapter, you need to address two critical questions:

• Exactly HOW will you carry out your research (i.e. what is your intended research design)?
• Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?

Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.

Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.

In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!

You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.

Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.

Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).

What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.

Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.

The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).

Next, you’ll typically discuss the implications of your findings . In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?

Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!

This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.

The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.

It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:

Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.

The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.

Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!

Time to recap…

And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:

• Acknowledgments page

Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).

I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the  Grad Coach Blog .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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36 Comments

many thanks i found it very useful

Glad to hear that, Arun. Good luck writing your dissertation.

Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!

what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much

Thanks so much this helped me a lot!

Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.

Thanks Ade!

Thank you so much sir.. It was really helpful..

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

You’re most welcome. Good luck with your dissertation.

best ever benefit i got on right time thank you

Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .

I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these

You have given immense clarity from start to end.

Morning. Where will I write the definitions of what I’m referring to in my report?

Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!

Thanks ! so concise and valuable

This was very helpful. Clear and concise. I know exactly what to do now.

Thank you for allowing me to go through briefly. I hope to find time to continue.

Really useful to me. Thanks a thousand times

Very interesting! It will definitely set me and many more for success. highly recommended.

Thank you soo much sir, for the opportunity to express my skills

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!

Do we need to mention the number of words the dissertation contains in the main document?

It depends on your university’s requirements, so it would be best to check with them 🙂

Such a helpful post to help me get started with structuring my masters dissertation, thank you!

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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How to Design and Defend a PhD Thesis

In 1996, I was an Erasmus student at the  University of Jyväskylä  in  Finland , coming from the  University of Porto  in Portugal. In 1997, I moved to Sao Paulo in Brazil to establish a subsidiary for a Finnish multinational. In 1999, I returned to the University of Jyväskylä to make a PhD on eleven Finnish multinationals in Portugal.

In 2004, I defended my PhD thesis and the jury from the  University of Uppsala  in Sweden praised the methodological chapter as their favourite. In the same year, I started teaching methodology at the  University of Vaasa  in Finland and in national courses of Kataja, the Finnish doctoral program of business studies.

Find PhD programmes

Discovering new theories for developing the PhD research

In 2005, I returned to Portugal as a senior researcher of  INESC Porto , a centre of excellence in information technologies. Although my primary duty was research, I also received several invitations from universities to teach methodology as a guest lecturer.

Some classes combined students from different postgraduate programmes giving me the opportunity to teach students of social sciences, mathematics, engineering, design, and architecture, among others.

Such interdisciplinary context inspired me to develop a new approach to research design which could be applied to any field of knowledge. The result was an analytical framework of 21 decisions which integrates theory, method, data, rhetoric, and authorship.

In 2008, I created an online platform in order to disseminate this new approach to research design globally. I also created the seminar ‘How to design and defend your PhD’ which has had 146 editions in 10 countries, and is annually offered by the European Institute for Advanced Studies in Management in Brussels.

Creating an online e-book dedicated to PhD candidates

In 2009, I created the Idea Puzzle® software, an online e-book that helps PhD candidates create a research design with 21 decisions. The software is recommended by Sage Publications and licensed to several universities in The Times Higher Education Top 400. The ebook is updated regularly based on feedback from users in 86 countries.

Meanwhile, recent studies in Australia, Canada, United Kingdom, and the United States confirmed a rumour that I used to hear in my seminars abroad: about 50% of doctoral students are unable to complete their PhD. Such low PhD completion rates constitute a global paradox because international institutions such as OECD recommend countries to maximize the number of ‘new doctorate graduates’.

The main factor associated with such low PhD completion rates is lack of time. I believe, however, that lack of time tends to be a consequence of lack of focus in research design. Such lack of focus reflects, in turn, three types of ambiguity to which PhD candidates are exposed: research ambiguity, philosophical ambiguity, and methodological ambiguity.

Research ambiguity results from the dominant view in methodology books that research is a sequence of tasks such as literature review, data collection, and data analysis. I followed such a process view of research in my own PhD and the consequences were disastrous.

After one year of exclusive work on my literature review, I was forced to change my topic due to the lack of data. I suggest, therefore, that the process view of research focused on tasks be complemented with a systemic view of research focused on decisions.

The task literature review, for instance, can be complemented with explicit decisions on which keywords, streams of thought, research gap, and research question focus on. These decisions, in turn, are part of a larger system of theoretical, methodological, empirical, rhetoric, and authorial decisions which define the research design.

How to reduce research ambiguity for your PhD?

In other words, decisions help PhD candidates focus their research design on a sample of theory, method, data, rhetoric, and authorship, whereas the dominant view of research as a process does not emphasise content and focus at all.

In addition to research ambiguity, PhD candidates have to cope with philosophical ambiguity. The proliferation of “isms” such as positivism, postpositivism, realism, constructivism, and constructionism, dissuades PhD candidates from explicitly positioning their research design in the light of philosophy of science.

In order to reduce such philosophical ambiguity, I have developed a synthesis of four philosophical stances based on two dimensions: discovery or justification, of facts or values. The resulting stances – objective discovery, subjective discovery, objective justification, and subjective justification – introduce PhD candidates to the importance of designing research which is consistent in terms of ontology, epistemology, methodology, and axiology.

Finally, PhD candidates need to overcome methodological ambiguity, that is, the endless debate about qualitative versus quantitative research. In this respect, I agree with authors who claim that no research strategy is perfect in the sense that it cannot maximize simultaneously deep description and broad measurement of phenomena.

I, therefore, suggest a list of fifteen alternative research strategies, qualitative and quantitative, which alert PhD candidates to the importance of knowing the strengths and weaknesses of each research strategy before choosing the one that better fits their research design.

Get a new approach on your research thesis

In sum, designing and defending a PhD thesis requires a new approach to research design which is available at  www.ideapuzzle.com  and applies to any field of knowledge. This new approach helps PhD candidates overcome research, philosophical, and methodological ambiguity with 21 decisions. The result is a focused research design that reduces the uncertainty of a PhD and the risk of not completing it.

Ready to start your  international PhD  experience?

About the author

Ricardo Morais is Professor of Management and Strategy at Catholic University of Portugal and methodological lecturer at the European Institute for Advanced Studies in Management. He holds a PhD in Strategic Management from the University of Jyväskylä (first Portuguese PhD in Finland in Social Sciences), having graduated in Management from the University of Porto.

He specialises in strategic management of research and internationalisation. Since 2002, he has lectured these topics in 10 countries and published about scientific method (Sage Publications), critical realism (Edward Elgar), doctoral paradox (Emerald) and multinational management (Elsevier).

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PhD Dissertation Defense Slides Design: Start

• Tips for designing the slides
• Presentation checklist
• Example slides
• Additional Resources

Purpose of the Guide

This guide was created to help ph.d. students in engineering fields to design dissertation defense presentations. the guide provides 1) tips on how to effectively communicate research, and 2) full presentation examples from ph.d. graduates. the tips on designing effective slides are not restricted to dissertation defense presentations; they can be used in designing other types of presentations such as conference talks, qualification and proposal exams, and technical seminars., the tips and examples are used to help students to design effective presentation. the technical contents in all examples are subject to copyright, please do not replicate. , if you need help in designing your presentation, please contact julie chen ([email protected]) for individual consultation. .

• Example Slides Repository
• Defense slides examples Link to examples dissertation defense slides.

Useful Links

• CIT Thesis and dissertation standards
• Dissertations and Theses @ Carnegie Mellon This link opens in a new window Covers 1920-present. Full text of some dissertations may be available 1997-present. Citations and abstracts of dissertations and theses CMU graduate students have published through UMI Dissertation Publishing. In addition to citations and abstracts, the service provides free access to 24 page previews and the full text in PDF format, when available. In most cases, this will be works published in 1997 forward.
• Communicate your research data Data visualization is very important in communicating your data effectively. Check out these do's and don'ts for designing figures.

Power Point Template and other Resources

• CEE Powerpoint Slide Presentation Template 1
• CEE Powerpoint Slide Presentation Template 2

Source: CEE Department Resources https://www.cmu.edu/cee/resources/index.html

• CMU Powerpoint Slide Template

Source: CMU Marketing and Communications

https://www.cmu.edu/marcom/brand-standards/downloads/index.html

• Use of CMU logos, marks, and Unitmarks

Email me for questions and schedule an appointment

Top 7 tips for your defense presentation

1. show why your study is important, remember, your audience is your committee members, researchers in other fields, and even the general public. you want to convince all of them why you deserve a ph.d. degree. you need to talk about why your study is important to the world. in the engineering field, you also need to talk about how your study is useful. try to discuss why current practice is problematic or not good enough, what needs to be solved, and what the potential benefits will be. , see how dr. posen and dr. malings explained the importance of their studies..

• Carl Malings Defense Slides with Notes
• I. Daniel Posen Defense Slides with Notes

2. Emphasize YOUR contribution 

Having a ph.d. means that you have made some novel contributions to the grand field. this is about you and your research. you need to keep emphasizing your contributions throughout your presentation. after talking about what needs to be solved, try to focus on emphasizing the novelty of your work. what problems can be solved using your research outcomes what breakthroughs have you made to the field why are your methods and outcomes outstanding you need to incorporate answers to these questions in your presentation. , be clear what your contributions are in the introduction section; separate what was done by others and what was done by you. , 3. connect your projects into a whole piece of work, you might have been doing multiple projects that are not strongly connected. to figure out how to connect them into a whole piece, use visualizations such as flow charts to convince your audience. the two slides below are two examples. in the first slide, which was presented in the introduction section, the presenter used a flow diagram to show the connection between the three projects. in the second slide, the presenter used key figures and a unique color for each project to show the connection..

• Xiaoju Chen Defense Slides with Notes

4. Tell a good story 

The committee members do not necessarily have the same background knowledge as you. plus, there could be researchers from other fields and even the general public in the room. you want to make sure all of your audience can understand as much as possible. focus on the big picture rather than technical details; make sure you use simple language to explain your methods and results. your committee has read your dissertation before your defense, but others have not. , dr. cook and dr. velibeyoglu did a good job explaining their research to everyone. the introduction sessions in their presentations are well designed for this purpose. .

• Laren M. Cook Defense Slides with Notes
• Irem Velibeyoglu Defense with Notes

5. Transition, transition, transition

Use transition slides to connect projects , it's a long presentation with different research projects. you want to use some sort of transition to remind your audience what you have been talking about and what is next. you may use a slide that is designed for this purpose throughout your presentation. , below are two examples. these slides were presented after the introduction section. the presenters used the same slides and highlighted the items for project one to indicate that they were moving on to the first project. throughout the presentation, they used these slides and highlighted different sections to indicate how these projects fit into the whole dissertation. .

You can also use some other indications on your slides, but remember not to make your slides too busy.  Below are two examples. In the first example, the presenter used chapter numbers to indicate what he was talking about. In the second example, the presenter used a progress bar with keywords for each chapter as the indicator. 

Use transition sentences to connect slides 

Remember transition sentences are also important; use them to summarize what you have said and tell your audience what they will expect next. if you keep forgetting the transition sentence, write a note on your presentation. you can either write down a full sentence of what you want to say or some keywords., 6. be brief, put details in backup slides , you won't have time to explain all of the details. if your defense presentation is scheduled for 45 minutes, you can only spend around 10 minutes for each project - that's shorter than a normal research conference presentation focus on the big picture and leave details behind. you can put the details in your backup slides, so you might find them useful when your committee (and other members of the audience) ask questions regarding these details., 7. show your presentation to your advisor and colleagues, make sure to ask your advisor(s) for their comments. they might have a different view on what should be emphasized and what should be elaborated. , you also want to practice at least once in front of your colleagues. they can be your lab mates, people who work in your research group, and/or your friends. they do not have to be experts in your field. ask them to give you some feedback - their comments can be extremely helpful to improve your presentation. , below are some other tips and resources to design your defense presentation. .

• Tips for designing your defense presentation

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• Last Updated: Jan 9, 2024 11:18 AM
• URL: https://guides.library.cmu.edu/c.php?g=883178

How To Structure A PhD With Our PhD Writing Template

Feb 9, 2019

• Introduction

Our   PhD Writing Template   is a way to visualise every element of your PhD on one page.  Once you have filled it in you will have an overview of each section of the thesis and an executive summary of the thesis as a whole. It’ll show you how to write a PhD. If you haven’t already download it for free now and then come back to this post. 

What is the PhD Writing Template?

The PhD Writing Template is a   way for you to visualise your PhD on one page.   It guides you through creating a   synopsis for each chapter   and an overall   outline of the thesis   using simple questions to structure and guide your thinking.  If you haven’t already download it for free now .

• Acknowledgements
• Literature review
• Theoretical framework
• Methodology
• Empirical chapters
• Discussion chapters

How do I write a PhD using the template?

It’s simple to use.  First, print it out.

Then, answer each of the questions in each section.

Answer on Post-it notes. One for each box. That way you can change your answers over time.

But aren’t Post-it notes too small? No! Small is good here. It means you have to be clear and concise. If you can’t fit your answers onto a Post-it note, you need to refine them.

To save space, use bullet points, but make sure you carefully think about and respond to each point.

Start with the ‘Aims and Objectives’ box, where you will list down the core headlines of the entire thesis. This is the  big-picture stuff.  You   should have this completed and refined before you move on. Without solid answers to these questions, the thesis will be disjointed and unclear.

Then, work through the boxes one by one. You may want to leave the abstract and acknowledgements to last. You may also want to work on the introduction last. That’s fine. Work in the way that suits you.

As you fill the template in, you will start to see the bigger picture. Each Post-it note will contain a synopsis for that particular element. Together, they can be combined to form an executive summary of the thesis as a whole.

Why do you need the template?

• All of the elements required in a thesis.
• Where they fit and how they relate to one another. 

Blog Posts That Can Help You

Hello, doctor….

Sounds good, doesn’t it?  Be able to call yourself Doctor sooner with our five-star rated How to Write A PhD email-course. Learn everything your supervisor should have taught you about planning and completing a PhD.

Now half price. Join hundreds of other students and become a better thesis writer, or your money back. 

Share this:

Hi – sorry to hear you haven’t received it. Have you checked your spam folder? I tried to email it to you again but the email address you left when leaving the comment doesn’t appear to be working.

Thank you so much You are doing a great job by helping PhD students like me to make it less stressful.

Have a great day

Thanks so much.

Hi, I withdrew from my PhD in the final months and am now planning to return to it and remodel it somewhat. This template will be really useful for restructuring what I already have and planning what I need to work on. Thank-you!

Gave my email to get template. No template. *sigh

Hi – I’ve just checked on our end and all the emails were sent out. They may be sitting in a spam folder. Get in touch if you’re still without them. [email protected]

This looks like it’s going to save my life. Let’s see!!

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• Resources designed for non-native English speakers
• PhD Writing Template
• Explore our back-catalogue of motivational advice

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• PhD in Design

The first PhD in design program in the US, Institute of Design’s PhD is a top-rated graduate program for those seeking to teach or conduct fundamental research in the field. Our PhD alumni have gone on to lead noted design programs at universities all over the world and lead practices at global corporations.

By pursuing rigorous research in an area that aligns with work by our PhD faculty, you’ll work directly in some of the most exciting design-focused work being done today. To learn more about research at ID and our PhD in Design, complete this form .

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Carlos Teixeira

Charles L. Owen Professor of Systems Design and PhD Program Director

Degree Requirements

All PhD students will work closely with their advisors to plan their course of study and research. Students complete a total of 92 credit hours:

• Up to 32 credits can be transferred from a master’s program
• 12 course credits
• 48 research credits

Courses may be selected from across the university’s course offerings to complement the objectives of the student’s program.

Admitted doctoral students will be required to submit and obtain approval for a program of study. Within two years of being admitted, students take a comprehensive examination, after which, students will be considered candidates for the PhD degree.

The research component of the program grows as the student progresses. The dissertation created from this work is intended to create a substantial and original contribution to design knowledge.

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Phd principles & methods of design research, phd research and thesis, phd philosophical context of design research, student work, future archetypes of ev charging, exploring controlled environment agriculture, partnership with city clerk’s office aims to reform fines and fees, phd corporate partnership initiative.

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Jessica meharry, phd, associate professor, columbia college chicago, id’s phds make their mark, andré nogueira, co-founder and deputy director of the design laboratory at the harvard t.h. chan school of public health.

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• CAREER COLUMN
• 31 January 2020

Design your own doctoral project

• Jesko Becker 0

Jesko Becker is a doctoral candidate at the University of Freiburg in Germany.

You can also search for this author in PubMed   Google Scholar

Browsing for funded PhD positions on the Internet and beyond can be time-consuming and exhausting; the constellation of topic, supervisors and location must fit together to suit the individual candidate. Creating my own project from scratch allowed me to choose a topic, supervisor and location separately. But it is certainly not a path for everyone: self-doubt, setbacks and the risk of not getting enough support for your plans are inevitable. This undertaking also requires strong autonomy, determination and perseverance to overcome the initial obstacles alone.

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doi: https://doi.org/10.1038/d41586-020-00268-1

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Prize-Winning Thesis and Dissertation Examples

Published on September 9, 2022 by Tegan George . Revised on July 18, 2023.

It can be difficult to know where to start when writing your thesis or dissertation . One way to come up with some ideas or maybe even combat writer’s block is to check out previous work done by other students on a similar thesis or dissertation topic to yours.

This article collects a list of undergraduate, master’s, and PhD theses and dissertations that have won prizes for their high-quality research.

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Award-winning undergraduate theses, award-winning master’s theses, award-winning ph.d. dissertations, other interesting articles.

University : University of Pennsylvania Faculty : History Author : Suchait Kahlon Award : 2021 Hilary Conroy Prize for Best Honors Thesis in World History Title : “Abolition, Africans, and Abstraction: the Influence of the “Noble Savage” on British and French Antislavery Thought, 1787-1807”

University : Columbia University Faculty : History Author : Julien Saint Reiman Award : 2018 Charles A. Beard Senior Thesis Prize Title : “A Starving Man Helping Another Starving Man”: UNRRA, India, and the Genesis of Global Relief, 1943-1947

University: University College London Faculty: Geography Author: Anna Knowles-Smith Award:  2017 Royal Geographical Society Undergraduate Dissertation Prize Title:  Refugees and theatre: an exploration of the basis of self-representation

University: University of Washington Faculty:  Computer Science & Engineering Author: Nick J. Martindell Award: 2014 Best Senior Thesis Award Title:  DCDN: Distributed content delivery for the modern web

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University:  University of Edinburgh Faculty:  Informatics Author:  Christopher Sipola Award:  2018 Social Responsibility & Sustainability Dissertation Prize Title:  Summarizing electricity usage with a neural network

University:  University of Ottawa Faculty:  Education Author:  Matthew Brillinger Award:  2017 Commission on Graduate Studies in the Humanities Prize Title:  Educational Park Planning in Berkeley, California, 1965-1968

University:  University of Ottawa Faculty: Social Sciences Author:  Heather Martin Award:  2015 Joseph De Koninck Prize Title:  An Analysis of Sexual Assault Support Services for Women who have a Developmental Disability

University : University of Ottawa Faculty : Physics Author : Guillaume Thekkadath Award : 2017 Commission on Graduate Studies in the Sciences Prize Title : Joint measurements of complementary properties of quantum systems

University:  London School of Economics Faculty: International Development Author: Lajos Kossuth Award:  2016 Winner of the Prize for Best Overall Performance Title:  Shiny Happy People: A study of the effects income relative to a reference group exerts on life satisfaction

University : Stanford University Faculty : English Author : Nathan Wainstein Award : 2021 Alden Prize Title : “Unformed Art: Bad Writing in the Modernist Novel”

University : University of Massachusetts at Amherst Faculty : Molecular and Cellular Biology Author : Nils Pilotte Award : 2021 Byron Prize for Best Ph.D. Dissertation Title : “Improved Molecular Diagnostics for Soil-Transmitted Molecular Diagnostics for Soil-Transmitted Helminths”

University:  Utrecht University Faculty:  Linguistics Author:  Hans Rutger Bosker Award: 2014 AVT/Anéla Dissertation Prize Title:  The processing and evaluation of fluency in native and non-native speech

University: California Institute of Technology Faculty: Physics Author: Michael P. Mendenhall Award: 2015 Dissertation Award in Nuclear Physics Title: Measurement of the neutron beta decay asymmetry using ultracold neutrons

University:  Stanford University Faculty: Management Science and Engineering Author:  Shayan O. Gharan Award:  Doctoral Dissertation Award 2013 Title:   New Rounding Techniques for the Design and Analysis of Approximation Algorithms

University: University of Minnesota Faculty: Chemical Engineering Author: Eric A. Vandre Award:  2014 Andreas Acrivos Dissertation Award in Fluid Dynamics Title: Onset of Dynamics Wetting Failure: The Mechanics of High-speed Fluid Displacement

University: Erasmus University Rotterdam Faculty: Marketing Author: Ezgi Akpinar Award: McKinsey Marketing Dissertation Award 2014 Title: Consumer Information Sharing: Understanding Psychological Drivers of Social Transmission

University: University of Washington Faculty: Computer Science & Engineering Author: Keith N. Snavely Award:  2009 Doctoral Dissertation Award Title: Scene Reconstruction and Visualization from Internet Photo Collections

University:  University of Ottawa Faculty:  Social Work Author:  Susannah Taylor Award: 2018 Joseph De Koninck Prize Title:  Effacing and Obscuring Autonomy: the Effects of Structural Violence on the Transition to Adulthood of Street Involved Youth

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How do I formulate the research design for my PhD thesis?

The research design must be done correctly otherwise the dissertation will not be successful. But how do I create a suitable research design for my topic? How can I even know that my approach is appropriate? How can I be sure that I will gain the right insight? Question after question. Here are the answers.

What is the research design anyway and why do I need it?

The research design is a detailed and systematic description of all steps needed to answer the research question. It shows your way of discovering new knowledge and consists of many elements. It helps to have the design handy when you start to organize your project. The more detailed the better and the more concrete your design, the easier it will be to implement.

What belongs in the research design?

• The research question, detailed questions and possibly hypotheses, the design of YOUR research model with relevant variables and factors
• Methods of data collection such as interviews, surveys, observations, documentations, measurements etc.,
• Decisions on the type of data, data sources and description of the samples,
• Tools for data collection such as interview guidelines or questionnaires etc.,
• Methods and tools for data evaluation such as statistical methods, content analysis etc.,
• Timetable for implementation.

When and how do I develop the appropriate research design?

You start with the design already in the proposal. This is your first draft. Prerequisites for the research design are the subject, research question and goal. They are your compass. You also need models on the topic for the classification of your variables and thus of the data. Here is an example: digitization in SMEs. How is digitization evolving inside SMEs? Operationalized research question: Which concepts do SMEs use when digitizing their business processes? You can create case studies and conduct an expert survey. You need models on SMEs, digitization and business processes. These models contain players, data, processes, activities, regulations, IT system and much more. Then you can collect data on the concrete concepts the SMEs studies used for digitization.

How do I check the research design for completeness and correctness?

Your design must meet 3 requirements:

• The methodology must definitely work and it must lead to an insight. A good test is whether the methods have already worked in other studies. Completely new methods are risky.
• The data must be obtainable, in quality and scope.
• The aids must be able to produce good results.

How do I test the research design?

• Simulate your research process. Are these the right detailed questions or sub questions?
• Do the answers to the detailed questions close the gap in research? Have I defined the correct data?
• Does this data match the objects in the detailed questions? Do I have the right data sources?
• Are there perhaps still better sources than the one I already found? Can the methods be used to evaluate the collected data?
• Has anyone ever described this in an article?
• How do I structure and describe the research design in the text?

Describe the research design in the text as a separate chapter in your dissertation.

To do so, you should answer about 20 questions. Here are the first so-called micro questions:

• What exactly is analyzed? Who or what is the focus of the analysis?
• What is the aim of the analysis? What insight will be gained?
• Which methods can be used for the analysis?
• What are the decision criteria for choosing a method?
• Why am I using a particular method?

Additional micro questions can be found in the 200 Days Dissertation Guide. Answer all these questions and your research design will be ready!

What sources do I need for the research design?

The best papers are those that have dealt with a related question. The methods are described there but are usually not comprehensive so you will also need method books. However, maybe an article is good but quite old. Don’t worry because methods are quite timeless. Papers on other issues are also interesting for the design if they have used certain suitable methods.

Method books are useful when it comes to the description. They are also more general and not just focused on one case.

How can I tell that my research design is "complete"?

The design is complete when the questions in the chapter ‘Research Design’ are answered and your supervisor knows the procedure and considers it useful. Actually this question is only finally answered when you have collected and evaluated all the data. Until then, minor changes in your research design are still necessary.

How do I work with the research design?

Just go for it! That's it! Let's go! Good luck writing your text!

Silvio and the Aristolo Team

PS: Check out the PhD Guide for writing a PhD in 200 days .

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UCI Libraries maintains the following  templates to assist in formatting your graduate manuscript. If you are formatting your manuscript in Microsoft Word, feel free to download and use the template. If you would like to see what your manuscript should look like, PDFs have been provided. If you are formatting your manuscript using LaTex, UCI maintains a template on OverLeaf.

• Annotated Template (Dissertation) 2024 PDF of a template with annotations of what to look out for
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Free Templates

For your green thesis, the ease of word, 1. interior layout.

We believe sustainable design and printing should become the new standard. That is why we do everything in our power to make this possible. GreenThesis offers you a free Word template for your thesis layout, when you let us design your cover. With this template, you can easily create a sleek and minimalist layout yourself without spending capital. If you still need help, we can provide it at a reasonable rate.

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2. effortless cover .

We are happy to help you design a sustainable and/or vegan cover for your thesis. All our designs are made with the environment in mind. From a hand-painted design to a photo collage with digitally painted details, everything is possible. Feel free to contact  us to discuss the possibilities.

If you would like to make the cover file yourself, you can do so using the  free PhD thesis cover template  for Indesign. You then only have to change the spine thickness based on the number of pages in your thesis.

Save a tree, read it digitally

3. qr-postcards.

As a PhD student, you probably have a dozen or more PhD theses from former colleagues on your bookshelves that you’ve never read. As an eco-conscious company, we’d like to save all this needless paper and material. That’s why we also print QR postcards that can double as an invitation. People can simply scan the QR link and end up at your personal webpage on the GreenThesis site. Here, they will find a digital version of your thesis and all other necessary information regarding your defence. To design your QR-postcard yourself, simply use this  free QR-postcard Indesign template . Of course, if you don’t have the time or an Indesign license, we’d be happy to help you with the design.

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2023 Urban Design Thesis Prize: Saad Boujane’s “Dwellings, Paths, Places: Configurative Habitat in Casablanca, Morocco “

by Saad Boujane (MAUD ’23) — Recipient of the Urban Design Thesis Prize. The Modernist…

Peter Rowe , Faculty Advisor

Spring 2023

2023 Landscape Architecture AP Thesis Prize and 2023 Digital Design Prize: Sonia Sobrino Ralston’s “Uncommon Knowledge: Practices and Protocols for Environmental Information”

by Sonia Sobrino Ralston (MLA I AP ’23) — Recipient of the Landscape Architecture AP…

Rosalea Monacella , Faculty Advisor

2023 Design Studies Thesis Prize: Alaa Suliman Eltayeb Mohamed Hamid’s Ghostopia: Interrogating Colonial Legacies and A Manifesto for The Modernized Nile

by Alaa Suliman Eltayeb Mohamed Hamid (MDes ’23) — Recipient of the Design Studies Thesis…

Montserrat Bonvehi Rosich, Faculty Advisor

2023 Landscape Architecture Thesis Prize: Kevin Robishaw’s Manatees and Margaritas: Toward a Strange New Paradise

by Kevin Robishaw (MLA I ’23) — Recipient of the Landscape Architecture Thesis Prize.

Craig Douglas , Faculty Advisor

2023 Outstanding Design Engineering Project Award: Rebecca Brand and Caroline Fong’s Jua: Cultivating Digital Knowledge Networks for Smallholder Farmers

by Rebecca Brand (MDE ’23) and…

Jock Herron , Faculty Advisor

2023 James Templeton Kelley Prize: Deok Kyu Chung’s “Boundaries of Everyday: walls to voids, voids to solids, solids to walls”

by Deok Kyu Chung (MArch II ’23) — Recipient of the James Templeton Kelley Prize,…

Lyndon Neri and Rossana Hu, Faculty Advisors

2023 Landscape Architecture AP Thesis Prize: Celina Abba and Enrique Cavelier’s Plantation Futures: Foregrounding Lost Narratives

by Celina Abba (MLA I AP ’23) and Enrique…

2022 Landscape Architecture Thesis Prize: Liwei Shen’s “The Echoes of Sky River – Two Pre-modern and Modern Atmospheric Assemblages”

by Liwei Shen (MLA I ’22) — Recipient of the Landscape Architecture Thesis Prize. The…

Sergio Lopez-Pineiro, Faculty Advisor

Spring 2022

2022 James Templeton Kelley Prize: Isaac Henry Pollan’s “This Is Not A Firehouse”

by Isaac Henry Pollan (MArch I ’22) — Recipient of the James Templeton Kelley Prize,…

Sean Canty , Faculty Advisor

2022 Clifford Wong Prize in Housing Design: Brian Lee’s “People’s Park Complex: Repairing the Modern City”

by Brian Lee (MArch ’22) — Recipient of the 2021 Clifford Wong Prize in…

Grace La and Jenny French , Faculty Advisors

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The Savvy Scientist

Experiences of a London PhD student and beyond

Thesis Title: Examples and Suggestions from a PhD Grad

When you’re faced with writing up a thesis, choosing a title can often fall to the bottom of the priority list. After all, it’s only a few words. How hard can it be?!

In the grand scheme of things I agree that picking your thesis title shouldn’t warrant that much thought, however my own choice is one of the few regrets I have from my PhD . I therefore think there is value in spending some time considering the options available.

In this post I’ll guide you through how to write your own thesis title and share real-world examples. Although my focus is on the PhD thesis, I’ve also included plenty of thesis title examples for bachelor’s and master’s research projects too.

Hopefully by the end of the post you’ll feel ready to start crafting your own!

Why your thesis title is at least somewhat important

It sounds obvious but your thesis title is the first, and often only, interaction people will have with your thesis. For instance, hiring managers for jobs that you may wish to apply for in the future. Therefore you want to give a good sense of what your research involved from the title.

Many people will list the title of their thesis on their CV, at least for a while after graduating. All of the example titles I’ve shared below came from my repository of academic CVs . I’d say roughly 30% of all the academics on that page list their thesis title, which includes academics all the way up to full professor.

Your thesis title could therefore feature on your CV for your whole career, so it is probably worth a bit of thought!

My suggestions for choosing a good thesis title

• Make it descriptive of the research so it’s immediately obvious what it is about! Most universities will publish student theses online ( here’s mine! ) and they’re indexed so can be found via Google Scholar etc. Therefore give your thesis a descriptive title so that interested researchers can find it in the future.
• Don’t get lost in the detail . You want a descriptive title but avoid overly lengthy descriptions of experiments. Unless a certain analytical technique etc was central to your research, I’d suggest by default* to avoid having it in your title. Including certain techniques will make your title, and therefore research, look overly dated, which isn’t ideal for potential job applications after you graduate.
• The title should tie together the chapters of your thesis. A well-phrased title can do a good job of summarising the overall story of your thesis. Think about each of your research chapters and ensure that the title makes sense for each of them.
• Be strategic . Certain parts of your work you want to emphasise? Consider making them more prominent in your title. For instance, if you know you want to pivot to a slightly different research area or career path after your PhD, there may be alternative phrasings which describe your work just as well but could be better understood by those in the field you’re moving into. I utilised this a bit in my own title which we’ll come onto shortly.
• Do your own thing. Having just laid out some suggestions, do make sure you’re personally happy with the title. You get a lot of freedom to choose your title, so use it however you fancy. For example, I’ve known people to use puns in their title, so if that’s what you’re into don’t feel overly constrained.

*This doesn’t always hold true and certainly don’t take my advice if 1) listing something in your title could be a strategic move 2) you love the technique so much that you’re desperate to include it!

Thesis title examples

To help give you some ideas, here are some example thesis titles from Bachelors, Masters and PhD graduates. These all came from the academic CVs listed in my repository here .

Bachelor’s thesis title examples

Hysteresis and Avalanches Paul Jager , 2014 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

The bioenergetics of a marine ciliate, Mesodinium rubrum Holly Moeller , 2008 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Functional syntactic analysis of prepositional and causal constructions for a grammatical parser of Russian Ekaterina Kochmar , 2008 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

Master’s thesis title examples

Creation of an autonomous impulse response measurement system for rooms and transducers with different methods Guy-Bart Stan , 2000 – Bioengineering – Imperial Professor –  direct link to Guy-Bart’s bioengineering academic CV

Segmentation of Nerve Bundles and Ganglia in Spine MRI using Particle Filters Adrian Vasile Dalca , 2012 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

The detection of oil under ice by remote mode conversion of ultrasound Eric Yeatman , 1986 – Electronics – Imperial Professor and Head of Department –  direct link to Eric’s electronics academic CV

Ensemble-Based Learning for Morphological Analysis of German Ekaterina Kochmar , 2010 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

VARiD: A Variation Detection Framework for Color-Space and Letter-Space Platforms Adrian Vasile Dalca , 2010 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

Identification of a Writer’s Native Language by Error Analysis Ekaterina Kochmar , 2011 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

On the economic optimality of marine reserves when fishing damages habitat Holly Moeller , 2010 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Sensitivity Studies for the Time-Dependent CP Violation Measurement in B 0 → K S K S K S at the Belle II-Experiment Paul Jager , 2016 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

PhD thesis title examples

Spatio-temporal analysis of three-dimensional real-time ultrasound for quantification of ventricular function Esla Angelini  – Medicine – Imperial Senior Data Scientist –  direct link to Elsa’s medicine academic CV

The role and maintenance of diversity in a multi-partner mutualism: Trees and Ectomycorrhizal Fungi Holly Moeller , 2015 – Ecology & Marine Biology – UC Santa Barbara Assistant Professor –  direct link to Holly’s marine biology academic CV

Bayesian Gaussian processes for sequential prediction, optimisation and quadrature Michael Osborne , 2010 – Machine Learning – Oxford Full Professor –  direct link to Michael’s machine learning academic CV

Global analysis and synthesis of oscillations: a dissipativity approach Guy-Bart Stan , 2005 – Bioengineering – Imperial Professor –  direct link to Guy-Bart’s bioengineering academic CV

Coarse-grained modelling of DNA and DNA self-assembly Thomas Ouldridge , 2011– Bioengineering – Imperial College London Senior Lecturer / Associate Prof –  direct link to Thomas’ bioengineering academic CV

4D tomographic image reconstruction and parametric maps estimation: a model-based strategy for algorithm design using Bayesian inference in Probabilistic Graphical Models (PGM) Michele Scipioni , 2018– Biomedical Engineer – Harvard Postdoctoral Research Fellow –  direct link to Michele’s biomedical engineer academic CV

Error Detection in Content Word Combinations Ekaterina Kochmar , 2016 – Computer Science – University of Bath Lecturer Assistant Prof –  direct link to Ekaterina’s computer science academic CV

Genetic, Clinical and Population Priors for Brain Images Adrian Vasile Dalca , 2016 – Machine Learning for healthcare – Harvard Assistant Professor & MIT Research Scientist –  direct link to Adrian’s machine learning academic CV

Challenges and Opportunities of End-to-End Learning in Medical Image Classification Paul Jager , 2020 – Medical Imaging – DKFZ Head of ML Research Group –  direct link to Paul’s machine learning academic CV

K 2 NiF 4  materials as cathodes for intermediate temperature solid oxide fuel cells Ainara Aguadero , 2006 – Materials Science – Imperial Reader –  direct link to Ainara’s materials science academic CV

Applications of surface plasmons – microscopy and spatial light modulation Eric Yeatman , 1989 – Electronics – Imperial Professor and Head of Department –  direct link to Eric’s electronics academic CV

Geometric Algorithms for Objects in Motion Sorelle Friedler , 2010 – Computer science – Haverford College Associate Professor –  direct link to Sorelle’s computer science academic CV .

Geometrical models, constraints design, information extraction for pathological and healthy medical image Esla Angelini  – Medicine – Imperial Senior Data Scientist –  direct link to Elsa’s medicine academic CV

Why I regret my own choice of PhD thesis title

I should say from the outset that I assembled my thesis in quite a short space of time compared to most people. So I didn’t really spend particularly long on any one section, including the title.

However, my main supervisor even spelled out for me that once the title was submitted to the university it would be permanent. In other words: think wisely about your title.

What I started with

Initially I drafted the title as something like: Three dimensional correlative imaging for cartilage regeneration . Which I thought was nice, catchy and descriptive.

I decided to go for “correlative imaging” because, not only did it describe the experiments well, but it also sounded kind of technical and fitting of a potential pivot into AI. I’m pleased with that bit of the title.

What I ended up with

Before submitting the title to the university (required ahead of the viva), I asked my supervisors for their thoughts.

One of my well intentioned supervisors suggested that, given that my project didn’t involve verifying regenerative quality, I probably shouldn’t state cartilage regeneration . Instead, they suggested, I should state what I was experimenting on (the materials) rather than the overall goal of the research (aid cartilage regeneration efforts).

With this advice I dialled back my choice of wording and the thesis title I went with was:

Three dimensional correlative imaging for measurement of strain in cartilage and cartilage replacement materials

Reading it back now I’m reminder about how less I like it than my initial idea!

I put up basically no resistance to the supervisor’s choice, even though the title sounds so much more boring in my opinion. I just didn’t think much of it at the time. Furthermore, most of my PhD was actually in a technique which is four dimensional (looking at a series of 3D scans over time, hence 4D) which would have sounded way more sciency and fitting of a PhD.

What I wish I’d gone with

If I had the choice again, I’d have gone with:

Four-dimensional correlative imaging for cartilage regeneration

Which, would you believe it, is exactly what it states on my CV…

Does the thesis title really matter?

In all honesty, your choice of thesis title isn’t that important. If you come to regret it, as I do, it’s not the end of the world. There are much more important things in life to worry about.

If you decide at a later stage that you don’t like it you can always describe it in a way that you prefer. For instance, in my CV I describe my PhD as I’d have liked the title to be. I make no claim that it’s actually the title so consider it a bit of creative license.

Given that as your career progresses you may not even refer back to your thesis much, it’s really not worth stressing over. However, if you’re yet to finalise your thesis title I do still think it is worth a bit of thought and hopefully this article has provided some insights into how to choose a good thesis title.

My advice for developing a thesis title

• Draft the title early. Drafting it early can help give clarity for the overall message of your research. For instance, while you’re assembling the rest of your thesis you can check that the title encompasses the research chapters you’re included, and likewise that the research experiments you’re including fall within what the title describes. Drafting it early also gives more time you to think it over. As with everything: having a first draft is really important to iterate on.
• Look at some example titles . Such as those featured above!
• If you’re not sure about your title, ask a few other people what they think . But remember that you have the final say!

I hope this post has been useful for those of you are finalising your thesis and need to decide on a thesis title. If you’ve enjoyed this article and would like to hear about future content (and gain access to my free resource library!) you can subscribe for free here:

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UT Electronic Theses and Dissertations

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• Published: 06 July 2024

Efficacy of relational agents for loneliness across age groups: a systematic review and meta-analysis

• Sia Sha   ORCID: orcid.org/0009-0000-2027-1316 1 ,
• Kate Loveys 2 ,
• Pamela Qualter 3 ,
• Haoran Shi 1 ,
• Dario Krpan   ORCID: orcid.org/0000-0002-3420-4672 1 &
• Matteo Galizzi 1  

BMC Public Health volume  24 , Article number:  1802 ( 2024 ) Cite this article

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Loneliness is a serious public health concern. Although previous interventions have had some success in mitigating loneliness, the field is in search of novel, more effective, and more scalable solutions. Here, we focus on “relational agents”, a form of software agents that are increasingly powered by artificial intelligence and large language models (LLMs). We report on a systematic review and meta-analysis to investigate the impact of relational agents on loneliness across age groups.

In this systematic review and meta-analysis, we searched 11 databases including Ovid MEDLINE and Embase from inception to Sep 16, 2022. We included randomised controlled trials and non-randomised studies of interventions published in English across all age groups. These loneliness interventions, typically attempt to improve social skills, social support, social interaction, and maladaptive cognitions. Peer-reviewed journal articles, books, book chapters, Master’s and PhD theses, or conference papers were eligible for inclusion. Two reviewers independently screened studies, extracted data, and assessed risk of bias via the RoB 2 and ROBINS-I tools. We calculated pooled estimates of Hedge’s g in a random-effects meta-analysis and conducted sensitivity and sub-group analyses. We evaluated publication bias via funnel plots, Egger’s test, and a trim-and-fill algorithm.

Our search identified 3,935 records of which 14 met eligibility criteria and were included in our meta-analysis. Included studies comprised 286 participants with individual study sample sizes ranging from 4 to 42 participants ( x̄  = 20.43, s  = 11.58, x̃  = 20). We used a Bonferroni correction with α Bonferroni  = 0.05 / 4 = 0.0125 and applied Knapp-Hartung adjustments. Relational agents reduced loneliness significantly at an adjusted α Bonferroni ( g  = -0.552; 95% Knapp-Hartung CI, -0.877 to -0.226; P  = 0.003), which corresponds to a moderate reduction in loneliness.

Our results are currently the most comprehensive of their kind and provide promising evidence for the efficacy of relational agents. Relational agents are a promising technology that can alleviate loneliness in a scalable way and that can be a meaningful complement to other approaches. The advent of LLMs should boost their efficacy, and further research is needed to explore the optimal design and use of relational agents. Future research could also address shortcomings of current results, such as small sample sizes and high risk of bias. Particularly young audiences have been overlooked in past research.

Peer Review reports

Loneliness is a subjective experience that emerges when people feel that their social relationships are unsatisfactory [ 1 ]. For some people, loneliness is experienced when they want more people to interact with, but it is also often felt when one’s social relationships are not as fulfilling as one would like. Loneliness is not the same as social isolation (i.e., the objective lack of social interactions) but is often associated with it [ 2 ]. There is strong evidence of the risks associated with loneliness, including poorer physical health outcomes [ 3 ]. Loneliness also affects mental health and psychological wellbeing, with growing evidence that loneliness is associated with the onset of depression and other common mental health problems [ 4 ]. Crucially, poor health and wellbeing can, in turn, exacerbate loneliness, placing those who experience loneliness in a negative feedback loop [ 5 ]. Evidence for a wide range of health effects, therefore, has led scholars to propose that loneliness should be regarded as a public health priority. Governments have consequently looked to offer interventions for people reporting loneliness, and although evidence for intervention efficacy is increasing [ 6 ], the evidence base suffers from some gaps [ 7 ], and potentially effective interventions may lack scalability or fail to produce cost savings [ 8 ]. Governments therefore have developed an interest in digital interventions, such as mobile phone apps or virtual reality [ 9 ]. Yet despite their promise, the efficacy of digital interventions across recent systematic reviews and meta-analyses is mixed [ 10 ].

“Relational agents” are a technology that show promise for delivering loneliness interventions in a scalable and engaging manner. Relational agents are software agents that build relationships with users through their behaviours (e.g., personal conversation, play, empathy), and they may be embodied (e.g., take the shape of humans or animals) or lack embodiment (e.g., voice agents) [ 11 ]. Relational agents can be broadly separated into two types: social robotic agents (e.g., those that possess physical bodies made of carbon or steel), and app-based agents (e.g., those embedded in everyday hardware such as computers and smartphones). Relational agents increasingly employ artificial intelligence (AI) such as emotion recognition for enhanced interactions and large language models (LLMs) to generate highly tailored and relevant speech [ 12 ]. Relational agents may promote engagement with internet-based psychological interventions for loneliness because of the social engagement and presence that they provide [ 13 ]. Moreover, preliminary but promising evidence suggests that relational agents may reduce loneliness by directly providing companionship, and by serving as catalysts for social interaction [ 14 ]. Appendix E provides video links for relational agents.

There are three key reasons research and investment in relational agents are worthwhile. First, not everyone can socialise with other humans. Physical disability, for example, can impact mobility, which in turn can restrict opportunities for socialising, thus contributing to loneliness [ 15 ]. While interventions such as social visits can be effective to alleviate the loneliness of people with physical disabilities, these interventions are constrained: a person who is bedridden may wait for several days before his or her next visitation. Relational agents, on the other hand, can be an on-demand solution. Second, loneliness can be due to the feeling that one is not heard. This, for example, can occur when people do not feel comfortable sharing their secrets due to stigma, and there is indeed evidence that people prefer sharing some secrets with relational agents rather than humans [ 16 , 17 ]. Relational agents, then, are not just an intermediate solution: they are a separate class of intervention with a suitable audience. Here, one might raise the question of “understanding”: that is, whether AI can truly understand people’s self-disclosure. The answer is probably complex, but from a practical perspective it seems that the answer may not matter: people seem to benefit from relational agents as long as they feel they are understood and heard by them – irrespective of whether this is actually the case [ 18 ]. Third, both qualitative and quantitative metrics suggest that human–agent and human–human relationships may have some similar features at times [ 17 , 19 ]. For example, there is a vast literature on how people anthropomorphise machines, imbuing them with human-like traits, personalities, and motivations [ 20 , 21 , 22 ]. People often treat machines like other people, developing similar feelings for them such as pity and even love [ 23 ]. One participant said: “Yes, explicitly I will tell my Replika [relational agent] that I think he is wonderful, that he is fantastic and smart and helps me and makes me feel good about myself and that I enjoy our talks” [ 17 ].

Several scoping reviews have qualitatively summarised the efficacy of relational agents for loneliness [ 14 , 24 , 25 , 26 , 27 ]. Combined, these reviews concluded that some evidence for the efficacy of social robotic relational agents existed but that further work on app-based relational agents was needed. Additionally, one 2019 meta-analysis investigated a sub-set of social robotic relational agents (i.e., robotic pets), but failed to find significant results, most likely due to including only two studies [ 28 ]. Previous reviews, moreover, exclusively focused on elderly samples, and the literature is therefore in need of a comprehensive and up-to-date quantitative synthesis to evaluate the efficacy of relational agents to mitigate loneliness across all age groups.

We preregistered our methodology with PROSPERO: CRD42022359737. We have also made our full paper trail available on the Open Science Framework (OSF): https://osf.io/c6rdk/files/osfstorage . There, the reader can also find the full data set to reproduce the analyses.

Search strategy and selection criteria

In this systematic review and meta-analysis, we searched 11 databases from inception to Sep 16, 2022: Ovid MEDLINE, Ovid Embase, Ovid PsycINFO, Ovid Global Health, EBSCO CINAHL, Scopus, Web of Science, IEEE Xplore, ACM Digital Library, PROSPERO, and ProQuest Dissertations. We also manually searched the bibliographies of selected studies to identify additional papers. We searched titles and abstracts using a range of search terms such as lonel*, robot*, computer* agent*, and relation* agent*. Appendix A outlines the full search strategy.

We included randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs). Factorial designs were eligible if they allowed us to collapse relevant intervention arms or drop irrelevant ones. Cluster-randomised trials were eligible if they included sufficient information (e.g., intra-cluster coefficient). Eligible studies had to be published in English and had to be peer-reviewed journal articles, books, book chapters, postgraduate theses, or conference papers. Government reports, company reports, newspaper articles, conference presentations, and similar were ineligible. There was no restriction on populations or settings. All eligible studies had to administer app-based or social robotic relational agents. Agents that did not use relational cues were ineligible. Any non-relational agent comparator made studies eligible (e.g., waiting lists). Finally, eligible studies had to report a quantitative, self-report loneliness outcome where follow-up was at least one week.

Coding of studies

SS, KL, and HS independently double-screened in Covidence the titles and abstracts of citations and then the full texts of remaining studies, using piloted and structured forms. We measured agreement between screeners via Cohen’s κ and resolved disagreements via discussion between screeners. SS, KL, and HS then extracted data in Covidence using a piloted and structured form, and we contacted primary study authors to obtain raw or missing data. Our data extraction forms are available on OSF, and we describe data imputations in Appendix B. Each study was coded for a range of variables such as sample size, research design, and loneliness scale used. Finally, SS, KL, HS, and DK independently double-assessed risk of bias in MS Excel, using the RoB 2 tool for RCTs and ROBINS-I tool for NRSIs.

Meta-analytic procedure

Our main outcome was loneliness for which we calculated a random-effects meta-analysis using the DerSimonian and Laird method because we expected the effects of relational agents to be heterogenous across populations, types of agents, etc. We used Hedge’s g to standardise results from diverse quantitative loneliness scales, and interpreted the magnitude of Hedge’s g according to the rules of thumb in the Cochrane Handbook for Systematic Reviews of Interventions . Hedge’s g itself was computed using standard formulas and relied on a range of data points such as group means and pooled standard deviations [ 29 ]. Our raw data on OSF show exactly how Hedge’s g was computed for each primary study.

We calculated four null hypothesis significance tests and applied a Bonferroni correction: α Bonferroni  = 0.05 / 4 = 0.0125. We also applied Knapp-Hartung adjustments to our 95% confidence intervals. As measures of heterogeneity, we calculated Cochrane’s Q using a p value of 0.1, I 2 , τ 2 , and a prediction interval. We conducted an RCT-only sensitivity analysis and separate sub-group analyses for app-based and social robotic relational agents. We evaluated publication bias via funnel plots and Egger’s test, and we calculated an adjusted estimate of Hedge’s g using Duval and Tweedie’s trim-and-fill algorithm. We conducted all analyses in the Comprehensive Meta-Analysis Software package. The systematic review and meta-analysis followed PRISMA 2020 reporting guidelines [ 30 ].

Characteristics of studies

Our database searches identified 3,935 records and our manual searches 38 records, of which 1,910 were duplicates. We screened the titles and abstracts of 2,063 studies, deeming 1,908 irrelevant. We screened the full texts of 155 studies, with Fig.  1 detailing reasons for exclusions. In the end, we included 14 studies. When screening abstracts and titles, Cohen’s kappa ranged from κ  = 0.46 to κ  = 1 across reviewer pairs; when screening full texts, it ranged from κ  = 0.71 to κ  = 0.81 across pairs.

PRISMA flow diagram

Nine of the 14 included studies were NRSIs [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ] and the rest RCTs [ 12 , 40 , 41 , 42 , 43 ]. All nine NRSIs were uncontrolled trials. Coding was generally straightforward, though some data points such as percentage of females in the sample were sometimes missing in manuscripts. Together, studies included 286 participants with individual study sample sizes ranging from 4 to 42 participants ( x̄  = 20.43, s  = 11.58, x̃  = 20). Attrition rates ranged from 0 to 94% ( x̄  = 21.39%, s  = 21.56%, x̃  = 16.50%). Based on guidance, we classified 86% of these studies as feasibility studies, since they included fewer than 25 participants in total, or fewer than 25 participants per group [ 44 ].

Figure A, Figure B, and Figure C provide a tabular summary of included studies, but we also provide below a prose summary. Participants’ age ranged from 19 to 100 years ( x̄  = 75.45, s  = 12.89, x̃  = 77.55). Only two studies reported inclusion of participants younger than 50 years [ 12 , 32 ]. A third study is likely to have included them [ 36 ]. Nevertheless, none of the three studies focused on participants younger than 50 years exclusively, and hence studies only included young participants along with older ones. Remaining studies explicitly reported excluding those younger than 50 [ 31 , 33 , 35 , 37 , 38 , 40 , 41 , 43 ] or their sampling frames implied this [ 34 , 39 , 45 ]. Where reported, the percentages of both females and non-White participants were high in most studies.

Nine studies used social robotic relational agents [ 31 , 32 , 33 , 34 , 35 , 39 , 41 , 43 , 45 ] and five app-based relational agents [ 12 , 36 , 37 , 38 , 40 ]. The social robotic agents included Sony’s AIBO [ 32 , 34 , 41 ], PARO developed by ISRI [ 31 , 33 , 45 ], NAO developed by Aldebaran Robotics [ 35 ], Pepper developed by SoftBank Robotics [ 43 ], and either a robotic cat or dog developed by Joy for All [ 39 ]. The app-based agents included Laura developed by MIT [ 40 ], Elena + developed by ETH Zurich and the University of St. Gallen [ 36 ], Amazon’s Alexa [ 37 ], Bella by Soul Machines [ 46 ], and PACO developed by a consortium of Dutch organisations [ 38 ]. The relational behaviours of these agents varied. AIBO is a robotic puppy, PARO a robotic seal, and together with the robotic pets by Joy for All, these agents simulated live pet behaviour (e.g., the agents expressed emotions via facial cues and body language such as wagging of tails, played with users, learned their own names, and recognised users via their facial recognition capabilities) [ 32 ]. The agents responded to touch (e.g., petting) and adapted behaviour through reinforcement learning [ 33 ]. NAO and Pepper were humanoid robots that simulated human behaviours, customs, and speech. NAO, for example, would bow to users, extend its palm for a handshake, ask if participants would want to hear a poem, and only proceed once receiving a reply [ 35 ]. All app-based relational agents simulated humans. All were embodied, i.e., had a visual form, except for Amazon’s Alexa [ 37 ]. App-based agents primarily or to a significant degree used speech for relational behaviour. Laura, for example, expressed empathy (“I am sorry to hear that”), asked follow-up questions (“How tired are you feeling?”), and attempted to get to know users (“So, are you from the East Coast originally?”) [ 40 ]. Whilst in previous research several agents used “wizard-of-Oz methodologies”, i.e., agents controlled by humans pretending to be autonomous, all agents in this review were autonomous [ 47 ].

Most relational agents in our review acted as direct companions and did not seek to mitigate loneliness via other modalities [ 31 , 32 , 33 , 34 , 35 , 37 , 39 , 40 , 41 , 43 , 45 ], although exceptions existed. Elena + sought to remove cognitive biases and improve social skills [ 36 ]. PACO sought to create opportunities for socialising [ 38 ]. Bella sought to enhance social skills, increase social support, and increase opportunities for socialising [ 12 ].

Studies generally did not mention behavioural theories or behavioural change techniques (BCTs) that underpinned intervention design, although exceptions existed. One study based its intervention on Self-Determination Theory [ 38 ] and another study based its intervention on the COM-B model and the Theory of Planned Behaviour [ 36 ]. Nevertheless, these studies provided little detail on how exactly theories informed design. We classified BCTs according to the BCTTv1 by Michie et al., using below in quotation marks the labels of the original authors [ 48 ]. Only one study confirmed the full range of BCTs it used, and two other studies provided examples of BCTs. One study used six BCTs: “credible source”, “review behaviour goals”, “goal setting”, “instruction on how to perform a behaviour”, “social comparison”, and “social support” [ 38 ]. Another study mentioned seven BCTs: “information about emotional consequences”, “action planning”, “behavioural contract”, “instruction on how to perform a behaviour”, “review behaviour goals”, “reducing exposure to cues for the behaviour”, and “reduce negative emotions” [ 12 ]. A third study mentioned five BCTs: “information about emotional consequences”, “goal setting”, “instruction on how to perform a behaviour”, “reducing exposure to cues for the behaviour”, and “reduce negative emotions” [ 36 ].

All RCTs were at high risk of bias due to potential deviations from the intended interventions [ 40 , 41 , 43 , 45 ] except for one [ 12 ]. All NRSIs were at high risk due to confounds and potential biases in measurements [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. Figures  2 and 3 illustrate these.

RCT risk of bias domains

NRSI risk of bias domains

Meta-analysis

The pooled estimate of Hedge’s g was -0.552 ( Z  = -3.833; 95% CI, -0.834 to -0.270; P  < 0.001), indicating on average a moderate effect of relational agents on loneliness reduction. This is shown in Fig.  4 . Using a Bonferroni-corrected α Bonferroni  = 0.0125, there was evidence to reject the null hypothesis. Using the Knapp-Hartung adjustment, there was also evidence to reject the null hypothesis ( t  = -3.66; 95% Knapp-Hartung CI, -0.877 to -0.226; P  = 0.003).

Main analysis forest plot

Heterogeneity measures indicated that, as anticipated, the true effect of relational agents varied ( Q  = 45.073; I 2  = 71%; τ 2  = 0.176; τ  = 0.420). Assuming a Gaussian distribution, the 95% prediction interval was estimated to range from -1.519 to 0.415, as seen in Fig.  5 .

Main analysis prediction interval

Funnel plots as well as Egger’s test ( b  = -2.81; t  = 3.5; P  = 0.004) suggested that a small study effect may exist. Figure  6 illustrates this. The small study effect could have been due to effect sizes being larger in smaller studies or due to publication bias. Assuming a severe publication bias, the trim-and-fill algorithm resulted in an adjusted estimate of g  = -0.198 (95% CI, -0.505 to 0.109), which attenuated the original estimate by roughly 64%.

Funnel plot using standard error

Five studies were available for the RCT-only model. Hedge’s g was -0.437 ( Z  = -2.495; 95% CI, -0.781 to -0.094; P  = 0.013), which was 21% less than the estimate of the main model. The results were significant at a traditional α  = 0.05 but not at the α Bonferroni . The Knapp-Hartung adjusted results were not significant ( t  = -2.49; 95% Knapp-Hartung CI, -0.924 to 0.049).

Six studies were available for the app-based relational agent model. The pooled estimate of Hedge’s g was -0.286 ( Z  = -1.611; 95% CI, -0.553 to -0.020; P  = 0.035), which was significant at a traditional α but not α Bonferroni . The Knapp-Hartung adjustment resulted in non-significant results ( t  = -2.11; 95% Knapp-Hartung CI, -0.636 to 0.063). Eight studies were available for the social robotic relational agent model. The pooled estimate of Hedge’s g was -0.774, which was significant at α Bonferroni ( Z  = -2.909; 95% CI, -1.296 to -0.252; P  = 0.004). Using a Knapp-Hartung adjustment, results were significant at a traditional α but not at α Bonferroni ( t  = -2.91; 95% Knapp-Hartung CI, -1.403, -0.145, P  = 0.023).

Our review is the first to provide quantitative evidence for the efficacy of relational agents to reduce loneliness in participants aged 19 to 100 years. Our results are promising, and although the effect size of g  = -0.552 is likely somewhat inflated due to publication bias, it is probably less inflated than our trim-and-fill algorithm suggested. This is because the trim-and-fill algorithm assumed that several studies were suppressed in which relational agent interventions exacerbated loneliness. This, however, is unlikely. Failed loneliness interventions tend to have no effect on loneliness, not exacerbate it [ 10 ]. Our review could have used different algorithms to adjust for publication bias, and alternatives would probably have yielded different adjustments. Recently, for example, researchers have applied four different algorithms to a high-profile meta-analysis, resulting in a mix of significant and non-significant adjustments [ 49 , 50 , 51 ]. Nevertheless, no algorithm for publication bias would provide the “correct” effect size [ 52 ]. Instead, algorithms provide a sensitivity analysis assuming certain parameters, and sometimes these parameters lead to flawed results, e.g., the trim-and-fill algorithm overcorrects under heterogeneity, which was the very assumption of our analysis [ 53 ]. Ultimately, the most likely interpretation is that the true average effect size of relational agents was small to moderate. Table 1 provides a summary of our results.

We believe the above results have two important implications for the current loneliness literature. First, the literature is in search for novel and effective interventions that are scalable. The NHS is already facing resource constraints, these constraints are expected to exacerbate, and the NHS has consequently called for the increased adoption of AI to ease its burden [ 54 ]. Relational agents can be highly scalable, once some groundwork has been completed, and a possible follow-up from our results is a national or regional pilot. Such a pilot, of course, would entail the resolution of complex issues (e.g., digital literacy, access to technology, and privacy). Researchers, for example, will need to determine who will have access to user data and in what form, and such choices can fundamentally impact the success of a pilot.

The second implication of our results is that relational agents may act as a standalone intervention, but they are likely to be more useful in multi-component interventions that are tailored to individual needs. In the UK, the NHS’s current main strategy for loneliness is “social prescribing”, an outsourcing approach in which staff refer individuals to community schemes such as lifestyle interventions (e.g., physical exercise) or social activity interventions (e.g., volunteering) [ 7 , 55 ]. While there are alternative intervention approaches for loneliness, social prescribing is viewed by individuals and service providers as helpful [ 7 ] and cost-effective [ 56 , 57 ]. Social prescribing is, in essence, a sign-posting intervention, and it could sign-post, among other things, to relational agents. This could be valuable because there is currently a notion that interventions improve lives, but that people do not recover from loneliness [ 58 ]. Potentially, this may be because not all loneliness is the same. Two people may feel lonely for two different reasons, and these people may then require different sets of solutions [ 58 ]. Relational agents can extend the set of available solutions, and agents can complement existing human-centred interventions, rather than replace them.

Relational agents, thus, could help in the fight against loneliness. What is more, their full potential has not yet been realised. On the one hand, this is due to the absence of state-of-the-art knowledge integration. For example, the use of behavioural theories and BCTs can enhance intervention efficacy, yet studies in our sample generally did not discuss such theories and BCTs. Similarly, interventions can modify loneliness via multiple modalities. Studies in our review, however, generally used only one of these modalities, and the others—such as the debiasing of social cognition that has shown particular promise [ 56 ]—are yet to be integrated into relational agent design [ 14 ]. On the other hand, relational agents have not yet realised their full potential due to the nascency of AI. Increasingly, LLMs are powering relational agents. These models allow relational agents to produce open-ended, original, and highly tailored conversation, and although much of the conversation of relational agents has already become indistinguishable from human conversation [ 59 ], research on LLMs is burgeoning, and the race is on between organisations such as OpenAI and Google to develop the next generation of LLMs [ 60 ].

Limitations

Our review faced common limitations such as the exclusion of non-English sources and the quality of underlying primary studies, but a particular limitation of our review were the mixed results of the sensitivity and sub-group analyses. There are three potential explanations for this. First, sample sizes in these sub-group analyses were less than 10, and analyses with fewer than 10 studies tend to lack power [ 52 ]. At the same time, it is likely that underlying studies themselves lacked power due to small sample sizes [ 61 ]. Indeed, Appendix C demonstrates that power was likely well below the recommended level of 80% in our sub-group analyses, while Appendix D presents an additional sensitivity analysis indicating that further primary studies would have meaningfully reduced p levels [ 52 ]. Second, our review may have tested for results too conservatively. The Bonferroni correction, as applied in this review, results in Type 2 error rates of roughly 33%, which some have referred to as unacceptably high [ 62 ]. Finally, our review conducted two-tailed significance tests. This is usually anodyne—since interventions can both improve and exacerbate outcomes. Nevertheless, in cases where interventions are unlikely to exacerbate outcomes, one-tailed tests may be warranted [ 52 ]. This, as discussed, is likely to be the case with loneliness and relational agents. Had we conducted one-tailed tests, this would have entailed the halving of p values, which would have made some results statistically significant. Third, execution may have been a problem. Primary studies may not have sufficiently exposed participants to relational agents, or participants may not have interacted with relational agents, or relational agents may not have been correctly designed. Chen et al. [ 63 ], for example, found no significant difference between control and experimental groups at a four-week interval [ 63 ]. They did, however, find a significant difference at an eight-week interval. In our review, the mean time between pre-test and final post-test was 5.92 weeks.

Future research

We lack an understanding of relational agents in several areas, and we suggest that future research could focus on three. First, research on relational agents and loneliness in young people is scarce. Among some youth groups loneliness rates are higher than those of the elderly, and these rates of youth loneliness are increasing [ 64 ]. At the same time, smartphone ownership is high among the young [ 64 ]. Young people therefore are pertinent and amenable for the study of loneliness. Second, the efficacy of relational agents will depend on a variety of population and design factors. On the population side, we suspect that factors such as age, education, and digital literacy may impact efficacy. On the design side, we suspect that a hierarchy of features exists, e.g., certain design features will deliver more bang for your buck, although it is less clear which [ 65 ]. Third, although general attitudes towards relational agents may be favourable, some are concerned about the introduction of relational agents and similar technologies [ 66 ]. Future research could therefore explore how technology should be harnessed to increase its benefits and reduce unintended consequences. Finally, future research could address the shortcomings of current research. Almost all underlying studies in our review suffered from high risk of bias in one or several domains, sample sizes were small, and follow-up periods were brief. Particularly, there is a need for more high-quality RCTs.

The current study is the first meta-analysis to explore the effects of relational agents on loneliness across all age groups. It is also the first meta-analysis to provide statistically significant evidence for the efficacy of relational agents, which on average had a moderate effect on loneliness reduction. Loneliness has serious physical and mental health consequences for individuals, and the monetary costs to the state and employers are staggering [ 67 , 68 , 69 ]. Unfortunately, current interventions for loneliness can suffer from low engagement and scalability [ 58 ]. Relational agents, on the other hand, are an emerging technology that due to advances in AI and LLMs will increase in sophistication and realism. Although a multi-pronged approach is required, relational agents could play a significant role in alleviating a growing public health concern [ 64 ]. Future work is required that addresses weaknesses of current studies such as risk of bias, small study size, and brief follow-up periods.

Availability of data and materials

As a meta-analysis, this study used data reported in the literature. Appendices and derived data for meta-analytic calculations are available the Open Science Framework here https://osf.io/c6rdk/files/osfstorage . Reader can also write directly to the corresponding author.

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Acknowledgements

We would like to thank LSE staff for additional feedback, including Alina Velias, Andra Fry, Jessica Kong, and Georgia Nichols. We thank Nina Shahrizad for proofreading. We would also like to thank all primary authors who made this systematic review and meta-analysis possible.  After our analysis was completed, a final version of one of our included studies [ 36 ] was published, which was a preprint. This final version is available here [ 70 ].

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SS drafted the first version of the protocol and search strategy. All other authors provided feedback and approved the final protocol. SS, KL, and HS screened the titles and abstracts and full texts of citations, and these authors also extracted data from included studies. SS, KL, HS, and DK conducted risk of bias assessment. SS completed the data analysis. SS, KL, and PQ co-wrote the first version of the final manuscript. All authors provided feedback and approved the final manuscript. All authors had access to the underlying data. SS, KL, and HS verified the data.

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Sha, S., Loveys, K., Qualter, P. et al. Efficacy of relational agents for loneliness across age groups: a systematic review and meta-analysis. BMC Public Health 24 , 1802 (2024). https://doi.org/10.1186/s12889-024-19153-x

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Received : 11 October 2023

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DOI : https://doi.org/10.1186/s12889-024-19153-x

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