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From ideas to studies: how to get ideas and sharpen them into research questions

Jan p vandenbroucke.

1 Leiden University Medical Center, Leiden, the Netherlands

2 Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark

3 Department of Medical Statistics and Centre for Global NCDs, London School of Hygiene and Tropical Medicine, London, UK

Neil Pearce

Where do new research questions come from? This is at best only partially taught in courses or textbooks about clinical or epidemiological research. Methods are taught under the assumption that a researcher already knows the research question and knows which methods will fit that question. Similarly, the real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. In this paper, we first discuss how to get an idea that is worth researching. We describe sources of new ideas and how to foster a creative attitude by “cultivating your thoughts”. Only a few of these ideas will make it into a study. Next, we describe how to sharpen and focus a research question so that a study becomes feasible and a valid test of the underlying idea. To do this, the idea needs to be “pruned”. Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains. This includes determining both the latent and the stated objectives, specific pruning questions, and the use of specific schemes to structure reasoning. After this, the following steps include preparation of a brief protocol, conduct of a pilot study, and writing a draft of the paper including draft tables. Then you are ready to carry out your research.

Introduction

How do you get an idea for a study? How do you turn your idea into a testable hypothesis, and turn this into an appropriate and feasible study design? This is usually at best only partially taught in epidemiology courses. Most courses and textbooks assume that you know your research question and the general methods that you will need to answer it. Somehow it is assumed that you can readily translate your idea into a specific framework, such as the PICO framework (Patient, Intervention, Control or Comparison, Outcome) 1 or the FINER framework (Feasible, Interesting, Novel, Ethical, and Relevant) 2 or that you can fit it into counterfactual reasoning. 3 However, before describing your project in one of these frameworks, you first need to have an idea for your study and think about it in general terms: why you might do a study and how you might do a study.

This paper considers the complex process of having ideas, keeping track of them, turning them into studies, trying them out in pilot studies, and writing a draft paper before you finally embark on your study.

The paper is intended for novice researchers in clinical or public health epidemiology. It is not intended to be a comprehensive literature review about creativity, nor a sociology or philosophical treatise about why scientists get particular ideas (and not other ideas). It is based on our personal experience of (a combined) 70+ epidemiologic research-years. We have worked on very different topics, mostly on opposite sides of the globe, yet found that our experiences are quite similar. The fact that these issues are rarely covered in epidemiology courses has provided motivation to reflect on our experience.

Getting new ideas

So how do you get an idea? How some juxtaposition of neural patterns in our brain suddenly creates a new idea is a process that we are far from understanding. According to Karl Popper, the origin of new ideas does not matter; the only thing of interest is to devise how to test them. 4 Over the past decades, the literature has been enriched with new ideas about “being creative” in science – as witnessed in the book Innovation Generation by Ness. 5

In the present paper, we will not cover the literature about creativity and discovery in depth, but we will discuss the issues that we consider relevant to epidemiologic research. We will first consider the more general principles.

The real complexity of the thought processes that lead to a scientific undertaking is almost never described in published papers. Immunologist Medawar claimed that in this respect almost all scientific papers may be a fraud – not in the sense that scientists deliberately produce misleading data, but in the sense that the real thought processes that lead to the data and conclusions are not mentioned. 6 Scientists tell us about their real thought processes in memoirs, inaugural, or valedictory lectures – which is why these are so much more interesting than “standard” papers or presentations.

What strikes our minds: regularities or anomalies?

All sciences study a particular “object of knowledge” (eg, “matter”, “life”). Ideas come from experience and previous knowledge or facts about this object of knowledge, although this knowledge is always filtered through the perspective of one or more theories. 7 Epidemiology studies the distribution and determinants of disease in human populations, 8 and epidemiological ideas arise from observing and thinking about populations. 9 These could be clinical populations (ie, clinical experience, sometimes involving just a few patients), exposure-based populations (eg, workers exposed to a particular chemical), or general populations (geographically defined or sociologically defined). Whatever the population we are interested in, ideas come from observing either regularities or anomalies.

The observation of regularities (“induction”) is a common origin of new ideas. 4 , 10 – 13 Philosopher David Hume described “Induction” as: regularly seeing two things happening in succession (like pushing a switch and a light going on) leads to suspicions of causality. As he pointed out, causality can never be proven by the mere observation of “constant conjunctions”, but observing regularities can start our train of thought. 12

An anomaly (or irregularity) strikes our mind, because it defies our expectations. The regularity that we expected was our “hypothesis” (even if it was not really explicitly formulated); the anomaly is a “refutation”. 4 , 13 It forces us to think about other explanations, and these lead to new hypotheses that we then try to test. Thus, scientists do not usually start from hypotheses that are nicely formulated “out of the blue”, but instead start from previous knowledge and experience; when they are challenged by anomalies, scientists seek new explanations. 14

An interesting way to discover anomalies is to enter a new field of research; since you have other background experience than the people already in the field, you see things that they take for granted but that strike you as odd – at the same time, you may also see new explanations for these anomalies. One of the pioneers of clinical epidemiology, Sackett, once wrote that scientists should “retire” from a field as soon as they become “experts”. 15 When you are too long in a field, you will no longer see the anomalies, and you may even obstruct newcomers with new explanations. Of course, there are differences between scientists: some roam across various fields and others stick to a problem area that they explore with increasing depth – then the increasing depth and the new techniques that one needs for advancing one’s thoughts will be like a “new field”.

Taxonomies of discovery

Few researchers have listed the different ways in which one can arrive at new ideas, that is, lists of ways of discovery. We will present two of them – which have very different origins but remarkable similarities. Several examples of studies corresponding to items on these two lists are given in Appendix Examples A1–A10 .

Sources for new ideas about health care evaluation were described by Crombie and Davies in the chapter “Developing the research question” of their book on Research in Health Care that reflects a UK public health experience. 16

• “Review existing practice […] the current organisation and delivery of health care is not as good as it could be […]”
• “Challenge accepted ideas […] much of health care is based on accepted practice rather than research evidence […]” ( Appendix Example A3 )
• “Look for conflicting views […] which indicate either that there is not enough evidence, or that some practitioners are misinformed”
• “Investigate geographical variation […] reflecting on the reasons [for geographical variation] can be a fruitful source of research questions […]” ( Appendix Example A6 )
• “Identify Cinderella topics […] important areas of health care are often overlooked […]”
• “Let loose the imagination […] look for wild or impossible ideas […] free the mind from the constraints of conventional wisdom […].”

A taxonomy for sources of clinical research questions about medical care and clinical problems was proposed by Hulley and Cummings, in the context of clinical research in the US: 2

• “Build on experience;” your own experience, that of close colleagues with whom you can freely discuss your research ideas, and that of a good mentor, because young researchers might not yet have much experience, “An essential strategy for a young investigator is to apprentice himself to an experienced senior scientist who has the time and interest to work with him regularly.”
• ○ By harvesting “the medical literature and attending journal clubs, national and international meetings, seeking informal conversations with other scientists and colleagues”
• ○ “A sceptical attitude about prevailing beliefs can stimulate good research questions”
• ○ Be alert to “careful observation of patients, which has historically been one of the major sources of descriptive studies” ( Appendix Examples A1 and A2 )
• ○ Your experiences in teaching; having to explain something may make you aware of gaps in your knowledge; questions by patients and colleagues may similarly identify things that we do not fully understand or ignore
• “Keep the imagination roaming […]” by a mixture of creativity and tenacity; “put an unresolved question clearly in view and turn on the mental switch that lets the mind run freely toward it”.

A special mention needs to be made about the last categories of both the lists: “Let loose the imagination” and “Keep the imagination roaming”. These are especially important to find innovative solutions. In many situations wherein you cannot do a perfect study and you run a grave danger of potential confounding or bias, it helps to “get deeply immersed”: to understand the problem biologically, clinically, socially, organizationally, and environmentally will help you to think about what is happening, why it is happening, and whether you can find situations in which the potential confounders or biases do not exist or exists in reverse. You should forget formal designs and think out of the box: you will find instances of studies that mutually reinforce each other and may even arrive at formulating new designs or analytic solutions (see Appendix Examples A7–A10 ).

Keeping track of your ideas

It is not only important to have good ideas but also important to develop them. Researchers who work in laboratories have the habit of keeping “lab logs”. They write down briefly the results of an experiment, note why they think it went wrong, and how they will perform the next experiment. This permits them to trace how they changed the experiments or even the content and the direction of their research. We should do the same in epidemiologic and clinical research, particularly in the stage of creating new ideas. Such notes about ideas can include not only hypotheses and views or results by others but also drawing directed acyclic graphs (DAGs) (see “Intermezzo: specific schemes to structure reasoning” section) to make the causal structures of ideas clear.

The greatest minds kept track of their thoughts. Charles Darwin’s notebooks document his ideas, his observations, his readings, and new theories and facts that struck him. 17 For example, Darwin noted a story that he heard from his father, a medical practitioner. His father recounted that he had been struck by one of his patients’ ways of expressing himself, because he had attended a parent of the patient who had had the same mannerisms – even though the parent had died when the patient was still an infant. Remarks like these still have relevance today when we think about the heredity and evolution of behavior.

The sociologist C Wright Mills carried the description of the process one step further in the appendix of his book on The Sociological Imagination . 18 He encourages young sociologists to set up a file of stacked cards to keep track of “[…] personal experience and professional activities, studies underway and studies planned […]” which “[…] encourages you to capture ‘fringe thoughts’: various ideas which may be by-products of everyday life, stretches of conversations […]”. These notes are continuously reshuffled, regrouped under new headings, and pondered. Mills denounced the habit of most (social) scientists who feel the need to write about their plans only when they are going to apply for a grant. He thought that scientists should continually work with their file of ideas and regularly take stock of how these have evolved.

Such strategies are still relevant today, even if our “logs” are kept in electronic form, particularly because grant writing has become more demanding, hectic, and time-consuming. From such files, new research projects are born: while your ideas gradually develop, you keep wondering what data you might need to prove a certain proposition, and how you might get those data in the easiest way possible. Often, ideas are reshuffled and regrouped under new headings. A new observation, a new piece of literature may make old ones fall into place, or there may suddenly be a new opportunity to work out an old idea.

A complementary advice recently came in a blog from a contemporary sociologist, Aldrich: his advice is to “Write as if you don’t have the data”, that is, to write “[…] the literature review and planning phase of a project, preferably before it has been locked into a specific research design”. 19

The role of emotions

Underlying the discovery process, there are often two emotions: “surprise” and “indignation”. Surprise is the intellectual emotion when we see something happening against expectation: a patient with an unusual exposure, unusual disease manifestation, sudden cure, or sudden ill-understood deterioration; a laboratory result that is an anomaly; and a sudden epidemic of disease in a population. Indignation is the moral emotion: a group of patients is not being treated well because we lack sufficient knowledge, or because we are blundering in organizing health care or in transmitting and applying public health knowledge. Some passion is useful to bring any undertaking to a good end, be it that the passion should be restrained and channeled into polite undertakings, like in a research protocol. While doing the research project, maintaining some of the original passion will help you to find ways to overcome the daily hassles of research, the misadventures, the difficulties of getting others to collaborate, and the difficulties of getting published ( Appendix Example A11 ).

Sharpening the research question: the pruning

Pruning a research question means cutting away anything that is unnecessary, so that only the essence remains.

The initial spark of an idea will usually lead to some rather general research question. Invariably, this is too ambitious, or so all-encompassing that it cannot be researched (at least not within the time frame of a single grant or PhD project). You have to refine your research question into something that is interesting, yet feasible. To do so, you have to know clearly where you are heading. The emphasis on a clear preconceived idea about what you want to attain by your research often comes as a surprise; some people object: “[…] isn’t research about discovery? How can you know in advance what you want to find?”

The social scientist Verschuren proposed the “wristwatch metaphor”. 20 A researcher is not like a beachcomber, who strolls along the beach to see whether anything valuable washed ashore. Rather, a researcher is like someone who has lost her wristwatch on the beach and returns to search for it. She knows what part of the beach to look, she can describe her wristwatch in detail, and once she has found it, she knows that this is the watch she was looking for. Some further background to these ideas can be found in Appendix B .

Charles Medawar wrote in his Advice to a Young Scientist (page 18) 21 that as much as politics is the ‘art of the possible’, research is the ‘art of the soluble’. A research question should be limited to a question that can be solved with the resources at hand. This does not mean that you should preferentially study “trivial” questions with easy solutions. It does mean that you should seek out your particular niche: something specific, something that was overlooked by others, or some new twist to a general question, so that you can make your own contribution.

The concept of “serendipity” is often invoked when thinking of “seeking novelty”: it means finding something that you were not looking for. For a full discussion of the more complex reality that shows how, in reality, “chance favors a prepared mind”, see Appendix C .

Proceed in the inverse order of the paper that you will write

From the aforementioned, we know that we need a precise aim and a soluble research question.

How can we achieve this? The best approach is to “begin at the end”, that is, the conclusion that you hope to support when you eventually publish your research findings, perhaps many years from now. 22 Most medical research papers have a fixed format: introduction, methods, results, discussion. Usually, the discussion has three parts: summary of the results, discussion of the strengths and limitations, and the importance and interpretation of the findings. There you start: you try to imagine what such last lines of the eventual paper might be – in particular what their intent, their message to the reader might be. Another useful strategy would be to imagine what might be written in the separate box “What this paper adds” that many journals nowadays ask to convey the message from the authors clearly and succinctly to the readers.

The “latent” versus the “stated” objective

The pioneer clinical epidemiologist Feinstein wrote that a good research consultant should be like a good clinician, who first wants to learn from the patient: “What is the chief complaint?”, that is, which is the problem that you want to study. Next, “What will you do with the answer?” 22 The latter question is not just about the potential conclusions of the research paper, but more importantly, their meaning. What is the intended effect (or impact) of the findings? He called this the “latent objective”: what do you want to achieve or change by your project; the “stated objective” is different, it is the type of result that the study will deliver. For example, the stated objective can be that you want to do a randomized trial to compare one intervention versus another and that you will look at recurrence of disease. The latent objective might be that you are concerned that one intervention may be harmful to patients, driven by special interests, and that if this is the case it should be abolished.

Rather analogously, the long-time editor of the Annals of Internal Medicine , Edward Huth, proposed in his book about medical publishing the “So-What” and the “Who-Cares” tests: “What may happen if the paper’s message is correct?”; may it change concepts and treatment or stimulate further exciting research? 23 In fact, many funders now require such an “impact statement” as part of the grant application process.

Experienced research consultants know that when trying to discover the latent objective, it is useful to brush aside the detailed protocol and to ask directly what the meaning of the research is. The meaning of the research is often not clearly stated in a formal study protocol that limits itself more or less to “stated aims”. 24 Like a patient who cannot articulate her/his complaints very well, would-be researchers lose themselves in trivial “side issues” or operational details of the protocol. Appendix Examples A2 and A11 explain the importance of elucidating the underlying frustration of the clinician-researcher to clearly guide a research effort.

After initial questions have set the scene and clarified the “latent objective” of a project, the next questions are more operational, translating the latent objective back into a “stated objective”. 22 The stated objective should be a feasible research project. According to Feinstein, one should ask: what maneuver is to be executed (what intervention, deliberate or not, and how is it administered), what groups are to be compared (and why those groups), and what is the outcome that we will study?

In these phases of discussion, one needs to immerse oneself into the problem: one has to understand it biologically and clinically, and how it is dealt with in the daily practice of health care in the setting in which you will do research. Getting deeply immersed in the problem is the only way of arriving at shrewd or new solutions for studies on vexing medical or public health problems ( Appendix Example A9 ). Mere discussion of technical or procedural aspects of a proposed design, data collection, or analysis will usually not lead to new insights.

Specific pruning questions, to ask yourself or others

In initial discussions, one goes back and forth between the general aim (the latent objective), the scientific questions that follow from it, and the possible research designs (with stated objectives). After feeling secure about the “latent” aim, proceed with more specific questions.

• Try to describe exactly the knowledge gap that you want to fill (ie, the watch that you lost at the beach). Is it about etiology, about pathogenesis, about prognosis? What should change for the benefit of a particular group of patients? Try to be as specific as possible. Do your colleagues see these problems and their solutions as you do? – and if not, why don’t they?
• Once you know the point you want to make, describe what table or figure you need to fill the gap in knowledge, that is, what would your results look like? This means drawing a simple table or graph. Are these the data you want? Will these tables convince your colleagues? What objections might they have? Keep in mind that if the research results go against ingrained beliefs, they will be scrutinized mercilessly, so the important aspects of your research should be able to withstand likely objections.
• Thereafter, the questions become more practical: what study design is needed to produce this table, this figure? Can we do this? Do we have the resources or can we find them?

Be self-critical

You should always remain self-critical about the aspects that threaten the validity of your study ( Appendix Example A12 ). 25 If the practical problems are too large, or the research question too unfeasibly grandiose, it might be wise to settle for a less ambitious aim ( Appendix Example A13 ).

Paraphrasing Miettinen, 26 the first decision is whether you should do the study at all. There might be several reasons to decide not to pursue a study. One might be that arriving at a satisfactory design will be impossible, because of biases that you are unable to solve. It serves no purpose to add another study that suffers from the same unsolved problems as previous studies. For example, it does not serve any purpose to do yet another study that shows lower mortality in vegetarians, if you cannot solve the problems of confounding that vegetarians are persons who have different lifestyles in comparison with others. 27 (If, however, you have found a solution – pursue it at all means!) Nevertheless, thinking about the potential problems and ultimate aims of a seemingly impossible question can foster the development of a new study design or a new method of analysis, ( Appendix Examples A2, A9, and A10 ). In the same vein, deciding that you cannot do a study yourself might make you look for collaboration with persons who have the type of data that you do not, for example, in a different population where it is believed that confounding is not so severe or may even be in the opposite direction.

All studies have imperfections, but you need to be aware which ones you can tolerate. 28 In the early stages of an enquiry, an “imperfect” study might still be worthwhile to see whether “there might be something in it”. For example, time trends or ecological comparisons are often seen as poor study designs to assess causality by themselves, but they can be very valuable in helping to develop ideas, as well as providing a “reality check” about the potential credibility of some hypothesis. 29

Conversely, it is pointless to add yet another study, however perfect, showing what is already known very well – unless you have to do it for “political” purposes, say, for convincing decision makers in your own country.

Finally, it is not a good use of your time to chase something completely improbable or futile. For example, at the present state of the debate, it serves no purpose to add another study about the presence or absence of clinical benefits or harms of homeopathy: no one will change his or her mind about the issue. 30 , 31 An exception might be something that is highly improbable, but that if true might lead to completely revolutionary insights – such an idea might be worth pursuing, even if the initial reaction of outsiders might remain incredulousness. Still, you should pursue unlikely hypotheses knowingly, that is, with the right amount of self-criticism – in particular, to make yourself aware when you are in a blind alley.

To keep yourself on the “straight and narrow”, it helps to form a group of people who cover different aspects of the problem you want to study: clinical, biochemical and physiological, and methodological – to discuss the project as equals. Such discussions can not only be tremendous fun but also will invariably lead to more profound and diverse research questions and will help to find solutions for practical as well as theoretical problems. In the right circumstances of a “machtsfreie Dialog” 32 (a communication in which all are equal and that is only based on rational arguments and not on power – which all scientific debates should be), such a circle of colleagues and friends will help you to be self-critical.

Finally, when pursuing one’s research interests, one should be prepared to learn new skills from other fields or collaborate with others from these fields. If one stays only with the techniques and skills that one knows, it might not lead to the desired answers. 33

What if the data already exist? And you are employed to do a particular analysis with an existing protocol?

Even in the circumstance that the data already exist, it greatly helps to not jump into an analysis, but to think for yourself what you would ideally like to do – if there were no constraints. As Aldrich mentioned, 19 also in that circumstance researchers should still

[…] begin their literature review and conceptual modeling as if they had the luxury of a blank slate […]. Writing without data constraints will, I believe, free their imaginations to range widely over the realm of possibilities, before they are brought to earth by practical necessities.

Moreover, this will make clear what compromises one will make by accepting the available data and the existing analysis protocol. Otherwise, one starts an analysis without being sufficiently aware of the limitations of a particular analysis on particular data.

The difference between explanatory and pragmatic research

A useful distinction is between explanatory and pragmatic research: the former is research that aims at discovery and explanation, whereas the latter is intended to evaluate interventions or diagnostic procedures. The first type of research consists of chasing explanations by pursuing different and evolving hypotheses; the second type of research aims at making decisions about actions in future patients. 27 The two opposites differ strongly in their thinking about the types of studies to pursue (eg, observational vs randomized), about the role of prior specification of a research hypothesis, about the need for “sticking to a prespecified protocol”, and about subgroup analyses and multiplicity of analyses. Some of these will be explained in the following subheadings.

The difference between explanatory and pragmatic trials is sometimes thought to mirror the difference between doing randomized trials versus observational research. However, even for randomized trials, a difference exists between “ pragmatic” and “explanatory” trials (coined first by Schwartz and Lellouch). 34 Because it is not always easy to delineate what aspects of a randomized trial are “pragmatic” or “explanatory”, instruments have been crafted to help researchers and evaluators. 35 , 36 Conversely, not all observational studies are explanatory: some are needed for pragmatic decisions (think about adverse effects of drugs and also about diagnostic evaluations where studies should influence practice guidelines) – while other studies aim at explaining how nature works.

Which iterations should you allow yourself? Anticipating the next project

Thinking about a research problem is a strongly iterative process. 2 , 33 , 37 One starts with a broad aim and then tries out several possible ideas about studies that might lead to better understanding or to better solutions.

Likewise, project proposals characteristically go through many iterations. In the early phases of the research, it is commonplace that the study design or even the research question is changed. Specific suggestions about common research problems and their potential solutions were given by Hulley and Cummings, 2 which we reproduce in Appendix D .

The revision of the aims of a project may be profound, in particular in explanatory research (see “The difference between explanatory and pragmatic research” section), in contrast to pragmatic research (see “Shouldn’t you stick to a predefined protocol?” section). The chemist Whitesides wrote: “Often the objectives of a paper when it is finished are different from those used to justify starting the work. Much of good science is opportunistic and revisionist”. 38 Along a similar line, Medawar proposed that to do justice to the real thought processes of a research undertaking, the discussion section of a paper should come at the beginning, since the thought processes of a scientist start with an expectation about particular results. The expectation determines which findings are of interest and why they will be interpreted in a particular way. 6 He added that in real scientific life, scientists get new ideas (ie, new expectations) while doing their research, but “[…] many of them apparently are ashamed to admit, that hypotheses appear in their mind along uncharted byways of thought”. 6

“Seeing something in the data” can be an important part of scientific discovery. This is often decried as “data dredging”, which it is not: one sees something because of one’s background knowledge and thereby there always is some “prior” that exists – even if that was not specified beforehand in the study protocol. 27 , 39 The word “exploratory” is often misused when it is used to characterize a study. True “exploratory” data analysis would only exists if it is mindlessly done, such as a Genome Wide Association Study (GWAS) analysis – but even GWAS analyses have specific aims, which becomes clear when results are interpreted and some findings are designated as “important” and others not. As stated by Rothman:

Hypotheses are not generated by data; they are proposed by scientists. The process by which scientists use their imagination to create hypotheses has no formal methodology […]. Any study, whether considered exploratory or not, can serve to refute a hypothesis. 40

Appendix Examples A5 and A7 show how projects changed mid-course because of a new discovery in the data or in the background knowledge about a research topic.

Generally, it is a good habit to think through what the next project might be, once you will have the result of the project you are currently thinking about, so as to know what direction your research might take. 33

Shouldn’t you stick to a predefined protocol?

Different research aims, in particular along the “explanatory” versus “pragmatic” continuum, may lead to different attitudes on the amount of change that protocols may endure while doing research. 27 , 39 For randomized trials, and also for pragmatic observational research, the research question is usually fixed: does a new therapy lead to better outcomes for a particular group of patients in a particular setting? Because findings from randomized trials or pragmatic observational research may lead to millions of patients to adopt or avoid a particular therapy (which means that their well-being or even life depends on the research) researchers are generally not at liberty to change their hypotheses at the last moment – for example, by suddenly declaring an interest in a particular subgroup. They should stick to the predefined protocol. If a change is needed for practical reasons, it should be clearly stated in the resulting publications. This makes thinking about research questions and doing pilot studies beforehand all the more important (see “Pilot Study” section).

In contrast, much epidemiologic and clinical research tries to explain how nature works. This gives greater leeway: exploration of data can lead to new insights. Thus, “sticking to the protocol” is a good rule for randomized trials and pragmatic observational research, but may be counterproductive for explanatory research. 39 , 41 Nevertheless, it is good to keep track of the changes in your thoughts and in the protocol, even if only for yourself. In practice, many situations are intermediate; in particular when using large available data sets, it often happens that one envisages in a protocol what one would do with the data, only to discover upon opening the data files that the data fall short or are more complex than imagined; this is another reason for doing pilot studies, even with large available data sets (see “Pilot Study” section).

How much literature should you read?

If you are setting up a new research project in a new area, do not start by reading too much. You will quickly drown in the ideas of others. Rather, read a few general reviews that identify unanswered problems. Only return to the literature after you have defined your research question and provisionally your study design. Now, the literature suddenly becomes extremely interesting, since you know what types of papers you need. You also know what the potential objections and shortcomings are of the different design options, because you thought about them yourself. The number of relevant papers usually greatly shrinks, see Appendix Example A4 .

Shouldn’t you do a systematic review first?

It is argued that before embarking on a new piece of research, one should first do a systematic review and/or meta-analysis, because this may help to define the gaps in knowledge more precisely, and guide new research – or may show that the question has been solved. This argument is somewhat circular. A systematic review is a piece of research in itself, intended for publication, and requires much time and effort. Like any piece of research, it requires a clear research question. As such it does not “identify gaps”: a systematic review is about a research question which is already specified, but for which more information is needed. Thus, the main function of the advice to first do a systematic review is to know whether the research question that one has in mind has not yet been solved by others. Perusing the literature in depth is absolutely needed, for example, before embarking on a randomized trial or on a major observational study. However, this is not the same as doing a formal systematic review. In-depth scoping of the literature will suffice. If it is found that potentially valuable studies already exist on the research question that one has in mind, then the new study that one is thinking about may be discarded, and a systematic review should be done instead.

Intermezzo: specific schemes to structure reasoning

Specific schemes have been proposed to guide our reasoning between the stage of delineation of the “gap in knowledge” and the stage of proposing the research design.

The acronym FINER (feasible, interesting, novel, ethical, and relevant) was coined by Hulley and Cummings 2 and denotes the different aspects that one should consider to judge a budding research proposal. These words are a good checklist for an in-depth self-scrutiny of your research. The central aspects are the feasibility and whether the possible answers are exciting (and/or much needed).

The PICO format (Patient, Intervention, Control or Comparison, Outcome) is advocated by the evidence-based medicine and Cochrane movements and is very useful for clinical therapeutic research, particularly randomized controlled trials (RCTs). 1 , 42 Questions about therapeutic interventions are highly specific, for example, a particular chemotherapeutic scheme (the intervention) is proposed to study survival (the outcome) among young women with a particular form of stage III breast cancer (the patients). This framework is less useful, and becomes a bit pointless, for etiologic research about generalizable questions such as: “Does smoking cause lung cancer?” which applies to all humans and to different types of smoking. Of course, all research will be done in particular population, with particular smoking habits, but this does not necessarily define the research question. Some of the first investigations about smoking and lung cancer were done in male doctors aged ≥35 years in the UK 43 – this was a very convenient group to research, but being a male doctor in the UK is not part of the research question.

The PICO format is thus most applicable for pragmatic research. A much more detailed and elaborate scheme for pragmatic research was proposed by the US Patient-Centered Outcomes Research Institute (PCORI) which has published Methodology Standards, including “Standards for Formulating Research Questions”. While we would not agree with all six standards, junior investigators may find the structure useful as they think through their options – especially for pragmatic research questions. 44

Counterfactual reasoning 3 emphasizes those aspects of the “ideal randomized trial” that should be mimicked by an observational study. A key question is whether your study is addressing a hypothesis that could in theory be studied in a randomized trial. For example, if the research question is “does smoking cause lung cancer?”, then this is a question that could in theory (but not in practice) be addressed by randomizing study participants to be smokers or nonsmokers. In this situation, it may be useful to design your observational study with the intention of obtaining the same answer that would have been obtained if you had been able to do a randomized trial.

However, the aims of explanatory observational research are different from those of randomized trials. 27 Explanatory research about disease etiology may involve “states” like being female, being old, being obese, having hypertension, having a high serum cholesterol, carrying the BrCa1 gene, and so on, as causes of disease. None of these causes are interventions. In contrast, RCTs focus on what to do to change particular causes: which interventions are feasible and work? For example, being female might expose a person to job discrimination; the intervention might be to have women on the appointment committee or to use some kind of positive discrimination. Likewise, the gene for phenylketonuria leads to disease, but the intervention is to change the diet. For carriers of BRCa1 genes, different strategies can be evaluated in RCTs to evaluate their effectiveness in preventing premature death due to breast cancer: frequent screening, prophylactic mastectomy, hormone treatment, and so on – which may have different effects. For obesity or hypertension or hypercholesterolemia, different types of interventions are possible – with potentially different effects and different adverse effects.

The interventionist outlook, that is, trying to mimic an RCT, can be very useful, for some type of observational studies, for example, about the adverse effects of drugs. It helps to make certain that one can mimic an “intervention” (ie, patients starting to use particular drugs) that is specific and consistent in groups of patients that are comparable (more technically, exchangeable – meaning that the results of the investigation would not change if the persons exposed and nonexposed were swapped). These conditions can be met in a credible way, if there are competing drugs for a similar indication, so that there is an active drug comparator: the interventions (use of different drugs in different patients) will be well defined, and the patients on the different drugs will tend to be comparable. This works particularly well if you are focusing on adverse drug effects that were unknown or unpredictable at the time of prescription. 45 , 46 For example, you may obtain more valid findings in a study that compares the adverse effects of two different beta agonists for asthma care (ie, two different drugs within the same class), than to design a study which compares patients who are prescribed beta agonists with patients who are prescribed other asthma medication, or no medication at all – because the latter might be a highly different group of patients. 47

As mentioned, there are some important studies about causes of diseases where a randomized trial is not feasible, even in theory. In particular, there are various “states” which are major causes of disease (obesity, cholesterol, hypertension, diabetes, etc). These states strongly affect the risks of disease and death, but cannot be randomized. For example, it is difficult to conceive of randomizing study participants to be obese or not obese; however, we could randomize them for the reduction of obesity, for example, through exercise, but such a study would assess the effects of a particular intervention, not of obesity itself. Still, it remains important to estimate the overall effects of obesity, that is, to answer the question “would this group of people have had different health status, on the average, if they had not been obese”. In this situation, the concept of “interventions” is not relevant to designing your study (at least in the way that the term “intervention” is commonly used). What is more relevant is simply to focus on the counterfactual contrast which is being assessed (eg, a body mass index [BMI] of 35 versus a BMI of 25), without specifying how this contrast came about.

A technique that has gone hand in hand with counterfactual reasoning in epidemiology is drawing DAGs; several introductions to DAG theory can be found in epidemiologic textbooks. 3 , 48 DAGs can be useful in the brainstorming phase of a study, after the general research question has been defined. At this stage, a general structure for the study is envisaged and the complexity of the causal processes needs clarification. A DAG can be extremely useful for illustrating the context in which a causal question is being asked, the assumptions that will be involved in the analyses (eg, whether a particular risk factor is a confounder, a mediator, or a col-lider), and help us question the validity of our reasoning. 49 Using DAGs helps us also decide which variables we need to collect information on and how they should be measured and defined. Given that DAGs root in causal thinking, their construction is, of necessity, subjective.

Preparation: pilot study, protocol, and advance writing

Doing a pilot study and collecting ancillary information about feasibility.

May I now start? is a question heard after lengthy deliberations about the research question and the potential studies that follow from it. Such deliberations almost invariably produce a lot of enthusiasm and exhilaration – because they are fun. The researcher wants to begin collecting data or start the analysis. However, Crombie and Davies, in their chapter about “Developing the research question” state emphatically: “Don’t rush into a study”. 16 Separate from doing a pilot study, which is about the procedures of your study, you may also need to collect ancillary information before actually starting your study.

Pilot study

Even if you think you are totally certain of what you want, you should first do a pilot study, based on a brief protocol. 2 , 22 That initial protocol should be easy to write. You have already discussed the aim and design of your study. Write them down. You expect a particular type of information that is essential and that will tell the essence of your message (a particular 2-by-2 or X-by-Y table, a particular graph), which you can describe.

Pilot studies are not done to know the likely direction of the results; instead, the aim is to see whether you will be able to perform the procedures of your study – and ultimately whether that really is the study you want to do. 50 The aim is to save yourself from embarrassment: data that very surprisingly do not turn out to be what you expected, questionnaires that are misunderstood or do not deliver the answers that you need or that are not returned, laboratories that do not produce, patients who do not show up, heads of other departments who block access to their patients or materials, or yourself who needs more time to manage the complexity of the undertaking.

We have never heard of someone who was sorry for having done a pilot. Conversely, we know many persons who found out at much personal embarrassment and institutional cost that their project was unfeasible. In intermediate cases, the pilot may show the need to change questionnaires or procedures before the study goes ahead.

In principle, a pilot study should be exactly like your final study and test out all your procedures on a small number of persons. Often, it is better to approach the task piecemeal and pilot different aspects of the research one by one.

A tough question is how to do pilot studies and pilot analyses when ethical or institutional review board approval is necessary for some of the actions in a pilot study. One solution might be to avoid piloting some procedures; for example, try parts of the procedure – for example, you may not be able to randomize in a pilot, but you may be able to try out data collection procedures and forms. There is a degree of circularity about piloting, also in obtaining funding, as one may need funding for the pilot. In practice, the best step might be to ask the ethics committee or review board of your institute which aspects of the research can be piloted and under what conditions.

In Appendix E , several questions that you might ask in pilot studies are listed. They may lead to profound reassessments of your research – particularly if you are piloting the collection of new data, but also if the research involves analyses of existing data.

Ancillary information

It may be necessary to collect additional information about event rates or standard deviations of measurements to calculate the statistical precision that might be obtained. Also, sometimes you need other ways of “testing the water” like procedures to streamlining data collection from different centers in order to know whether the study is feasible. Depending on the study size and importance, such activities may become studies in themselves and actually take a lot of time and money.

Advance writing of paper: before full data collection and/or analysis

Whitesides’ advice is:

The key to efficient use of your and my time is that we start exchanging outlines and proposals as early in a project as possible. Do not, under any circumstances, wait until the collection of data is ‘complete’ before starting to write an outline. 38

After the pilot study, you have a firm grasp of all elements that are necessary for a scientific paper: introduction, materials and methods, results, and discussion. In the introduction, you explain why you have done this research. Almost always, an introduction comprises three ideas: what is the general problem? what is the particular research question? what study will you perform to answer that question? This is followed by the materials and methods section. They have been extensively discussed and have been fine-tuned in the study protocol and the pilot study. Thereafter come the results sections. By now, you know what tables or figures you want and how you can obtain them, but not what the final numbers will look like. You will also have an idea about the auxiliary tables that you might need to explain your data to others (such as a table with the baseline characteristics or an additional table with a subgroup analysis). You can now draft the layouts of all these tables. Visualizing the presentation of your results in advance is the “bare minimum” of writing in advance.

Finally, the discussion section. Can you write a discussion before you know the final data? Of course you can; you even must think ahead. In principle, there are only three possible outcomes: the study can give the results that you hoped for; it can show the inverse; or something indeterminate in between. In all instances, you can imagine how you will react. One possibility is that you are disappointed by the results of your study, and you will tend to find excuses for why it did not produce the results you hoped for. What excuses might your produce? The other possibility is that it does show what you wanted; then you may have to imagine how others will react and what their objections might be. If the results are indeterminate, everybody might be disappointed, and you will need to explain the failure of your research to give clear-cut results. When you detect a specific weakness by imagining this situation, you may wish to change aspects of your study.

As we explain in Appendix F , there is no need to write a very extensive paper as a first draft – on the contrary, it might be more useful to write a short paper, which has the advantage that others will more readily read it and comment on it.

Never be afraid to discuss your study at all stages extensively with others, not only your immediate research colleagues but also semi-outsiders and also in this advance-writing stage. If you know, or are told by others, that a particular direction of your results might not be believed and therefore draw criticism because of some potential deficiency in your study, why not remedy it at this stage? Looking at what you have written, or by discussing potential results with others, you will be able to imagine more clearly what your readers and critical colleagues might object to.

Writing a paper beforehand is the ultimate test of whether the research project is what you wanted, whether your reasoning flows logically, or whether you forgot something. The initial draft will be a yardstick for yourself and for others – whatever happens during the course of your research. This will help you to surmount surprise happenings: you have written down where you started and why, and therefore you will also know very securely when and why you have to take a detour – or even a U-turn.

Writing is difficult and time-consuming. Writing a paper can easily take 5–10 revisions, which might span a full year (inclusive of the time it takes your supervisor or your colleagues to produce comments). During the writing, you will often be obliged to go back to the data and do additional or different analyses. Since your paper will need many revisions, and this will take such a long time, why not take a head-start at the beginning of your data collection? It will save frustration and lost time at the end of your project.

Many guidelines and advices exist about writing, both about the substance (how to use words and phrases) and about the process. All beginning researchers should have a look at some books and papers about writing, and seasoned researchers can still profit from rereading them. Several reporting guidelines exist for several types of studies (RCTs, observational, diagnostic research, etc). They are often very detailed, in describing what should be in title, abstract, and so on. Although they should not be mechanically adhered to, 28 they help writing. In Appendix F , we have collected some wisdom that we particularly liked; several books on writing are listed, as well as reporting guidelines that help researchers to craft papers that are readable and contain all the information that is necessary and useful to others.

Now you can start “your research”

After the piloting and after having written your paper, you are ready to start your data collection, your analysis, or whatever is needed to “do your research”.

The work that is needed before you can start to “do your research” will take a great deal of time and effort. What will you have achieved after setting up a piece of research following the lengthy and involved precepts of this paper? You will have specified a limited research question that you will solve. You will add one little shining stone to the large mosaic of science. At the time that you do the study, you may still be too close to see its effect on the overall picture. That will come over the years.

Further reading

Some texts that we mention in the paper might be especially worthwhile for further reading; see Appendix G .

Acknowledgments

We thank Miguel Hernán, Stuart Pocock, and Bianca De Stavola for their informative comments on an earlier draft manuscript, as well as two anonymous reviewers of Clinical Epidemiology . The Centre for Global NCDs is supported by the Wellcome Trust Institutional Strategic Support Fund (097834/Z/11/B). This work was also supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013 / ERC grant agreement number 668954).

The authors report no conflicts of interest in this work.

WashU Libraries

Conducting research.

• The Process

How to choose a topic

Testing your topic, formulate your research strategy, types of sources.

• Step 2: Finding background info.
• Step 3: Gathering more info.
• Get it This link opens in a new window
• Step 5: Evaluating your sources
• Step 6: Citing your sources
• FAQs This link opens in a new window
• Library Vocabulary
• Research in the Humanities
• Research in the Social Sciences
• Research in the Sciences

Information Overload: Narrowing your Research

Overwhelmed with too many or irrelevant results? Consider the following questions for refining your topic:

• Is there a specific time period you want to cover?
• Is there a geographic region or country on which you would like to focus?
• Is there a particular aspect of this subject that interests you? For example, historical influence, sociological aspects, ethical issues, cultural significance.
• Is there a specific group or individual you could research?

You can also combine multiple questions to further narrow your subject.

Information Desert: Broadening your Research

When exploring your research focus, consider the following questions for broadening your topic:

• What elements could you add to your paper? For example, expanding the time period or changing the geographic location. 
• What other issues are involved in this research?
• What is the bigger concept of your subject?

The very first step in the research process is choosing a topic that is not too broad or too narrow in scope.

To help you define a good topic you are advised to do one or all of the following:

• use reference sources (such as encyclopedias );
• consult other sources as suggested on the page find and read background information ;
• state your topic as a question (e.g., Can sleep disorders effect academic success in college students?);
• identify the main concepts or keywords in your question (e.g., college students, grade point average, sleep disorders);
• consult with your instructor or TA;
• or consult with a subject librarian who specializes in the field of study you are researching.

If you think you have a good topic or are getting close, try applying your topic ideas to the questions listed below.

Test the main concepts or keywords in your topic by looking them up in the appropriate background sources or by using them as search terms in the WUSTL Discovery Catalog and in library databases .

• If you are finding too much information and too many sources, narrow your topic by using the and operator: college students and grade point average and sleep disorders.
• Finding too little information may indicate that you need to broaden your topic. For example, look for information on students, rather than college students.
• Link synonymous search terms with or : academic achievement or grade point average or school failure.
• When you use a truncation symbol, most often the asterisk (*), the system will search for all terms and phrases starting with the word stem that appears before the symbol.  For example, searching "sleep disorder*" will yield results including disorder, disorders, disordered, etc. This will broaden your search and increase the number of items you find.

Once you have identified and tested your topic, you're ready to take the next step, finding background information .

The steps to your research strategy will depend on how much time you have and the type of project on which you are working. In order to conduct effective research, you need to gather appropriate information for your topic. Consider the following questions to help you determine the best research strategy:

How much time do you have?

If you have limited time, it is advisable to focus your information gathering on articles from journals, magazines, newspapers and on books which are in the library or on the web.

If you have more time to plan your research, you will be able to incorporate a variety of materials on your topic and to obtain resources from other libraries .

On what type of project are you working?

The depth of research will depend on the nature of your project. You may need to consider the guidelines specified by your professor on the length of paper or presentation.

What type of information do you need?

Your approach to the topic will determine the type of resources you will use. For example, some research may involve collecting facts, while other research may include gathering various opinions on an issue or argument. You may also want to consider whether your topic will be enhanced by including primary resources. The following types of resources may serve as a guide:

• Internet resources
• Book reviews
• Dissertations
• Statistical information
• Music scores
• Sound recordings
• Internet reference sources
• Government documents
• Manuscripts

Do you need primary sources? Secondary sources? Both?

"You need to consider whether your project requires primary or secondary sources and, if you will use both, whether a particular work is a primary or a secondary source in the context of your work. Primary sources are basic materials with little or no annotation or editorial alteration, such as manuscripts, diaries, letters, interviews, and laboratory reports. Secondary sources derive from primary materials and include analysis, interpretation, and commentary on primary materials."

"Depending on the point of view of your research paper, a given source may be either primary or secondary. A research paper on William James, the nineteenth-century philosopher, would treat R.W.B. Lewis's The Jameses: A Family Narrative as a secondary source, whereas a paper on Lewis, a well-known critic and biographer, would treat the same book as a primary source. Your assignment may require you to emphasize either primary or secondary sources or to use a combination of the two." -- (Slade, Carole. Form and style. Boston : Houghton Mifflin Co., c1997.)

Primary sources  can be tricky.  Whether a source is  primary  depends on how you use it. A primary source is a written text, artifact, or other original creation upon which you focus your analysis and interpretation. For example, an article that analyzes a book, song, or society would be considered a secondary source. However, that article could function as a primary source--if you are analyzing the ideas of the author of that article, then it functions as a primary source. So anything could function as a primary source--just consider how you are using it: if it's the object of your analysis, then it's a primary source.

A  secondary source  is a work that interprets or analyzes an historical event or phenomenon. It is generally at least one step removed from the event is often based on primary sources. Examples include: scholarly or popular books and articles, reference books, and textbooks.

Tertiary sources are encyclopedias, dictionaries, textbooks and other reference materials that provide broad overviews of particular topics. Where secondary sources summarize and interpret an event or phenomenon, tertiary sources summarize and interpret other resources. They can be a great place to begin studying unfamiliar topics.

• << Previous: The Process
• Next: Step 2: Finding background info. >>
• Last Updated: Apr 11, 2024 3:23 PM
• URL: https://libguides.wustl.edu/research

What (Exactly) Is A Research Proposal?

A simple explainer with examples + free template.

By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020 (Updated April 2023)

Whether you’re nearing the end of your degree and your dissertation is on the horizon, or you’re planning to apply for a PhD program, chances are you’ll need to craft a convincing research proposal . If you’re on this page, you’re probably unsure exactly what the research proposal is all about. Well, you’ve come to the right place.

Overview: Research Proposal Basics

• What a research proposal is
• What a research proposal needs to cover
• How to structure your research proposal
• Example /sample proposals
• Proposal writing FAQs
• Key takeaways & additional resources

What is a research proposal?

Simply put, a research proposal is a structured, formal document that explains what you plan to research (your research topic), why it’s worth researching (your justification), and how  you plan to investigate it (your methodology). 

The purpose of the research proposal (its job, so to speak) is to convince  your research supervisor, committee or university that your research is  suitable  (for the requirements of the degree program) and  manageable  (given the time and resource constraints you will face). 

The most important word here is “ convince ” – in other words, your research proposal needs to  sell  your research idea (to whoever is going to approve it). If it doesn’t convince them (of its suitability and manageability), you’ll need to revise and resubmit . This will cost you valuable time, which will either delay the start of your research or eat into its time allowance (which is bad news). 

What goes into a research proposal?

A good dissertation or thesis proposal needs to cover the “ what “, “ why ” and” how ” of the proposed study. Let’s look at each of these attributes in a little more detail:

Your proposal needs to clearly articulate your research topic . This needs to be specific and unambiguous . Your research topic should make it clear exactly what you plan to research and in what context. Here’s an example of a well-articulated research topic:

An investigation into the factors which impact female Generation Y consumer’s likelihood to promote a specific makeup brand to their peers: a British context

As you can see, this topic is extremely clear. From this one line we can see exactly:

• What’s being investigated – factors that make people promote or advocate for a brand of a specific makeup brand
• Who it involves – female Gen-Y consumers
• In what context – the United Kingdom

So, make sure that your research proposal provides a detailed explanation of your research topic . If possible, also briefly outline your research aims and objectives , and perhaps even your research questions (although in some cases you’ll only develop these at a later stage). Needless to say, don’t start writing your proposal until you have a clear topic in mind , or you’ll end up waffling and your research proposal will suffer as a result of this.

Need a helping hand?

As we touched on earlier, it’s not good enough to simply propose a research topic – you need to justify why your topic is original . In other words, what makes it  unique ? What gap in the current literature does it fill? If it’s simply a rehash of the existing research, it’s probably not going to get approval – it needs to be fresh.

But,  originality  alone is not enough. Once you’ve ticked that box, you also need to justify why your proposed topic is  important . In other words, what value will it add to the world if you achieve your research aims?

As an example, let’s look at the sample research topic we mentioned earlier (factors impacting brand advocacy). In this case, if the research could uncover relevant factors, these findings would be very useful to marketers in the cosmetics industry, and would, therefore, have commercial value . That is a clear justification for the research.

So, when you’re crafting your research proposal, remember that it’s not enough for a topic to simply be unique. It needs to be useful and value-creating – and you need to convey that value in your proposal. If you’re struggling to find a research topic that makes the cut, watch  our video covering how to find a research topic .

It’s all good and well to have a great topic that’s original and valuable, but you’re not going to convince anyone to approve it without discussing the practicalities – in other words:

• How will you actually undertake your research (i.e., your methodology)?
• Is your research methodology appropriate given your research aims?
• Is your approach manageable given your constraints (time, money, etc.)?

While it’s generally not expected that you’ll have a fully fleshed-out methodology at the proposal stage, you’ll likely still need to provide a high-level overview of your research methodology . Here are some important questions you’ll need to address in your research proposal:

• Will you take a qualitative , quantitative or mixed -method approach?
• What sampling strategy will you adopt?
• How will you collect your data (e.g., interviews, surveys, etc)?
• How will you analyse your data (e.g., descriptive and inferential statistics , content analysis, discourse analysis, etc, .)?
• What potential limitations will your methodology carry?

So, be sure to give some thought to the practicalities of your research and have at least a basic methodological plan before you start writing up your proposal. If this all sounds rather intimidating, the video below provides a good introduction to research methodology and the key choices you’ll need to make.

How To Structure A Research Proposal

Now that we’ve covered the key points that need to be addressed in a proposal, you may be wondering, “ But how is a research proposal structured? “.

While the exact structure and format required for a research proposal differs from university to university, there are four “essential ingredients” that commonly make up the structure of a research proposal:

• A rich introduction and background to the proposed research
• An initial literature review covering the existing research
• An overview of the proposed research methodology
• A discussion regarding the practicalities (project plans, timelines, etc.)

In the video below, we unpack each of these four sections, step by step.

Research Proposal Examples/Samples

In the video below, we provide a detailed walkthrough of two successful research proposals (Master’s and PhD-level), as well as our popular free proposal template.

Proposal Writing FAQs

How long should a research proposal be.

This varies tremendously, depending on the university, the field of study (e.g., social sciences vs natural sciences), and the level of the degree (e.g. undergraduate, Masters or PhD) – so it’s always best to check with your university what their specific requirements are before you start planning your proposal.

As a rough guide, a formal research proposal at Masters-level often ranges between 2000-3000 words, while a PhD-level proposal can be far more detailed, ranging from 5000-8000 words. In some cases, a rough outline of the topic is all that’s needed, while in other cases, universities expect a very detailed proposal that essentially forms the first three chapters of the dissertation or thesis.

The takeaway – be sure to check with your institution before you start writing.

How do I choose a topic for my research proposal?

Finding a good research topic is a process that involves multiple steps. We cover the topic ideation process in this video post.

How do I write a literature review for my proposal?

While you typically won’t need a comprehensive literature review at the proposal stage, you still need to demonstrate that you’re familiar with the key literature and are able to synthesise it. We explain the literature review process here.

How do I create a timeline and budget for my proposal?

We explain how to craft a project plan/timeline and budget in Research Proposal Bootcamp .

Which referencing format should I use in my research proposal?

The expectations and requirements regarding formatting and referencing vary from institution to institution. Therefore, you’ll need to check this information with your university.

What common proposal writing mistakes do I need to look out for?

We’ve create a video post about some of the most common mistakes students make when writing a proposal – you can access that here . If you’re short on time, here’s a quick summary:

• The research topic is too broad (or just poorly articulated).
• The research aims, objectives and questions don’t align.
• The research topic is not well justified.
• The study has a weak theoretical foundation.
• The research design is not well articulated well enough.
• Poor writing and sloppy presentation.
• Poor project planning and risk management.
• Not following the university’s specific criteria.

Key Takeaways & Additional Resources

As you write up your research proposal, remember the all-important core purpose:  to convince . Your research proposal needs to sell your study in terms of suitability and viability. So, focus on crafting a convincing narrative to ensure a strong proposal.

At the same time, pay close attention to your university’s requirements. While we’ve covered the essentials here, every institution has its own set of expectations and it’s essential that you follow these to maximise your chances of approval.

By the way, we’ve got plenty more resources to help you fast-track your research proposal. Here are some of our most popular resources to get you started:

• Proposal Writing 101 : A Introductory Webinar
• Research Proposal Bootcamp : The Ultimate Online Course
• Template : A basic template to help you craft your proposal

If you’re looking for 1-on-1 support with your research proposal, be sure to check out our private coaching service , where we hold your hand through the proposal development process (and the entire research journey), step by step.

Psst… there’s more!

This post is an extract from our bestselling short course, Research Proposal Bootcamp . If you want to work smart, you don't want to miss this .

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51 Comments

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Bundle of thanks to you for the research proposal guide it was really good and useful if it is possible please send me the sample of research proposal

You’re most welcome. We don’t have any research proposals that we can share (the students own the intellectual property), but you might find our research proposal template useful: https://gradcoach.com/research-proposal-template/

Cheruiyot Moses Kipyegon

Thanks alot. It was an eye opener that came timely enough before my imminent proposal defense. Thanks, again

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• Schools & departments

Developing your own research idea

How do you know if your own research idea is suitable for doctoral study? There are many factors you should consider, including time, topic, size and supervisor availability.

Is it the right time?

We recommend you start planning your research application one year in advance.

Be aware of funding deadlines and make sure you apply on time, regardless of whether you are still waiting on information from a prospective supervisor, for example. It is essential you apply before the deadline.

If you will need an international student visa in order to study in the UK, then you should leave enough time to process your visa application before you begin your studies.

Is it the right topic?

Many prospective students are interested in studying at Edinburgh because of our excellent reputation for research, but it is still worth checking that we offer the type of PhD and specialism in research that you are interested in.

Look at the websites for the academic school, institute or research centre that hosts the field you’re interested in. Check whether they specialise in the area you are interested in, and look for information on their outputs and the impact of their research.

It’s also worth checking if a project is already available in the field you wish to research.

PhD research projects

Is it the right size and scope?

Is your research idea the right size and scope to undertake over a four-year period?  Will the subject matter sustain your interest for an extended period of intense research?

It is often useful to begin writing your research proposal in order to define your project and determine whether the scope is sufficient, or even too much.

How to write a good proposal

Is the right supervisor available?

Many programmes will tell you to talk with a potential supervisor before applying. At the very least you should have an awareness of who the experts are in your field. If you’re considering a specific programme, you should think about who will you be working with and who will supervise your research.

How to find the right supervisor

How to Research: Ultimate Guide [+Online Tools]

The ability to effectively research is a skill that every student needs to succeed in their educational career. However, most people don’t really understand what research entails. Does it mean spending hours at your university library exploring archives? Or is searching for information online from the comfort of your home enough? And why can’t you just rely on Wikipedia, after all?

Our specialists have created this guide for students who feel lost when putting together an essay, paper, or presentation. Here, we will describe how to research in a detailed, step-by-step manner. We have also provided links to useful tools and resources that will help you along the way. First of all, let’s cover the definitions.

❓ What Is Research?

• Develop a Topic
• Look Through Sources
• Evaluate the Sources
• Write Your Paper
• Cite Your Sources

💡 9 Online Tools for Research

Research refers to the systematic process of discovering information and developing knowledge. We use it to understand new topics and to gain more insight into known issues. This happens through the collection and analysis of relevant data. The ability to research efficiently is one of the most fundamental skills in academia.

Any type of research will include the following features:

• A sound hypothesis on which the rest of the study is based. It will be either proven or disproven by the evidence gathered.
• Systematic investigative methods . These are controlled and follow a pre-established set of rules.
• Logical analysis . It follows a set procedure that involves deductive and inductive reasoning.
• Empirical data based on actual observation and evidence.
• Analytical study of the findings . This ensures in-depth exploration and minimizes mistakes.
• Creation of new questions and new lines of inquiry about the subject via the research.

With that being said, a research paper is more than just the sum of its sources. Its primary purpose is to analyze or argue a particular perspective. In the end, your thoughts and ideas should be the ones you investigate. The evidence you discover during the research process will be the basis for your hypothesis.

There are three universal purposes of research that you should know about:

📚 How to Research: Step-by-Step Guide

As all the definitions you need are covered, we can proceed to learn about the process itself. We have developed this guide so that you won’t have any trouble conducting your research. In the image below, you can see all the required steps.

In the following sections, you will examine each step in detail. Also, you’ll see the reasons why our tips are practical and how to find sources for your research. Good luck!

1. Develop a Topic

1.1. pick or create a topic.

The first step to research is landing on the right idea. This process isn’t always easy, especially when you aren’t familiar with the chosen area of study. However, don’t fret. You can always change your topic later.

Let’s explore how to select your first research idea.

Research is always conducted for a particular reason. It will always relate to writing a paper, creating a project, validating existing results, etc. Your research depends on the goal of your assignment.

The answers will help you define the direction of your work:

• Do you have a list of pre-assigned topics? Can you come up with one yourself?
• What is the due date for your work? How much time does that leave for research?
• What is the scope of your assignment? (Presentation length, number of words/pages, etc.)
• Are there any specific requirements regarding the sources that you are allowed to use?
• Is it essential to use recent information and current sources?

When you have the answers to all the key questions, you can think of your topic. The following tips will help you:

• Choose an idea that is relevant to your assignment. Usually, your instructor will give you detailed instructions before you start working. If you are unsure about your guidelines, don’t be afraid to ask for clarification.
• Ensure that there are enough resources for you to use. When you think of an idea, do a quick preliminary search. It will allow you to determine whether there is enough available information on your topic. Take time to validate those resources and make sure they’re reliable.
• Search for a topic that is not too broad or too narrow. This step directly correlates with the one above. If you are finding too much general information, narrowing down your search might be a good idea. However, if you struggle to find credible sources, it could be a sign to broaden your topic.
• Try to be original. Restating the same ideas that have been explored thousands of times could damage your grade. Chances are, your instructor has heard it all before and isn’t all that interested in hearing it again. Yet, choosing an unconventional approach with a fresh perspective might earn you extra credit for creativity.
• Aim to find an area that will be interesting to explore. If you find a topic that you, personally, are curious about, researching it will be much more pleasant. This way, when you start writing or searching for information, you might actually enjoy the process.

1.2. Formulate Research Questions

As soon as you have chosen a topic, take the time to format it correctly. Wording it as a question will ensure that your focus is precise and nuanced.

And here is how you create research questions:

Step 1 : Do some research.

Take a look at the most recent discussions and debates on your selected topic. You can check out academic journals and scholarly conferences. Keep your focus on the main arguments to acquaint yourself with the concepts.

Step 2 : Try narrowing down your topic.

It is a lot more effective to target a single dimension of a broader topic than to tackle everything. To do this, try focusing on a particular aspect, such as a specific location or time period. You can also aim to discuss certain debates or issues that exist within the topic.

Step 3 : Keep your audience in mind.

There is a difference between crafting a presentation for your classmates and writing a research paper. Your audience will determine the level of detail that goes into your question.

Step 4 : Ask questions.

Once you have considered the above steps, it is time to begin asking yourself questions. Make sure they’re open-ended and start with ‘why,’ ‘how,’ or ‘what.’

Step 5 : Evaluate your questions.

After you come up with a couple of ideas, jot them down on paper. Look back at all the requirements for a successful research question. Which one of them will be the most effective for your assignment?

1.3. Choose a Research Strategy

To develop constructive research questions, you will need to conduct an initial survey of your resources. Take everything you’ve learned so far as your foundation. Now, you will need to create an efficient strategy for your further actions.

Your research strategy will depend on the following:

1.4. Figure out Keywords

With your research questions, strategy, and some background info covered, it will be easier to determine the keywords . They will help you look for resources and locate your work in the future. Over here, see how to work with keywords.

Once you have a selection of keywords, you can improve them by doing the following:

• Break them into related concepts. By the end, you should have four or five columns with associated keywords.
• Choose one keyword from each column. Use your library’s search engine to look them up. Don’t forget to type ‘AND’ in-between the words. It will narrow down the search so that only articles containing all the selected keywords will appear.
• Explore the results! Don’t be afraid to try several different combinations. You should also make sure to list all those keywords that bring you the most valuable results.
• If you don’t have enough results, try using fewer keywords. Alternatively, you can try to make your keywords broader.
• If you have too many results, try using more keywords. Alternatively, you can try to make your keywords narrower.
• Pay attention to which articles are the most relevant to your needs. Make sure to save them and skim them for a list of keywords. Write them down, and create a new list!
• Once you have exhausted your first list, you can create another one. Run another search following these steps. Don’t forget to note down the relevant materials – you’ll need them for your citations!

1.5. Improve Your Topic

As we mentioned above, you can change and refine your topic as many times as you need before you begin writing. That is why in this section, we will talk about how to polish and improve your idea. At the very least, we’ll give you tips on how to format it correctly.

First of all, we need to make sure that your topic is researchable. To accomplish this, answer the 5 ‘w’ questions :

• Why are you choosing this particular topic? How is it interesting or different from the rest? What is your stance on the matter?
• What are the main issues your topic is trying to explore? Is it controversial? What other opinions and questions exist on the subject?
• Who is talking about the topic? What points of view exist, and who is giving them? What is their agenda?
• When was this topic discussed? Is the issue recent or historical? Does the time frame matter?
• Where lays the importance of your topic? Is it debated on an international, national, or local level? Is there a particular place that is more affected than the rest of the world?

After answering these questions, you need to evaluate your idea from these two perspectives:

• Is your topic too broad?

It may happen if you find far too much information on the subject that doesn’t seem relevant. You will want to narrow it down and include some specifics, such as:

• Place (country, city, street, part of the world, etc.);
• Time (year, era, century, etc.);
• Populace (ethnicity, gender, age, occupation, etc.);
• Event or characteristic (historical occurrence, institutional perspective, etc.);
• Individual or group (a particular point of view, specific person or persons, etc.).
• Is your topic too narrow?

If you are discovering too few sources to build a proper case, your topic is too narrow. Try to broaden it using the following methods:

• Remove some of the specifics (place, time, populace, etc.).
• Expand some of the specifics (place, time, populace, etc.).
• Use synonyms to reword your topic.
• Look in other databases to broaden your horizons.
• Consider looking into a less current issue (the newer an idea is, the harder it is to find sources).

2. Look Through Sources

2.1. determine possible sources.

By this time, you most probably looked for background information on your topic a couple of times. Now it’s time to look for more specific info.

For starters, get the keywords you’ve chosen and see if there is enough information available. You can start by checking appropriate titles in the online libraries. Look for sources in encyclopedias and dictionaries to overview what books or articles you can use.

You can use the following websites for this purpose:

• Oxford English Dictionary
• Wordreference.com
• Encyclopedia Britannica Online
• Oxford Reference Online

Apart from encyclopedias and dictionaries, there are, of course, other places you can check. For instance, you can search for books in your local or university library . When you look through the text on the shelf, pay attention to the books nearby – they can become useful too in the subject area.

Additionally, you can find information in your textbooks and assigned readings. Use your library’s electronic databases that keep magazines and newspapers on the topic. In case you are not sure how to do that, ask your librarian. Also, use search engines to locate materials on the Internet. These types of sources will be helpful when looking for generic information.

2.2. Skim Some Books

When it comes to using books for your research, both hard and electronic copies work as well. In this section, we will tell you how to use them for your research.

If you are a student, you probably do not have time to read every single book. When working on a short paper, essay, or presentation with limited time, you are simply looking for citations. Luckily, there is no need to waste your time examining each book thoroughly. Skimming is enough to understand if the source works for you or not.

To get the needed information in the book, look at the following elements:

• Title Page. There, you can find all the essential details about the book, the author’s name, title, the publisher’s name, the date of publication, etc.
• Table of Contents. This part provides you with a list of all the chapters in the book. You can get a general idea of what topics the author covered.
• List of Illustrations. In some books, authors use illustrations, tables, drawings to support the arguments and the facts. Looking through them can help you see the stats or some other facts quickly.
• Preface or Introduction. Usually, this part of the book provides the author’s intentions and the purpose of the book. Read it to see whether the book’s topic is necessary for your research.
• Bibliography. This part of the book provides a list of materials that the author used. You can check the bibliography for additional resources or references.
• Index. Skimming an index is excellent for identifying where the relevant information is located in the book. It can also give you some additional keywords that might be helpful for your research.

How to Find Books: Free Resources

You can find paperback books in your school’s library or ask your professor if he can lend you some helpful resources. To look for ebooks, we recommend using one of the following services:

For more free books and textbooks, check out the list of online learning resources for different subjects.

2.3. Find Relevant Articles

Scholarly articles are essential parts of every research. Even small argumentative essays usually contain citations from these resources. Here, we will explain how to work with them.

But first, you have to understand how to differentiate based on where these articles are being published. There are two types:

• Peer-reviewed journals

These journals include articles written by an expert in the field. Another expert (experts) read the article and provided feedback. Thus, the author implemented the needed changes based on the review.

• Scholarly journals

Experts write articles for these journals. They address the papers to other academics in the same field. Usually, scholarly journals are written by professional associations or academic press.

Usually, students can use academic and scholarly journals interchangeably. However, you should ask your instructor to explain if sources called “academic” are acceptable.

Not to read every single piece of writing, you need to learn how to identify if the article is credible or not. For that, pay attention to the following elements:

• Author. Look out for the author’s degrees and credentials. Additionally, see if they are a member of any association or work at a university or official organization.
• Intended audience. Understanding the article’s aim is essential. If the author intends to entertain and inform the general public, it may not be the best source for a student. You can still read and learn from without citing.
• Publication type. Some of the ways to recognize the type are:
• Go online and read the sections’ “aims and scope.”
• Check the visual appearance. If the article has colorful images and graphics, it is most probably written for the general public.
• Structure. You can also look at the length and formatting of the article. If it has a clear organization with headings, then most probably, the piece is scholarly. Same with the size. Short papers (with less than five pages) in general are likely to be not academic articles.
• Style. Examine the language, the point of view, and the tone of the article. If the document has many technical terms and professional jargon, then it is usually scholarly or peer-reviewed. Ask yourself what level of education one needs to comprehend the text entirely.

If all of the following parameters fit your expectations, you can only start by reading and analyzing the article.

How to Find Articles: Free Resources

Not sure where to look for articles? Check the following resources that our team recommends:

2.4. Examine Useful Databases

If you still don’t know what sources to use, you can study databases. These collections contain many high-quality books and articles and conference presentations, video lectures, illustrations, etc. In this section, see how to use them and how to benefit from doing this.

A database is a collection of stored and structured information, usually controlled by a dates management system (DBMS). Information is generally modeled in rows and columns in different tables. Thus, even your university’s online library can be considered a database.

Here are some crucial tips on using databases:

• AND ➡️ when you want to use both terms.
• OR ➡️ when you can choose either time.
• NOT ➡️ when you want to exclude words.
• Type asterisks, exclamation points, and questions marks. If you don’t use asterisks and wildcards, some databases will not provide the search you need. They are also beneficial in making your search more specific.
• Look out for the “subject search” option. This way, you will search for information located on the heading field. It is possible due to a system called controlled vocabulary .
• Improve your keywords. Try to be creative with your key phrases and words. Look for all the possible ways to express your topic by using synonyms and associated concepts.
• Try using parentheses . When you look for complex queries, use parentheses. They will allow you to group terms together.
• Search for clues. Carefully look for tips and hints in the results. Analysis of the trends, indications, and numbers can help you understand the information better.
• Check the stacks . Stacks are linear data structures that follow a specific pattern. As collections of elements, they can help you with one particular search.
• Look through different databases. You can look across other databases and combine what you’ve found. The more data you will consider, the more precise your results are.

Free Databases to Use for Research

There are many open-access databases that you can use when conducting your research. Our experts previously mentioned a lot of those in the sections about ebooks and scholarly articles.

Here are some more databases that you can find to be helpful:

We also recommend looking at the available open databases prepared by the University of California at Santa Barbara and Elmira College .

2.5. See Other Websites

Besides search engines and databases, there are other online resources that you can use as a starting point for your research. The only issue is that you might not know if the information is legit.

These websites are suitable for academic research:

• Educational sites (*.edu)
• Government sites (*.gov)
• News sites (CNN, NBC News, FOX News, etc.)
• Professional, nonprofit organizations (Unicef, WWF, etc.)
• General informative websites (Wikipedia)

Of course, you can use online resources for research. They are especially great when you’re looking for background information or defining the topic. Yet, one thing to keep in mind is to choose the websites and data from them carefully.

Here are some cons of using these online sources:

• Unreliable. Anyone can write websites, and they are rarely checked for accuracy, bias, and credibility. They are also regularly filled with old content.
• Chargeable. A lot of websites are free of charge. Yet, very often, to read the full article or cite the page you need, you have to pay.
• Tricky to cite. Most websites do not have any citation tools, so it can be hard to add them as references.
• Unstable. Websites are usually not permanent. Both the content and the address change – the link might not be available later on.

Free Websites to Use for Research

Using different websites for background information search and a general understanding of a given topic makes total sense. But when needed, you can use them for actual research.

For this purpose, we recommend the following websites:

3. Evaluate the Sources

3.1. select what sources to use.

By this step, you have collected many sources for your work. Now is the time to sort through them and get rid of the ones you don’t need. Here, we will explain how to choose appropriate sources for your research.

When checking the quality and credibility of a source, use this checklist:

3.2. Take Notes

When you have sorted through your sources, you can start reading through them at length. You will still have the opportunity to filter out unneeded information. To accomplish this, we recommend marking down the relevant fragments that you will use in your work.

We advise you to study your sources in the following order:

Step 1 : Skim through the text.

Don’t immediately spend an excessive amount of time reading paragraphs and paragraphs of text. First, run through the source to identify the most relevant passages and headings. Note any words or terminology that catch your eye. It will allow you to form a rough idea of the author’s main arguments.

Step 2 : Ask questions.

After you finish skimming through the text, write down any questions that formed in your mind. Make sure that you keep them relevant to your topic. These questions will help you figure out what information you are hoping to obtain from the source.

Step 3 : Underline or highlight.

It’s time to read the source actively. Grab a highlighter or a pen and note down anything that seems relevant or interesting. Pay special attention to the passages that caught your eye earlier. Once you find answers to your questions (or think of even more questions), make sure to jot them in the margins.

Step 4 : Summarize .

As you have finished reading, write down a quick summary of your findings. Do this immediately after you finish while the information is still fresh in your mind. Organize your notes and look up any terminology that isn’t familiar. Also, take a quick look at the bibliography provided by the source – you could find something useful!

Step 5 : Write down key information.

Before moving on to the next source, don’t forget to note everything you need for the bibliography. Write down the title, the author’s name, the publisher, and the date of publishing. If you are using a website, save the URL. Double-check which citation format you’re required to use.

4. Write Your Paper

4.1. formulate your thesis.

A thesis statement is often referred to as the heart of your work since it contains the main idea and stance of the author. The writing process starts with figuring out what you want to say. State it in one sentence, referring back to all the research that you have conducted thus far.

Here are a few tips you could use in writing a compelling thesis statement based on your research:

• State your point clearly. Your argument needs to be explicit and direct. Remember that you will have to address it within the limited confines of your work. There isn’t the space to consider too many points of view. That is why your audience must be clear on the direction your debate is going to follow.
• Be specific. You have to ensure that your wording is as clear-cut as possible. The thesis needs to state the exact idea you will be exploring. If you formulate it too vaguely, the content of your work will be all over the place. Polish your thesis until it becomes specific to your argument.
• Question what you think. To accomplish this, you will need to keep your target audience in mind. Consider what views your readers must have to understand the point you are trying to make. Your statement must be grounded to those who don’t necessarily have the same ideas as you.
• Showcase a strong position. Don’t forget that your thesis statement is a reflection of your comprehension of the topic. While it must be clear and coherent, it should also advance your unique position on the matter. Instead of simply making an observation about something, don’t hesitate to take a stance.

Formulating a successful thesis statement takes time and practice. It is likely that you will not get it completely right on your first try. If you feel like you need some training or require examples, try using our thesis statement generator .

4.2. Outline Your Paper

If you have reached this stage in your work process, it means that you have everything you need. You have composed a strong thesis statement and have your notes and arguments beside you. Now, you have to put them together in a logical order. This way, your reader will see your thought process clearly.

To organize your paper , try this approach:

• Determine the research problem. This isn’t just your thesis statement but is also the key to creating your title. It is the central point of your work. Try formulating it in a single sentence or phrase for efficiency.
• Identify the key arguments. Think of what points you are trying to make with your research. Very briefly note them in your introduction. You will proceed to explore and build on them throughout the rest of your paper.
• Formulate the first category. Consider which point you should cover first. Typically, it is a good idea to start with definitions and clarifications of any critical terminology. You may also want to introduce the background of a particular theory or concept you are exploring.
• Include subcategories if needed. For now, try listing them in the form of a bullet list. The subcategories should provide the basis and support the main points you’re making.
• Sum up and conclude. Once you have created the rough draft, tie everything together. Conclude your project and refer back to your thesis. Make sure that you haven’t strayed away from your research question in creating your outline.

If you have followed these steps, you should end up with a defined beginning, middle, and end. Naturally, different research papers will have carrying outlines. For example, a term paper will have a smaller number of subcategories than a dissertation. Moreover, some projects will require you to mention your research methods, results, etc. You can find more information on how to write an essay or another type of paper in specialized online guides.

4.3. Add Quotes and Examples

To prove that you aren’t making up arguments on the fly, you should provide supporting evidence. You have to refer back to your sources and cite articles and books found during your research.

You can cite a source as supporting evidence like this:

You will be rephrasing and analyzing others’ opinions on your chosen topic for most of your work. However, from time to time, a direct quotation is necessary to support your arguments. This is suitable in the following cases:

• You don’t want to lose the author’s original meaning by summarizing or paraphrasing their words.
• The language in the source material is very effective and would be weakened if you tried to reword it.
• The language that the author is using is important historically.
• The authority found in the source will lend more credibility to the point you are trying to make.

5. Cite Your Sources

Congratulations – your work is nearly finished! You have only a couple of steps left. To round up your research, compile a list of sources you have used. You should also indicate which parts you have cited in your text. That is what we are going to discuss in this section.

Simply put, a citation is used to refer back to the source material. You can cite anything, from an academic article or book to a video or even a viral tweet. This is how you give credit to the original author for their work.

There are a couple of ways to utilize citations in your work correctly:

• When employing quotations, summarizing, or paraphrasing in your text, use in-text citations . These must be placed directly in the body of the work in parenthesis, following the cited fragment. The in-text citations are always shortened, referring only to the author and the year of publishing. Sometimes, for larger works, the page number is also included.
• The full citations go into the references/works cited page at the end of your work. This is also sometimes referred to as a bibliography. These include various features, such as the title of the work, the author’s name, date of publishing, etc. Different citation styles require different elements to be mentioned. Make sure to double-check which one your institution expects you to use.

As we mentioned, while creating any academic work, you are expected to use references. You will have to choose a particular citation style or be directed to one by your instructor. This style will be used consistently throughout your work. Each one has its specific features and guidelines.

Here is what you can expect from them:

You can read more about each citation style if you follow the links for the related referencing guides .

In the previous sections, we have examined search engines, databases, and websites that you can use in your research. However, there are plenty of other online tools that can be very useful for your work process. We are going to talk about them here.

The following online tools can help you immensely while you research:

• ProCon.org is a website that allows you to consider several viewpoints on debatable issues. It features multiple controversial topics and lets the readers experience different sides of the arguments in a non-biased manner.
• Journal TOCs is a service that allows you to discover the newest academic papers as soon as they are available online. When writing about current events, it is essential to stay up-to-date, especially concerning research.
• EndNote is a multifunctional tool with many valuable features. It provides you with fast database search, automatic bibliography, and more. Research takes an incredible amount of time and effort, and this program is determined to save you time and resources.
• Paperpile is an extension for your browser and can be installed on your mobile devices as well. Tracking down and compiling your references can become a hassle – this is why Paperpile manages them for you.
• Zotero is another useful extension for your browser. It collects and organizes your research for you. It can also help you with the creation of your citations and allows you to collaborate with others.
• RefWorks is a tool that allows you to save your references from any webpage. It also helps you import them from online databases. You will be able to annotate and highlight your texts, as well as quickly search through them.
• Science Daily allows its readers to browse through all the latest news in several different spheres. Keeping up with updates in the scientific sphere is essential for any researcher, but especially those in the STEM fields. ScienceDaily is a must-have if you need to save time.
• DeepDyve gives you access to different current research articles for a limited time. A large number of valuable sources online are locked behind a paywall. It tends to be troublesome and expensive. DeepDyve allows you to check articles for free to see whether you need them for your research or not.

Thank you for your attention! We hope that you are now feeling more prepared to approach research in any sphere. Share this page with other students who you think could use our guide.

🔗 References

• Basic Steps in the Research Process – North Hennepin Community College
• How to Do Research A Step-By-Step Guide: Get Started – LibGuides at Elmira College
• Conducting Research: the Process – Research Guides at Washington University in St. Louis
• Research Process: Select your Topic – Nash Library & Student Learning Commons at Gannon University
• Developing Research Questions – Research & Learning Online, Monash University
• How to Write a Research Question – Guides at The Writing Center, George Mason University
• Research Process Step by Step: Identify Keywords – Subject and Course Guides at University of Texas at Arlington
• Start Your Research: Evaluate Your Info – Library Guides at University of California, Santa Cruz
• 19 Notetaking Tips for College Students – Post University
• Writing a Paper: Outlining – Academic Guides at Walden University
• How to Outline – Purdue Online Writing Lab, College of Liberal Arts, Purdue University
• What Is Research: Definition, Types, Methods & Examples – QuestionPro
• Thesis Statements – The Writing Center, University of North Carolina at Chapel Hill
• 5 Steps to Create the Perfect Outline – Brandon Ramey, Herzing University
• How to Cite – University of Arizona Libraries
• The Research Process: How to Cite – LibGuides at Franklin & Marshall College
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Idea – Definition, Types and Examples

Table of Contents

Definition:

Idea is a mental concept or thought that represents something that does not exist in the physical world or is not directly perceived by the senses. It is a product of imagination, creativity, or inspiration that can be used to solve a problem, create something new, or achieve a goal.

Types of Idea

Types of Ideas are as as follows:

Creative Ideas

These are ideas that involve thinking outside of the box and coming up with new and innovative solutions to problems or challenges.

Business Ideas

These are ideas for new products, services, or business models that can potentially generate revenue and profit.

Scientific Ideas

These are ideas that involve developing new theories or concepts to explain phenomena in the natural world, or devising new experimental methods to test hypotheses.

Philosophical Ideas

These are ideas that relate to fundamental questions about the nature of reality, knowledge, ethics, and meaning.

Social Ideas

These are ideas that aim to address social issues such as inequality, discrimination, poverty, and environmental sustainability.

Political Ideas

These are ideas that relate to government policies, systems of governance, and political ideologies.

Artistic Ideas

These are ideas that relate to creative expression in various forms such as music, literature, visual arts, and performing arts.

Technological Ideas

These are ideas that involve the development of new technologies or the improvement of existing ones.

Personal Ideas

These are ideas that relate to personal growth, self-improvement, and self-discovery.

Examples of Idea

• A social network exclusively for pet owners where they can share pictures, stories, and connect with other pet owners.
• A subscription service that sends monthly surprise boxes of locally sourced, organic produce to customers’ homes.
• A mobile app that provides personalized workout routines based on the user’s fitness level, goals, and available equipment.
• A virtual interior design service that allows customers to upload photos of their space and receive customized design recommendations.
• A charity that collects and distributes unused toiletries from hotels to homeless shelters and other organizations that serve those in need.
• A platform that connects freelance graphic designers with businesses looking for logo designs, social media graphics, and other design work.
• A meal kit delivery service that focuses on providing healthy and organic meals for families with young children.
• A travel company that curates eco-friendly and sustainable travel experiences for adventurous travelers.
• A language learning app that uses virtual reality technology to immerse users in real-life scenarios and conversations.
• A subscription service that sends monthly boxes of art supplies and project ideas to inspire creativity in kids and adults alike.

Applications of Idea

Applications of Idea are a follows:

• Business : In the business world, an “idea” can refer to a new product or service that a company wants to develop, or to a new approach to solving a problem or improving efficiency. Generating and implementing innovative ideas is crucial for staying competitive and growing a successful business.
• Creativity : In the realm of art, literature, and other creative pursuits, an “idea” can refer to a concept or inspiration that forms the basis of a work. Artists and writers often seek out new and unique ideas to help them create original and compelling pieces.
• Innovation : In the context of technological or scientific advancements, an “idea” can refer to a new concept or theory that has the potential to revolutionize an industry or field. Ideas in this sense often require extensive research, development, and testing before they can be successfully implemented.
• Problem-solving: In the context of problem-solving, an “idea” can refer to a proposed solution or strategy for addressing a particular issue or challenge. Brainstorming and generating ideas is an important part of the problem-solving process, as it can help individuals and teams come up with creative and effective solutions.

Purpose of Idea

The purpose of an idea can vary depending on the context in which it is used. In general, an idea is a thought or concept that can be used to solve a problem, create something new, improve an existing product or process, or inspire creativity and innovation. Ideas can also be used to communicate, persuade, or inform others, or to express artistic or philosophical concepts. The ultimate purpose of an idea is often to bring about positive change or achieve a particular goal, whether that goal is personal, social, or professional in nature.

Characteristics of Idea

Here are some key characteristics of ideas:

• Originality : A good idea is often novel and unique. It should bring a new perspective or solution to an existing problem.
• Relevance : A good idea should be relevant to the context or situation in which it is being used. It should be applicable and useful in solving the problem or achieving the goal at hand.
• Feasibility : A good idea should be feasible and achievable within the given resources and constraints. It should be realistic and not overly ambitious or impractical.
• Clarity : A good idea should be clear and easy to understand. It should be able to be explained in a concise and understandable way.
• Impact : A good idea should have the potential to create a significant positive impact. It should be able to bring about positive change or solve a problem in a meaningful way.
• Adaptability : A good idea should be adaptable and flexible. It should be able to evolve and change over time as circumstances change.
• Scalability : A good idea should be scalable, meaning it can be expanded or replicated to have a broader impact or reach a larger audience.

Advantages of Idea

There are several advantages of having good ideas:

• Creativity and Innovation : Ideas fuel creativity and innovation, allowing individuals and organizations to come up with new and unique solutions to problems and challenges.
• Competitive Advantage: Good ideas can give individuals and organizations a competitive advantage by providing a unique selling point or value proposition that sets them apart from others.
• Cost Savings: Ideas can help reduce costs by identifying more efficient and effective ways of doing things or by finding ways to eliminate unnecessary expenses.
• Improved Productivity : Ideas can lead to improved productivity by streamlining processes and procedures, eliminating bottlenecks, and improving overall efficiency.
• Enhanced Problem-solving: Good ideas can help individuals and organizations to better solve problems and overcome challenges by providing new and creative solutions.
• Better Decision Making : Ideas can improve decision making by providing new and innovative options, enabling individuals and organizations to make more informed and effective choices.
• Personal and Professional Growth: Having good ideas can lead to personal and professional growth by fostering creativity, innovation, and critical thinking skills.

Disadvantages of Idea

Disadvantages of Idea are as follows:

• Idea overload: Sometimes, when brainstorming or generating new ideas, it can be easy to become overwhelmed with the number of potential options. This can lead to decision paralysis or a lack of focus on any one idea.
• Lack of practicality: Not all ideas are feasible or practical. While it’s important to think outside the box and consider innovative solutions, it’s also important to evaluate whether an idea is realistic and can be implemented within the given constraints.
• Resistance to change : New ideas can sometimes be met with resistance or skepticism from others, particularly if the idea challenges existing norms or requires significant changes to established processes.
• Implementation challenges : Even the most promising idea may face implementation challenges. This can include difficulty securing resources, lack of support from key stakeholders, or unforeseen roadblocks that arise during implementation.
• Fear of failure: The process of generating new ideas can be exciting and energizing, but it can also be intimidating. Fear of failure or fear of being judged can sometimes stifle creativity and prevent individuals or teams from fully exploring new possibilities.

Limitations of Idea

Limitations of Idea are as follows:

• Implementation : Having a great idea is only the first step. The real challenge is implementing that idea in a way that brings it to life. This requires resources, time, and effort, and can often be more difficult than coming up with the idea itself.
• Context : Ideas are often generated in specific contexts, and may not be applicable or relevant in other contexts. For example, an idea that works well in one country may not work as well in another country with different cultural norms, economic conditions, or political systems.
• Competition : In many cases, multiple people may have the same idea, or similar ideas, at the same time. This can lead to intense competition for resources, funding, and attention, and may make it difficult for any one person or group to fully realize their vision.
• Execution : Even if an idea is well-conceived and well-suited to its context, it may not be successful if it is not executed properly. This requires careful planning, attention to detail, and the ability to adapt to changing circumstances.
• Unintended consequences: Ideas can have unintended consequences that may be difficult to predict or control. For example, a new technology may have unforeseen negative impacts on the environment, or a social policy may unintentionally exacerbate existing inequalities.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research writing.

• What is Research?
• The Research Process
• Choosing a Topic
• Finding Sources

Thesis Statements

• What is your Main Idea?
• Presenting your Sources
• Organizing your Material
• Discipline-Specific Research
• Citing Sources This link opens in a new window
• Tips and Examples for Writing Thesis Statements This resource from Purdue University's Online Writing Lab (OWL) provides tips for creating a thesis statement and examples of different types of thesis statements.

Need more help writing a thesis statement? Check out this video from East Tennessee State University

Hypothesis or Theory?

The terms theory and hypothesis are often used interchangeably in everyday use. However, the difference between them in scholarly research is important, particularly when using an experimental design.

The key distinctions are:

• A theory  predicts events in a broad, general context;  a hypothesis  makes a specific prediction about a specified set of circumstances.
• A theory  has been extensively tested and is generally accepted among scholars;  a hypothesis  is a speculative guess that has yet to be tested.

Hypothesis Example

A worker on a fish-farm notices that his trout seem to have more fish lice in the summer, when the water levels are low, and wants to find out why. His research leads him to believe that the amount of oxygen is the reason - fish that are oxygen stressed tend to be more susceptible to disease and parasites.

He proposes a general hypothesis.

“Water levels affect the amount of lice suffered by rainbow trout.”

This is a good general hypothesis, but it gives no guide to how to design the  research  or  experiment . The hypothesis must be refined to give a little direction.

“Rainbow trout suffer more lice when water levels are low.”

Now there is some directionality, but the hypothesis is not really  testable , so the final stage is to design an experiment  around which research can be designed, a testable hypothesis.

“Rainbow trout suffer more lice in low water conditions because there is less oxygen in the water.”

This is a testable hypothesis - he has established  variables , and by measuring the amount of oxygen in the water, eliminating other  controlled variables , such as temperature, he can see if there is a correlation  against the number of lice on the fish.

This is an example of how a gradual focusing of research helps to define  how to write a hypothesis .

Material adapted from "Research Methods: Hypothesis" by George A. Spiva Library, Missouri Southern State University

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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Research idea: How to write your own

The world of European programmes is based on ideas, facts and research on pretty much anything that has...

The world of European programmes is based on ideas, facts and research on pretty much anything that has to do with improving the labor market, the scientific world, current technologies, and society as we know it. If your organization or you as a researcher want to become a part of the programmes then you are going to need to work on a specific idea.

In most cases, the project starts based on the call to action provided by the European Union. And yes, this might be considered one of the easiest ways to do so. The Commission requires specific actions to be taken on a specific matter. If your organisation can form a proposal suggesting solutions to those actions then you just write your proposal, you submit it to your national agency and if approved you start implementing the project.

And yes, this might be a great way for you to start entering the world of European programmes. However, it is not the kind of way that will make you a well-known experienced partner or someone who is making a great impact through European programme implementation.

The solution, in this case, is a research idea. Instead of creating a proposal and by default the project based on a call, you could create a research idea that serves a particular purpose. After you do so, you can match that idea to a specific European commission call and build the entire proposal around it. But why is this such a good way to start?

This is a valid question. In most cases, people will claim that this is quite a complicated process. Why create a research idea when you can just create the proposal based on what the court requires? The answer is quite simple. A research idea and a very specific matter that offers a very specific solution will attract a much better consortium. The entire proposal that will be built around that idea will have a purpose. You will notice that writing that proposal is going to be a lot easier if you have a research idea. Last but not least, you are going to build a reputation. If you do have the ability to create your research ideas, the kind of ideas that people will like them by default more and more partners will want to become a part of your consortium.

Writing the idea

Coming up with a research idea can be quite complicated. There are a lot of different things that will need to be taken into account. First and foremost, you will need to focus on the expertise of your organization to build the idea. For example, if you are an expert in entrepreneurship you cannot hope to build a research idea specified in the health department. Coming up with a product or a machine that will help solve a worldwide health crisis is not something the businessman can do.

However, as a researcher, you can focus on your expertise which could be pretty much any scientific field and start building a specific research idea. You will want to narrow down your options to the one subject matter that you can support the best with valid arguments and provable solutions.

Do your research

Let's assume that you are a researcher on the health field and you are interested in creating a research idea that will help solve a very specific problem. Before you start writing the idea you need to do your research to know exactly what kinds of actions have already been taken regarding the problem you are attempting to solve.

That alone is going to help you create the research idea. You can draw from those actions are perhaps even use them as arguments to suggest your solutions. Moreover, you could use the results of those actions as a way to boost your very own research idea thus giving it a lot more prestige.

Now your limits

As a researcher, whether you are working alone or are employed in a research facility, you will need to know your limits. There are only so many things you can do as an individual or as part of the consortium. Creating a research idea that will require top-quality partners, expertise and technology that is difficult to find is not going to make things easy for you.

On the contrary, if you keep your idea just a tad lower you could find a consortium capable of supporting that idea that's creating an effective proposal. If that proposal gets approved and that research idea is implemented then you can simply take things to the next level. Use the results of the first project to create a new research idea, maybe an improvement of the old one. In other words, built on your ideas one step at a time. A process like that could take years to be completed and as a researcher, you already know that.

Take your time to create the idea

This is a common mistake that a lot of researchers out there might make. They get excited about a project or a concept and they start creating a research idea aiming at completing it very fast. As a result, they will have an inconclusive idea in their hands. More importantly, they will not be able to find a call to match the idea. They are most likely going to apply to a call that does not have complete relevancy resulting in the idea of getting rejected.

By taking the time to create your research idea you will have the opportunity to gather as much information as possible. At the same time, you will study all of the European Commission's calls around your sector and the sector of the research idea, aiming at finding the one call that will suit you the best.

Create drafts

Rome was not built in a day. No research idea can be born and completed in one night. You will need to create drafts upon drafts, built on the idea in multiple different ways and try to combine as many of them as possible until you have a final product in your hands. Those drafts will help you create the final idea which will be the center of your proposal.

Simultaneously, the drafts you will create could provide you with more ideas for the future. Keeping notes and creating drafts is certainly going to give you enough material to build your research idea focusing on the important aspects of it and of course, utilizing all information and possible outcomes the right way.

Create your database

Who's to say that the idea you are currently working on has not already been developed by someone on the other end of the world? By taking your time as suggested above, you will have the opportunity to do a lot of research and find all the valuable information concerning your research idea.

By doing so, you will start creating a massive database of information surrounding a particular subject matter. You need to try and think about this as your library. A library that will contain all the valuable information regarding your research idea and any kind of research you might want to conduct in the future.

Editing is important.

This is a much more technical process but it is most certainly a very important one. A research idea can be quite complicated and by not processing it correctly you could end up with a bad result. You are going to be presenting that idea to your potential partners.

Proper wording will make it easier for you to process and explain your idea as well as others to understand it!

As a researcher, you already know how to conduct proper research to form an idea. As a business owner, our most valuable tip is the following. Do not appoint the task of creating a research idea to someone inexperienced or irrelevant to the field of the idea. Always make sure that your researchers will be up to the task and ready to create the best research idea for project proposal!

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Decolonising global health research: Shifting power for transformative change

Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations United Nations University-International Institute for Global Health, Kuala Lumpur, Malaysia, Department of Community and Family Medicine, Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka

Roles Conceptualization, Writing – review & editing

Affiliation United Nations University-International Institute for Global Health, Kuala Lumpur, Malaysia

Roles Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing

• Ramya Kumar, 
• Rajat Khosla, 
• David McCoy

Published: April 24, 2024

• https://doi.org/10.1371/journal.pgph.0003141
• Reader Comments

Recent debates on decolonizing global health have spurred interest in addressing the power asymmetries and knowledge hierarchies that sustain colonial ideas and relationships in global health research. This paper applies three intersecting dimensions of colonialism (colonialism within global health; colonisation of global health; and colonialism through global health) to develop a broader and more structural understanding of the policies and actions needed to decolonise global health research. It argues that existing guidelines and checklists designed to make global health research more equitable do not adequately address the underlying power asymmetries and biases that prevail across the global health research ecosystem. Beyond encouraging fairer partnerships within individual research projects, this paper calls for more emphasis on shifting the balance of decision-making power, redistributing resources, and holding research funders and other power-holders accountable to the places and peoples involved in and impacted by global health research.

Citation: Kumar R, Khosla R, McCoy D (2024) Decolonising global health research: Shifting power for transformative change. PLOS Glob Public Health 4(4): e0003141. https://doi.org/10.1371/journal.pgph.0003141

Editor: Ananya Banerjee, McGill University, CANADA

Copyright: © 2024 Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

Inequity within international research partnerships has troubled the field of global health for decades. In particular, power asymmetries between actors from wealthier and historically-privileged countries and their counterparts in the Global South (GS) have led to paternalistic ways of working, unequal sharing of resources, skewed distribution of benefits, and limited commitments to capacity strengthening [ 1 ]. Recent debates on decolonizing global health have brought renewed attention to addressing these problems in global health research. In addition to highlighting equity concerns, these discussions draw attention to the epistemic injustice and “white saviour” mentalities that underpin research collaborations [ 2 – 8 ].

Recognising that power asymmetries in global health are produced by both historical and current exploitation and resource extraction, our approach to decolonizing global health involves three intersecting dimensions: 1) colonialism within global health; 2) colonisation of global health; and 3) colonialism through global health [ 9 ]. The first dimension speaks to power differentials and resource disparities between different actors within the field of global health. The second deals with the dominance of certain powerful actors and vested interests over the overall complex of global health structures, systems, policies and practices. The third dimension refers to exploitative and extractive practices that occur through the health sector [ 9 ].

This paper uses this framework of three dimensions to arrive at a broader understanding of the scope of policies and actions needed to decolonise global health research. We begin by briefly outlining persisting inequities within research partnerships- already addressed by a large body of literature. Next, we draw attention to issues that are underexplored, specifically who controls the agenda of global health research (i.e., colonisation of global health research), and who benefits from such research (i.e., colonialism through global health research) ( Fig 1 ). We then present a brief review of recent guidelines and checklists that seek to decolonize global health research and/or centre the needs and aspirations of the GS in research, revealing an emphasis on addressing inequity within research partnerships. We end by recommending policies and actions that would decolonize the field of global health research in an effective and comprehensive manner.

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https://doi.org/10.1371/journal.pgph.0003141.g001

This paper employs the terminology “Global North” (GN) and “Global South” (GS) to reflect asymmetries in power and access to resources between not just countries but also population groups. This terminology only partly corresponds to the classification of countries according to per capita gross national income, i.e., low-income, middle-income, and high-income countries (LIC, MIC, and HIC) [ 10 ]. However, where we quote from sources that explicitly refer to LICs, MICs or HICs, these terms are retained. We borrow from Garcia-Basteiro and Abimbola [ 11 ] to define global health research as research that seeks to address health inequity within and across countries, aiming to improve health in what they call “low-resource settings” described as regions weighed down by financial constraints, suboptimal service delivery, underdeveloped physical and knowledge infrastructure, historical, political and sociocultural contexts/specificities, and geographical, environmental and human resource limitations.

2. Colonialism within global health research: Who leads?

According to the World Health Organization (WHO), in 2020, of the USD 37 billion spent worldwide on ‘biomedical research’, 98.7% went to HICs [ 12 ]. Perhaps more reflective of the global health research landscape, in 2021, 82% of the Bill and Melinda Gates Foundation’s (BMGF) grant funding went to HIC recipients [ 13 ]. This unequal distribution of funding is striking when one considers that much global health research is carried out in GS settings.

The inequitable global health research funding patterns reflect not only the wider socio-economic disparity between GN and GS, but also the biases within the global health research system. For example, grant calls, either explicitly or through eligibility criteria or capacity requirements, favour GN-based institutions [ 14 ] with research funding agencies of key donor countries often requiring principal investigators (PI) to be based in their country or compel PIs from the GS to partner with a researcher based in the donor country [ 15 , 16 ]. Eligibility criteria based on geographic location and experience may further restrict applications from GS-based researchers [ 17 ]. GN-based researchers are also better able to navigate the funding terrain with their training, networks and resources [ 18 , 19 ].

Although most global health funding agencies require GN-based researchers to “collaborate” with local “partners,” the terms of collaboration are usually set by the former who typically conceptualise the research before inviting others onboard [ 20 ]. This gives GS-based researchers limited influence over the research, despite their expertise and familiarity with the context [ 7 , 21 , 22 ], thus supporting what has been called “parachute” research, where GN-based collaborators fly in for weeks at a time for onsite “supervision” [ 23 , 24 ]. As grant cycles are usually short, the urgency to meet deadlines results in lopsided decision-making, hasty administrative approvals and, at times, the undermining of local administrative and ethics procedures [ 8 ].

Much grant funding goes towards the salaries of GN-based researchers with substantially less dedicated to research systems and capacity strengthening in GS settings [ 2 , 14 ]. This lack of long-term commitment to the development of GS-based institutions sustains the status quo [ 25 ]. Meanwhile, extant capacity strengthening initiatives are often uni-directional and paternalistic, involving assumptions about what competencies GS collaborators may lack [ 26 ].

Inequity is further reinforced by authorship patterns that are biased towards GN-based researchers [ 27 , 28 ]. Authorship guidelines of prominent journals systematically exclude non-native English writers [ 29 ] by giving weight to written contributions over field work [ 30 ]. Representation at conferences and symposia is similarly unequal, although research collaborations do enable participation for some GS-based researchers. Even so, visa and other barriers challenge researchers from travelling to meeting destinations [ 31 ].

3. Colonisation of global health research: Who controls?

Global health funding agencies wield significant power in defining global health problems and the approaches taken to addressing them [ 7 , 32 ]. Under the current system, researchers based at universities and other research institutions respond to grant calls, crafting their research to fit with the agendas and ideologies of global health funders rather than vice versa [ 33 ].

Extreme wealth concentration under neoliberal globalization and the rise of ‘philanthrocapitalism’ by which global health problems are framed as market opportunities, has seen a shift from public to private financing in global health [ 34 , 35 ]. However, private actors have interests and priorities that may be at odds with the public interest or with achieving equity in health. For instance, the shift from publicly-funded to industry-funded research has distorted scientific evidence on infant formula with detrimental effects on infant and child health [ 36 ]. Moreover, the funding decisions of corporations and foundations are ultimately approved by a handful of largely GN-based board members, who are not subjected to any independent mechanisms of accountability for their funding decisions or their impact on people affected by these decisions [ 32 , 37 ]. Although some funders have recently instituted measures to address diversity within their leadership [ 13 , 38 ], such change will not be transformative without redistributing power and resources, and genuine efforts to improve accountability [ 39 ].

Research funders favour specific thematic areas, not always based on the health problems prevailing in specific GS settings [ 19 , 40 ]. They tend to promote technology-based solutions and favour innovation and entrepreneurship in projects that yield quick and quantifiable results [ 41 ]. The preference for short-term impact over longer-term improvements in health results in grant proposals that centre “magic bullets” (e.g., vaccines, medicines, bed nets, mobile apps) rather than systems building, local capacity strengthening and unblocking the social and political barriers to the scale up of proven and more sustainable alternatives [ 42 , 43 ].

Academic programmes in global health continue to be characterised by what has been called a “white saviour complex” or a depoliticized, patronizing and charity-based approach shaped, in part, by a wider aid industry [ 44 , 45 ]. Global health curricula remain largely disconnected from the many realities and locales of the GS, both in geography and lived experience. Dominant Eurocentric epistemologies, which are embraced and propagated by powerful global health institutions, are usually given primacy in research training, even as heterodox methodologies that interrogate power and inequality are marginalized [ 45 , 46 ].

The inability of countries of the GS to weigh in on the global health research agenda and define their own priorities is perpetuated by their minimal contributions to research funding [ 25 , 47 , 48 ]. While domestic investment is critical to shift the balance of power, debt-ridden governments of lower-income countries may have limited leeway with their health and R&D budgets owing to fiscal constraints [ 19 ]. For these countries, HIC-driven global health research collaborations may present a welcome source of foreign currency. Too often however, external funding for health research takes place with little coordination among granting agencies [ 49 , 50 ], facilitating duplication, and making impact assessment difficult.

4. Colonialism through global health research: Who benefits?

The asymmetric global health research funding structure also gives powerful states and private actors opportunities to craft research in the GS in ways that they benefit from financially or economically. These benefits are primarily driven by the commercialization of research and publishing, supported by imperatives to expand markets, unfair intellectual property rights (IPR) regimes, and predatory academic journals.

Arguably, the biggest profits are made by commercial entities that hold patents for global health technologies often tested through research carried out in GS settings. Such research aids market expansion for medicines, vaccines, diagnostic tests, mobile devices, etc. benefitting big pharma, biotechnology, and big tech companies, while doing little to strengthen public health infrastructure and services or reduce dependency [ 19 , 41 ]. Indeed, some private foundations are routing a growing proportion of their tax-subsidised grants to private for-profit organisations, in both GN and GS settings [ 37 , 51 ].

Current IPR regimes which provide private companies with extensive monopoly rights over new and modified technologies despite much basic research being funded publicly is one aspect of an R&D ecosystem biased in favour of private financial interests at the expense of public health. This was seen with the billions of dollars of private profits generated from COVID-19 vaccines despite vast amounts of public and charitable funds that went into their development [ 52 ].

The unequal benefits accrued through authorship in global health journals have been widely studied [ 27 , 28 ] but less is known about their commercial dimensions. The revenue of academic publishers is estimated to be about USD 19 billion annually, where about half the market share is controlled by five transnational companies, with Elsevier alone accounting for 16% of the market share, with profit margins in the order of 40 per cent [ 53 ]. These corporations are all headquartered in the GN and maximise profits through article processing charges (APCs), subscriptions, and the uncompensated labour of authors and peer-reviewers. Ever-increasing APCs are required to publish ‘open access’ in prestigious journals, implemented in the name of equity, but barring most GS-based researchers through stringent waiver criteria [ 54 ]. Global spending on APCs alone is estimated to exceed USD 2 billion annually [ 55 ]. Academic journals are, in turn, linked to bibliometric platforms that track the ‘impact’ of research communications, which feed into commercialised university ranking systems [ 56 ]. With research funding and citations in ‘high-impact’ journals being key elements of performance indices, the top-twenty universities, as ranked by Academic Ranking of World Universities and Time Higher Education, are all located in the GN [ 57 ].

The current system of global health education supports extraction of wealth and other resources from GS to GN. A recent analysis of masters in global health degrees revealed that 95% of them are based in HICs, costing on average USD 37,732 in tuition [ 58 ]. Given the location and cost of global health postgraduate programmes, their graduates, including those from GS settings, are likely to be drawn to work with global or GN-based institutions both to repay the debt incurred and because of the lack of well-remunerated positions back home [ 58 ]. Ultimately, career trajectories in global health are skewed towards the GN and not “low-resource settings” where global health work and resources are much needed [ 23 ].

In sum, whether in terms of leadership, control or benefits, GN-based actors and institutions are privileged within the broader global health research ecosystem, often to the detriment of researchers, institutions and ‘beneficiaries’ in GS settings. It appears that global health research supports a renewed form of extractivism, where resources in the GS, including funding, knowledge and researchers, are drawn to the GN. In the next section, we examine whether and to what extent recent guidelines on decolonising global health research address the three intersecting dimensions of colonialism in global health research.

5. Recent guidelines that aim to decolonise global health research

We searched the literature for tools that either explicitly or in their framing seek to decolonise global health research and/or centre the needs and aspirations of the GS in research. As searches on PubMed and Scopus [(“decol*” OR “colonial*”) AND “global health” AND “research” AND (manual OR guideline OR checklist)] yielded less than 10 publications, we also searched Google Scholar, Google, and pursued reference lists of identified publications. Criteria for inclusion were: addressing equity in global health research with reference to colonialism or explicit attention to making research fairer for peoples and institutions in the GS; including a set of standards or guidelines; targeting researchers, research institutions or funders; published within the five-year period of 2019 to 2023. We identified eight tools that fit our criteria as described below.

Hodson et al. [ 40 ] offer a set of “practical measures” for global health researchers, underpinned by four principles: “1) seek locally derived and relevant solutions to global health issues, 2) create paired collaborations between HIC and LMIC institutions at all levels of training, 3) provide funding for both HIC and LMIC team members, [and] 4) assign clear roles and responsibilities to value, leverage, and share the strengths of all team members.” This guideline addresses specific challenges experienced in GS settings by advocating for: educating all team members on global health history; early engagement of GN-based researchers with local administrations; capacity strengthening to support independent research in GS settings; protected research time for all team members; preventing GS-based researchers being drawn away from regular work; and ensuring knowledge translation to local communities, among other measures. Despite the commitment to long-term capacity strengthening, the guideline focuses primarily on research processes within partnerships.

Kumar et al. [ 26 ] propose a set of individual and institutional level actions to advance equity in global health research. Those at the individual level include questioning “notions of absolute scientific objectivity” (p.146), adopting a decolonial approach towards global health concepts and implicit hierarchies, cultivating respect and humility, promoting fairness at all levels (including at the level of global health leadership), and going beyond ‘equality’ to recognize ‘equity’ within collaborations. At the institutional level, they support decentring the GN in global health efforts (including the location of centres of knowledge), promoting solidarity, investing in researchers from LMICs, bi-directional capacity strengthening, evaluating partnerships by “measures of fairness” and “ethical and culturally responsive engagement,” and correcting “colonising and unethical practices” (p.146). While some of these actions aim to rectify power asymmetries well beyond research partnerships, they do not include specific guidance on implementation.

Embracing a feminist decolonial approach, Singh et al. [ 59 ] offer a guideline for researchers working in situations of forced displacement that centres participant agency, voice, and experience; it aims to address power hierarchies through a set of recommendations targeting various stages of research. The guideline demands: consideration to “political, social, economic, and historical contexts and power hierarchies of the research setting” (p.561); involving marginalised groups in the research design; reflecting on how coloniality and gendered power relations may be reinforced during data collection; an intersectional analysis of gendered power relations; collaboration in analysis and knowledge dissemination; and using research to “challenge unjust systems and policies and deliver gender transformative and equitable programmes” (p.561). Although the guideline aims to reconfigure power within individual research projects, it offers no direction on how to redistribute power.

Rashid [ 8 ] offers guidance for researchers in LICs to “[navigate] the violent process of decolonisation in global health research.” The guideline includes a list of dos and don’ts to help researchers in LICs contend with power asymmetries in international research collaborations. They recommend carefully reviewing agreements, clarifying systems of reporting and accountability, insisting on inclusion in communications with funders, meticulous documentation, boosting one’s profile, expanding networks, and building solidarity. However, this guideline focuses on change at the individual level on the part of researchers in GS settings rather than systemic change.

The TRUST Code–“A Global Code of Conduct for Equitable Research Partnerships” is based on the core values of fairness, respect, care, and honesty [ 60 ]. Compiled by a team with wide representation from the GS, the TRUST Code consists of 23 articles. Apart from conventional ethical standards, the tool emphasises: bona fide involvement of local communities in research, fairness in the transfer and ownership of data and biological materials, and fair compensation of local collaborators. It emphasises cultural acceptability, community assent, respect for local ethics review and giving consideration to the impact of research on local human resources, animal welfare, and the environment. It calls for clarity on roles, responsibilities, capacity strengthening, transparency, and integrity of the research process. Although broadly framed around justice for communities and researchers in the GS, the tool primarily concentrates on making individual research partnerships more equitable.

The Research for Health Justice Framework proposed by Pratt and colleagues [ 61 ] offers two sets of guidelines, one for health researchers and another for granting agencies. Developed through an iterative process and fine-tuned through case studies in GS settings, the guidelines emphasize equity, justice, and inclusion, with accompanying explanations on implementation. The guideline for researchers addresses: selection of the research population and research problem, research capacity development, delivery of ancillary care, and knowledge translation practices. With respect to granting agencies, it asks that they prioritise the health concerns of the worst-off, promote ownership of the research agenda by LMIC researchers and support projects that seek to advance equity within healthcare systems, atop measures to support equitable research practices. While this framework is comprehensive in scope, the guidelines are still largely limited to the research process and do not explicitly seek to transform the global health granting system and the power asymmetries within it.

Focusing specifically on global health research funding, Charani et al. [ 19 ] outline eight areas of action for funders: 1) developing situational awareness, including an understanding of institutional dynamics and who benefits from grants; 2) formulating a mission statement that pledges equity in research; 3) equitable allocation of funds to cover differential needs of HIC- and LMIC-based researchers; 4) funding structures that encourage local ownership and leadership; 5) bi-directional capacity strengthening that enables all partners to engage with funders; 6) diversity and inclusion across the grant cycle, including in design, knowledge dissemination, access to training etc.; 7) knowledge generation, including methodologies, frameworks, tools and clarity on data ownership; and 8) reflection and feedback involving HIC and LMIC researchers on equal terms. Encouraging funders to include specific requirements for grant recipients to comply with participatory approaches and fair sharing of resources and benefits, the guideline also speaks to what should be funded, who should be funded and how. Moreover, among its recommendations—albeit with no details provided—are “a transparent process for tracking the progress of funding” and “a code of ethics for global health funders”.

The Global Health Decolonisation Movement Africa [ 17 ], self-described as a collective of African citizens, has published a guideline called, Pragmatic Approaches to Decolonising Global Health in Africa . What is unique about this guideline is that it addresses multiple “stakeholders” in HICs, including individual practitioners, funding agencies, academic and training institutions, scientific publishers, and event conveners and organisers, among others. The guideline broadly seeks to address racism against Africans within global health, and promotes African leadership and self-determination. The section for funders calls for diversifying grant review panels, rejecting “parachute” proposals, and removing requirements for researchers based in Africa to collaborate with HIC-based institutions. For academic and training institutions, the guideline recommends diversifying leadership and recruitment practices, and addressing coloniality in global health curricula. And for scientific journals, it demands diversifying authorship and peer-review panels. While this guideline emphasises diversity, equity, and inclusion, it remains constrained by the limitations of the current system of global health research funding.

In sum, there is considerable variation in guidance on improving equity in research partnerships and decolonising global health research. All reviewed sources strive to make the research process fairer and rectify power asymmetries through diversity, equity and inclusion measures, but only some engage with historical imbalances in power, interrogate dominant knowledge paradigms, centre the concerns of marginalized groups, and create space for self-determination. The guidelines for funders go beyond research partnerships to address who and what is funded. However, for the most part, these guidelines neglect the wider contextual factors that shape agenda-setting in global health research, as well as the actors and institutions that control and benefit from them.

6. Shifting the balance of power in global health research: Going forward

In this section, we draw on the three intersecting dimensions of colonialism in global health research to present seven action areas that we call for to mitigate inequitable, exploitative and extractive arrangements in global health research ( Fig 2 ).

https://doi.org/10.1371/journal.pgph.0003141.g002

First, and most fundamentally, we call for a critical examination of the epistemological and ideological underpinnings of global health research. While current debates engage to some extent with the marginalization of indigenous perspectives, few question the dominance of positivist approaches and the biomedical paradigm. Guided by a biased hierarchy of evidence that favours quantitative assessments, global health research remains over-occupied with testing the efficacy of discrete, downstream and often clinical technologies and interventions, taking attention away from the social and structural determinants of health, which are more challenging to measure [ 41 , 43 , 62 ]. Shaped by neoliberal ideology, understandings of health and healthcare have evolved from collectivist to individualist interpretations, giving way to economistic evaluations based on assumptions that resource constraints in low-income settings are inevitable [ 63 ]. Global health education could challenge dominant paradigms and mainstream approaches that advance social justice and equity in health [ 64 ].

Second, we need a better and more detailed analysis of the overall pattern and performance of research funding: where it comes from, where it goes, how it is spent, and its impact. A few of the guidelines reviewed earlier do address the global health research funding system. For instance, Charani et al. [ 19 ] recommend that funding agencies self-monitor whom they fund and also call for a code of ethics for funders, while the Global Health Decolonisation Movement Africa [ 17 ] asks funders to remove requirements for researchers based in Africa to collaborate with GN-based institutions. Even so, these measures remain couched within the current structure and system of grant funding that lacks transparency and leaves power concentrated in the hands of largely GN-based donors. The problematic norm of donors funding favoured research areas over those that are identified locally remains largely unchallenged. At the very least, information should be available by funder, recipient, research area, and research setting, possibly through a centralized system that requires funders to provide information on their funding practices. Auditing such data should enable analysis of not only where research funding comes from and who receives it but also its impact.

Third, efforts to address power asymmetries in global health research must compel reform at the highest levels of global governance. By virtue of their funding contributions, powerful states, their bilateral agencies, private foundations, and corporate actors, among others, shape the global health research agenda. Bilateral agencies tend to push foreign policy and other domestic interests [ 65 , 66 ], while corporate actors are driven by profit, and many private foundations by the creed that the private sector can more effectively tackle intractable global health problems [ 67 ]. Bilateral and multilateral agencies should be held accountable for what they fund with taxpayer contributions, while private funders—who are primarily accountable to their boards—must be appropriately regulated and prevented from having undue influence on the shaping of research priorities [ 68 , 69 ].

A comprehensive guideline for research funders that promotes fairer distribution of resources and improved accountability is needed. Such a guideline could incorporate the measures proposed by Charani et al. [ 19 ], Pratt et al. [ 61 ] and the Global Health Decolonisation Movement Africa [ 17 ]. An international agreement, akin to the Declaration of Helsinki [ 70 ]—the World Medical Association’s ethical principles for medical research—could encourage and eventually normalise funding of equity-oriented research and local ownership. Decision-making on funding priorities must be shared with the GS, not just with governments but also with researchers, institutions, and the beneficiaries of research [ 26 ].

Fourth, national research systems should be supported and strengthened with in-built mechanisms of accountability. While there are calls for LMIC governments to invest more in R&D [ 25 ], the onus for change cannot be placed on these countries alone. Rather donors must also commit to investing in local research infrastructure, human resources, and higher education systems, all key to building research capacities. Meanwhile, government allocations for health research in GS settings should be guided by appropriate needs assessments and strategic plans to strengthen national research capacity [ 71 ] as once encouraged by the Commission on Health Research for Development (COHRED), an independent global initiative that supported research for heath and development in LMICs [ 72 ]. Systemic investments in research capacity strengthening with long-term budget commitments and harmonised mechanisms should be established [ 73 ] to replace the current piecemeal manner in which health research is conducted, often subject to the whims of external funders. Bi-directional scholarships for postgraduate training in research, with service requirements in GS settings, could target specific human resource gaps. Fifth, a global fund for research [ 74 ], guided by a multilateral framework that pools donor funds and channels them based on national health priorities may help to harmonise external funding, avoid duplication, and enable greater transparency and accountability.

Sixth, given acute human resource constraints in many GS countries, brain drain must be stemmed. The WHO Global Code of Practice on the International Recruitment of Health Personnel [ 75 ] provides a multilateral framework but fails to hold the GN to account for their unethical recruitment practices. Instead, the Code focuses on the rights of migrating health workers and places the onus on ‘developing countries’ to retain them. It does not recognize the vast amounts of (often public) resources invested in health worker training in GS settings, nor does it recommend compensation to source countries for this training. Academic global health programmes should re-orient their curricula [ 76 ] so that the primary career pathways for global health practitioners are viewed to be in GS settings.

Lastly, interventions to promote fairer distribution of benefits should look beyond authorship and academic credit, to address extractivist practices within the research industry that impede access to knowledge and technologies in the GS. The current IPR regime upholds patent protection, allowing big pharma to control product pricing and restrict market entry of generic manufacturers who could drive down the cost of medicines and other health products [ 77 , 78 ]. IPR regimes need to be revised to enhance fairness in the distribution of the benefits of science rather than support industry benefits and profit over public health.

In this paper, we applied three intersecting dimensions (colonialism within global health; colonisation of global health; and colonialism through global health) to develop a broader and more structural understanding of the policies and actions needed to decolonise global health research. We highlighted the tendency of existing guidelines that seek to make research partnerships more equitable and less colonial, to target the behaviour of researchers and research institutions within the boundaries of individual research projects. Following such guidance should result in better and more appropriate global health research. However, efforts to decolonise global health research should go beyond addressing equity within research partnerships to reconfiguring power arrangements within the global health research ecosystem. This means re-orienting research along social justice and equity lines, building research capacities in GS settings, and moving away from the existing donor-driven model.

Of critical concern is the prevailing system of research funding that functions with little transparency or downward accountability. Data should be made available to scrutinize and evaluate the funding processes of research funders and the appropriateness and impact of funding patterns and practices. It would be important to examine not just the specific outputs and outcomes of individual grant programmes and research projects, but also the impact of the entire global health research portfolio on the overall functioning of health research systems at global and national levels and, in particular, how research outputs contribute towards advancing health equity. Quick fixes and half-hearted measures would simply not work. Time is now for the global health community to come together and demand a complete overhaul of the competitive global health research funding system, and its replacement or accompaniment with a more strategic and publicly-driven pooling and harmonised allocation of resources aimed at correcting the many deep and structural inequalities across the global health research ecosystem. This would also require fostering equity-oriented research approaches, grounded in local ownership, with systems of accountability built in.

Acknowledgments

The authors thank Emer Breen, Tiffany Nassiri-Ansari, and Emma Rhule, for helpful feedback on earlier versions of the paper.

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Hey Dave, I've got an idea for you: What's the potential of AI-led workshopping?

In a paper published in JOSPT Open (Journal of Orthopaedic and Sports Physical Therapy), UTS Graduate School of Health Senior Lecturer in Physiotherapy Dr Joshua Pate and PhD candidate Rebecca Fechner write that AI chatbots offer a novel avenue for idea generation, simulating multidisciplinary workshops that traditionally require significant time and resources.

"We sought to simulate a multidisciplinary workshop on a complex clinical research question using three freely available AI chatbots -- ChatGPT, Bing Creative Mode and Google Bard -- aiming to broaden and accelerate the co-generation of ideas," Dr Pate said.

"Our focus was on AI's practical applications in educational and clinical settings, particularly to address the challenge of pain in schools, but the findings likely generalise for wider applications -- essentially anyone wanting help brainstorming on problem solving, policy or practice.

"We found that the different chatbots provided some different responses to each of the prompts, but overall the most prominent responses were similar. In our simulation they consistently suggested an online platform or curriculum for pain science education in schools.

"So, the consistency in responses suggested some reliability of the chatbots in co-generating ideas, while the differences between chatbots offered a range of perspectives, enriching the brainstorming process.

"These freely available chatbots are accessible tools for broadening participation in idea generation across various domains.

"While the technology might not be good at the details right now, the chatbots are very good at finding new perspectives and connecting dots in previously unexplored ways."

Dr Pate said the study highlights the potential for AI to contribute to educational strategies and clinical research, leveling the field for resource-limited settings. "By demonstrating the chatbots' ability to seemingly simulate complex workshops, we provide a proof-of-concept that could influence future research methodologies and policy making," he said.

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• Rebecca Fechner and Joshua Pate. Could freely available artificial intelligence chatbots simulate a multidisciplinary workshop to more efficiently co-generate ideas? JOSPT Open , 2024 DOI: 10.2519/josptopen.2024.1133

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Harvard Library is Launching Harvard Open Journals Program

Harvard Library is launching a new initiative called the Harvard Open Journals Program (HOJP), which will help researchers advance scholarly publishing that is open access, sustainable, and equitable. HOJP will provide publishing services, resources, and seed funding to participating Harvard researchers for new academic journals. All journal articles will be entirely free for authors and readers, with no barriers to publish or to access.

Martha Whitehead, Vice President for the Harvard Library and University Librarian, sees the initiative as an important step in championing open access. Whitehead said, “We want to model the original ethos of open access by reducing barriers and enabling the free flow of ideas and knowledge across the research ecosystem and beyond to the public at large.”

The Harvard Open Journals Program will offer publishing and hosting services to help the Harvard community launch new open access journals, or to convert existing journals to open access. The program will offer two support models: an overlay model which takes advantage of open access repositories, such as Harvard’s  DASH , and a brand-new academic press model. 

Yuan Li, University Scholarly Communication Officer and Director of Open Scholarship and Research Data Services at Harvard Library, pointed out the innovative nature of the program, “It is new for an institution to support faculty in seeking out an academic press to publish a no-fee open access journal and to provide assistance in securing its long-term funding. And offering a repository overlay journal model provides an alternative that appeals to some editorial boards and is gaining traction through initiatives such as Episciences. As we implement and refine this program on our campus, we hope it will inspire other universities to adopt such approaches to supporting barrier-free scholarly publishing.”

The program is a direct response to faculty interest in alternatives to the article-processing-charge model, in which journals charge author-side fees to publish papers open access. It also supports federal requirements that publications resulting from publicly-funded research be open access.

The open access movement in scholarly publishing seeks to grant free and public online access to publications and data. In recent decades, many researchers have become increasingly concerned that commercial rather than scholarly interests are driving the publishing ecosystem. With some publishers charging article processing fees of over $10,000 per article, skyrocketing costs inhibit many researchers and institutions from publishing in these journals. At the same time, research institutions continue to pay high subscription costs, even as their faculty provide editorial and peer review services mainly for free to the publishers. These practices have led to widespread outcry in the scholarly community, and tensions between publishers and editorial boards have led to the latter’s  mass resignations .

Scott Edwards, Professor of Organismic and Evolutionary Biology, and a member of the Harvard Library Faculty Advisory Council, applauds the library’s exploration of new models for supporting open access publishing. Edwards said, “In this increasingly challenging publishing ecosystem, the Harvard Open Journals Program is a welcome new approach.” 

“These are sustainable and equitable open access publishing models that allow scholars to take control of scholarly communication,” added Li. “I hope that many research-heavy institutions adopt our approach. The first  Harvard Open Access policy launched in 2008 has been adopted nationally and internationally, and it would be great to see similar reach.”

Under Harvard’s Open Access policies, Harvard faculty and researchers give the University a nonexclusive, irrevocable right to distribute their scholarly articles for any non-commercial purpose. Stored and preserved in  DASH , Harvard Library’s open access repository, these articles are made available to the scholarly community and the public—anyone with an internet connection can read them for free.

Harvard Library is working closely with the Office of the Vice Provost for Research on launching the HOJP program. John Shaw, Vice Provost for Research and Harry C. Dudley Professor of Structural and Economic Geology, is eager to promote the initiative in the suite of programs that support faculty research. Shaw said, “The launch of HOJP provides very encouraging options for removing barriers to making research results open and expanding their reach.”

The Harvard Open Journals Program will be open to all journals with a current Harvard affiliate on the editorial team or editorial board. Student-run journals are also eligible, as long as they are sponsored by a Harvard faculty member or administrator.

In preparing to launch HOJP this summer, Harvard Library is currently seeking input on program details from interested faculty. HOJP will begin accepting applications in the fall from journals and editorial boards. Colleen Cressman, Librarian for Open Publishing, will manage the program and can be reached by email for more information.

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Your Career Doesn’t Need to Have a Purpose

• Stephen Friedman

Focus on making your work meaningful instead.

Outside of popular anecdotes and social media stories, there is little evidence that a single, defined “purpose” is necessary for a rewarding career. In fact, it can be quite the opposite. It’s surprisingly common to go after what we think is our purpose only to discover that we hate it. Instead, shift your focus from “purpose” to “meaning.” Ask yourself:

• What do I like, prefer, or enjoy doing? Let go of yearning for a career purpose. Dial it back and consider what you liked about any of your previous jobs, school projects or other ways you spend your time. Perhaps you liked helping your peers organize their work or enjoyed researching sources for group projects. Or maybe you liked working on a team than alone. Use that as a starting point. 
• What am I good at? Early on in your career, you will have many bourgeoning skills. These are skills that you are good at now and can get even better at with more practice. Think about stuff you are progressively getting better at. Getting to use and improve skills that you’re already good will energize you, and provide you with a feeling of recognition and usefulness.
• Would this role provide growth and learning that I can use later? Research shows that what scholars call “ability development” (i.e. getting better at what you do) brings with it greater happiness, satisfaction, and meaning.

As an organizational studies professor at the Schulich School of Business in Toronto, Canada, I get the opportunity to help my students with various aspects of their career development. In the process, I’ve noticed two common threads. First, most of my students are not only eager to enter the world of work, but also to be excellent at what they do. Second, they want their post-graduation job to be loaded with purpose .

• Stephen Friedman is an Adjunct Professor of Organizational Studies and a Senior Faculty of Executive Education, at The Schulich School of Business, York University in Toronto. He teaches and writes about leadership development, organizational behavior, complexity science, career development, human resource management, workplace inclusion, and mental health.

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How to Find Your Faith

The key to transcendence starts with a practice, not your feelings.

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T he United States has long had a great deal of religious diversity, and was built on the idea of religious tolerance. But one type of belief was always rare: none . Until recently, that is. According to the Pew Research Center , the percentage of Americans who profess no religion (as opposed even to having one that they rarely or never practice) has risen from 16 percent in 2007 to 29 percent in 2021. (Back in the early 1970s, only about 5 percent of Americans espoused this position.)

This phenomenon of declining belief is of great concern to many religious leaders, as one can easily imagine. The Catholic theologian and bishop Robert Barron has built an enormous internet-based ministry in no small part by seeking to reach these so-called nones . Rather than simply railing against a secular culture, Barron turns the criticism around and calls the growth of this disavowal “an unnerving commentary on the effectiveness of our evangelical strategies.”

The growing phenomenon of the nones, however, is not evidence of a lack of interest in spiritual life. Many today who previously fell away from their faith—or never had one to begin with—are seeking something faith-like in their life. They are open to thinking about such commitments, but just don’t know what to look for. Maybe this describes you. If so, ironically, the research data on why people say they became nones in the first place might hold the answer of what to focus on to set you on your spiritual path.

I n tracking the rise of the nones in American religious life, Pew has also studied people who had faith in childhood but left it in adulthood. In 87 percent of the cases, this came down to one of three reasons: They stopped believing (49 percent), they felt too uncertain (18 percent), or they didn’t like the way the faith was practiced (20 percent). More concisely, most people leave their faith because of belief, feeling, or practice.

Derek Thompson: The true cost of the churchgoing bust

These are the reasons people quit religion, but we can also infer that these same three aspects of religious experience are central to maintaining faith—or to finding it anew and then keeping it. You might say that belief, feeling, and practice are the macronutrients—the necessary elements—of healthy faith. With only one of them, you will be spiritually malnourished: Belief alone is desiccated theory; by itself, feeling is unreliable sentimentality; practice in isolation is dogmatism. To build a new, sustaining spiritual diet, you need to focus on all three.

Many great thinkers have made essentially this point. For example, the ardently religious Russian novelist Leo Tolstoy wrote in his book of daily pensées , A Calendar of Wisdom , that in times of trouble, “you have to embrace what the wisdom of humanity, your intellect, and your heart tell you: that the meaning of life is to serve the force that sent you into the world.”

Feeling is fundamental to religious experience, as scholarship on emotion has shown . Some religions elevate trancelike states of ecstasy, such as samadhi in both Hinduism and Buddhism, which involves complete meditative absorption. Most faiths emphasize the role of the emotional adoration of the divine, as in the Prophet Muhammad’s teaching that believers should “love Allah with all of your hearts.” One cannot rely on feeling alone, however, because it is so mutable. As the 16th-century founder of the Jesuit Order, Saint Ignatius of Loyola, noted, faith features feelings of not only consolation but also desolation, at moments when God feels absent from one’s life.

The second element of faith is belief, which are tenets you have accepted as truths, at least provisionally. These truths are not testable as scientific propositions are, so, in Thomas Aquinas’s definition , they are the “mean between science and opinion.” These are the propositions that you learn from reading and listening to other believers, and that you ultimately choose to accept; examples would be God’s laws for the Jewish people or the Eightfold Path to enlightenment for Buddhists.

Accepting such beliefs as truth does not mean they’re impossible to revise. In fact, research has shown that spiritual people are generally open to reflection on existential questions and willing to modify their views. But these tenets of faith are based on considered arguments, rather than feelings, so they tend to be stable and enduring.

Peter Wehner: David Brooks’s journey toward faith

Finally, religious practice offers a set of actions and rituals that you commit to observing in order to demonstrate your adherence to the faith for yourself and others. This is the element of faith that takes it out of the realm of abstraction and makes it part of your real, physical life. You can say you believe in the ideas of Zen, but Zen itself will not become a meaningful part of your life until you practice Zen meditation. Similarly, you can say you believe in the divine inspiration of the Quran, but that doesn’t mean much if you don’t actually read it.

You might assume that any practice requires both belief and feeling—entailing that, for example, you would feel impelled to go to a political demonstration only if you already believed in the cause. But you may have noticed the opposite occurring in your life: If you go to a demonstration uncommitted, you may find that the experience stimulates feelings and belief, which might then lead you to go to future demonstrations.

This is a basic form of what academics call “ path dependence ,” a phenomenon in which past decisions lead to similar actions in future. The concept is usually used by economists and political scientists to explain institutional inertia or resistance to organizational change, but the same principle can suggestively be applied to individual human behavior. Such path dependence can be affected by both positive and negative feedback, the sense either that people’s choices elicit increasing returns or that they are self-reinforcing or “locked in.”

That feedback loop can be a problem if your religious practice makes you become rigid in your ideology; economists, for example, have modeled that voter path dependence might be one of the causes of our increasing polarization. As it pertains to faith, the trick, then, is to be wary of your path dependence if it results in negative feedback: If you feel or behave like a “locked-in” party-line voter, you might be too rigid in your belief. Yet if you use path dependence on your faith exclusively for positive feedback—that is, your belief elicits increasing returns, perhaps boosting your altruism, community ties, or sense of meaning in life—then you will be using it as a force for good.

Put simply, be completely honest with yourself about why you’re practicing your faith; if your belief spurs positive feedback, carry on.

Faith Hill: The messy line between faith and reason

A healthy faith thus requires all three sources of spiritual nourishment. The data suggest that when one or more of those elements—of belief, feeling, and practice—are missing, people fall away. So if you’re looking for faith in your life, you need to seek all three.

Here is an optimal way to do so. In Tolstoy’s Calendar of Wisdom , he quotes an ancient Chinese proverb: “Those who know the rules of true wisdom are baser than those who love them. Those who love them are baser than those who follow them.” In other words, to develop a healthy faith, practice is more important than feeling, and feeling is more important than belief. This implies the reverse of what most people do to develop a spiritual life: They read and think to acquire knowledge and opinions—that is, beliefs—then they see if they “feel” their faith, and only then will they move on to practicing it. But as the proverb implies, this order of priorities won’t work very well.

The right approach is to start practicing, notwithstanding your current state of belief and feeling. If the practice evokes sentiment in you, then study the faith to develop knowledge and opinions. This is an experimental, hands-on approach, much in the manner of how many inventions and innovations come about: An inventor tries something, sees whether it works, and then figures out precisely what’s going on.

In a faith context, this means that you might go to a service of worship a few times. Then you could interrogate your feelings as to whether the services stimulated something deep within (or, alternatively, whether they left you cold). Finally, if the former feels true, you could start investigating the belief system intellectually.

Arthur C. Brooks: Jung’s five pillars of a good life

T he three elements of faith can be useful to apply to many parts of life, not just your spiritual quest. Consider marriage, for instance: Without the feelings of love and affection, a relationship is dead; without knowledge and opinions about your spouse, it has no depth; without practicing the rituals of love, your partnership will wither. This same algorithmic progression of faith can also map out your path to marriage. You start out with practice in the form of a date; you continue the relationship if you feel attraction and the beginnings of love; the pairing develops as you gain knowledge and form favorable opinions about your partner.

Obviously, this connubial example is not a random one. To find faith is to find a form of love—a love of the divine, or a rapturous spiritual connection with the universe. But like all good and worthwhile things in life, faith and love merit deep thought and serious effort.

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Diverse Cultures and Shared Experiences Shape Asian American Identities

About six-in-ten feel connected to other asians in the u.s., table of contents.

• The making of Asian American identity and knowledge of Asian history in the U.S.
• Immigrant ties shape Asian Americans' identities and their life in the U.S.
• Asians in the U.S. share similar views among themselves and with the U.S. public on what it means to be American
• How Asians in the U.S. describe their identity
• Asian adults and the general public agree: U.S. Asians have many different cultures
• Whom do U.S. Asians consider Asian?
• A majority of Asian adults say others would describe them as Asian when walking past them on the street
• For many Asian adults, where they were born shapes friendships formed in the U.S.
• Most Asian adults are comfortable with intermarriage
• Some Asians say they have hidden their heritage
• Connections with other Asian Americans, politics and political parties
• Need for a national leader advancing the concerns of Asian Americans
• Asian American registered voters and political party
• About one-quarter of Asian adults say they are informed about U.S. Asian history
• What being ‘truly American’ means to U.S. Asians
• Fewer than half of U.S. Asians consider themselves typical Americans
• What do Asian Americans view as important for the American dream?
• Most Asian adults say the American dream is within reach, but about a quarter say they will never achieve it
• Acknowledgments
• Sample design
• Data collection
• Weighting and variance estimation
• Largest origin groups
• Educational attainment
• Immigration status
• Length of time living in the U.S. among immigrants
• Citizenship status among immigrants

Pew Research Center conducted this analysis to understand the rich diversity of people of Asian origin or ancestry living in the United States and their views of identity. The study is part of the Center’s multiyear, comprehensive, in-depth quantitative and qualitative research effort focused on the nation’s Asian population. Its centerpiece is this nationally representative survey of 7,006 Asian adults exploring the experiences, attitudes and views of Asians living in the U.S. The survey sampled U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic ethnicity. It was offered in six languages: Chinese (Simplified and Traditional), English, Hindi, Korean, Tagalog and Vietnamese. Responses were collected from July 5, 2022, to Jan. 27, 2023, by Westat on behalf of Pew Research Center.

The Center recruited a large sample to examine the diversity of the U.S. Asian population, with oversamples of the Chinese, Filipino, Indian, Korean and Vietnamese populations. These are the five largest origin groups among Asian Americans. The survey also includes a large enough sample of self-identified Japanese adults, making findings about them reportable. In this report, the six largest ethnic groups include those who identify with one Asian ethnicity only, either alone or in combination with a non-Asian race or ethnicity. Together, these six groups constitute 81% of all U.S. Asian adults, according to a Pew Research Center analysis of the Census Bureau’s 2021 American Community Survey (ACS), and are the six groups whose attitudes and opinions are highlighted throughout the report. Survey respondents were drawn from a national sample of residential mailing addresses, which included addresses from all 50 states and the District of Columbia. Specialized surnames list frames maintained by the Marketing Systems Group were used to supplement the sample. Those eligible to complete the survey were offered the opportunity to do so online or by mail with a paper questionnaire. For more details, see the Methodology . For questions used in this analysis, see the Topline Questionnaire .

The survey research plan and questionnaire were reviewed and approved by Westat’s institutional review board (IRB), which is an external and independent committee of experts specializing in protecting the rights of research participants.

Even though the U.S. Asian population was the fastest growing racial and ethnic group in the country from 2000 to 2019 , it is still a relatively small population. According to the 2021 American Community Survey, the country’s Asian population constitutes 7% of the U.S. population (of all ages) and 7% of adults (those ages 18 and older).

Pew Research Center designed this study with these details in mind to be as inclusive as possible of the diversity of Asian American experiences. Even so, survey research is limited when it comes to documenting the views and attitudes of the less populous Asian origin groups in the U.S. To address this, the survey was complemented by 66 pre-survey focus groups of Asian adults , conducted from Aug. 4 to Oct. 14, 2021, with 264 recruited participants from 18 Asian origin groups. Focus group discussions were conducted in 18 different languages and moderated by members of their origin groups.

Findings for less populous Asian origin groups in the U.S., those who are not among the six largest Asian origin groups, are grouped under the category “Other” in this report and are included in the overall Asian adult findings in the report. These ethnic origin groups each make up about 2% or less of the Asian population in the U.S., making it challenging to recruit nationally representative samples for each origin group. The group “Other” includes those who identify with one Asian ethnicity only, either alone or in combination with a non-Asian race or Hispanic ethnicity. Findings for those who identify with two or more Asian ethnicities are not presented by themselves in this report but are included in the overall Asian adult findings.

To learn more about how members of less populous Asian origin groups in the U.S. identify, see the quote sorter based on our focus group discussions. There, you can read how participants describe their identity in their own words.

For this analysis, an additional national survey of 5,132 U.S. adults was conducted from Dec. 5 to 11, 2022, using Pew Research Center’s American Trends Panel . The survey of U.S. adults was conducted in English and Spanish. Respondents are recruited through national, random sampling of residential addresses.

Pew Research Center has conducted multiple studies that focus on Asian Americans. Previous demographic studies examined the diversity of origins , key facts , and rising income inequality among Asians living in the U.S. and key findings about U.S. immigrants. Qualitative studies have focused on what it means to be Asian in America as well as barriers to English language learning among Asian immigrants. Previous surveys have focused on concerns over discrimination and violence against Asian Americans, as well as studies about their religious beliefs . Find these publications and more on the Center’s Asian Americans topic page .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. The Center’s Asian American portfolio was funded by The Pew Charitable Trusts, with generous support from The Asian American Foundation; Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation; the Robert Wood Johnson Foundation; the Henry Luce Foundation; the Doris Duke Foundation; The Wallace H. Coulter Foundation; The Dirk and Charlene Kabcenell Foundation; The Long Family Foundation; Lu-Hebert Fund; Gee Family Foundation; Joseph Cotchett; the Julian Abdey and Sabrina Moyle Charitable Fund; and Nanci Nishimura.

We would also like to thank the Leaders Forum for its thought leadership and valuable assistance in helping make this survey possible.

The strategic communications campaign used to promote the research was made possible with generous support from the Doris Duke Foundation.

The terms Asian, Asians living in the United States , U.S. Asian population and Asian Americans are used interchangeably throughout this report to refer to U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic identity.

Ethnicity and ethnic origin labels, such as Chinese and Chinese origin, are used interchangeably in this report for findings for ethnic origin groups, such as Chinese, Filipino, Indian, Japanese, Korean or Vietnamese. For this report, ethnicity is not nationality. For example, Chinese in this report are those self-identifying as of Chinese ethnicity, rather than necessarily being a current or former citizen of the People’s Republic of China. Ethnic origin groups in this report include those who self-identify as one Asian ethnicity only, either alone or in combination with a non-Asian race or ethnicity.

Less populous Asian origin groups in this report are those who self-identify with ethnic origin groups that are not among the six largest Asian origin groups. The term includes those who identify with only one Asian ethnicity. These ethnic origin groups each represent about 2% or less of the overall Asian population in the U.S. For example, those who identify as Burmese, Hmong or Pakistani are included in this category. These groups are unreportable on their own due to small sample sizes, but collectively they are reportable under this category.

The terms Asian origins and Asian origin groups are used interchangeably throughout this report to describe ethnic origin groups.

Immigrants in this report are people who were not U.S. citizens at birth – in other words, those born outside the U.S., Puerto Rico or other U.S. territories to parents who are not U.S. citizens. I mmigrant , first generation and foreign born are used interchangeably to refer to this group.  

Naturalized citizens are immigrants who are lawful permanent residents who have fulfilled the length of stay and other requirements to become U.S. citizens and who have taken the oath of citizenship.

U.S. born refers to people born in the 50 U.S. states or the District of Columbia, Puerto Rico or other U.S. territories.

Second generation refers to people born in the 50 states or the District of Columbia, Puerto Rico or other U.S. territories with at least one first-generation (immigrant) parent.

Third or higher generation refers to people born in the 50 states or the District of Columbia, Puerto Rico or other U.S. territories with both parents born in the 50 states, D.C., Puerto Rico or other U.S. territories.

The nation’s Asian population is fast growing and diverse. Numbering more than 23 million, the population has ancestral roots across the vast, ethnically and culturally rich Asian continent. For Asians living in the United States, this diversity is reflected in how they describe their own identity. According to a new, nationwide, comprehensive survey of Asian adults living in the U.S., 52% say they most often use ethnic labels that reflect their heritage and family roots, either alone or together with “American,” to describe themselves. Chinese or Chinese American, Filipino or Filipino American, and Indian or Indian American are examples of these variations.

There are other ways in which Asians living in the U.S. describe their identity. About half (51%) of Asian adults say they use American on its own (10%), together with their ethnicity (25%) or together with “Asian” as Asian American (16%) when describing their identity, highlighting their links to the U.S.

And while pan-ethnic labels such as Asian and Asian American are commonly used to describe this diverse population broadly, the new survey shows that when describing themselves, just 28% use the label Asian (12%) on its own or the label Asian American (16%).

The survey also finds that other labels are used by Asian Americans. Some 6% say they most often prefer regional terms such as South Asian and Southeast Asian when describing themselves.

Asian adults see more cultural differences than commonalities across their group as well. When asked to choose between two statements – that Asians in the U.S. share a common culture, or that Asians in the U.S. have many different cultures – nearly all (90%) say U.S. Asians have many different cultures. Just 9% say Asians living in the U.S. share a common culture. This view is widely held across many demographic groups among Asian Americans, according to the survey.

The view that Asian Americans have many different cultures is also one held by the general public, according to another Pew Research Center survey of U.S. adults, conducted in December 2022. Among all U.S. adults, 80% say Asians in the U.S. have many different cultures, while 18% say they share a common culture. 1

Though Asian Americans’ identities reflect their diverse cultures and origins, Asian adults also report certain shared experiences. A majority (60%) say most people would describe them as “Asian” while walking past them on the street, indicating most Asian adults feel they are seen by others as a single group, despite the population’s diversity. One-in-five say they have hidden a part of their heritage (their ethnic food, cultural practices, ethnic clothing or religious practices) from others who are not Asian, in some cases out of fear of embarrassment or discrimination. Notably, Asian adults ages 18 to 29 are more likely to say they have done this than Asians 65 and older (39% vs. 5%).

Asian adults in the U.S. also feel connected with other Asian Americans. About six-in-ten (59%) say that what happens to Asians in the U.S. affects their own lives, at least to some extent. 2 And about two-thirds (68%) of Asian Americans say it is extremely or very important to have a national leader advocating for the concerns and needs of the Asian population in the U.S.

The new survey also shows that large majorities of Asian adults share similar views on what it takes to be considered truly American. And they consider many of the same factors to be important in their views of the American dream.

These are among the key findings from Pew Research Center’s new survey of Asian American adults, conducted by mail and online from July 5, 2022, to Jan. 27, 2023. This is the largest nationally representative survey of its kind to date that focused on Asian Americans. The survey was conducted in English and five Asian languages, among a representative sample of 7,006 Asian adults living in the United States. 

Asian Americans are 7% of the U.S. population, according to a Pew Research Center analysis of the 2021 American Community Survey. Their population is diverse, with roots in more than 20 countries in East Asia, Southeast Asia and the Indian subcontinent. About 54% of the national Asian population are immigrants. The six largest origin groups (Chinese, Filipino, Indian, Japanese, Korean and Vietnamese), a focus of this survey and report, together account for 79% of all Asian Americans.

Overall, about 34% of Asian Americans are the U.S.-born children of immigrant parents, and another 14% are of third or higher generation (meaning their parents were born in the U.S. as well), according to a Pew Research Center analysis of the 2022 Current Population Survey, March Annual Social and Economic Supplement.

This survey and report focus on Asian adults in the U.S. The six largest origin groups together account for 81% of Asian adults. And 68% of Asian American adults are immigrants, according to Center analysis of the 2021 American Community Survey. Additionally, 25% are the U.S.-born children of immigrant parents and 10% are of third or higher generation, according to Center analysis of government data.

The pan-ethnic term “Asian American” emerged in Berkeley, California, in the 1960s as part of a political movement to organize the diverse U.S. Asian population. The creation of an Asian American identity was in reaction to a long history of exclusion of Asians in the country, including the 1882 Chinese Exclusion Act and a pair of Supreme Court cases in the 1920s clarifying that Asians, including South Asians, are not “free White persons” and therefore were excluded from becoming naturalized U.S. citizens. 3 Subsequently, the term was adopted by the federal government and today is the principal identity label used by media, academics, researchers and others to describe today’s diverse Asian American population.

In most cases today, someone is considered Asian or Asian American if they self-identify as such. But Asian Americans do not necessarily agree on which regional or ethnic groups from the Asian continent they consider to be Asian, according to the new survey. The vast majority of Asian adults say they consider those from East Asia, such as Chinese or Koreans (89%); Southeast Asia, such as Vietnamese or Filipinos (88%); and to a lesser extent South Asia such as Indians or Pakistanis (67%) to be Asian.

But Asian adults are split on whether they consider Central Asians such as Afghans or Kazakhs to be Asian (43% of Asian adults say they are). While about half of Indian adults (56%) say they would include Central Asians in the category Asian, fewer than half of Filipino (40%), Chinese (39%), Japanese (34%), Korean (32%) and Vietnamese (30%) adults consider them Asian.

Few Asians say they are knowledgeable about U.S. Asian history

Asian Americans have a long history in the United States. From Chinese laborers who helped build the first transcontinental railroad, to Japanese immigrants who arrived as plantation workers in what is now the state of Hawaii, to the incarceration of Japanese Americans during World War II, to Filipinos being treated as U.S. nationals while the Philippines was a U.S. territory, the Asian American experience has been a part of U.S. history.

With the passage of the landmark Immigration and Nationality Act of 1965, a new wave of immigrants from Asia began arriving in the United States, creating a new, contemporary U.S. Asian history. The Vietnam War and other conflicts in Southeast Asia brought Vietnamese and other Southeast Asian refugees to the U.S. , first with the passage of the 1975 Indochina Migration and Refugee Assistance Act and then with the Refugee Act of 1980. The 1990 Immigration Act raised immigration ceilings and set in place processes that allowed the flows of Asian immigrants, particularly of high-skilled immigrants, to continue and expand. The U.S. technology boom of the 1990s and 2000s attracted many high-skilled immigrants, particularly from India and China, to tech centers around the country.

This rich history, however, is little-known to Asian adults, according to the new survey. One-in-four (24%) say they are very or extremely informed about history of Asians in the United States, while an equal share (24%) say they are little or not at all informed.

The majority of those very or extremely informed about the history of Asians in the U.S. say they learned about this history through informal channels: internet (82%), media (76%) and family and friends (70%). In contrast, 49% learned about it from college or university courses and 39% from elementary through high school.

Immigrant ties shape Asian Americans’ identities and their life in the U.S.

Immigration experiences, connections with home countries, and how long someone has lived in the U.S. shape many Asian Americans’ identities. Among Asian adults in the U.S., immigrants are more likely than those who are U.S. born to describe their identity most often with their ethnic labels, either alone or together with the label American (56% vs. 41%).

Meanwhile, Asian immigrants are less likely than U.S.-born Asians (46% vs. 65%) to say they most often describe themselves as American in some way – whether by their ethnic label combined with American, as Asian American, or simply as American. Still, nearly half of Asian immigrants describe themselves in one of these three ways.

When it comes to identifying with the label Asian – either alone or as Asian American – immigrant and U.S.-born Asians are about equally likely to say they do so (28% and 29% respectively). Immigrant Asians are less likely than U.S.-born Asians to identify most often as Asian American (14% vs. 21%).

On the question of seeing themselves more as a “typical American” or “very different from a typical American,” Asian immigrant adults are far less likely than those born in the U.S. to think of themselves as a typical American (37% vs. 69%).

Nativity is also tied to how Asians in the U.S. develop their friendships. Those who immigrated to the U.S. are more likely to have friends who are Asian or of the same ethnicity as them than are U.S.-born Asians (56% vs. 38%).

Asian immigrants (15%) are also less likely than U.S.-born Asians (32%) to have ever hidden a part of their heritage from people who are not Asian. When asked in an open-ended question to explain why they hide aspects of their culture, some U.S.-born respondents mentioned phrases such as “fear of discrimination,” “being teased” and “embarrassing.”

Views of identity among Asian American immigrants are often tied to time spent in the U.S.

How long Asian immigrants have lived in the U.S. also shapes their identity and experiences. Those who arrived in the U.S. in the past 10 years are more likely than those who arrived more than 20 years ago to say they most often use their ethnicity, such as Filipino or Vietnamese, to describe themselves. And about two-thirds (65%) of those who arrived in the U.S. in the past decade describe their identity most often with their ethnicity’s name, either alone or combined with American, compared with 54% among those who have been in the country for more than two decades.

Roughly half (54%) of those who have arrived in the past 10 years say they most often use only their ethnicity to describe themselves, compared with just 21% of those who arrived more than two decades ago who say the same.

On the other hand, just 17% of Asian immigrants who arrived in the country in the past 10 years describe themselves most often as American, by their ethnic label combined with American, or as Asian American, while 59% of those who arrived more than 20 years ago do so.

When it comes to their circle of friends, 60% of Asian immigrants who arrived in the past 10 years say most or all of their friends are also Asian Americans, while 50% of those who arrived more than 20 years ago say the same.

And when asked if they think of themselves as typical Americans or not, Asian immigrants who arrived in the U.S. in the past decade are substantially less likely than those who arrived more than two decades ago to say they are typical Americans (20% vs. 48%).

The new survey also explored the views Asian Americans have about traits that make one “truly American.” Overall, Asian Americans and the general U.S. population share similar views of what it means to be American. Nearly all Asian adults and U.S. adults say that accepting people of diverse racial and religious backgrounds (94% and 91%), believing in individual freedoms (92% and 94%) and respecting U.S. political institutions and laws (89% and 87%) are important for being truly American.

Similarly, Asian Americans and the U.S. general population share in their views about the American dream. They say having freedom of choice in how to live one’s life (96% and 97% respectively), having a good family life (96% and 94%), retiring comfortably (96% and 94%) and owning a home (both 86%) are important to their view of the American dream. Smaller shares of Asian and U.S. adults (30% and 27%) say owning a business is important to their view of the American dream.

Here are other survey findings highlighting the diverse views and attitudes of Asian adults living in the U.S.:

• Indian adults are the most likely of the six largest Asian origin groups to say they most often use their ethnicity, without the addition of “American,” to describe themselves. About four-in-ten Indian adults (41%) say they do this. By comparison, smaller shares of Korean (30%), Filipino (29%), Chinese (26%) and Vietnamese (23%) adults do the same. Japanese adults (14%) are the least likely among the largest groups to use their ethnic identity term alone.
• Japanese adults are the least likely among the largest Asian origin groups to say they have friendships with other Asians. About one-in-three Japanese adults (34%) say most or all their friends share their own ethnicity or are otherwise Asian. By contrast, about half of all Indian (55%), Vietnamese (55%), Chinese (51%), Korean (50%) and Filipino (48%) respondents say the same.
• One-in-four Korean adults (25%) say they have hidden part of their heritage from people who are not Asian. Some 20% of Indian, 19% of Chinese, 18% of Vietnamese, 16% of Filipino and 14% of Japanese adults say they have done the same.
• Across the largest ethnic groups, about half or more say that what happens to Asians in the U.S. affects what happens in their own lives. About two-thirds of Korean (67%) and Chinese (65%) adults say this. By comparison, 61% of Japanese, 54% of Filipino, 55% of Indian and 52% of Vietnamese adults say they are impacted by what happens to Asians nationally.
• Most Asian adults among the largest ethnic origin groups say a national leader advancing the U.S. Asian community’s concerns is important. Roughly three-in-four Filipino (74%) and Chinese (73%) adults say it is very or extremely important to for the U.S. Asian community to have a national leader advancing its concerns. A majority of Vietnamese (69%), Korean (66%), Japanese (63%) and Indian adults (62%) says the same.  
• About half of Vietnamese registered voters (51%) identify with or lean to the Republican Party. In contrast, about two-thirds of Indian (68%), Filipino (68%) and Korean (67%) registered voters identify with or lean toward the Democratic Party. And 56% of Chinese registered voters also associate with the Democratic Party. 
• This finding is from a nationally representative survey of 5,132 U.S. adults conducted by Pew Research Center from Dec. 5 to 11, 2022, using the Center’s American Trends Panel . ↩
• In recent years, a major source of concern and fear among many Asian adults in the U.S. has been the rise in reported violence against Asian Americans . ↩
• For more on the history of the creation of an Asian American identity, see Lee, Jennifer and Karthick Ramakrishnan. 2019. “ Who counts as Asian .” Ethnic and Racial Studies. ↩

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• Integration & Identity
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• Racial Bias & Discrimination

Key facts about Asian Americans living in poverty

Methodology: 2023 focus groups of asian americans, 1 in 10: redefining the asian american dream (short film), the hardships and dreams of asian americans living in poverty, key facts about asian american eligible voters in 2024, most popular, report materials.

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