why research is not

June 19, 2013

What's So Hard about Research?

By Jody Passanisi and Shara Peters

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American

We are told that the students that we teach are “digital natives.” This term implies that from the time they were born, technology has played such a large part in students’ lives that they know no other way. Also, it has been noted that digital natives have an aptitude for technology that is significantly different from the older generations (who have been dubbed “digital immigrants”); the joke goes that if you give a digital native and a digital immigrant a new digital camera, the native will be taking pictures before the immigrant has finished reading page two of the manual. The assumption is that this new generation is simply better than us at technology.

However, as we wrote about in another article for Scientific American , just because students are digital natives, does not mean that they have skills to figure out all technology, or to use technology in a purposeful way. We noticed that, though these digital natives have the world of information at their fingertips, for some reason they are often unable to take basic problem-solving skills and apply them to simple online research. They had no problem figuring out how to work the newest update to Facebook, but when asked to find out any information that required the smallest amount of critical thinking, students were hampered. The best example we have of this is when we asked students what the most important causes of the Revolutionary War were—we heard a student ask Siri: “What are the most important causes of the Revolutionary War?” When Siri did not know the answer, the student said, “I don’t know, I can’t find it.”

Students can find out basic names, dates, and facts through online research. If we ask them what year the Declaration of Independence was signed, they will Google that exact question, and most of the time, produce the right answer. But when asked to research a question that does not have one “right” answer, the room quickly dissolves into a chorus of “I don’t get it” and “I need help” and “I can’t find it.”

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In this article we will attempt to answer this question that we have posed and discussed often here at Scientific American:

What about online research is challenging to students?

Through observation of our students, we have come up with five hypotheses as to why this may be:

· Students today are accustomed to instant gratification, and therefore can be overwhelmed by tasks that require time-consuming research.

There are very few things in life that our students have to wait for today. Information they need to know is posted instantly online, they can connect with their friends through social media without needing to wait for school the next day, and Googling a question will give them a quick answer to any fact they want to know. However, research isn’t actually easy--in fact, it’s quite deceptive how the Internet makes it seem easy. In reality, research requires students to read, interpret, and analyze new information, reshape their research question, and start again. This kind of sustained focus on a challenging task is very hard for most students to hold. Here is an exchange that exemplifies this facet of the issue:

Student: “I can’t find anything about the buildings of the South during Reconstruction.”

Teacher: “Ok, show me what sites you’ve used.”

(Student pulls up an article from the History Channel)

Teacher: “Well, I see a good starting place right here. It says that much of the South was destroyed during Sherman’s March to the Sea during the Civil War. Why don’t you find out what areas his march destroyed, and then look up those cities to see what kind of destruction they faced?”

Student: (while pouting and walking back to his desk) “But that’s going to take forever !”

What the student meant to tell the teacher was, “ I can’t find anything easily about the buildings of the South during Reconstruction.” It isn’t true that, as a whole, these students have a difficult time with sustained attention. They do not stop researching and begin another activity because they got distracted; in our experience, they are more likely to spin themselves in circles making no progress for an entire class period because they do not want to go through a cognitive process that will take “forever.”

· When researching online, students unsuccessfully scan pages of text as opposed to reading those pages of text for comprehension. Therefore, they cannot tell whether or not the source they are looking at is applicable to their research question.

There are many techniques one can use to quickly locate information on an Internet page. For example, CTRL + F will bring up a “find” tool that will allow you to highlight all instances of a particular word or phrase on a page. Students use this tool quite frequently; when one student needed to find out what President Polk thought about U.S. expansion, she found an article about expansion, hit CTRL + F, and searched for “Polk.” All of the results on the page linked Polk to legislation that was passed, and land that was acquired during his term, but nowhere on the page could she find a sentence that said that President Polk thought that expansion was ________. Instead of reading the article and using inductive reasoning to figure out that President Polk was probably in favor of expansion, she told us that she couldn’t find the answer.

There are a few factors that we believe are at work here. It is faster to CRTL + F a keyword than it is to read an article, so perhaps some of hypothesis number 1 is at work, here: students want to take the fastest and quickest route. However, there are also issues of monitoring reading comprehension. The problem is not necessarily that the language of the article was too sophisticated for this student; the real problem is that she never stopped to ask herself the question, “Do I understand what this means?”

· When students are given a research prompt by their teacher, students often do not care enough about the topic to really persevere. Therefore, when they find that answers are not immediately apparent, they do not have the motivation necessary to fuel their sustained attention.

We have noticed that when students look up information we tell them to look up, they ask us many questions during a class period. Most are interested in making sure they have the “right answers”, and checking that their assignment is “long enough”. When students conduct research about a topic they have interest in, they have a much stronger sense of purpose. While some do still ask us questions in which they seek our approval, it is more often for approval about their thoughts pertaining to content than for approval of the length of their assignment. They seem to take more ownership of the material, and think about it on a higher level.

· Because there is so much information online, and not all of it is credible, Internet search results can be overwhelming to students. Therefore, the amount of information paralyzes rather than empowers students.

It seems counter-intuitive that a student could pull up 500,000 search results and still tell her teacher that she can’t find anything (just like flipping through a billion channels on cable, but finding that nothing is on)-- but students do often feel that way. The best way to illustrate this is to describe the difference in student responses when they were researching using a search engine other than Google.

Dulcinea Media came up with a search engine designed for students called SweetSearch . It works similarly to Google, in that there is a database of files that one can search by typing keywords into a search bar. What is different about SweetSearch is that the database only contains 30,000 documents, all of which have been previously vetted for academic reliability. For a particular project, the only Internet search engine we allowed the students to use was SweetSearch.

When they researched in class using Google, five to ten students per class period would say they were unable to find what they needed. When they researched in class using SweetSearch, there was not a single student who told us that they could not find any information about their topic. So whether students liked using SweetSearch or not, it is clear that it helped them be more successful when conducting their research.

· Developmentally, middle school students are just beginning to be able to think critically, but they seem programmed to look for “the” answer, and do not have a strong sense of self-efficacy when presented with open-ended questions.

Some of our unit assessments are structured in the style of Project Based Learning where students can present their findings in any form, as long as it answers the inquiry-based prompt. Many students were very uncomfortable with the idea that they would be making the decision about what form their project will take, and continually tried to get a stamp of approval. Questions like, “Do you think it will be okay if we make a movie?” Or “Will it be good if we make a poster?” were all answered with some version of, “It doesn’t matter what we think. What do you think?” We could see the frustration in their faces when they did not get the answer they wanted, but our goal here was for them to realize that their opinions were the ones that mattered.

Students also asked for their teachers’ opinions about their research findings. Students felt unsure about their authority, and wanted us to tell them that they had found the right answer. It takes the responsibility off of them; however, we wanted the students to take ownership of the information, and unless they were historically inaccurate in their findings (which almost never happened), we answered all of these questions in the same manner as the questions about their projects: “It doesn’t matter what I think. What do you think?”

Now that we know students struggle with research, now that we’ve discussed why that might be so, what steps can we take to help improve the situation? The next frontier for us will be to design curricular interventions that help students overcome some of these challenges they face, and to provide opportunities--like our Project Based Learning research unit assessment-- for students to research in more productive ways. SweetSearch and critical thinking are just the beginning. This question of research will only be more acute in the coming years as information in this age is becoming even more accessible and available to students. It is our job as their teachers to help students understand and be able to use this information that they discover.

Peter DeWitt's

Finding common ground.

A former K-5 public school principal turned author, presenter, and leadership coach, DeWitt provides insights and advice for education leaders. He can be found at www.petermdewitt.com . Read more from this blog .

4 Reasons Educators Use Research and 4 Reasons They Don’t

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This is a deeply complicated topic with many layers of complexity. It’s easy to judge one of the parties in this topic for living in an ivory tower and the other party for not wanting to develop professionally and remain current by using peer-reviewed research. However, none of that is true. There are some basic reasons why educators and researchers do not always interact, and I’ve recently discovered how sad that is because both parties are really missing out.

Recently, I attended and presented at the ICSEI Conference in Stavanger, Norway. Not only were 45 countries represented, it was also perhaps the most eclectic group I have ever had the pleasure to spend time with over four days.

There were teachers, building, district, regional, and large territory leaders, as well as Ph.D. students, professors, consultants, and researchers. It was a conference filled with opportunities to expand the way we think and practice. Knowing that I was entering into this domain, I was asked to give a preconference keynote to Ph.D. students on the topic of making their research practical.

It’s a topic I care deeply about because I work with researchers and try and help to make their research practical for those who are intended to use it ... teachers and leaders. However, over the time I have been writing this blog, I realized that even the most well-known research used in schools by Dweck, Gardner, and Tomlinson had to be clarified by the authors of that research because many times teachers and leaders were not using it correctly.

What I have also learned is that there is a great deal of research out there that could be so beneficial to teachers, leaders, instructional coaches, special education teachers, school psychologists, counselors, and everyone else who works in a school, but most times they will never come across it. In fact, my Education Week colleague Sarah Sparks over at the Inside School Research blog recently wrote about the fact that the feds spend millions on research, but few educators ever read it, which you can read here in it’s entirety .

Why Educators Use It, and Why They Don’t There are probably countless reasons why educators use research and just as many reasons to explain why they don’t. So, in an effort to bridge that gap between the two, I wanted to list a few reasons. I usually hear from people who have other reasons I didn’t mention, so please feel free to add those to the comment section down below.

Why Educators Use Research:Fits their context - First and foremost, we use research when it fits our context. If we love an idea and want to get better at it, then we will most likely do action research or some sort of independent research to find something that will help us improve.

Social media - Those educators we follow Tweet about it. My principal is talking about it at the faculty meeting, and my favorite colleague just bought the book. I have major FOMO, so I really need to check this out!

Easy to put into practice - We read about it in a journal that a friend sent, and it seems easy to put into practice.

District makes them - The district says this is extremely important, or they want to “pilot it,” which means we will have to do it next year, so I’m going to jump on board now.

The Reasons We Don’t:Too complicated - Why do researchers have to use so many numbers and educational words? I’m actually not being flippant here. I seriously wonder why researchers do that, because it often means we can’t get past Page 1. I find that there are times that I can’t figure out the point of the study much less use it with my students.

Not relevant - Not sure where this fits in with my reality.

You do it well already - I’ve mastered this already. Time to move on. Sometimes, however, if we don’t collect evidence to actually understand our impact, a confirmation bias may be at play here.

Not enough time - I have PLC meetings, faculty meetings, district-required meetings, and grades to do. I simply don’t have time to take something else on. Plus, the district didn’t say we have to read this, so I’m not sure it’s worth the little time I have.

Why Researchers and Educators Don’t Always Communicate Sometimes it’s hard to communicate when you aren’t in the same venue. Friends who are researchers have said that their universities do not always offer an incentive to publish in teacher and leader education journals like Educational Leadership or Education Week . They say their universities pressure them to publish in peer-reviewed research journals that other researchers read. You know, the ones that make their way around the university-professor crowd.

Unfortunately, that’s like preaching to the choir instead of going to a new church that may do something with the research they read. Researchers, although they may lack the guidance from their universities, need to publish in media that teachers and leaders actually read. After all, if teachers and leaders do not know research exists because they are not reading those journals, what’s the point of doing the research?

It’s the difference between a teacher that expects their students to go to them, as opposed to teachers who know how to go to their students.

In the End Teachers often have most of their day planned for them, as they plan for student learning, PLCs, faculty meetings, and other duties as assigned. It’s not that many do not want to read the latest research, but it’s that they don’t have time to do so. Researchers need to do a better job of making their research practical for those that they hope to use it, regardless of if that’s what their university wants. As we know, the WHY is important. Why did researchers do their research in the first place? Hopefully, because they wanted to get it into the hands of teachers and have an impact on students.

How can researchers go to teachers?

• Blog about it—blogs are usually short, keep you on task, and allow for teachers and leaders to get a taste of what your research is all about.
• Get into schools and work with teachers from time to time.
• Skip the big words and use the practical ones. This is not meant to be flippant. I find the best way to explain something is to keep it simple.

Where can teachers and leaders go to read research?

Research 4 Schools The Conversation Regional Education Labs What Works Clearinghouse

Last but not least, I am starting to take pieces of research like self-efficacy, collective efficacy, and teacher talk and creating five- minute YouTube videos on it. The short video focusing on Collective Efficacy is below.

Peter DeWitt, Ed.D., is the author of several books including Coach It Further: Using the Art of Coaching to Improve School Leadership (Corwin Press. 2018). Connect with him on Twitter .

The opinions expressed in Peter DeWitt’s Finding Common Ground are strictly those of the author(s) and do not reflect the opinions or endorsement of Editorial Projects in Education, or any of its publications.

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Why Most Clinical Research Is Not Useful

* E-mail: [email protected]

Affiliations Stanford Prevention Research Center, Department of Medicine and Department of Health Research and Policy, Stanford University School of Medicine, Palo Alto, California, United States of America, Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Palo Alto, California, United States of America

• John P. A. Ioannidis

Published: June 21, 2016

• https://doi.org/10.1371/journal.pmed.1002049
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Citation: Ioannidis JPA (2016) Why Most Clinical Research Is Not Useful. PLoS Med 13(6): e1002049. https://doi.org/10.1371/journal.pmed.1002049

Copyright: © 2016 John P. A. Ioannidis. 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 Meta-Research Innovation Center at Stanford (METRICS) is funded by a grant from the Laura and John Arnold Foundation ( http://www.arnoldfoundation.org ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The author is a member of the editorial board of PLOS Medicine .

Abbreviations: NIH, National Institutes of Health; PCORI, Patient-Centered Outcomes Research Institute; PCSK9, proprotein convertase subtilisin-kexin type 9

Provenance: Commissioned; externally peer-reviewed

Summary Points

• Blue-sky research cannot be easily judged on the basis of practical impact, but clinical research is different and should be useful. It should make a difference for health and disease outcomes or should be undertaken with that as a realistic prospect.
• Many of the features that make clinical research useful can be identified, including those relating to problem base, context placement, information gain, pragmatism, patient centeredness, value for money, feasibility, and transparency.
• Many studies, even in the major general medical journals, do not satisfy these features, and very few studies satisfy most or all of them. Most clinical research therefore fails to be useful not because of its findings but because of its design.
• The forces driving the production and dissemination of nonuseful clinical research are largely identifiable and modifiable.
• Reform is needed. Altering our approach could easily produce more clinical research that is useful, at the same or even at a massively reduced cost.

Practicing doctors and other health care professionals will be familiar with how little of what they find in medical journals is useful. The term “clinical research” is meant to cover all types of investigation that address questions on the treatment, prevention, diagnosis/screening, or prognosis of disease or enhancement and maintenance of health. Experimental intervention studies (clinical trials) are the major design intended to answer such questions, but observational studies may also offer relevant evidence. “Useful clinical research” means that it can lead to a favorable change in decision making (when changes in benefits, harms, cost, and any other impact are considered) either by itself or when integrated with other studies and evidence in systematic reviews, meta-analyses, decision analyses, and guidelines.

There are many millions of papers of clinical research—approximately 1 million papers from clinical trials have been published to date, along with tens of thousands of systematic reviews—but most of them are not useful. Waste across medical research (clinical or other types) has been estimated as consuming 85% of the billions spent each year [ 1 ]. I have previously written about why most published research is false [ 2 ] and how to make more of it true [ 3 ]. In order to be useful, clinical research should be true, but this is not sufficient. Here I describe the key features of useful clinical research ( Table 1 ) and the current state of affairs and suggest future prospects for improvement.

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https://doi.org/10.1371/journal.pmed.1002049.t001

Making speculative, blue-sky research more productive represents a partly intractable problem, given the unpredictability of such research, but significantly improving clinical research—and developing tools for assessing its utility or lack thereof—appears conceptually more straightforward.

Features of Clinically Useful Research

Problem base.

There is higher utility in solving problems with higher disease burdens. However, context is important. Solving problems with low prevalence but grave consequences for affected patients is valuable, and broadly applicable useful research may stem from studying rare conditions if the knowledge is also relevant to common conditions (e.g., discovering the importance of the proprotein convertase subtilisin-kexin type 9 [PCSK9] pathway in familial hypercholesterolemia may help develop treatments for many other patients with cardiovascular disease). Furthermore, for explosive epidemics (e.g., Ebola), one should also consider the potential burden if the epidemic gets out of control.

Conversely, clinical research confers actual disutility when disease mongering [ 4 ] creates a fictitious perception of disease burden among healthy people. In such circumstances, treated people, by definition, cannot benefit, because there is no real disease to treat.

Data show only weak or modest correlations between the amount of research done and the burden of various diseases [ 5 , 6 ]. Moreover, disease mongering affects multiple medical specialties [ 4 , 7 , 8 ].

Context Placement and Information Gain

Useful clinical research procures a clinically relevant information gain [ 9 ]: it adds to what we already know. This means that, first, we need to be aware of what we already know so that new information can be placed in context [ 10 ]. Second, studies should be designed to provide sufficiently large amounts of evidence to ensure patients, clinicians, and decision makers can be confident about the magnitude and specifics of benefits and harms, and these studies should be judged based on clinical impact and their ability to change practice. Ideally, studies that are launched should be clinically useful regardless of their eventual results. If the findings of a study are expected to be clinically useful only if a particular result is obtained, there may be a pressure to either obtain that result or interpret the data as if the desired result has been obtained.

Most new research is not preceded or accompanied by systematic reviews [ 10 , 11 ]. Interventions are often compared to placebos or normal care, despite effective interventions having previously been demonstrated. Sample-size calculations almost always see each trial in isolation, ignoring other studies. Across PubMed, the median sample size for published randomized trials in 2006 was 36 per arm [ 12 ]. Nonvalidated surrogate outcomes lacking clinical insight [ 13 ] and composite outcomes that combine outcomes of very different clinical portent [ 14 ] are often utilized so that authors can claim that clinical studies are well powered. The value of “negative” results is rarely discussed when clinical studies are being designed.

Research inferences should be applicable to real-life circumstances. When the context of clinical research studies deviates from typical real-life circumstances, the question critical readers should ask is, to what extent do these differences invalidate the main conclusions of the study? A common misconception is that a trial population should be fully representative of the general population of all patients (for treatment) or the entire community (for prevention) to be generalizable. Randomized trials depend on consent; thus, no trial is a perfect random sample of the general population. However, treatment effects may be similar in nonparticipants, and capturing real-life circumstances is possible, regardless of the representativeness of the study sample, by utilizing pragmatic study designs.

Pragmatism has long been advocated in clinical research [ 15 ], but it is rare. Only nine industry-funded pragmatic comparative drug effectiveness trials were published between 1996 and 2010 according to a systematic review of the literature [ 16 ], while thousands of efficacy trials have been published that explore optimization of testing circumstances.

Studying treatment effects under idealized clinical trial conditions is attractive, but questions then remain over the generalizability of the findings to real-life circumstances. Observational studies (performed in the thousands) are often precariously interpreted as able to answer questions about causal treatment effects [ 17 ]. The use of routinely collected data is typically touted as being more representative of real life, but this is often not true. Most of the widely used observational studies deal with peculiar populations (e.g., nurses, physicians, or workers) and/or peculiar circumstances (e.g., patients managed in specialized health care systems or covered by specific insurance or fitting criteria for inclusion in a registry). Eventually, observational studies often substantially overestimate treatment effects [ 18 , 19 ].

Patient Centeredness

Useful research is patient centered [ 20 ]. It is done to benefit patients or to preserve health and enhance wellness, not for the needs of physicians, investigators, or sponsors. Useful clinical research should be aligned with patient priorities, the utilities patients assign to different problems and outcomes, and how acceptable they find interventions over the period for which they are indicated. Proposed surrogate outcomes used in research need to closely correlate with real patient-relevant outcomes for patients in the clinic.

There is currently a heightened interest in patient-centered research, as exemplified by the Patient-Centered Outcomes Research Institute (PCORI), which was launched in 2012 in the United States to foster research relevant to patient needs [ 21 ]. Similar activities are ongoing in the United Kingdom and elsewhere. However, patients are still rarely involved in setting research priorities, despite the frequent mismatch between patient priorities and research agenda. Patients and physicians are frequently bombarded with information that tries to convince them that surrogates or other unimportant outcomes are important—such short-cuts either have commercial benefits or facilitate fast publication and academic advancement.

Value for Money

Good value for money is an important consideration, especially in an era of limited resources, and this can be assessed with formal modeling (value of information) [ 22 ]. Different studies may require very different levels of financial investment and may differ substantially in how much we can learn from them. However, the benefits of useful clinical research more than offset the cost of performing it [ 23 ].

Most methods for calculating value for money remain theoretical constructs. Practical applications of value-of-information methods are counted in single digit numbers [ 24 , 25 ]. Clinical research remains extremely expensive, even though an estimated 90% of the present cost of trials could be safely eliminated [ 26 , 27 ]. Reducing costs by streamlining research could do more than simply allow more research to take place. It could help make research better by reducing the pressure to cut corners, which leads to studies lacking sufficient power, precision, duration, and proper outcomes to convincingly change practice.

Feasibility

Even if all other features are met, some studies may be very difficult or practically impossible to conduct. Feasibility of research can sometimes be difficult to predict up front, and there may be unwarranted optimism among investigators and funders.

Many clinical trials are terminated because of futility. Twenty-five percent of the trials approved by six research ethics committees between 2000 and 2003 in Canada, Germany, and Switzerland were discontinued [ 28 ], and the discontinuation rate was 43% for a cohort of surgical trials registered between 2008 and 2009 [ 29 ]. For other types of research, feasibility problems are less accurately known but probably even more common.

Transparency (Trust)

Utility decreases when research is not transparent, when study data, protocols, and other processes are not available for verification or for further use by others. Trust is also eroded when major biases occur in the design, conduct, and reporting of research.

Only 61% of trials published in clinical journals in 2010 had been registered [ 30 ], and rates are much lower for nonregulated interventions [ 31 ] (e.g., 21% and 29% for trials published in psychological or behavioral [ 32 ] and physical therapy [ 33 ] journals, respectively). Only 55/200 (28%) of journals that publish clinical trials required trial registration as of 2012 [ 34 ]. Few full protocols are registered, analysis plans are almost never prespecified, and the full study data are rarely available [ 35 ]. Trust has been eroded whenever major subversion of the evidence has been uncovered by legal proceedings [ 36 ] or reanalysis [ 37 ] with different conclusions (e.g., as in the case of neuraminidase inhibitors for influenza) [ 38 ]. Biases in the design, analysis, reporting, and interpretation remain highly prevalent [ 39 – 41 ].

Other Considerations

Uncertainty..

Some uncertainty may exist for each of the features of clinical research outlined above, even though it is less than the uncertainty inherent in blue-sky and preclinical investigation. Uncertainty also evolves over time, especially when research efforts take many years. Questions can lose their importance when circumstances change. In one of my first papers, a systematic review of zidovudine monotherapy [ 42 ], the question was extremely relevant when we started work in 1993 and still important when the paper was accepted in late 1994. However, by the time the study was published in mid-1995, the question was of no value, as new highly effective regimens had emerged: clinical utility was demolished by technological advances.

Other sources of evidence besides trials.

Observational studies often add more confusion rather than filling the information deficits [ 18 , 19 ]. Meta-analyses, decision analyses, and guidelines cannot really salvage the situation based on largely useless studies and may add their own problems and biases [ 43 – 45 ].

Focusing on major journals.

Some clinicians prefer to read only research published in major general medical journals ( The New England Journal of Medicine , The Lancet , BMJ , JAMA , and PLOS Medicine ). However, these journals cover a tiny minority of published clinical research. Out of the 730,447 articles labeled as “clinical trial” in PubMed as of May 26, 2016, only 18,231 were published in the major medical journals. Most of the articles that inform guidelines and clinical practice are published elsewhere. Studies in major general medical journals may do better in terms of addressing important problems, but given their visibility, they can also propagate more disease mongering than less visible journals. Clinical trials published in major medical journals are larger on average (e.g., median sample size 3,116 and 3,104, respectively, for papers published in The Lancet and BMJ in September 2007 [ 46 ]). However, the small clinical trials published in major general journals actually have more exaggerated results, on average, than equally small studies published elsewhere [ 47 ]. The Lancet requires routinely systematic placement of the research in context for trials, and increasingly, major journals request full protocols for published trials. Pragmatism, patient centeredness, assessments of value for money, and transparency and protection from bias remain suboptimal for most clinical research published in major journals ( Table 2 ).

https://doi.org/10.1371/journal.pmed.1002049.t002

Overall Picture

Ultimately, no utility feature is met by the majority of clinical research studies, perhaps with the exception of feasibility ( Table 2 ). Studies that meet all utility features or almost all of them are extreme rarities, even in the most highly selective journals.

Improving the Situation

The problem of nonuseful research should not be seen as a blame game against a specific group (e.g., clinical researchers) but instead should be seen as an opportunity to improve. The challenges and the problems to solve involve not only researchers but also institutions, funding mechanisms, the industry, journals, and many other stakeholders, including patients and the public. Joint efforts by multiple stakeholders may yield solutions that are more likely to be more widely adopted and thus successful [ 3 ].

Clinical Research Workforce and Physicians

The clinical research workforce is huge: millions of people have coauthored at least one biomedical paper, and most have done so only once [ 48 ]. Students, residents, and clinical fellows are often expected to do some research. This exposure can be interesting, but trainees are judged on their ability to rapidly produce publications, a criterion that lends itself badly to the production of the sort of large, long-term, team-performed studies often needed to inform us about health, disease, and health care. Such researchers can become exploited as low-paid or volunteer personnel [ 49 ], and an untrained, noncommitted workforce cannot produce high-quality research. Other perverse recipes in clinical research include universities and other institutions simply asking for more papers (e.g., least publishable units) instead of clinically useful papers and clinical impact not being a formal part of the publication metrics so often used to judge academic performance. Instead of trying to make a prolific researcher of every physician, training physicians in understanding research methods and evidence-based medicine may also help improve the situation by instilling healthy skepticism and critical thinking skills.

The Industry–Regulator Dipole and Academic Partners

The industry and regulators are a closely connected dipole in licensing drugs and other products. Industry responds to regulatory requirements, and regulatory agencies increasingly act as both guardians of the common good and industry facilitators. This creates tension and ambiguity in mission. Industry should be enabled to better champion useful clinical research, with regulators matching commercial rewards to clinical utility for industry products, thus helping good companies outperform bad ones and aligning the interests of shareholders with those of patients and the public. Regulatory agencies may need to assume a more energetic role towards ensuring the conduct of large, clinically useful megatrials.

Current research funding incentivizes small studies of short duration that can be quickly performed and generate rapidly publishable results, while answering important questions may sometimes require long-term studies whose financial needs exceed the resources of most currently available funding cycles. Partnerships with patient-centered research initiatives [ 50 ] and academia can potentially solve some of the challenges of designing and implementing more pragmatic trials [ 51 ]. One should acknowledge that even for streamlined randomized trials, the cost may be substantial if multiple such trials require support by public funds. The industry may still participate by contributing funds towards a common pool of resources under public control for trials conducted by nonconflicted academic investigators. One to two percent of the sales of blockbuster drugs diverted in such a pool [ 52 ] could earmark ample funding.

Funding Agenda for Blue-Sky, Preclinical, and Clinical Science

Discovery research without prespecified deliverables—blue-sky science—is important and requires public support. However, a lot of “basic” investigation does have anticipated deliverables, like research into developing new drug targets or new tests. This research may best be funded by industry and those standing to profit if they deliver a product that is effective. Much current public funding could move from such preclinical research to useful clinical research, especially in the many cases in which a lack of patent protection means there is no commercial reason for industry to fund studies that might nevertheless be useful in improving care. Reallocation of funds could help improve all research (basic, preclinical, and clinical) ( Table 3 ).

https://doi.org/10.1371/journal.pmed.1002049.t003

Journals can be very influential is setting standards of acceptable research. External groups could also appraise the clinical utility of the papers published in journals. For example, one could track a “Journal Clinical Usefulness Factor” scoring some features mentioned above.

Patients and Related Advocacy Groups

Patients and related advocacy groups stand to gain most by an increase in clinically useful research. These groups can influence positively the utility of research when they are savvy about science-in-the-making and protected from biased influences. Public media and related commentators of health news [ 53 ] may also help by focusing on the need to obtain clinically useful research and not compromise for less.

Overall, not only are most research findings false, but, furthermore, most of the true findings are not useful. Medical interventions should and can result in huge human benefit. It makes no sense to perform clinical research without ensuring clinical utility. Reform and improvement are overdue.

Author Contributions

Wrote the first draft of the manuscript: JPAI. Contributed to the writing of the manuscript: JPAI. Agree with the manuscript’s results and conclusions: JPAI. The author has read, and confirms that he meets, ICMJE criteria for authorship.

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• 8. Frances A. Saving normal: an insider's revolt against out-of-control psychiatric diagnosis, DSM-5, big pharma, and the medicalization of ordinary life. HarperCollins, New York, 2013.
• 49. Emanuel EJ. Reinventing American health care. PublicAffairs, New York, 2014.

Doing Research: A New Researcher’s Guide pp 1–15 Cite as

What Is Research, and Why Do People Do It?

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  
• Open Access
• First Online: 03 December 2022

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

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.

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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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Five steps every researcher should take to ensure participants are not harmed and are fully heard

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Academic research is not always abstract or theoretical. Nor does it take place in a vacuum. Research in many different disciplines is often grounded in the real world; it aims to understand and address problems that affect people and the environment, such as climate change, poverty, migration or natural hazards.

This means researchers often have to interact with and collect data from a wide range of different people in government, industry and civil society. These are known as research participants.

Over the last 50 years, the relationship between researcher and participant has fundamentally changed . Previously, research participants were viewed merely as objects of study. They had little input into the research process or its outcomes. Now, participants are increasingly viewed as collaborative partners and co-creators of knowledge. There are also many ways in which they can engage with researchers. This shift has been largely driven by the need for research that is relevant to today’s world as well as greater recognition of the diversity of people and cultures, and the internet, social media and other communication tools.

In this context, ethical research practices are more important than ever. However, guidelines and standards for research ethics vary between country and institution. Expectations may also vary between disciplines. So, it’s a good time to identify the key issues in human research ethics that transcend institutional or disciplinary differences.

Issues to consider

I am a long-time chair of one my institutions’ research ethics committees, and I do research ethics training for researchers and managers across southern Africa. I have also published on research ethics. Based on this experience and drawing from other work done on the topic , I suggest there are five critical ethics issues for researchers to consider.

Managing vulnerability: Research participants, especially in the developing world, may be potentially vulnerable to coercion, exploitation and the exertion of soft power.

This vulnerability may arise because of systemic social, economic, political and cultural inequalities, which are particularly marked in developing countries. And it may be amplified by inequalities in healthcare and education. Some groups in any society – among them minors, people with disabilities, prisoners, orphans, refugees, and those with stigmatised conditions like HIV and AIDS or albinism – may be more vulnerable than others.

This issue can be managed by considering what the participant group is like and by making sure that the data collection process does not increase any existing vulnerabilities.

Obtaining informed consent: This is a key precondition for participation in any study. Potential participants should first be informed about the nature of the study and the terms and conditions of their participation. That includes details about anonymity, confidentiality and their right to withdraw.

The researcher then needs to ensure that the potential participant understands this information and has the opportunity to ask questions. This should be done in a language and using words that the person can understand. After these steps are taken, the participant can give informed consent. Informal (verbal or any other non-written) consent is more appropriate if participants are not literate or are particularly vulnerable.

Protecting people: The overarching principle of protecting research participants was articulated in the landmark Belmont Report . The report emerged from a national commission in the US in the 1970s to consider research ethics principles. It called for researchers in any study to demonstrate non-maleficence (the principle of not doing harm) and ensure that they protect both participants and their data.

This can be done at different stages through the research process: by decreasing the potential for risk or harm through careful study design; by providing support or counselling services to participants during or after data collection; and by maintaining confidentiality and anonymity in data collection and reporting. Finally, personal data must be protected or de-identified if they are being stored for later analysis.

Managing risk: Potential sources of risk or harm to participants should, as far as possible, be identified and mitigated when the study is being designed. Risk may arise in any study, either at the time of data collection or afterwards. Sometimes this is unexpected, such as where data collection becomes more dangerous due to civil unrest or under COVID-19 restrictions.

It is important that researchers provide the details of support or counselling service for participants in case these are needed. Any trade-offs between risk and benefits can be considered through a risk-benefits analysis. But researchers should be realistic about any potential benefits that may result from their study.

Championing human rights: Researchers have responsibilities: to their disciplines, funders, institutions and participants. This means they should not merely be passive analysers of data. Instead they should be positive role models in society by seeking solutions, advocating for change and upholding human rights and social justice through their actions.

Research activities, especially those involving participants, should address and find solutions for local and global problems. They ought to result in positive societal and environmental outcomes. This should be the context for all types of research activities in a 21st century world.

Making it happen

Increasingly, there are national and international codes of research ethics, guiding researchers in different fields. An example is the 2010 Singapore Statement on Research Integrity . It emphasises the principles of honesty, accountability, professional courtesy and fairness, and good stewardship of data. These are the characteristics not just of ethical researchers, but of good researchers too.

These principles and processes should make research less risky and protect the rights of participants by building trust between researchers and participants. These principles can also help in making research more transparent, accountable and equitable – critical in an increasingly divided and unequal world.

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What is useful research? The good, the bad, and the stable

• David M. Ozonoff 1 &
• Philippe Grandjean 2 , 3  

Environmental Health volume  19 , Article number:  2 ( 2020 ) Cite this article

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A scientific journal like Environmental Health strives to publish research that is useful within the field covered by the journal’s scope, in this case, public health. Useful research is more likely to make a difference. However, in many, if not most cases, the usefulness of an article can be difficult to ascertain until after its publication. Although replication is often thought of as a requirement for research to be considered valid, this criterion is retrospective and has resulted in a tendency toward inertia in environmental health research. An alternative viewpoint is that useful work is “stable”, i.e., not likely to be soon contradicted. We present this alternative view, which still relies on science being consensual, although pointing out that it is not the same as replicability, while not in contradiction. We believe that viewing potential usefulness of research reports through the lens of stability is a valuable perspective.

Good science as a purpose

Any scientific journal wishes to add to the general store of knowledge. For Environmental Health, an additional important goal is also to publish research that is useful for public health. While maximizing scientific validity is an irreducible minimum for any research journal, it does not guarantee that the outcome of a “good” article is useful. Most writing on this subject concerns efficiencies and criteria for generating new and useful research results while avoiding “research waste” [ 1 ]. In this regard, the role of journals is hard to define. Indeed, a usefulness objective depends upon what happens after publication, thus to some extent being out of our control. That said, because of the importance of this issue the Editors have set out to clarify our thinking about what makes published research useful.

First the obvious: properly conducted scientific research may not be useful, or worse, may potentially mislead, confuse or be erroneously interpreted. Journal editors and reviewers can mitigate such regrettable outcomes by being attentive to faulty over- or under-interpretation of properly generated data, and vice versa, ensuring that unrealistic standards don’t prevent publication of a “good” manuscript. In regard to the latter, we believe our journal should not shy away from alternative or novel interpretations that may be counter to established paradigms and have consciously adopted a precautionary orientation [ 2 ]: We believe that it is reasonable to feature risks that may seem remote at the moment because the history of environmental and occupational health is replete with instances of red flags ignored, resulting in horrific later harms that could no longer be mitigated [ 3 , 4 ].

Nonetheless, it has happened that researchers publishing results at odds with vested interests have become targets of unreasonable criticism and intimidation whose aim is to suppress or throw suspicion on unwelcome research information, as in the case of lead [ 3 , 5 ] and many other environmental chemicals [ 6 ]. An alternative counter strategy is generating new results favorable to a preferred view [ 7 , 8 ], with the objective of casting doubt on the uncomfortable research results. Indeed, one trade association involved in supporting such science once described its activities with the slogan, “Doubt is our product” [ 9 ]. Thus, for better or for worse, many people do not separate science, whether good or bad, from its implications [ 10 ].

Further, even without nefarious reasons, it is not uncommon for newly published research to be contradicted by additional results from other scientists. Not surprisingly, the public has become all too aware of findings whose apparent import is later found to be negligible, wrong, or cast into serious doubt, legitimately or otherwise [ 11 ]. This has been damaging to the discipline and its reputation [ 12 ].

Replication as a criterion

A principal reaction to this dilemma has been to demand that results be “replicated” before being put to use. As a result, both funding agencies [ 13 ] and journals [ 14 ] have announced their intention of emphasizing the reproducibility of research, thereby also facilitating replication [ 15 ]. On its face this sounds reasonable, but usual experimental or observational protocols are already based on internal replication. If some form of replication of a study is desired, attempts to duplicate an experimental set-up can easily produce non-identical measurements on repeated samples, and seemingly similar people in a population may yield somewhat different observations. Given an expected variability within and between studies, we need to define more precisely what is to be replicated and how it is to be judged.

That said, in most instances, it seems that what we are really asking for is interpretive replication (i.e., do we think two or more studies mean the same thing), not observational or measurement replication. Uninterpreted evidence is just raw data. The main product of scientific journals like Environmental Health is interpreted evidence. It is interpreted evidence that is actionable and likely to affect practice and policy.

Research stability

This brings us back to the question of what kind of evidence and its accompanying interpretation is likely to be of use? The philosopher Alex Broadbent distinguishes between how results get used and the decision about which results are likely to be used [ 16 ]. Discussions of research translation tend to focus on the former question, while the latter is rarely discussed. Broadbent introduces a new concept into the conversation, the stability of the research results.

He begins by identifying which results are not likely to be used. Broadbent observes that if a practitioner or policy-maker thinks a result might soon be overturned she is unlikely to use it. Since continual revision is a hallmark of science, this presents a dilemma. All results are open to revision as science progresses, so what users and policy makers really want are stable results, ones whose meaning is unlikely to change in ways that make a potential practice or policy quickly obsolete or wrong. What are the features of a stable result?

This is a trickier problem than it first appears. As Broadbent observes it does not seem sufficient to say that a stable a result is one that is not contradicted by subsequent work, an idea closely related to replication. Failure to contradict, like lack of replication, may have many reasons, including lack of interest, lack of funding, active suppression of research in a subject, or external events like social conflict or recession. Moreover, there are many examples of clinical practice, broadly accepted as stable in the non-contradiction sense, that have not been tested for one reason or another. Contrariwise, contradictory results may also be specious or fraudulent, e.g., due to attempts to make an unwelcome result appear unstable and hence unusable [ 6 , 9 ]. In sum, lack of contradiction doesn’t automatically make a result stable, nor does its presence annul the result.

One might plausibly think that the apparent truth of a scientific result would be sufficient to make a result stable. This is also in accordance with Naomi Oreskes’ emphasis of scientific knowledge being fundamentally consensual [ 10 ] and relies on the findings being generalizable [ 15 ]. Our journal, like most, employs conventional techniques like pre-publication peer review and editorial judgment, to maximize scientific validity of published articles; and we require Conflict of Interest declarations to maximize scientific integrity [ 6 , 17 ]. Still, a result may be true but not useful, and science that isn’t true may be very useful. Broadbent’s example of the latter is the most spectacular. Newtonian physics continues to be a paragon of usefulness despite the fact that in the age of Relativity Theory we know it to be false. Examples are also prevalent in environmental health. When John Snow identified contaminated water as a source of epidemic cholera in the mid-nineteenth Century he believed a toxin was the cause, as the germ theory of disease had not yet found purchase. This lack of understanding did not stop practitioners from advocating limiting exposure to sewage-contaminated water. Nonetheless, demands for modes of action or adverse outcome pathways are often used to block the use of new evidence on environmental hazards [ 18 ].

Criteria for stability

Broadbent’s suggestion is that a result likely to be seen as stable by practitioners and policy makers is one that (a) is not contradicted by good scientific evidence; and (b) would not likely be soon contradicted by further good research [ 16 ] (p. 63).

The first requirement, (a), simply says that any research that produces contradictory evidence be methodologically sound and free from bias, i.e., “good scientific evidence.” What constitutes “good” scientific evidence is a well discussed topic, of course, and not a novel requirement [ 1 ], but the stability frame puts existing quality criteria, in a different, perhaps more organized, structure, situating the evidence and its interpretation in relation to stability as a criterion for usefulness.

More novel is requirement (b), the belief that if further research were done it would not likely result in a contradiction. The if clause focuses our attention on examining instances where the indicated research has not yet been done. The criterion is therefore prospective, where the replication demand can only be used in retrospect.

This criterion could usefully be applied to inconclusive or underpowered studies that are often incorrectly labeled “negative” and interpreted to indicate “no risk” [ 18 ]. A U.S. National Research Council committee called attention to the erroneous inference that chemicals are regarded inert or safe, unless proven otherwise [ 19 ]. This “untested-chemical assumption” has resulted in exposure limits for only a small proportion of environmental chemicals, limits often later found to be much too high to adequately protect against adverse health effects [ 20 , 21 ]. For example, some current limits for perfluorinated compounds in drinking water do not protect against the immunotoxic effects in children and may be up to 100-fold too high [ 22 ].

Inertia as a consequence

Journals play an unfortunate part in the dearth of critical information on emerging contaminants, as published articles primarily address chemicals that have already been well studied [ 23 ]. This means that environmental health research suffers from an impoverishing inertia, which may in part be due to desired replications that may be superfluous or worse. The bottom line is that longstanding acceptance in the face of longstanding failure to test a proposition should not be used as a criterion of stability or of usefulness, although this is routinely done.

If non-contradiction, replication or truth are not reliable hallmarks of a potentially useful research result, then what is? Broadbent makes the tentative proposal that a stable interpretation is one which has a satisfactory answer to the question, “Why this interpretation rather than another?” Said another way, are there more likely, almost or equally as likely, or other possible explanations (including methodological error in the work in question)? Sometimes the answer is patently obvious. Such an evaluation is superfluous in instances where the outcomes have such forceful explanations that this exercise would be a waste of time, for example a construction worker falling from the staging. We only need one instance and (hopefully no repetitions) to make the case.

Consensus and stability

Having made the argument for perspicuous interpretation, we must also issue a note of caution. It is quite common to err in the other direction by downplaying conclusions and implications. Researchers frequently choose to hedge their conclusions by repeated use of words such as ‘maybe’, ‘perhaps’, ‘in theory’ and similar terms [ 24 ]. Indeed, we might call the hedge the official flower of epidemiology. To a policy maker, journalist or member of the public not familiar with the traditions of scientific writing, the caveats and reservations may sound like the new results are irredeemably tentative, leaving us with no justification for any intervention. To those with a vested interest, the soft wording can be exploited through selective quotation and by emphasizing real or alleged weaknesses [ 25 ]. This tendency goes beyond one’s own writings and affects peer review and evaluations of manuscripts and applications. Although skepticism is in the nature of science, a malignant form is the one that is veiled and expressed in terms of need for further replication or emphasizing limitations of otherwise stable observations [ 9 ]. By softening the conclusions and avoiding attribution of specific causality and the possible policy implications, researchers protect themselves against critique by appearing well-balanced, unassuming, or even skeptical toward one’s own findings. In seeking consensus, researchers often moderate or underestimate their findings, a tendency that is not in accordance with public health interests.

These are difficult issues, requiring a balancing act. The Editors continue to ponder the question how to inspire, improve and support the best research and its translation. We believe Broadbent’s stability idea is worth considering as an alternative perspective to the replication and research translation paradigms prevalent in discussions of this topic. We also believe in Oreskes’ vision of consensus, though not to a degree that will preclude new interpretations. Meanwhile, we will endeavor to keep the Journal’s standards high while encouraging work that will make a difference.

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Why Most Clinical Research Is Not Useful

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John Ioannidis argues that problem base, context placement, information gain, pragmatism, patient centeredness, value for money, feasibility, and transparency define useful clinical research. He suggests most clinical research is not useful and reform is overdue.

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What is Research? – Purpose of Research

• By DiscoverPhDs
• September 10, 2020

The purpose of research is to enhance society by advancing knowledge through the development of scientific theories, concepts and ideas. A research purpose is met through forming hypotheses, collecting data, analysing results, forming conclusions, implementing findings into real-life applications and forming new research questions.

What is Research

Simply put, research is the process of discovering new knowledge. This knowledge can be either the development of new concepts or the advancement of existing knowledge and theories, leading to a new understanding that was not previously known.

As a more formal definition of research, the following has been extracted from the Code of Federal Regulations :

While research can be carried out by anyone and in any field, most research is usually done to broaden knowledge in the physical, biological, and social worlds. This can range from learning why certain materials behave the way they do, to asking why certain people are more resilient than others when faced with the same challenges.

The use of ‘systematic investigation’ in the formal definition represents how research is normally conducted – a hypothesis is formed, appropriate research methods are designed, data is collected and analysed, and research results are summarised into one or more ‘research conclusions’. These research conclusions are then shared with the rest of the scientific community to add to the existing knowledge and serve as evidence to form additional questions that can be investigated. It is this cyclical process that enables scientific research to make continuous progress over the years; the true purpose of research.

What is the Purpose of Research

From weather forecasts to the discovery of antibiotics, researchers are constantly trying to find new ways to understand the world and how things work – with the ultimate goal of improving our lives.

The purpose of research is therefore to find out what is known, what is not and what we can develop further. In this way, scientists can develop new theories, ideas and products that shape our society and our everyday lives.

Although research can take many forms, there are three main purposes of research:

• Exploratory: Exploratory research is the first research to be conducted around a problem that has not yet been clearly defined. Exploration research therefore aims to gain a better understanding of the exact nature of the problem and not to provide a conclusive answer to the problem itself. This enables us to conduct more in-depth research later on.
• Descriptive: Descriptive research expands knowledge of a research problem or phenomenon by describing it according to its characteristics and population. Descriptive research focuses on the ‘how’ and ‘what’, but not on the ‘why’.
• Explanatory: Explanatory research, also referred to as casual research, is conducted to determine how variables interact, i.e. to identify cause-and-effect relationships. Explanatory research deals with the ‘why’ of research questions and is therefore often based on experiments.

Characteristics of Research

There are 8 core characteristics that all research projects should have. These are:

• Empirical  – based on proven scientific methods derived from real-life observations and experiments.
• Logical  – follows sequential procedures based on valid principles.
• Cyclic  – research begins with a question and ends with a question, i.e. research should lead to a new line of questioning.
• Controlled  – vigorous measures put into place to keep all variables constant, except those under investigation.
• Hypothesis-based  – the research design generates data that sufficiently meets the research objectives and can prove or disprove the hypothesis. It makes the research study repeatable and gives credibility to the results.
• Analytical  – data is generated, recorded and analysed using proven techniques to ensure high accuracy and repeatability while minimising potential errors and anomalies.
• Objective  – sound judgement is used by the researcher to ensure that the research findings are valid.
• Statistical treatment  – statistical treatment is used to transform the available data into something more meaningful from which knowledge can be gained.

Finding a PhD has never been this easy – search for a PhD by keyword, location or academic area of interest.

Types of Research

Research can be divided into two main types: basic research (also known as pure research) and applied research.

Basic Research

Basic research, also known as pure research, is an original investigation into the reasons behind a process, phenomenon or particular event. It focuses on generating knowledge around existing basic principles.

Basic research is generally considered ‘non-commercial research’ because it does not focus on solving practical problems, and has no immediate benefit or ways it can be applied.

While basic research may not have direct applications, it usually provides new insights that can later be used in applied research.

Applied Research

Applied research investigates well-known theories and principles in order to enhance knowledge around a practical aim. Because of this, applied research focuses on solving real-life problems by deriving knowledge which has an immediate application.

Methods of Research

Research methods for data collection fall into one of two categories: inductive methods or deductive methods.

Inductive research methods focus on the analysis of an observation and are usually associated with qualitative research. Deductive research methods focus on the verification of an observation and are typically associated with quantitative research.

Qualitative Research

Qualitative research is a method that enables non-numerical data collection through open-ended methods such as interviews, case studies and focus groups .

It enables researchers to collect data on personal experiences, feelings or behaviours, as well as the reasons behind them. Because of this, qualitative research is often used in fields such as social science, psychology and philosophy and other areas where it is useful to know the connection between what has occurred and why it has occurred.

Quantitative Research

Quantitative research is a method that collects and analyses numerical data through statistical analysis.

It allows us to quantify variables, uncover relationships, and make generalisations across a larger population. As a result, quantitative research is often used in the natural and physical sciences such as engineering, biology, chemistry, physics, computer science, finance, and medical research, etc.

What does Research Involve?

Research often follows a systematic approach known as a Scientific Method, which is carried out using an hourglass model.

A research project first starts with a problem statement, or rather, the research purpose for engaging in the study. This can take the form of the ‘ scope of the study ’ or ‘ aims and objectives ’ of your research topic.

Subsequently, a literature review is carried out and a hypothesis is formed. The researcher then creates a research methodology and collects the data.

The data is then analysed using various statistical methods and the null hypothesis is either accepted or rejected.

In both cases, the study and its conclusion are officially written up as a report or research paper, and the researcher may also recommend lines of further questioning. The report or research paper is then shared with the wider research community, and the cycle begins all over again.

Although these steps outline the overall research process, keep in mind that research projects are highly dynamic and are therefore considered an iterative process with continued refinements and not a series of fixed stages.

Self-plagiarism is when you try and pass off work that you’ve previously done as something that is completely new.

Academic conferences are expensive and it can be tough finding the funds to go; this naturally leads to the question of are academic conferences worth it?

The purpose of research is to enhance society by advancing knowledge through developing scientific theories, concepts and ideas – find out more on what this involves.

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Dr Britton gained his DPhil in material science research at Oxford University in 2010. He is now a Senior Lecturer in Materials Science and Engineering at Imperial College London.

Freya’s in the final year of her PhD at the University of Leeds. Her project is about improving the precision of observations between collocated ground-based weather radar and airborne platforms.

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2.1 Why Is Research Important?

Learning objectives.

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( Figure 2.2 ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the explosion in our use of technology has led researchers to question whether this ultimately helps or hinders us. The use and implementation of technology in educational settings has become widespread over the last few decades. Researchers are coming to different conclusions regarding the use of technology. To illustrate this point, a study investigating a smartphone app targeting surgery residents (graduate students in surgery training) found that the use of this app can increase student engagement and raise test scores (Shaw & Tan, 2015). Conversely, another study found that the use of technology in undergraduate student populations had negative impacts on sleep, communication, and time management skills (Massimini & Peterson, 2009). Until sufficient amounts of research have been conducted, there will be no clear consensus on the effects that technology has on a student's acquisition of knowledge, study skills, and mental health.

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding early intervention programs. These programs are designed to help children who come from low-income backgrounds, have special needs, or face other disadvantages. These programs may involve providing a wide variety of services to maximize the children's development and position them for optimal levels of success in school and later in life (Blann, 2005). While such programs sound appealing, you would want to be sure that they also proved effective before investing additional money in these programs. Fortunately, psychologists and other scientists have conducted vast amounts of research on such programs and, in general, the programs are found to be effective (Neil & Christensen, 2009; Peters-Scheffer, Didden, Korzilius, & Sturmey, 2011). While not all programs are equally effective, and the short-term effects of many such programs are more pronounced, there is reason to believe that many of these programs produce long-term benefits for participants (Barnett, 2011). If you are committed to being a good steward of taxpayer money, you would want to look at research. Which programs are most effective? What characteristics of these programs make them effective? Which programs promote the best outcomes? After examining the research, you would be best equipped to make decisions about which programs to fund.

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Watch this video about early childhood program effectiveness to learn how scientists evaluate effectiveness and how best to invest money into programs that are most effective.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine that your sister, Maria, expresses concern about her two-year-old child, Umberto. Umberto does not speak as much or as clearly as the other children in his daycare or others in the family. Umberto's pediatrician undertakes some screening and recommends an evaluation by a speech pathologist, but does not refer Maria to any other specialists. Maria is concerned that Umberto's speech delays are signs of a developmental disorder, but Umberto's pediatrician does not; she sees indications of differences in Umberto's jaw and facial muscles. Hearing this, you do some internet searches, but you are overwhelmed by the breadth of information and the wide array of sources. You see blog posts, top-ten lists, advertisements from healthcare providers, and recommendations from several advocacy organizations. Why are there so many sites? Which are based in research, and which are not?

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

NOTABLE RESEARCHERS

Psychological research has a long history involving important figures from diverse backgrounds. While the introductory chapter discussed several researchers who made significant contributions to the discipline, there are many more individuals who deserve attention in considering how psychology has advanced as a science through their work ( Figure 2.3 ). For instance, Margaret Floy Washburn (1871–1939) was the first woman to earn a PhD in psychology. Her research focused on animal behavior and cognition (Margaret Floy Washburn, PhD, n.d.). Mary Whiton Calkins (1863–1930) was a preeminent first-generation American psychologist who opposed the behaviorist movement, conducted significant research into memory, and established one of the earliest experimental psychology labs in the United States (Mary Whiton Calkins, n.d.).

Francis Sumner (1895–1954) was the first African American to receive a PhD in psychology in 1920. His dissertation focused on issues related to psychoanalysis. Sumner also had research interests in racial bias and educational justice. Sumner was one of the founders of Howard University’s department of psychology, and because of his accomplishments, he is sometimes referred to as the “Father of Black Psychology.” Thirteen years later, Inez Beverly Prosser (1895–1934) became the first African American woman to receive a PhD in psychology. Prosser’s research highlighted issues related to education in segregated versus integrated schools, and ultimately, her work was very influential in the hallmark Brown v. Board of Education Supreme Court ruling that segregation of public schools was unconstitutional (Ethnicity and Health in America Series: Featured Psychologists, n.d.).

Although the establishment of psychology’s scientific roots occurred first in Europe and the United States, it did not take much time until researchers from around the world began to establish their own laboratories and research programs. For example, some of the first experimental psychology laboratories in South America were founded by Horatio Piñero (1869–1919) at two institutions in Buenos Aires, Argentina (Godoy & Brussino, 2010). In India, Gunamudian David Boaz (1908–1965) and Narendra Nath Sen Gupta (1889–1944) established the first independent departments of psychology at the University of Madras and the University of Calcutta, respectively. These developments provided an opportunity for Indian researchers to make important contributions to the field (Gunamudian David Boaz, n.d.; Narendra Nath Sen Gupta, n.d.).

When the American Psychological Association (APA) was first founded in 1892, all of the members were White males (Women and Minorities in Psychology, n.d.). However, by 1905, Mary Whiton Calkins was elected as the first female president of the APA, and by 1946, nearly one-quarter of American psychologists were female. Psychology became a popular degree option for students enrolled in the nation’s historically Black higher education institutions, increasing the number of Black Americans who went on to become psychologists. Given demographic shifts occurring in the United States and increased access to higher educational opportunities among historically underrepresented populations, there is reason to hope that the diversity of the field will increasingly match the larger population, and that the research contributions made by the psychologists of the future will better serve people of all backgrounds (Women and Minorities in Psychology, n.d.).

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested in the real world; in inductive reasoning , real-world observations lead to new ideas ( Figure 2.4 ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests Figure 2.5 .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( Figure 2.6 ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

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Six Reasons Why Research is Important

Everyone conducts research in some form or another from a young age, whether news, books, or browsing the Internet. Internet users come across thoughts, ideas, or perspectives - the curiosity that drives the desire to explore. However, when research is essential to make practical decisions, the nature of the study alters - it all depends on its application and purpose. For instance, skilled research offered as a  research paper service  has a definite objective, and it is focused and organized. Professional research helps derive inferences and conclusions from solving problems. visit the HB tool services for the amazing research tools that will help to solve your problems regarding the research on any project.

What is the Importance of Research?

The primary goal of the research is to guide action, gather evidence for theories, and contribute to the growth of knowledge in data analysis. This article discusses the importance of research and the multiple reasons why it is beneficial to everyone, not just students and scientists.

On the other hand, research is important in business decision-making because it can assist in making better decisions when combined with their experience and intuition.

Reasons for the Importance of Research

• Acquire Knowledge Effectively
• Research helps in problem-solving
• Provides the latest information
• Builds credibility
• Helps in business success
• Discover and Seize opportunities

1-  Acquire Knowledge Efficiently through Research

The most apparent reason to conduct research is to understand more. Even if you think you know everything there is to know about a subject, there is always more to learn. Research helps you expand on any prior knowledge you have of the subject. The research process creates new opportunities for learning and progress.

2- Research Helps in Problem-solving

Problem-solving can be divided into several components, which require knowledge and analysis, for example,  identification of issues, cause identification,  identifying potential solutions, decision to take action, monitoring and evaluation of activity and outcomes.

You may just require additional knowledge to formulate an informed strategy and make an informed decision. When you know you've gathered reliable data, you'll be a lot more confident in your answer.

3- Research Provides the Latest Information

Research enables you to seek out the most up-to-date facts. There is always new knowledge and discoveries in various sectors, particularly scientific ones. Staying updated keeps you from falling behind and providing inaccurate or incomplete information. You'll be better prepared to discuss a topic and build on ideas if you have the most up-to-date information. With the help of tools and certifications such as CIRS , you may learn internet research skills quickly and easily. Internet research can provide instant, global access to information.

4- Research Builds Credibility

Research provides a solid basis for formulating thoughts and views. You can speak confidently about something you know to be true. It's much more difficult for someone to find flaws in your arguments after you've finished your tasks. In your study, you should prioritize the most reputable sources. Your research should focus on the most reliable sources. You won't be credible if your "research" comprises non-experts' opinions. People are more inclined to pay attention if your research is excellent.

5-  Research Helps in Business Success

R&D might also help you gain a competitive advantage. Finding ways to make things run more smoothly and differentiate a company's products from those of its competitors can help to increase a company's market worth.

6-  Research Discover and Seize Opportunities

People can maximize their potential and achieve their goals through various opportunities provided by research. These include getting jobs, scholarships, educational subsidies, projects, commercial collaboration, and budgeted travel. Research is essential for anyone looking for work or a change of environment. Unemployed people will have a better chance of finding potential employers through job advertisements or agencies. 

How to Improve Your Research Skills

Start with the big picture and work your way down.

It might be hard to figure out where to start when you start researching. There's nothing wrong with a simple internet search to get you started. Online resources like Google and Wikipedia are a great way to get a general idea of a subject, even though they aren't always correct. They usually give a basic overview with a short history and any important points.

Identify Reliable Source

Not every source is reliable, so it's critical that you can tell the difference between the good ones and the bad ones. To find a reliable source, use your analytical and critical thinking skills and ask yourself the following questions: Is this source consistent with other sources I've discovered? Is the author a subject matter expert? Is there a conflict of interest in the author's point of view on this topic?

Validate Information from Various Sources

Take in new information.

The purpose of research is to find answers to your questions, not back up what you already assume. Only looking for confirmation is a minimal way to research because it forces you to pick and choose what information you get and stops you from getting the most accurate picture of the subject. When you do research, keep an open mind to learn as much as possible.

Facilitates Learning Process

Learning new things and implementing them in daily life can be frustrating. Finding relevant and credible information requires specialized training and web search skills due to the sheer enormity of the Internet and the rapid growth of indexed web pages. On the other hand, short courses and Certifications like CIRS make the research process more accessible. CIRS Certification offers complete knowledge from beginner to expert level. You can become a Certified Professional Researcher and get a high-paying job, but you'll also be much more efficient and skilled at filtering out reliable data. You can learn more about becoming a Certified Professional Researcher.

Stay Organized

You'll see a lot of different material during the process of gathering data, from web pages to PDFs to videos. You must keep all of this information organized in some way so that you don't lose anything or forget to mention something properly. There are many ways to keep your research project organized, but here are a few of the most common:  Learning Management Software , Bookmarks in your browser, index cards, and a bibliography that you can add to as you go are all excellent tools for writing.

Make Use of the library's Resources

If you still have questions about researching, don't worry—even if you're not a student performing academic or course-related research, there are many resources available to assist you. Many high school and university libraries, in reality, provide resources not only for staff and students but also for the general public. Look for research guidelines or access to specific databases on the library's website. Association of Internet Research Specialists enjoys sharing informational content such as research-related articles , research papers , specialized search engines list compiled from various sources, and contributions from our members and in-house experts.

of Conducting Research

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The role of research at universities: why it matters.

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Teaching and learning, research and discovery, synthesis and creativity, understanding and engagement, service and outreach. There are many “core elements” to the mission of a great university. Teaching would seem the most obvious, but for those outside of the university, “research” (taken to include scientific research, scholarship more broadly, as well as creative activity) may be the least well understood. This creates misunderstanding of how universities invest resources, especially those deriving from undergraduate tuition and state (or other public) support, and the misperception that those resources are being diverted away from what is believed should be the core (and sole) focus, teaching. This has led to a loss of trust, confidence, and willingness to continue to invest or otherwise support (especially our public) universities.

Why are universities engaged in the conduct of research? Who pays? Who benefits? And why does it all matter? Good questions. Let’s get to some straightforward answers. Because the academic research enterprise really is not that difficult to explain, and its impacts are profound.

So let’s demystify university-based research. And in doing so, hopefully we can begin building both better understanding and a better relationship between the public and higher education, both of which are essential to the future of US higher education.   

Why are universities engaged in the conduct of research?

Universities engage in research as part of their missions around learning and discovery. This, in turn, contributes directly and indirectly to their primary mission of teaching. Universities and many colleges (the exception being those dedicated exclusively to undergraduate teaching) have as part of their mission the pursuit of scholarship. This can come in the form of fundamental or applied research (both are most common in the STEM fields, broadly defined), research-based scholarship or what often is called “scholarly activity” (most common in the social sciences and humanities), or creative activity (most common in the arts). Increasingly, these simple categorizations are being blurred, for all good reasons and to the good of the discovery of new knowledge and greater understanding of complex (transdisciplinary) challenges and the creation of increasingly interrelated fields needed to address them.

It goes without saying that the advancement of knowledge (discovery, innovation, creation) is essential to any civilization. Our nation’s research universities represent some of the most concentrated communities of scholars, facilities, and collective expertise engaged in these activities. But more importantly, this is where higher education is delivered, where students develop breadth and depth of knowledge in foundational and advanced subjects, where the skills for knowledge acquisition and understanding (including contextualization, interpretation, and inference) are honed, and where students are educated, trained, and otherwise prepared for successful careers. Part of that training and preparation derives from exposure to faculty who are engaged at the leading-edge of their fields, through their research and scholarly work. The best faculty, the teacher-scholars, seamlessly weave their teaching and research efforts together, to their mutual benefit, and in a way that excites and engages their students. In this way, the next generation of scholars (academic or otherwise) is trained, research and discovery continue to advance inter-generationally, and the cycle is perpetuated.

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University research can be expensive, particularly in laboratory-intensive fields. But the responsibility for much (indeed most) of the cost of conducting research falls to the faculty member. Faculty who are engaged in research write grants for funding (e.g., from federal and state agencies, foundations, and private companies) to support their work and the work of their students and staff. In some cases, the universities do need to invest heavily in equipment, facilities, and personnel to support select research activities. But they do so judiciously, with an eye toward both their mission, their strategic priorities, and their available resources.

Medical research, and medical education more broadly, is expensive and often requires substantial institutional investment beyond what can be covered by clinical operations or externally funded research. But universities with medical schools/medical centers have determined that the value to their educational and training missions as well as to their communities justifies the investment. And most would agree that university-based medical centers are of significant value to their communities, often providing best-in-class treatment and care in midsize and smaller communities at a level more often seen in larger metropolitan areas.

Research in the STEM fields (broadly defined) can also be expensive. Scientific (including medical) and engineering research often involves specialized facilities or pieces of equipment, advanced computing capabilities, materials requiring controlled handling and storage, and so forth. But much of this work is funded, in large part, by federal agencies such as the National Science Foundation, National Institutes of Health, US Department of Energy, US Department of Agriculture, and many others.

Research in the social sciences is often (not always) less expensive, requiring smaller amount of grant funding. As mentioned previously, however, it is now becoming common to have physical, natural, and social scientist teams pursuing large grant funding. This is an exciting and very promising trend for many reasons, not the least of which is the nature of the complex problems being studied.

Research in the arts and humanities typically requires the least amount of funding as it rarely requires the expensive items listed previously. Funding from such organizations as the National Endowment for the Arts, National Endowment for the Humanities, and private foundations may be able to support significant scholarship and creation of new knowledge or works through much more modest grants than would be required in the natural or physical sciences, for example.

Philanthropy may also be directed toward the support of research and scholarly activity at universities. Support from individual donors, family foundations, private or corporate foundations may be directed to support students, faculty, labs or other facilities, research programs, galleries, centers, and institutes.

Who benefits?

Students, both undergraduate and graduate, benefit from studying in an environment rich with research and discovery. Besides what the faculty can bring back to the classroom, there are opportunities to engage with faculty as part of their research teams and even conduct independent research under their supervision, often for credit. There are opportunities to learn about and learn on state-of-the-art equipment, in state-of-the-art laboratories, and from those working on the leading edge in a discipline. There are opportunities to co-author, present at conferences, make important connections, and explore post-graduate pathways.

The broader university benefits from active research programs. Research on timely and important topics attracts attention, which in turn leads to greater institutional visibility and reputation. As a university becomes known for its research in certain fields, they become magnets for students, faculty, grants, media coverage, and even philanthropy. Strength in research helps to define a university’s “brand” in the national and international marketplace, impacting everything from student recruitment, to faculty retention, to attracting new investments.

The community, region, and state benefits from the research activity of the university. This is especially true for public research universities. Research also contributes directly to economic development, clinical, commercial, and business opportunities. Resources brought into the university through grants and contracts support faculty, staff, and student salaries, often adding additional jobs, contributing directly to the tax base. Research universities, through their expertise, reputation, and facilities, can attract new businesses into their communities or states. They can also launch and incubate startup companies, or license and sell their technologies to other companies. Research universities often host meeting and conferences which creates revenue for local hotels, restaurants, event centers, and more. And as mentioned previously, university medical centers provide high-quality medical care, often in midsize communities that wouldn’t otherwise have such outstanding services and state-of-the-art facilities.

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And finally, why does this all matter?

Research is essential to advancing society, strengthening the economy, driving innovation, and addressing the vexing and challenging problems we face as a people, place, and planet. It’s through research, scholarship, and discovery that we learn about our history and ourselves, understand the present context in which we live, and plan for and secure our future.

Research universities are vibrant, exciting, and inspiring places to learn and to work. They offer opportunities for students that few other institutions can match – whether small liberal arts colleges, mid-size teaching universities, or community colleges – and while not right for every learner or every educator, they are right for many, if not most. The advantages simply cannot be ignored. Neither can the importance or the need for these institutions. They need not be for everyone, and everyone need not find their way to study or work at our research universities, and we stipulate that there are many outstanding options to meet and support different learning styles and provide different environments for teaching and learning. But it’s critically important that we continue to support, protect, and respect research universities for all they do for their students, their communities and states, our standing in the global scientific community, our economy, and our nation.

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7 Why Is Research Important?

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Learning Objectives

By the end of this section, you will be able to:

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession ( [link] ). It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

USE OF RESEARCH INFORMATION

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the hypothesized link between exposure to media violence and subsequent aggression has been debated in the scientific community for roughly 60 years. Even today, we will find detractors, but a consensus is building. Several professional organizations view media violence exposure as a risk factor for actual violence, including the American Medical Association, the American Psychiatric Association, and the American Psychological Association (American Academy of Pediatrics, American Academy of Child & Adolescent Psychiatry, American Psychological Association, American Medical Association, American Academy of Family Physicians, American Psychiatric Association, 2000).

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the D.A.R.E. (Drug Abuse Resistance Education) program in public schools ( [link] ). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in 75% of school districts in the United States and in more than 40 countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

Watch this news report to learn more about some of the controversial issues surrounding the D.A.R.E. program.

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with your doctor and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

THE PROCESS OF SCIENTIFIC RESEARCH

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested against the empirical world; in inductive reasoning , empirical observations lead to new ideas ( [link] ). These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

Play this “Deal Me In” interactive card game to practice using inductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests [link] .

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors ( [link] ). However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

Visit this website to apply the scientific method and practice its steps by using them to solve a murder mystery, determine why a student is in trouble, and design an experiment to test house paint.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Review Questions

Scientific hypotheses are ________ and falsifiable.

________ are defined as observable realities.

Scientific knowledge is ________.

A major criticism of Freud’s early theories involves the fact that his theories ________.

• were too limited in scope
• were too outrageous
• were too broad
• were not testable

Critical Thinking Questions

In this section, the D.A.R.E. program was described as an incredibly popular program in schools across the United States despite the fact that research consistently suggests that this program is largely ineffective. How might one explain this discrepancy?

There is probably tremendous political pressure to appear to be hard on drugs. Therefore, even though D.A.R.E. might be ineffective, it is a well-known program with which voters are familiar.

The scientific method is often described as self-correcting and cyclical. Briefly describe your understanding of the scientific method with regard to these concepts.

This cyclical, self-correcting process is primarily a function of the empirical nature of science. Theories are generated as explanations of real-world phenomena. From theories, specific hypotheses are developed and tested. As a function of this testing, theories will be revisited and modified or refined to generate new hypotheses that are again tested. This cyclical process ultimately allows for more and more precise (and presumably accurate) information to be collected.

Personal Application Questions

Healthcare professionals cite an enormous number of health problems related to obesity, and many people have an understandable desire to attain a healthy weight. There are many diet programs, services, and products on the market to aid those who wish to lose weight. If a close friend was considering purchasing or participating in one of these products, programs, or services, how would you make sure your friend was fully aware of the potential consequences of this decision? What sort of information would you want to review before making such an investment or lifestyle change yourself?

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10 Reasons Why Research is Important

No matter what career field you’re in or how high up you are, there’s always more to learn . The same applies to your personal life. No matter how many experiences you have or how diverse your social circle, there are things you don’t know. Research unlocks the unknowns, lets you explore the world from different perspectives, and fuels a deeper understanding. In some areas, research is an essential part of success. In others, it may not be absolutely necessary, but it has many benefits. Here are ten reasons why research is important:

#1. Research expands your knowledge base

The most obvious reason to do research is that you’ll learn more. There’s always more to learn about a topic, even if you are already well-versed in it. If you aren’t, research allows you to build on any personal experience you have with the subject. The process of research opens up new opportunities for learning and growth.

#2. Research gives you the latest information

Research encourages you to find the most recent information available . In certain fields, especially scientific ones, there’s always new information and discoveries being made. Staying updated prevents you from falling behind and giving info that’s inaccurate or doesn’t paint the whole picture. With the latest info, you’ll be better equipped to talk about a subject and build on ideas.

#3. Research helps you know what you’re up against

In business, you’ll have competition. Researching your competitors and what they’re up to helps you formulate your plans and strategies. You can figure out what sets you apart. In other types of research, like medicine, your research might identify diseases, classify symptoms, and come up with ways to tackle them. Even if your “enemy” isn’t an actual person or competitor, there’s always some kind of antagonist force or problem that research can help you deal with.

#4. Research builds your credibility

People will take what you have to say more seriously when they can tell you’re informed. Doing research gives you a solid foundation on which you can build your ideas and opinions. You can speak with confidence about what you know is accurate. When you’ve done the research, it’s much harder for someone to poke holes in what you’re saying. Your research should be focused on the best sources. If your “research” consists of opinions from non-experts, you won’t be very credible. When your research is good, though, people are more likely to pay attention.

#5. Research helps you narrow your scope

When you’re circling a topic for the first time, you might not be exactly sure where to start. Most of the time, the amount of work ahead of you is overwhelming. Whether you’re writing a paper or formulating a business plan, it’s important to narrow the scope at some point. Research helps you identify the most unique and/or important themes. You can choose the themes that fit best with the project and its goals.

#6. Research teaches you better discernment

Doing a lot of research helps you sift through low-quality and high-quality information. The more research you do on a topic, the better you’ll get at discerning what’s accurate and what’s not. You’ll also get better at discerning the gray areas where information may be technically correct but used to draw questionable conclusions.

#7. Research introduces you to new ideas

You may already have opinions and ideas about a topic when you start researching. The more you research, the more viewpoints you’ll come across. This encourages you to entertain new ideas and perhaps take a closer look at yours. You might change your mind about something or, at least, figure out how to position your ideas as the best ones.

#8. Research helps with problem-solving

Whether it’s a personal or professional problem, it helps to look outside yourself for help. Depending on what the issue is, your research can focus on what others have done before. You might just need more information, so you can make an informed plan of attack and an informed decision. When you know you’ve collected good information, you’ll feel much more confident in your solution.

#9. Research helps you reach people

Research is used to help raise awareness of issues like climate change , racial discrimination, gender inequality , and more. Without hard facts, it’s very difficult to prove that climate change is getting worse or that gender inequality isn’t progressing as quickly as it should. The public needs to know what the facts are, so they have a clear idea of what “getting worse” or “not progressing” actually means. Research also entails going beyond the raw data and sharing real-life stories that have a more personal impact on people.

#10. Research encourages curiosity

Having curiosity and a love of learning take you far in life. Research opens you up to different opinions and new ideas. It also builds discerning and analytical skills. The research process rewards curiosity. When you’re committed to learning, you’re always in a place of growth. Curiosity is also good for your health. Studies show curiosity is associated with higher levels of positivity, better satisfaction with life, and lower anxiety.

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NCBI Bookshelf. A service of the National Library of Medicine, National Institutes of Health.

StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Common pitfalls in the research process.

Jacob Shreffler ; Martin R. Huecker .

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Last Update: March 6, 2023 .

• Definition/Introduction

Conducting research from planning to publication can be a very rewarding process. However, multiple preventable setbacks can occur within each stage of research. While these inefficiencies are an inevitable part of the research process, understanding common pitfalls can limit those hindrances. Many issues can present themselves throughout the research process. It has been said about academics that “the politics are so harsh because the stakes are so low.” Beyond interpersonal and political / funding concerns, prospective authors may encounter some disenchantment with the publish or perish culture. With a metric of (any) publication, the motivation to contribute meaningfully to science can be overshadowed by a compulsive drive to publish. [1]  We believe in quality over quantity and highlight the importance of channeling creativity when pursuing scholarly work.

When considering embarking on a medical research project, one must begin with detailed planning. Do not underestimate the amount of time a project can take, often spanning years from conception to manuscript preparation. Will you conduct a retrospective chart review, a prospective study, or a true clinical trial with randomization and blinding? Will you systematically seek out and remove sources of bias from the study design and interpretation of results? Will you ensure the study is powered properly to justify conclusions? Will you eliminate or explain any conflicts of interest occurring among your author group? Will you fall victim to the temptation of frivolous subgroup analyses, or will you stick with the original plan? Will your study have a realistic chance at publication in a journal within your specialty, or perhaps another subfield? The study results may prove the null hypothesis, a ‘negative study,’ and therefore be difficult to publish. [2]  Additionally, the intervention you find beneficial may subsequently be proven unhelpful or even dangerous, leading to prudent medical reversal. [3]

These considerations and more necessitate meticulous planning and vigilant adherence to a sound protocol. Along the way, you will encounter obstacles, pitfalls, some of which are presented in this article. But remain persistent, and your efforts will be rewarded with publication and contribution to science. This review covers common pitfalls researchers encounter and suggested strategies to avoid them.

• Issues of Concern

There are five phases of research: planning phase, data collection/analysis phase, writing phase, journal submission phase, and rejections/revisions/acceptance phase.

Phase I Pitfalls: Planning a Study

The highest yield preempting of pitfalls in the research process occurs in the planning phase. This is when a researcher can set the stage for an optimal research process. Below are pitfalls that can occur during the planning phase.

Pitfall: Underestimating what committing to a research project requires

Conducting a research study and achieving publication sounds fulfilling, right?

Consider the many steps: conducting a literature search, writing an IRB proposal, planning and having research meetings, long and cumbersome data collection processes, working with statisticians or analyzing complex data, having unexpected research setbacks (e.g., subjects drop out, newly published papers on same topic, etc.), the possibility that after data collection you have no statistically (or clinically) significant findings, conducting an updated literature search, writing introduction, methods, results, and discussion sections of a paper, going through the many journal options to determine best fit while aiming for high impact factors, adhering to journal guidelines/fixing drafts, writing cover letters stating importance of the topic to respective journals, creating journal portal accounts, possibly being rejected numerous times, waiting months for journal decisions, working on numerous revisions and being informed by numerous individuals about all of the flaws in your writing and research.

Does it sound, maybe less fulfilling ?

Conducting a research project from inception to publication can be a rewarding experience. Research requires significant time. Setbacks are normal. To produce an important and sought-after research product, an individual must understand the magnitude of commitment required.

Pitfall: Choosing the wrong research pursuit/topic lacks precision

Consider an investigator interested in substance use research. The first challenge is the immense amount of research already published on this topic. Fortunately, there is still a massive amount of uncharted territory in substance use research.

It is important to understand what has been done and what is still undiscovered in your area of research. Do not simply study a topic because you find it interesting; passion is advantageous, but you should ensure that your study will contribute to some field/specialty or research in a significant way.

How does your research differ from what has been done?

How will it impact practice in a way that no previous study has?

Consider these questions when choosing a topic for research. Otherwise, you may struggle to get the work published. It can be demoralizing if you have already written your paper and realize that your paper is not going to get accepted by a reputable journal due to the presence of other papers already describing the same concepts you have.

As always, the first step is a thorough literature search.

Pitfall: Not considering research bias

A common theme noted in literature is that bias can, unfortunately, lead to failure to reproduce results, raising concerns regarding the integrity of science. [4]  Bias can be considered various (inadvertent) poor strategies related to data design, analysis, and results reporting that produce spurious results and papers that perhaps should not be published. [5]

While one cannot completely eliminate bias from the research process, researchers should take steps to understand research bias in study endeavors and determine how to minimize bias during the planning phase of the study.  

Pitfall: Not focusing on which variables to collect

Researchers often want to collect as much data as possible but should not build a list of variables that includes every single detail about subjects if the variables collected are unlikely to yield insight into the topic of research. The longer the data collection instrument, the higher likelihood of (human) errors (if manually data entry) and the longer duration of the data collection phase. Instead of taking time to build a database with many variables, consider cutting irrelevant variables and use that time to increase the sample size. Determine, based on your own clinical knowledge and published empirical works, which variables are most crucial. 

Pitfall: Worrying about the statistics after the data has been collected

A vital part of the research process is ensuring you have a rigorous statistical approach. Involve your statistician very early in the project, preferably in the planning stages. They will have insight into the types of variables to collect and help shape the research methods. Statistical power is an important concept to consider before data collection to avoid false-negative results (Zlowodzki et al., 2006). Furthermore, other concepts, such as covariates, need to be part of the planning phase. Do not wait until after the data collection phase to give data to the statistician who cannot transform the data you have into outputs you want.

Pitfall: Not setting defined author roles

It is important to define who will be declared authors at the beginning of the research process to avoid conflict. Do most people want to be an author? Sure. Does everybody do the work worthy of authorship? No. While placing general comments in a shared document's margin may make the paper slightly better, it probably should not qualify for authorship. Review authorship criteria to determine what constitutes authorship. Clear expectations can ensure that everyone is on the same page and that everyone feels the process is fair, especially for individuals who plan to invest significant time in the project. Clear expectations for each author should occur before any writing begins, including deadlines and specific contributions. [6] [7] [6]

Pitfall: Not considering limitations of work before the paper is written

Avoid this pitfall by reviewing recent manuscripts and reading the limitations sections of these papers. Many of these limitations sections will make notions about generalizability to other populations. Some will discuss low power. Even the best papers in the top journals have many limitations. The best way to avoid or mitigate your work's limitations is to consider them during the planning phase.

How can you set up your project to limit your limitations section?

What (types of) samples should you include in your study?

Were you originally thinking of retrospective design, but it could be prospective?

What steps can you utilize to control baseline characteristics between groups?

Consider all limitations and think about how you can control these before data collection.

Phase II Pitfalls: Data Collection and Analysis

After the planning has occurred, typically after institutional review board (IRB) approval, the data collection and analysis phase can transpire. The entire team should typically stay involved throughout these phases. Below are pitfalls to avoid.

Pitfall: Not being involved in the data collection phase

It is important to be involved with the data collection phase, even if you do not personally collect data. Train the individuals who collect data to ensure all are on the same page and provide periodic oversight to ensure accuracy and quality of the data over time. [8]  Do not assume the data collection phase is going smoothly – you may find yourself with a huge dataset riddled with inconsistencies or errors. Schedule periodic meetings to review data.

Pitfall: Not being involved with the statistical analysis phase

If you are not conducting the statistical analysis, do not assume that the person who is analyzing the data is 100% on the same page. Have meetings about the data, how to interpret the data, and the limitations of the data. Ask what other ways the data could be analyzed and how reviewers might negatively critique the data itself or the statistical methods.

The person conducting the analysis will not have the same familiarity with the topic. You are not going to be as familiar with the outputs. By understanding each other, you will a) have clearer, more robust methods and results in sections of the paper, b) limit critiques regarding the statistical approach/data outcomes, c) understand your research better for any presentations, discussion, or future work, and d) develop a positive collaboration for future work.

Phase III Pitfalls: The Writing Phase

The next phase is the writing phase. While this section covers pitfalls during the writing phase, for recommendations on conducting a literature search, writing, and publishing research, see StatPearls Evidence-Base Medicine Chapter: How to Write and Publish a Scientific Manuscript. [9]  Below are pitfalls that can occur during the writing phase. 

Pitfall: Poor or outdated references

When writing your paper, perform multiple literature searches to ensure all recent, salient references are covered—claims about recent similar work or research that frames your study if the references are outdated. Journals may even ask reviewers to comment on the presence or absence of up-to-date/suitable references. Conduct a literature search prior to data collection and stay on top of references throughout the research process as new papers become available.

Pitfall: No clearly defined purpose of the paper

Many aspects of manuscripts can get overlooked. Lack of a clear purpose statement can doom a paper to futility. Remind the readers of the goal of the project. You do not want consumers of your research to read the results section and forget what the goals/main outcomes are. The purpose statement should be located at the end of the introduction section.  

Pitfall: Unclear methods making research hard to reproduce

A common concern in science is the lack of transparency in methods for reproducibility. The methods section should allow a reader to understand exactly what was done and conduct the study. Consider examining the S treng T hening the R eporting of OB servational studies in E pidemiology (STROBE) checklist for the methods (as well as other paper sections) to ensure best reporting practices for reproducibility. [10]

Pitfall: The tables and narratives are the same

Reviewers prefer you not to state findings in narratives that are in tables. Tables focus readers on the most important results and are not redundant with the written content. Make call-outs to the table in the paper's narrative sections, but do not state information found in tables.  

Pitfall: Not reporting all data/outcomes

Some authors will state the main outcome of interest or have a statement such as “there were no other statistically significant findings between other groups.” Authors must report all outcomes and statistical analyses for reproducibility of the research. While this may be difficult to do with a broad approach, utilize tables and appendices to report all outcomes to show transparency and limit researcher bias.

Pitfall: Repeating results in discussion

Do not simply restate in the discussion what you already have in the results section. Utilize this section of the paper to link other references to your work and reflect on other empirical investigations' similarities or differences. Explain why your research provides an impactful contribution to the topic.  

Pitfall: Making conclusions that do not align with your work

Authors sometimes note in their conclusions how the work impacts a topic due to X reason when X may be too broad a claim and the work doesn’t really support or prove that notion. Researchers should align their conclusions to their own results and highlight the significance of their findings.

Pitfall: Thinking the title is not a big deal

A strong title will help with the impact/readership of your paper. Consider keeping a short title that provides the main takeaway. Papers with more concise titles and present the study conclusion result in a bigger impact/receive more citations. [11]

Pitfall: Completing the abstract last minute

Similar to the title, do not underestimate an abstract. Journal and conference reviewers (and the general audience) may only read your abstract. The abstract must have the key results and contributions of the study and be well-written.

Phase IV Pitfalls: Submitting to a Journal

After the paper has been written, it is time to choose the journal. This phase also has numerous pitfalls. Below are pitfalls that can occur during this phase.  

Pitfall: Choosing the wrong journal

Choosing the journal for your work can be overwhelming due to the number of options. Always look at the aims and scope of prospective journals. Look through the author guidelines to ensure that your manuscript adheres. This will save time. Review your reference list for any journals that appear more than once; if so, consider submitting to that journal. You do not want to submit your paper, wait two weeks, and then get a desk rejection because the editors state the paper is not aligned to the journal's aims and scope.

Additionally, researchers can aim too high and spend months (and numerous hours in journal submission portals) trying to publish a manuscript in a journal with a very large impact factor. Though admirable, if the research design and results lacking “gold standard” reporting, authors should consider a journal that is more likely to accept. Find a balance between the quality of your paper and the quality of the journal. Seek feedback from the other authors and/or senior colleagues who can provide honest feedback.

Pitfall: Poor cover letter on journal submission

Do not submit work with a flawed cover letter (errors or lack of clarity in how your work contributes to the body of literature). Spend time writing a detailed cover letter once, have it edited by someone else, and utilize that for all future projects. You can highlight the differences (e.g., the purpose of this work, our results showed) with each project. Use the cover letter to highlight the significance of the study while adhering to the disclosure guidelines (e.g., conflicts of interests, authors contributions, data releases, etc.), which will help the editorial board determine not only the suitability of the paper for the journal but also streamline the review process. [12]

Pitfall: Assuming that after the paper has been submitted to a journal, the work is done             

The paper has been submitted! You think you are finished…but, unfortunately, the publishing game may still be far from over. Researchers often do not recognize the amount of time going into the submission/rejection/revisions phases. Revisions can sometimes be total overhauls, more work than writing a whole new paper. Be prepared to continue working.

Phase V Pitfalls: The Rejections, Revisions, and Acceptance Phase

Finally, perhaps the most unpredictable phase, the rejections, revisions, and acceptance phase, has unique pitfalls and other obstacles.

Pitfall: Mourning rejections too long/ “sitting on” a rejected paper             

Did you get a desk to reject (i.e., the manuscript was not even sent for blind review)? That is unfortunate but common. You do not have time to sulk. Get that paper submitted somewhere else. The older the data, the less desirable your paper becomes. If the paper went in for a full review and was rejected, that may be even tougher than a desk reject because more time has elapsed. The good news is that (hopefully) you received feedback to incorporate in a revision. Do not spend too much time grieving rejections.

Pitfall: Not laying to rest rejected papers when it is indeed their time to go

Did you write a paper a couple of years ago, and you’ve submitted it to 20 different journals? The data is getting old. The topic wasn’t focused on. The sample size was small. Perhaps the project is not worth pursuing any longer. Do not give in to the sunk cost fallacy. If, however, you are proud of the work and stand by the paper, do not give up. If you believe after the numerous rejections that the topic/project is flawed, you can use this failure as a personal learning/growth opportunity. Do not repeat controllable mistakes on future projects.

Pitfall: Not addressing all of reviewer feedback

Did you get a revise and resubmit? Great news! The reviewers and editors will likely ask you to respond to each comment when you resubmit. Address all of the reviewer feedback. Take your time reading through the feedback, digest it, and re-read it. Carefully respond and decide how to revise your manuscript based on the feedback. Share the reviews and the duties of revision with coauthors. In your response to reviewers, stay professional and address each statement, even if you disagree with what is stated. If you do not respond to each statement, the reviewers often highlight the concern(s) again.

Pitfall: Thinking you know what the reviewers are going to say

Research reviewers are like a box of chocolates. You never know what you are going to get. You may be worried about a section of your paper/research approach, and the reviewers do not mention it at all in their review; instead, they criticize a section of your manuscript that you are most proud of.

In some reviews, you may get feedback like the following:

Reviewer #1

Please change lines 104-108 as I believe they are irrelevant to your study.

Reviewer #2

Please build on lines 104-108, as I believe they are the foundation of your study.

Sometimes, after multiple revisions, there are new concerns presented by the reviewers. This can be disheartening. Should some regulations restrict reviewers from bringing up new ideas/concerns during revision #7? Perhaps. Does any current rule prevent them from doing this? No.

During the review process, we must have faith that the reviewers are knowledgeable and provide fair, insightful, and constructive feedback. While the review process can be arbitrary or frustrating in some cases, peer review remains the gold standard in a scientific publication. Stay positive and persistent. Stay professional in responses to the reviewers. Remember that the review process can be very beneficial as it often leads to feedback that truly elevates your work and makes the product (and you) look better. [13]

Pitfall: Not rewarding yourself for a published paper

You did it! Celebrate your accomplishment. Reflect on the merit of your effort before you move on to other work or re-enter the cycle of IRBs, data coding, journal submissions, etc. Remember and appreciate how remarkable it is that you just contributed knowledge to the world.

• Clinical Significance

Many pitfalls can occur throughout the research process. Researchers should understand these pitfalls and utilize strategies to avoid them to produce high-quality, sought-after research results that are useful for basic science and clinical practice.

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Disclosure: Jacob Shreffler declares no relevant financial relationships with ineligible companies.

Disclosure: Martin Huecker declares no relevant financial relationships with ineligible companies.

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• Cite this Page Shreffler J, Huecker MR. Common Pitfalls In The Research Process. [Updated 2023 Mar 6]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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It’s Time to Reconceptualize What “Imposter Syndrome” Means for People of Color

• Kevin Cokley

How racism, bias, and imposter feelings are intertwined.

The recent pushback against the imposter phenomenon in the media has largely focused on how and why it’s inappropriate for people of color. In this article, the author argues that, while there is merit to these arguments, getting rid of the idea entirely for Black students and workers is a disservice. Instead, he recommends reconceptualizing the term to include new research on how imposterism affects people of color, and urges organizations to better understand how racism, bias, and imposter feelings are intertwined.

Over the past few years, there has been increased attention paid to the imposter phenomenon (a.k.a., imposter syndrome) in the media. Its popularity is understandable given that it’s an intuitive, common-sense concept about a tremendously relatable topic: feeling like a phony on the job. It’s also, at least according to recent review of the literature , fairly common: up to 80% of people have experienced imposter feelings.

• Kevin Cokley is the University Diversity and Social Transformation Professor and Professor of Psychology at the University of Michigan where he serves as Associate Chair of Diversity Initiatives. He is editor of the forthcoming book The Impostor Phenomenon: Psychological Theory, Research, and Interventions . His Hidden Brain podcast “Success 2.0: The Psychology of Self-Doubt” addresses the corrosive effects of self-doubt and how we can turn that negative voice in our heads into an ally.

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• 06 March 2024

Why scientists trust AI too much — and what to do about it

You have full access to this article via your institution.

AI-run labs have arrived — such as this one in Suzhou, China. Credit: Qilai Shen/Bloomberg/Getty

Scientists of all stripes are embracing artificial intelligence (AI) — from developing ‘self-driving’ laboratories , in which robots and algorithms work together to devise and conduct experiments, to replacing human participants in social-science experiments with bots 1 .

Many downsides of AI systems have been discussed. For example, generative AI such as ChatGPT tends to make things up , or ‘hallucinate’ — and the workings of machine-learning systems are opaque .

Artificial intelligence and illusions of understanding in scientific research

In a Perspective article 2 published in Nature this week, social scientists say that AI systems pose a further risk: that researchers envision such tools as possessed of superhuman abilities when it comes to objectivity, productivity and understanding complex concepts. The authors argue that this put researchers in danger of overlooking the tools’ limitations, such as the potential to narrow the focus of science or to lure users into thinking they understand a concept better than they actually do.

Scientists planning to use AI “must evaluate these risks now, while AI applications are still nascent, because they will be much more difficult to address if AI tools become deeply embedded in the research pipeline”, write co-authors Lisa Messeri, an anthropologist at Yale University in New Haven, Connecticut, and Molly Crockett, a cognitive scientist at Princeton University in New Jersey.

The peer-reviewed article is a timely and disturbing warning about what could be lost if scientists embrace AI systems without thoroughly considering such hazards. It needs to be heeded by researchers and by those who set the direction and scope of research, including funders and journal editors. There are ways to mitigate the risks. But these require that the entire scientific community views AI systems with eyes wide open.

ChatGPT is a black box: how AI research can break it open

To inform their article, Messeri and Crockett examined around 100 peer-reviewed papers, preprints, conference proceedings and books, published mainly over the past five years. From these, they put together a picture of the ways in which scientists see AI systems as enhancing human capabilities.

In one ‘vision’, which they call AI as Oracle, researchers see AI tools as able to tirelessly read and digest scientific papers, and so survey the scientific literature more exhaustively than people can. In both Oracle and another vision, called AI as Arbiter, systems are perceived as evaluating scientific findings more objectively than do people, because they are less likely to cherry-pick the literature to support a desired hypothesis or to show favouritism in peer review. In a third vision, AI as Quant, AI tools seem to surpass the limits of the human mind in analysing vast and complex data sets. In the fourth, AI as Surrogate, AI tools simulate data that are too difficult or complex to obtain.

Informed by anthropology and cognitive science, Messeri and Crockett predict risks that arise from these visions. One is the illusion of explanatory depth 3 , in which people relying on another person — or, in this case, an algorithm — for knowledge have a tendency to mistake that knowledge for their own and think their understanding is deeper than it actually is.

How to stop AI deepfakes from sinking society — and science

Another risk is that research becomes skewed towards studying the kinds of thing that AI systems can test — the researchers call this the illusion of exploratory breadth. For example, in social science, the vision of AI as Surrogate could encourage experiments involving human behaviours that can be simulated by an AI — and discourage those on behaviours that cannot, such as anything that requires being embodied physically.

There’s also the illusion of objectivity, in which researchers see AI systems as representing all possible viewpoints or not having a viewpoint. In fact, these tools reflect only the viewpoints found in the data they have been trained on, and are known to adopt the biases found in those data. “There’s a risk that we forget that there are certain questions we just can’t answer about human beings using AI tools,” says Crockett. The illusion of objectivity is particularly worrying given the benefits of including diverse viewpoints in research.

Avoid the traps

If you’re a scientist planning to use AI, you can reduce these dangers through a number of strategies. One is to map your proposed use to one of the visions, and consider which traps you are most likely to fall into. Another approach is to be deliberate about how you use AI. Deploying AI tools to save time on something your team already has expertise in is less risky than using them to provide expertise you just don’t have, says Crockett.

Journal editors receiving submissions in which use of AI systems has been declared need to consider the risks posed by these visions of AI, too. So should funders reviewing grant applications, and institutions that want their researchers to use AI. Journals and funders should also keep tabs on the balance of research they are publishing and paying for — and ensure that, in the face of myriad AI possibilities, their portfolios remain broad in terms of the questions asked, the methods used and the viewpoints encompassed.

All members of the scientific community must view AI use not as inevitable for any particular task, nor as a panacea, but rather as a choice with risks and benefits that must be carefully weighed. For decades, and long before AI was a reality for most people, social scientists have studied AI. Everyone — including researchers of all kinds — must now listen.

Nature 627 , 243 (2024)

doi: https://doi.org/10.1038/d41586-024-00639-y

Grossmann, I. et al. Science 380 , 1108–1109 (2023).

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Messeri, L. & Crockett, M. J. Nature 627 , 49–58 (2024).

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Rozenblit, L. & Keil, F. Cogn. Sci. 26 , 521–562 (2002).

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2.2: Why Is Research Important?

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Learning Objectives

• Explain how scientific research addresses questions about behavior
• Discuss how scientific research guides public policy
• Appreciate how scientific research can be important in making personal decisions

Scientific research is a critical tool for successfully navigating our complex world. Without it, we would be forced to rely solely on intuition, other people’s authority, and blind luck. While many of us feel confident in our abilities to decipher and interact with the world around us, history is filled with examples of how very wrong we can be when we fail to recognize the need for evidence in supporting claims. At various times in history, we would have been certain that the sun revolved around a flat earth, that the earth’s continents did not move, and that mental illness was caused by possession. It is through systematic scientific research that we divest ourselves of our preconceived notions and superstitions and gain an objective understanding of ourselves and our world.

The goal of all scientists is to better understand the world around them. Psychologists focus their attention on understanding behavior, as well as the cognitive (mental) and physiological (body) processes that underlie behavior. In contrast to other methods that people use to understand the behavior of others, such as intuition and personal experience, the hallmark of scientific research is that there is evidence to support a claim. Scientific knowledge is empirical : It is grounded in objective, tangible evidence that can be observed time and time again, regardless of who is observing.

While behavior is observable, the mind is not. If someone is crying, we can see behavior. However, the reason for the behavior is more difficult to determine. Is the person crying due to being sad, in pain, or happy? Sometimes we can learn the reason for someone’s behavior by simply asking a question, like “Why are you crying?” However, there are situations in which an individual is either uncomfortable or unwilling to answer the question honestly, or is incapable of answering. For example, infants would not be able to explain why they are crying. In such circumstances, the psychologist must be creative in finding ways to better understand behavior. This chapter explores how scientific knowledge is generated, and how important that knowledge is in forming decisions in our personal lives and in the public domain.

Use of Research Information

Trying to determine which theories are and are not accepted by the scientific community can be difficult, especially in an area of research as broad as psychology. More than ever before, we have an incredible amount of information at our fingertips, and a simple internet search on any given research topic might result in a number of contradictory studies. In these cases, we are witnessing the scientific community going through the process of reaching a consensus, and it could be quite some time before a consensus emerges. For example, the hypothesized link between exposure to media violence and subsequent aggression has been debated in the scientific community for roughly \(60\) years. Even today, we will find detractors, but a consensus is building. Several professional organizations view media violence exposure as a risk factor for actual violence, including the American Medical Association, the American Psychiatric Association, and the American Psychological Association (American Academy of Pediatrics, American Academy of Child & Adolescent Psychiatry, American Psychological Association, American Medical Association, American Academy of Family Physicians, American Psychiatric Association, 2000).

In the meantime, we should strive to think critically about the information we encounter by exercising a degree of healthy skepticism. When someone makes a claim, we should examine the claim from a number of different perspectives: what is the expertise of the person making the claim, what might they gain if the claim is valid, does the claim seem justified given the evidence, and what do other researchers think of the claim? This is especially important when we consider how much information in advertising campaigns and on the internet claims to be based on “scientific evidence” when in actuality it is a belief or perspective of just a few individuals trying to sell a product or draw attention to their perspectives.

We should be informed consumers of the information made available to us because decisions based on this information have significant consequences. One such consequence can be seen in politics and public policy. Imagine that you have been elected as the governor of your state. One of your responsibilities is to manage the state budget and determine how to best spend your constituents’ tax dollars. As the new governor, you need to decide whether to continue funding the D.A.R.E. (Drug Abuse Resistance Education) program in public schools (Figure \(\PageIndex{2}\)). This program typically involves police officers coming into the classroom to educate students about the dangers of becoming involved with alcohol and other drugs. According to the D.A.R.E. website (www.dare.org), this program has been very popular since its inception in 1983, and it is currently operating in \(75\%\) of school districts in the United States and in more than \(40\) countries worldwide. Sounds like an easy decision, right? However, on closer review, you discover that the vast majority of research into this program consistently suggests that participation has little, if any, effect on whether or not someone uses alcohol or other drugs (Clayton, Cattarello, & Johnstone, 1996; Ennett, Tobler, Ringwalt, & Flewelling, 1994; Lynam et al., 1999; Ringwalt, Ennett, & Holt, 1991). If you are committed to being a good steward of taxpayer money, will you fund this particular program, or will you try to find other programs that research has consistently demonstrated to be effective?

Ultimately, it is not just politicians who can benefit from using research in guiding their decisions. We all might look to research from time to time when making decisions in our lives. Imagine you just found out that a close friend has breast cancer or that one of your young relatives has recently been diagnosed with autism. In either case, you want to know which treatment options are most successful with the fewest side effects. How would you find that out? You would probably talk with your doctor and personally review the research that has been done on various treatment options—always with a critical eye to ensure that you are as informed as possible.

In the end, research is what makes the difference between facts and opinions. Facts are observable realities, and opinions are personal judgments, conclusions, or attitudes that may or may not be accurate. In the scientific community, facts can be established only using evidence collected through empirical research.

The Process of Scientific Research

Scientific knowledge is advanced through a process known as the scientific method . Basically, ideas (in the form of theories and hypotheses) are tested against the real world (in the form of empirical observations), and those empirical observations lead to more ideas that are tested against the real world, and so on. In this sense, the scientific process is circular. The types of reasoning within the circle are called deductive and inductive. In deductive reasoning , ideas are tested against the empirical world; in inductive reasoning , empirical observations lead to new ideas. These processes are inseparable, like inhaling and exhaling, but different research approaches place different emphasis on the deductive and inductive aspects.

In the scientific context, deductive reasoning begins with a generalization—one hypothesis—that is then used to reach logical conclusions about the real world. If the hypothesis is correct, then the logical conclusions reached through deductive reasoning should also be correct. A deductive reasoning argument might go something like this: All living things require energy to survive (this would be your hypothesis). Ducks are living things. Therefore, ducks require energy to survive (logical conclusion). In this example, the hypothesis is correct; therefore, the conclusion is correct as well. Sometimes, however, an incorrect hypothesis may lead to a logical but incorrect conclusion. Consider this argument: all ducks are born with the ability to see. Quackers is a duck. Therefore, Quackers was born with the ability to see. Scientists use deductive reasoning to empirically test their hypotheses. Returning to the example of the ducks, researchers might design a study to test the hypothesis that if all living things require energy to survive, then ducks will be found to require energy to survive.

Deductive reasoning starts with a generalization that is tested against real-world observations; however, inductive reasoning moves in the opposite direction. Inductive reasoning uses empirical observations to construct broad generalizations. Unlike deductive reasoning, conclusions drawn from inductive reasoning may or may not be correct, regardless of the observations on which they are based. For instance, you may notice that your favorite fruits—apples, bananas, and oranges—all grow on trees; therefore, you assume that all fruit must grow on trees. This would be an example of inductive reasoning, and, clearly, the existence of strawberries, blueberries, and kiwi demonstrate that this generalization is not correct despite it being based on a number of direct observations. Scientists use inductive reasoning to formulate theories, which in turn generate hypotheses that are tested with deductive reasoning. In the end, science involves both deductive and inductive processes.

For example, case studies, which you will read about in the next section, are heavily weighted on the side of empirical observations. Thus, case studies are closely associated with inductive processes as researchers gather massive amounts of observations and seek interesting patterns (new ideas) in the data. Experimental research, on the other hand, puts great emphasis on deductive reasoning.

We’ve stated that theories and hypotheses are ideas, but what sort of ideas are they, exactly? A theory is a well-developed set of ideas that propose an explanation for observed phenomena. Theories are repeatedly checked against the world, but they tend to be too complex to be tested all at once; instead, researchers create hypotheses to test specific aspects of a theory.

A hypothesis is a testable prediction about how the world will behave if our idea is correct, and it is often worded as an if-then statement (e.g., if I study all night, I will get a passing grade on the test). The hypothesis is extremely important because it bridges the gap between the realm of ideas and the real world. As specific hypotheses are tested, theories are modified and refined to reflect and incorporate the result of these tests.

To see how this process works, let’s consider a specific theory and a hypothesis that might be generated from that theory. As you’ll learn in a later chapter, the James-Lange theory of emotion asserts that emotional experience relies on the physiological arousal associated with the emotional state. If you walked out of your home and discovered a very aggressive snake waiting on your doorstep, your heart would begin to race and your stomach churn. According to the James-Lange theory, these physiological changes would result in your feeling of fear. A hypothesis that could be derived from this theory might be that a person who is unaware of the physiological arousal that the sight of the snake elicits will not feel fear.

A scientific hypothesis is also falsifiable , or capable of being shown to be incorrect. Recall from the introductory chapter that Sigmund Freud had lots of interesting ideas to explain various human behaviors. However, a major criticism of Freud’s theories is that many of his ideas are not falsifiable; for example, it is impossible to imagine empirical observations that would disprove the existence of the id, the ego, and the superego—the three elements of personality described in Freud’s theories. Despite this, Freud’s theories are widely taught in introductory psychology texts because of their historical significance for personality psychology and psychotherapy, and these remain the root of all modern forms of therapy.

In contrast, the James-Lange theory does generate falsifiable hypotheses, such as the one described above. Some individuals who suffer significant injuries to their spinal columns are unable to feel the bodily changes that often accompany emotional experiences. Therefore, we could test the hypothesis by determining how emotional experiences differ between individuals who have the ability to detect these changes in their physiological arousal and those who do not. In fact, this research has been conducted and while the emotional experiences of people deprived of an awareness of their physiological arousal may be less intense, they still experience emotion (Chwalisz, Diener, & Gallagher, 1988).

Scientific research’s dependence on falsifiability allows for great confidence in the information that it produces. Typically, by the time information is accepted by the scientific community, it has been tested repeatedly.

Scientists are engaged in explaining and understanding how the world around them works, and they are able to do so by coming up with theories that generate hypotheses that are testable and falsifiable. Theories that stand up to their tests are retained and refined, while those that do not are discarded or modified. In this way, research enables scientists to separate fact from simple opinion. Having good information generated from research aids in making wise decisions both in public policy and in our personal lives.

Contributors and Attributions

Rose M. Spielman with many significant contributors. The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the creative commons license and may not be reproduced without the prior and express written consent of Rice University. For questions regarding this license, please contact  [email protected] .Textbook content produced by OpenStax College is licensed under a  Creative Commons Attribution License 4.0  license. Download for free at http://cnx.org/contents/[email protected] .

Intermittent fasting linked to higher risk of cardiovascular death, research suggests

Intermittent fasting, a diet pattern that involves alternating between periods of fasting and eating, can lower blood pressure and help some people lose weight , past research has indicated.

But an analysis presented Monday at the American Heart Association’s scientific sessions in Chicago challenges the notion that intermittent fasting is good for heart health. Instead, researchers from Shanghai Jiao Tong University School of Medicine in China found that people who restricted food consumption to less than eight hours per day had a 91% higher risk of dying from cardiovascular disease over a median period of eight years, relative to people who ate across 12 to 16 hours.

It’s some of the first research investigating the association between time-restricted eating (a type of intermittent fasting) and the risk of death from cardiovascular disease.

The analysis — which has not yet been peer-reviewed or published in an academic journal — is based on data from the Centers for Disease Control and Prevention’s National Health and Nutrition Examination Survey collected between 2003 and 2018. The researchers analyzed responses from around 20,000 adults who recorded what they ate for at least two days, then looked at who had died from cardiovascular disease after a median follow-up period of eight years.

However, Victor Wenze Zhong, a co-author of the analysis, said it’s too early to make specific recommendations about intermittent fasting based on his research alone.

“Practicing intermittent fasting for a short period such as 3 months may likely lead to benefits on reducing weight and improving cardiometabolic health,” Zhong said via email. But he added that people “should be extremely cautious” about intermittent fasting for longer periods of time, such as years.

Intermittent fasting regimens vary widely. A common schedule is to restrict eating to a period of six to eight hours per day, which can lead people to consume fewer calories, though some eat the same amount in a shorter time. Another popular schedule is the "5:2 diet," which involves eating 500 to 600 calories on two nonconsecutive days of the week but eating normally for the other five.

Zhong said it’s not clear why his research found an association between time-restricted eating and a risk of death from cardiovascular disease. He offered an observation, though: People who limited their eating to fewer than eight hours per day had less lean muscle mass than those who ate for 12 to 16 hours. Low lean muscle mass has been linked to a higher risk of cardiovascular death .

Cardiovascular and nutrition experts who were not involved in the analysis offered several theories about what might explain the results.

Dr. Benjamin Horne, a research professor at Intermountain Health in Salt Lake City, said fasting can increase stress hormones such as cortisol and adrenaline, since the body doesn’t know when to expect food next and goes into survival mode. That added stress may raise the short-term risk of heart problems among vulnerable groups, he said, particularly elderly people or those with chronic health conditions.

Horne’s research has shown that fasting twice a week for four weeks, then once a week for 22 weeks may increase a person’s risk of dying after one year but decrease their 10-year risk of chronic disease.

“In the long term, what it does is reduces those risk factors for heart disease and reduces the risk factors for diabetes and so forth — but in the short term, while you’re actually doing it, your body is in a state where it’s at a higher risk of having problems,” he said.

Even so, Horne added, the analysis “doesn’t change my perspective that there are definite benefits from fasting, but it’s a cautionary tale that we need to be aware that there are definite, potentially major, adverse effects.” 

Intermittent fasting gained popularity about a decade ago, when the 5:2 diet was touted as a weight loss strategy in the U.K. In the years to follow, several celebrities espoused the benefits of an eight-hour eating window for weight loss, while some Silicon Valley tech workers believed that extreme periods of fasting boosted productivity . Some studies have also suggested that intermittent fasting might help extend people’s lifespans by warding off disease .

However, a lot of early research on intermittent fasting involved animals. In the last seven years or so, various clinical trials have investigated potential benefits for humans, including for heart health.

“The purpose of intermittent fasting is to cut calories, lose weight,” said Penny Kris-Etherton, emeritus professor of nutritional sciences at Penn State University and a member of the American Heart Association nutrition committee. “It’s really how intermittent fasting is implemented that’s going to explain a lot of the benefits or adverse associations.”

Dr. Francisco Lopez-Jimenez, a cardiologist at Mayo Clinic, said the timing of when people eat may influence the effects they see. 

“I haven’t met a single person or patient that has been practicing intermittent fasting by skipping dinner,” he said, noting that people more often skip breakfast, a schedule associated with an increased risk of heart disease and death .

The new research comes with limitations: It relies on people’s memories of what they consumed over a 24-hour period and doesn’t consider the nutritional quality of the food they ate or how many calories they consumed during an eating window.

So some experts found the analysis too narrow.

“It’s a retrospective study looking at two days’ worth of data, and drawing some very big conclusions from a very limited snapshot into a person’s lifestyle habits,” said Dr. Pam Taub, a cardiologist at UC San Diego Health.

Taub said her patients have seen “incredible benefits” from fasting regimens.

“I would continue doing it,” she said. “For people that do intermittent fasting, their individual results speak for themselves. Most people that do intermittent fasting, the reason they continue it is they see a decrease in their weight. They see a decrease in blood pressure. They see an improvement in their LDL cholesterol.” 

Kris-Etherton, however, urged caution: “Maybe consider a pause in intermittent fasting until we have more information or until the results of the study can be better explained,” she said.

Aria Bendix is the breaking health reporter for NBC News Digital.

Most sportswomen experience gendered online harm, affecting wellbeing, research says

Sport Most sportswomen experience gendered online harm, affecting wellbeing, research says

A study by researchers from Deakin University has found that an overwhelming majority of elite sportswomen (nine in 10) have experienced some form of gendered online harm, including 87 per cent in the past year.

And while the mention of trolling and women in sport is often associated with high-profile athletes like Tayla Harris, results showed that women of all profiles, and across all sports, were affected.

Felicity Goodwin, who played elite-level rugby union, says she experienced both blatant sexism, and more insidious attempts to make her feel unwelcome.

"There were the stereotypical comments of 'get back in the kitchen and make me a sandwich," she says.

"But there were also ones like 'oh, so you like the Wallabies? Tell me the top try scorers for the last few seasons, or the last three winners of the John Eales medal.' I can do that — but why should I have to?

"The problem was just the fact that I was female, and I had the nerve to be in that space."

The Deakin study surveyed 138 professional and semi-professional athletes from 32 sports, with 85 per cent saying their wellbeing had been affected by online harm, while two in three felt unsafe.

The most common examples of gendered online harm were personal insults (81 per cent), hate speech (62 per cent), attempts to embarrass (60 per cent) and both general and sexual harassment (50 per cent and 39 per cent respectively).

One in four sportswomen also experienced homophobic abuse, and one in five racist abuse.

Goodwin, who last year worked as an assistant coach at the Queensland Reds, was one of those targeted by homophobia.

"Straight-identifying teammates copped it too, but more often with comments around their appearance, like 'what's a pretty girl like you doing in a sport like this?'

"We were probably an easy target, playing women's team sports. Especially if you look at rugby, it's historically a private boys' school sport, and there's very much an 'old boys' mentality to it."

Women in sport stuck in 'vicious cycle'

Associate professor Kim Toffoletti, one of the report's co-authors, said the study explored the impacts of not just being the direct target of abuse, but witnessing it.

"If you're an athlete, and you're seeing women in high-profile positions being abused in these kinds of spaces, the message it sends is that if you succeed in your sport, you'll be trolled, harassed, judged and shamed," she said.

"It's a pretty powerful way of regulating women and sending a message to them about getting back in their place."

As Associate professor Toffoletti explained it, sportswomen are caught in a catch-22 situation when it comes to maintaining an online presence.

More than 97 per cent of athletes reported that it was necessary for them to maintain a social media presence, including 69 per cent who said they needed an account for work, sponsorship or their professional profile.

"They recognised a vicious cycle where their sports weren't getting enough visibility, but when they attempted to put themselves out there — to promote themselves and their activities — they received abuse," she said.

Making matters worse, 81 per cent said that experiencing online harm in turn affected their economic opportunities.

One in 10 also felt it necessary to close their social media accounts, while 64 per cent said they changed their online behaviour in some way, including posting less, or avoiding 'heavy' or politically-charged topics.

"Women felt compelled to present a palatable, pleasant online presence that didn't disrupt or challenge the status quo," Associate professor Toffoletti said.

Onus to solve online harm put on athletes, not offenders

According to Goodwin, the issue of online harm was compounded by sporting organisations and clubs putting the onus onto athletes to solve the problem.

"We have education sessions where we talk about expectations on players and their role in things, like, 'don't go out and antagonise people; don't give them anything and don't respond to them,'" she said.

"But the thing is it's not just a me problem. I'm only replying to things that were sent to me."

Lead researcher Dr Caitlin McGrane said this was a common theme in interviews with athletes, who were consistently told to 'block' and 'ignore' offenders, and be careful about what they posted:

"It puts the onus back on women to be defending themselves from the potential of harassment and harm, rather than stopping men from doing it in the first place," she said.

"Basically we're asking women to shrink themselves down, to take up less space, be less visible and not promote themselves as much, just in case."

Athletes were also regularly encouraged to report abuse, but 80 per cent did not feel safer after doing so.

Goodwin said she reported multiple abusive posts on platforms like Facebook, but was told they did not go against community standards.

"That was despite the fact the phrasing was rather threatening and homophobic."

It also regularly took weeks for her to receive a response.

"So my attitude is, 'what's reporting going to do?'"

Athletes sometimes felt harmed by their own clubs

The results of the research likewise showed that over half of those who experienced gendered online harm did not seek support for it.

Those who did overwhelmingly turned to friends and family or fellow athletes, rather than their clubs, sporting organisations or player unions.

"Some of the athletes we spoke to felt that if they raised it with their club, they were going to be seen as 'mentally fragile', as a complainer, or someone who couldn't 'hack' it," Associate professor Toffoletti said.

Alarmingly, some athletes also felt harmed by their own sporting clubs or organisations.

Respondents provided a variety of examples of this, including being excluded from group chats, misrepresented by their social media teams and lacking autonomy over what was posted about them.

Some of these posts led to body shaming, or sexist and homophobic comments about their appearance (for example being perceived as too 'masculine' or 'aggressive').

As a result, Dr McGrane said researchers came to the conclusion that gendered online harm was not just about trolling from strangers, but "a much broader range of behaviours".

"We understand that social media teams are often under-resourced, and have a lot of pressure to put out content that gets traction," she said.

"But what we'd like to see is cultural change within clubs, to explore the ways that we talk about women's sport, and the way that women athletes are expected to present and perform femininity, because those things drive change in the way that women athletes get treated online."

Culture change required to address gendered online harm

The study also made clear that diverse women experience online harm differently, including LGBTQI+ women and women of colour.

Researchers found that those sportswomen who had experienced both racist and sexist abuse, or racist and homophobic abuse, suffered greater impacts on their wellbeing.

However, they did not experience as significant an impact on their athletic performance, or economic opportunities, compared to other respondents.

"My reading of that is that for women of colour, and queer women, being denied economic opportunities, and having your sexuality and race commented on in relation to your performance is kind of par for the course," Dr McGrane said.

"The fact is, women of colour and queer women are often denied economic opportunities in the first place."

"What it's telling me is that those women are absorbing the impact of online abuse on their own," Associate professor Toffoletti added.

"They often don't feel like they have the same kinds of support, or capacity to talk about it, so they carry the burden alone."

This was compounded by the fact that sporting organisations and clubs were seen as reluctant to 'call out' gendered abuse online.

"This research shows what we've been saying was a problem; it's evidence-based now. They can't turn around and dismiss it, or women, any longer," Goodwin said.

Associate professor Toffoletti agreed, arguing that cultural change was necessary from within sport.

"Perhaps the best way we can shift cultures of online hate and hostility is for organisations not just to back their athletes when they're trolled, but to respect them through adequate remuneration, fair access to facilities, and marketing and promotion budgets that really celebrate women's sport."

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Read our research on: TikTok | Podcasts | Election 2024

Regions & Countries

8 in 10 americans say religion is losing influence in public life, few see biden or trump as especially religious.

Pew Research Center conducted this survey to explore Americans’ attitudes about religion’s role in public life, including politics in a presidential election year.

For this report, we surveyed 12,693 respondents from Feb. 13 to 25, 2024. Most of the respondents (10,642) are members of the American Trends Panel, an online survey panel recruited through national random sampling of residential addresses, which gives nearly all U.S. adults a chance of selection.

The remaining respondents (2,051) are members of three other panels, the Ipsos KnowledgePanel, the NORC Amerispeak panel and the SSRS opinion panel. All three are national survey panels recruited through random sampling (not “opt-in” polls). We used these additional panels to ensure that the survey would have enough Jewish and Muslim respondents to be able to report on their views.

The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education, religious affiliation and other categories.

For more, refer to the ATP’s Methodology and the Methodology for this report. Read the questions used in this report .

A new Pew Research Center survey finds that 80% of U.S. adults say religion’s role in American life is shrinking – a percentage that’s as high as it’s ever been in our surveys.

Most Americans who say religion’s influence is shrinking are not happy about it. Overall, 49% of U.S. adults say both that religion is losing influence and that this is a bad thing. An additional 8% of U.S. adults think religion’s influence is growing and that this is a good thing.

Together, a combined 57% of U.S adults – a clear majority – express a positive view of religion’s influence on American life.

The survey also finds that about half of U.S. adults say it’s “very” or “somewhat” important to them to have a president who has strong religious beliefs, even if those beliefs are different from their own. But relatively few Americans view either of the leading presidential candidates as very religious: 13% of Americans say they think President Joe Biden is very religious, and just 4% say this about former President Donald Trump.

Overall, there are widespread signs of unease with religion’s trajectory in American life. This dissatisfaction is not just among religious Americans. Rather, many religious and nonreligious Americans say they feel that their religious beliefs put them at odds with mainstream culture, with the people around them and with the other side of the political spectrum. For example:

• 48% of U.S. adults say there’s “a great deal” of or “some” conflict between their religious beliefs and mainstream American culture, up from 42% in 2020.
• 29% say they think of themselves as religious minorities, up from 24% in 2020.
• 41% say it’s best to avoid discussing religion at all if someone disagrees with you, up from 33% in 2019.
• 72% of religiously unaffiliated adults – those who identify, religiously, as atheist, agnostic or “nothing in particular” – say conservative Christians have gone too far in trying to control religion in the government and public schools; 63% of Christians say the same about secular liberals.

These are among the key findings of a new Pew Research Center survey, conducted Feb. 13-25, 2024, among a nationally representative sample of 12,693 U.S. adults.

This report examines:

• Religion’s role in public life
• U.S. presidential candidates and their religious engagement
• Christianity’s place in politics, and “Christian nationalism”

The survey also finds wide partisan gaps on questions about the proper role for religion in society, with Republicans more likely than Democrats to favor religious influence in governance and public life. For instance:

• 42% of Republicans and Republican-leaning independents say that when the Bible and the will of the people conflict, the Bible should have more influence on U.S. laws than the will of the people. Just 16% of Democrats and Democratic-leaning independents say this.
• 21% of Republicans and GOP leaners say the federal government should declare Christianity the official religion of the United States, compared with 7% of Democrats and Democratic leaners.

Moral and religious qualities in a president

Almost all Americans (94%) say it is “very” or “somewhat” important to have a president who personally lives a moral and ethical life. And a majority (64%) say it’s important to have a president who stands up for people with their religious beliefs.

About half of U.S. adults (48%) say it is important for the president to hold strong religious beliefs. Fewer (37%) say it’s important for the president to have the same religious beliefs as their own.

Republicans are much more likely than Democrats to value religious qualities in a president, and Christians are more likely than the religiously unaffiliated to do so. For example:

• Republicans and GOP leaners are twice as likely as Democrats and Democratic leaners to say it is important to have a president who has the same religious beliefs they do (51% vs. 25%).
• 70% of White evangelical Protestants say it is important to have a president who shares their religious beliefs. Just 11% of religiously unaffiliated Americans say this.

Views of Biden, Trump and their religious engagement

Relatively few Americans think of Biden or Trump as “very” religious. Indeed, even most Republicans don’t think Trump is very religious, and even most Democrats don’t think Biden is very religious.

• 6% of Republicans and GOP leaners say Trump is very religious, while 44% say he is “somewhat” religious. Nearly half (48%) say he is “not too” or “not at all” religious.
• 23% of Democrats and Democratic-leaning independents say Biden is very religious, while 55% say he is somewhat religious. And 21% say he is not too or not at all religious.

Though they don’t think Trump is very religious himself, most Republicans and people in religious groups that tend to favor the Republican Party do think he stands up at least to some extent for people with their religious beliefs. Two-thirds of Republicans and independents who lean toward the GOP (67%) say Trump stands up for people with their religious beliefs “a great deal,” “quite a bit” or “some.” About the same share of White evangelical Protestants (69%) say this about Trump.

Similarly, 60% of Democrats and Democratic-leaning independents, as well as 73% of Jewish Americans and 60% of Black Protestants, say Biden stands up for people with their religious beliefs a great deal, quite a bit or some.

Overall, views of both Trump and Biden are generally unfavorable.

• White evangelical Protestants – a largely Republican group – stand out as having particularly favorable views of Trump (67%) and unfavorable views of Biden (86%).
• Black Protestants and Jewish Americans – largely Democratic groups – stand out for having favorable views of Biden and unfavorable views of Trump.

Views on trying to control religious values in the government and schools

Americans are almost equally split on whether conservative Christians have gone too far in trying to push their religious values in the government and public schools, as well as on whether secular liberals have gone too far in trying to keep religious values out of these institutions.

Most religiously unaffiliated Americans (72%) and Democrats (72%) say conservative Christians have gone too far. And most Christians (63%) and Republicans (76%) say secular liberals have gone too far.

Christianity’s place in politics, and Christian nationalism

In recent years, “Christian nationalism” has received a great deal of attention as an ideology that some critics have said could threaten American democracy .

Despite growing news coverage of Christian nationalism – including reports of political leaders who seem to endorse the concept – the new survey shows that there has been no change in the share of Americans who have heard of Christian nationalism over the past year and a half. Similarly, the new survey finds no change in how favorably U.S. adults view Christian nationalism.

Overall, 45% say they have heard or read about Christian nationalism, including 25% who also have an unfavorable view of it and 5% who have a favorable view of it. Meanwhile, 54% of Americans say they haven’t heard of Christian nationalism at all.

One element often associated with Christian nationalism is the idea that church and state should not be separated, despite the Establishment Clause in the First Amendment to the U.S. Constitution.

The survey finds that about half of Americans (49%) say the Bible should have “a great deal” of or “some” influence on U.S. laws, while another half (51%) say it should have “not much” or “no influence.” And 28% of U.S. adults say the Bible should have more influence than the will of the people if the two conflict. These numbers have remained virtually unchanged over the past four years.

In the new survey, 16% of U.S. adults say the government should stop enforcing the separation of church and state. This is little changed since 2021.

In response to a separate question, 13% of U.S. adults say the federal government should declare Christianity the official religion of the U.S., and 44% say the government should not declare the country a Christian nation but should promote Christian moral values. Meanwhile, 39% say the government should not elevate Christianity in either way. 1

Overall, 3% of U.S. adults say the Bible should have more influence on U.S. laws than the will of the people; and that the government should stop enforcing separation of church and state; and that Christianity should be declared the country’s official religion. And 13% of U.S. adults endorse two of these three statements. Roughly one-fifth of the public (22%) expresses one of these three views that are often associated with Christian nationalism. The majority (62%) expresses none.

Guide to this report

The remainder of this report describes these findings in additional detail.  Chapter 1  focuses on the public’s perceptions of religion’s role in public life. Chapter 2  examines views of presidential candidates and their religious engagement. And  Chapter 3  focuses on Christian nationalism and views of the U.S. as a Christian nation.

• The share saying that the government should declare Christianity the official national religion (13%) is almost identical to the share who said the government should declare the U.S. a Christian nation in a March 2021 survey that asked a similar question (15%). ↩

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Report Materials

Table of contents, 5 facts about religion and americans’ views of donald trump, u.s. christians more likely than ‘nones’ to say situation at the border is a crisis, from businesses and banks to colleges and churches: americans’ views of u.s. institutions, most u.s. parents pass along their religion and politics to their children, growing share of americans see the supreme court as ‘friendly’ toward religion, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .

How to research the judges on your 2024 Illinois primary ballot

This cycle, there’s a democratic primary for a seat on the illinois supreme court, one of three justices elected from cook county, by mary ann ahern , shelby bremer and nbc chicago staff • published march 19, 2024 • updated on march 19, 2024 at 9:03 am.

Many of the names on the 2024 ballot for Illinois primary election this cycle are judicial candidates.

While those races may not garner as much attention as the names at the top of each ticket, experts say voters should research every candidate, because those judicial seats carry a lot of power.

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“I think the judicial elections are elections that are really rarely talked about, and we really don't understand how this system works until you're a part of this system,” said Alejandra Cancino, a senior reporter for Injustice Watch, a nonprofit newsroom that prepares a Cook County judicial evaluation guide each election cycle.

“The people you vote for are going to be in traffic court. They're going to be in a criminal courts. They're also going to handle if you are in a car accident and have a personal injury lawsuit, if you have a contested will, they're handling those types of issues,” said Jessica Durkin, who chairs the Illinois State Bar Association’s judicial evaluation committee.

“Evictions, discrimination cases and even constitutionality of different laws in Illinois. Any type of legal matter could go before a judge, and most of the judges are elected by the people of the state of Illinois," she continued. "So that's a lot of power at the ballot box to decide who is going to be judging you and your peers in the future in any type of case that they can come before the legal system.”

This election, there’s a Democratic primary for a seat on the Illinois Supreme Court, one of three justices elected from Cook County. There are no candidates from any other party, meaning whoever wins the Democratic primary will win the seat for a 10-year term.

The candidates are incumbent Justice Joy Cunningham, who was appointed to fill the vacancy of Justice Anne Burke after her retirement in 2022, and Justice Jesse Reyes, who previously ran for the state Supreme Court in 2020, coming in second in a crowded Democratic primary field of seven candidates. Both are 71-year-old John Marshall law graduates with years of experience on the Illinois Appellate Court.

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“What was interesting to me about the race is that every time that both candidates spoke, they kept coming back to the issue of race and ethnicity,” Cancino said.

Reyes is Latino and often says it’s time for a Latino to serve on Illinois’ highest court. Cunningham is a Black woman who has the Cook County Democratic Party endorsement. Cancino reported last month that Cunningham’s mother is from Panama, which gives her Latin American roots as well.

“The story was really helping the reader understand this issue of race and ethnicity, the issue of representation and why it matters as well for the Latino community, people who are really wanting to have representation at all levels of government,” Cancino said of her reporting. “On the other hand, you also have a Black community that has fought really hard for representation, and they've been holding on to seats that were really hard won by them.”

Cancino noted that state courts have risen in prominence in recent years.

“The Supreme Court is the highest court in the state and that means that if there's any questions over a state law or the state constitution, the Supreme Court is really the one deciding what is the final answer on those legal questions,” she said. “Part of the reason why they're in the news is because there are big questions right now for voters, right, questions over about abortion rights, questions over gun rights, and the state courts are really the ones deciding those issues.”

But the Supreme Court’s reach extends far beyond that as well.

“Not only do they hear cases, they're in charge of the whole administration of the judicial system in Illinois,” Durkin said. “They set the court rules, so how the courts function, how they're run, and then they also have a power if a judge does not finish their elected term, the Supreme Court can appoint someone in their place to finish out the elected term until the next election.”

“So the Supreme Court really can help shape the judiciary for the whole state, not just make decisions on cases before them. They really are in control of the whole system from top to bottom,” she added.

The Illinois State Bar Association interviews and evaluates judicial candidates each election cycle to share their nonpartisan recommendations with voters.  

“We want to make sure people have the information before they're going into the ballot box, so they're able to determine if the different candidates are going to be fair, if they're going to be punctual and diligent and really, most importantly, what their legal expertises are and what their acumen is and if they can handle being in a courtroom,” Durkin said.

The Illinois State Bar Assocation rated both Reyes and Cunningham as highly qualified.

But it’s not just the Supreme Court – experts say you should check every judicial candidate on your ballot because they rule on so many legal matters.

“You need to think about all the power that's held in the judiciary, and the check and balance the judiciary has on the power that's held by the executive and legislative branch,” Durkin said.

“If you end up in a situation where you're going to have to go before a judge, right, like what kind of judge do you want to be there sitting in front of you?” Cancino asked.

You can find the Illinois State Bar Association's evaluations here , and Injustice Watch’s guide here .  

How Illinois State Bar Association evaluations work

The evaluations rank judicial candidates on a scale of “not qualified” to “highly qualified.”

The candidates are also evaluated by ISBA Judicial Evaluations Committee (JEC) members based on “detailed information supplied by candidates, a background check by trained lawyers/investigators and interviews of each candidate,” according to the  evaluation .

The rankings reflect the committee’s opinion of whether candidates have the necessary qualifications for judicial service, not a reflection of the candidates’ abilities as lawyers or judges, according to the ISBA.

Candidates who did not participate in the evaluation process were marked as “not recommended.”

Why does voting for a judge matter?

Judges are elected to judge and rule over cases in specific districts or circuits, not over the entire state. Judges are voted on during the primary election, along with the 2024 presidential candidates and Illinois state representative candidates.

Voting for judges allows voters to help guide who is ruling in cases and what consequences for crimes could look like.

The judges at the different levels of the court system are based on where you live, so the person you choose will be determining the criminal justice system outcomes in your residential area.

Vacancies and rankings per candidate

There are 45 judicial races on the ballot for the 2024 primary election.

For this election cycle, judges will be voted on to fill:

• One full term on the Illinois Supreme Court
• Four positions on the Illinois Appellate Court
• 11 countywide circuit court seats
• 29 subcircuit court seats

Out of 69 candidates, the ISBA ranked:

• 13 candidates as “highly qualified”
• 42 candidates are ranked as “qualified”
• Nine candidates are listed as “not qualified”
• Five candidates did not participate in the evaluation and were ranked as “not recommended”

Where can I go to see the rankings on each candidate?

The ISBA uploads their candidate qualification rankings on their  website  every election cycle.

For a more in-depth analysis of just Cook County,  Injustice Watch  has compiled information on each candidate, including their backgrounds, any controversies, ratings, fundraising and more.

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