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Understanding Clinical Trials

Clinical research: what is it.

Your doctor may have said that you are eligible for a clinical trial, or you may have seen an ad for a clinical research study. What is clinical research, and is it right for you?

Clinical research is the comprehensive study of the safety and effectiveness of the most promising advances in patient care. Clinical research is different than laboratory research. It involves people who volunteer to help us better understand medicine and health. Lab research generally does not involve people — although it helps us learn which new ideas may help people.

Every drug, device, tool, diagnostic test, technique and technology used in medicine today was once tested in volunteers who took part in clinical research studies.

At Johns Hopkins Medicine, we believe that clinical research is key to improve care for people in our community and around the world. Once you understand more about clinical research, you may appreciate why it’s important to participate — for yourself and the community.

What Are the Types of Clinical Research?

There are two main kinds of clinical research:

Observational Studies

Observational studies are studies that aim to identify and analyze patterns in medical data or in biological samples, such as tissue or blood provided by study participants.

Clinical Trials

Clinical trials, which are also called interventional studies, test the safety and effectiveness of medical interventions — such as medications, procedures and tools — in living people.

Clinical research studies need people of every age, health status, race, gender, ethnicity and cultural background to participate. This will increase the chances that scientists and clinicians will develop treatments and procedures that are likely to be safe and work well in all people. Potential volunteers are carefully screened to ensure that they meet all of the requirements for any study before they begin. Most of the reasons people are not included in studies is because of concerns about safety.

Both healthy people and those with diagnosed medical conditions can take part in clinical research. Participation is always completely voluntary, and participants can leave a study at any time for any reason.

“The only way medical advancements can be made is if people volunteer to participate in clinical research. The research participant is just as necessary as the researcher in this partnership to advance health care.” Liz Martinez, Johns Hopkins Medicine Research Participant Advocate

Types of Research Studies

Within the two main kinds of clinical research, there are many types of studies. They vary based on the study goals, participants and other factors.

Biospecimen studies

Healthy volunteer studies.

Clinical trials study the safety and effectiveness of interventions and procedures on people’s health. Interventions may include medications, radiation, foods or behaviors, such as exercise. Usually, the treatments in clinical trials are studied in a laboratory and sometimes in animals before they are studied in humans. The goal of clinical trials is to find new and better ways of preventing, diagnosing and treating disease. They are used to test:

Drugs or medicines

New types of surgery

Medical devices

New ways of using current treatments

New ways of changing health behaviors

New ways to improve quality of life for sick patients

 Goals of Clinical Trials

Because every clinical trial is designed to answer one or more medical questions, different trials have different goals. Those goals include:

Treatment trials

Prevention trials, screening trials, phases of a clinical trial.

In general, a new drug needs to go through a series of four types of clinical trials. This helps researchers show that the medication is safe and effective. As a study moves through each phase, researchers learn more about a medication, including its risks and benefits.

Is the medication safe and what is the right dose?   Phase one trials involve small numbers of participants, often normal volunteers.

Does the new medication work and what are the side effects?   Phase two trials test the treatment or procedure on a larger number of participants. These participants usually have the condition or disease that the treatment is intended to remedy.

Is the new medication more effective than existing treatments?  Phase three trials have even more people enrolled. Some may get a placebo (a substance that has no medical effect) or an already approved treatment, so that the new medication can be compared to that treatment.

Is the new medication effective and safe over the long term?   Phase four happens after the treatment or procedure has been approved. Information about patients who are receiving the treatment is gathered and studied to see if any new information is seen when given to a large number of patients.

“Johns Hopkins has a comprehensive system overseeing research that is audited by the FDA and the Association for Accreditation of Human Research Protection Programs to make certain all research participants voluntarily agreed to join a study and their safety was maximized.” Gail Daumit, M.D., M.H.S., Vice Dean for Clinical Investigation, Johns Hopkins University School of Medicine

Is It Safe to Participate in Clinical Research?

There are several steps in place to protect volunteers who take part in clinical research studies. Clinical Research is regulated by the federal government. In addition, the institutional review board (IRB) and Human Subjects Research Protection Program at each study location have many safeguards built in to each study to protect the safety and privacy of participants.

Clinical researchers are required by law to follow the safety rules outlined by each study's protocol. A protocol is a detailed plan of what researchers will do in during the study.

In the U.S., every study site's IRB — which is made up of both medical experts and members of the general public — must approve all clinical research. IRB members also review plans for all clinical studies. And, they make sure that research participants are protected from as much risk as possible.

Earning Your Trust

This was not always the case. Many people of color are wary of joining clinical research because of previous poor treatment of underrepresented minorities throughout the U.S. This includes medical research performed on enslaved people without their consent, or not giving treatment to Black men who participated in the Tuskegee Study of Untreated Syphilis in the Negro Male. Since the 1970s, numerous regulations have been in place to protect the rights of study participants.

Many clinical research studies are also supervised by a data and safety monitoring committee. This is a group made up of experts in the area being studied. These biomedical professionals regularly monitor clinical studies as they progress. If they discover or suspect any problems with a study, they immediately stop the trial. In addition, Johns Hopkins Medicine’s Research Participant Advocacy Group focuses on improving the experience of people who participate in clinical research.

Clinical research participants with concerns about anything related to the study they are taking part in should contact Johns Hopkins Medicine’s IRB or our Research Participant Advocacy Group .

Learn More About Clinical Research at Johns Hopkins Medicine

For information about clinical trial opportunities at Johns Hopkins Medicine, visit our trials site.

Video Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

Clinical Research for a Healthier Tomorrow: A Family Shares Their Story

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Understanding Medical Research

Related issues, see, play and learn, videos and tutorials, statistics and research.

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It seems to happen almost every day - you hear about the results of a new medical research study. Sometimes the results of one study seem to disagree with the results of another study.

It's important to be critical when reading or listening to reports of new medical findings. Some questions that can help you evaluate health information include:

• Was the study in animals or people?
• Does the study include people like you?
• How big was the study?
• Was it a randomized controlled clinical trial ?
• Where was the research done?
• If a new treatment was being tested, were there side effects?
• Who paid for the research?
• Who is reporting the results?

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Journal Articles References and abstracts from MEDLINE/PubMed (National Library of Medicine)

• Article: Considering Sex as a Variable at a Research University: Knowledge, Attitudes,...
• Article: Different domains of dengue research in the Philippines: A systematic review...
• Article: The impact of a digital platform on migraine patient-centered outcome research....
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The information on this site should not be used as a substitute for professional medical care or advice. Contact a health care provider if you have questions about your health.

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Different sections are needed in different types of scientific papers (lab reports, literature reviews, systematic reviews, methods papers, research papers, etc.). Projects that overlap with the social sciences or humanities may have different requirements. Generally, however, you'll need to include:

INTRODUCTION (Background)

METHODS SECTION (Materials and Methods)

What is a title?

Titles have two functions: to identify the main topic or the message of the paper and to attract readers.

The title will be read by many people. Only a few will read the entire paper, therefore all words in the title should be chosen with care. Too short a title is not helpful to the potential reader. Too long a title can sometimes be even less meaningful. Remember a title is not an abstract. Neither is a title a sentence.

What makes a good title?

A good title is accurate, complete, and specific. Imagine searching for your paper in PubMed. What words would you use?

• Use the fewest possible words that describe the contents of the paper.
• Avoid waste words like "Studies on", or "Investigations on".
• Use specific terms rather than general.
• Use the same key terms in the title as the paper.
• Watch your word order and syntax.
• Avoid abbreviations, jargon, and special characters.

The abstract is a miniature version of your paper. It should present the main story and a few essential details of the paper for readers who only look at the abstract and should serve as a clear preview for readers who read your whole paper. They are usually short (250 words or less).

The goal is to communicate:

•  What was done?
•  Why was it done?
•  How was it done?
•  What was found?

A good abstract is specific and selective. Try summarizing each of the sections of your paper in a sentence two. Do the abstract last, so you know exactly what you want to write.

• Use 1 or more well developed paragraphs.
• Use introduction/body/conclusion structure.
• Present purpose, results, conclusions and recommendations in that order.
• Make it understandable to a wide audience.

What is an introduction?

The introduction tells the reader why you are writing your paper (ie, identifies a gap in the literature) and supplies sufficient background information that the reader can understand and evaluate your project without referring to previous publications on the topic.

The nature and scope of the problem investigated.

The pertinent literature already written on the subject.

The method of the investigation.

The hypothesized results of the project.

What makes a good introduction?

A good introduction is not the same as an abstract. Where the abstract summarizes your paper, the introduction justifies your project and lets readers know what to expect.

• Keep it brief. You conducted an extensive literature review, so that you can give readers just the relevant information. • Cite your sources using in-text citations. • Use the present tense. Keep using the present tense for the whole paper. • Use the same information that you use in the rest of your paper.

What is a methods section?

Generally a methods section tells the reader how you conducted your project. 

It is also called "Materials and Methods".

The goal is to make your project reproducible.

What makes a good methods section?

A good methods section gives enough detail that another scientist could reproduce or replicate your results.

• Use very specific language, similar to a recipe in a cookbook. • If something is not standard (equipment, method, chemical compound, statistical analysis), then describe it. • Use the past tense. • Subheadings should follow guidelines of a style (APA, Vancouver, etc.) or journal (journals will specify these in their "for authors" section). For medical education writing, refer to the AMA Manual of Style .

  What is a results section?

The results objectively present the data or information that you gathered through your project. The narrative that you write here will point readers to your figures and tables that present your relevant data.

Keep in mind that you may be able to include more of your data in an online journal supplement or research data repository.

What makes a good results section?

A good results section is not the same as the discussion. Present the facts in the results, saving the interpretation for the discussion section. The results section should be written in past tense.

• Make figures and tables clearly labelled and easy to read. If you include a figure or table, explain it in the results section. • Present representative data rather than endlessly repetitive data . • Discuss variables only if they had an effect (positive or negative) • Use meaningful statistics . • Describe statistical analyses you ran on the data.

What is a discussion section?

The discussion section is the answer to the question(s) you posed in the introduction section. It is where you interpret your results. You have a lot of flexibility in this section. In addition to your main findings or conclusions, consider:

• Limitations and strengths of your project. • Directions for future research.

What makes a good  discussion section?

A good discussion section should read very differently than the results section. The discussion is where you interpret the project as a whole.

• Present principles, relationships and generalizations shown by the results. • Discuss the significance or importance of the results. • Discuss the theoretical implications of your work as well as practical applications • Show how your results agree or disagree with previously published works.

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Structure of Scholarly Articles and Peer Review: Structure of a Biomedical Research Article

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Title, Authors, Sources of Support and Acknowledgments

Structured abstract, introduction, results and discussion, international committee of medical journal editors (icmje).

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Medical research articles tend to be structured in similar ways. This standard structure helps assure that research is reported with the information readers need to critically appraise the research process and results.

This guide to the structure of a biomedical research article was informed by the description of standard manuscript sections found in the International Committee of Medical Journal Editors (ICMJE) Recommendations chapter on Manuscript Preparation: Preparing for Submission .

If you are writing an article for submisson to a particular journal be sure to obtain that journal's instructions for authors for specific guidelines.

Example Article: Lyons EJ, Tate DF, Ward DS, Wang X. Energy intake and expenditure during sedentary screen time and motion-controlled video gaming. Am J Clin Nutr. 2012 Aug;96(2):234-9. doi: 10.3945/ajcn.111.028423. Epub 2012 Jul 3. PubMed PMID: 22760571; PubMed Central PMCID: PMC3396440. (Free full text available)

Article title:  Should provide a succinct description of the purpose of the article using words that will help it be accurately retrieved by search engines. 

Author information:  Includes the author names and the institution(s) where each author was affiliated at the time the research was conducted. Full contact information is provided for the corresponding author. 

Source(s) of support: Specific information about grant funding or source of equipment, drugs, etc. obtained to support the research. 

Acknowledgments:  This section may found at the end of the article and is used to name people who contributed to the paper, but not fully enough to be named as an author. It may also include more information about the authors' specific roles.

The structure of quantitative research articles is derived from the scientifc process and includes sections covering introduction, methods, results, and discussion (IMRaD). The actual labels for the various parts may vary between journals.

Abstract:  A structured abstract reports a summary of each of the IMRaD sections. Enough information should be included to provide the purpose of the research; an outline of methods used; results with data; and conclusions that highlight the findings. 

The introduction provides background information about what is known from previous related research, citing the relevant studies, and points out the gap in previous research that is being addressed by the new study. Often, many of the references cited in a paper are in the introduction. The purpose of the research should be clearly stated in this section.

The sample paper's introduction links television watching to increased energy intake and obesity, notes that several studies have shown a similar link with video gaming, and states no study was identified that compared television and video gaming. Eighteen of the thirty-one references used in the paper are cited in the introduction. The final paragraph of the introduction has two sentences that clearly state the purpose and the hypothesized expected outcome of the study.

The methods section clearly explains how the study was conducted. The ICMJE recommends that this section include information about how participants were selected, detailed demographics about who the participants were, and explanations of why any particular populations were included or excluded from the study. The details of how the study was conducted should be described with enough detail that the study could be replicated. Selected statistical methods should be reported in enough detail that readers can evaluate their appropriateness to the data being gathered.

The sample paper’s methods section includes subsections covering:  recruitment; procedures used for each study subgroup (TV, VG, motion-controlled VG); what snacks and beverages were used and how they were made available; how energy intake and energy expenditure were measured; how the data was analyzed and the specific statistical analysis and secondary analysis that was used.

The results section reports the data gathered and the statistical analysis of the data. Tables and / or graphs are often used to clearly and compactly present the data.

The results section of the sample paper  has two subsections and two tables. One subsection and related table shows the analysis of participant characteristics, The other subsection and table covers the analysis of energy intake, expenditure, and surplus.

In order to critically appraise the quality of the study you need to be able to understand the statistical analysis of the data. Two articles that help with this task are:

• Greenhalgh Trisha.  How to read a paper: Statistics for the non-statistician. I: Different types of data need different statistical tests  BMJ 1997; 315:364
• Greenhalgh Trisha.  How to read a paper: Statistics for the non-statistician. II: “Significant” relations and their pitfalls  BMJ 1997; 315:422

Another aid to critically reading a paper is to see if it has been included and evaluated in a systematic review. Try searching for the article you are reading in Google Scholar and seeing if the cited references include a systematic review. The sample paper was critically reviewed in:

• Marsh S, Ni Mhurchu C, Maddison R. The non-advertising effects of screen-based sedentary activities on acute eating behaviours in children, adolescents, and young adults. A systematic review. Appetite. 2013 Dec;71:259-73. doi: 10.1016/j.appet.2013.08.017. Epub 2013 Aug 31. PubMed Abstract . Full-text for UNC-CH .

The  discussion section  clearly states the primary findings of the study, poses explanations for the findings and any conclusions that can be drawn from them. It may also include the author’s assessment of limitations in the research as conducted and suggestions for further research that is needed.

The structure of biomedical research articles has been standardized across different journals at least in part due to the work of the International Committee of Medical Journal Editors. This group first published the  Uniform Requirements for Manuscripts Submitted to Biomedical Journals  in 1978.

The  Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly work in Medical Journals  (2013) is the most recent update of ICMJE's work. 

• Next: Compare Types of Journals >>
• Last Updated: May 14, 2024 12:50 PM
• URL: https://guides.lib.unc.edu/scholarly-articles

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Elements of medical research

Affiliation.

• 1 Division of Biostatistics & Medical Informatics, University College of Medical Sciences, Delhi, India. [email protected]
• PMID: 15115159

Most medical research is empirical based on evidence rather than hunches or preferences. It follows a series of specific steps. There are no short cuts. Collection of evidence and its analysis should follow a carefully drawn protocol. Most of the modern medical research requires biostatistical tools to reach to a valid and reliable conclusion. Researcher must have an adequate knowledge and skill to be really effective. The endeavours should be consistent with the accepted medical and research ethics. Medical research can provide immense satisfaction when conducted on scientific lines, and can be occasionally frustrating when years of efforts fail to produce expected results. This article focuses on aspects that can increase the credibility of research. It is addressed to all interested in medical research, and seeking answers to questions such as what actually is research, what are its types, what specific steps should be followed, what a research protocol should contain, and what makes research credible etc.

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Why all doctors should be involved in research

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• Hannah Jacob , academic clinical fellow
• 1 UCL Institute of Child Health, London WC1N 1EH
• hcjacob{at}gmail.com

Neena Modi tells Hannah Jacob about her career in research and why this is a fundamental part of every doctor’s job

Neena Modi is president of the Royal College of Paediatrics and Child Health and professor of neonatal medicine at Imperial College, London. She is a practising clinician and academic lead of a neonatal research programme focusing on nutritional and other perinatal determinants of lifelong metabolic health. After a period as vice president for science and research at the college, she was elected president in April 2015.

How did you become interested in research?

I realised that what I was being taught during my training was wrong, and my very enlightened consultant challenged me to design a trial to back my contention. There were no training posts in neonatal medicine when I started my paediatric training, but there were lots of opportunities to learn and undertake research because the rate of change was so great. That was really exciting.

Which research projects are you most proud of? Which do you think has had the biggest impact?

We did a series of studies to develop methods for measuring body water compartments in extremely preterm babies and to describe the postnatal alterations in fluid balance. We also tested the hypothesis that immediate sodium supplementation in babies with respiratory distress syndrome was harmful. That was a big achievement.

Most recently we have identified possible biological mechanisms that underpin the epidemiological associations between early onset of features of the metabolic syndrome and being born extremely preterm. That is of real interest as we learn more about the long term effects of extremely preterm birth.

How have you coped with the inevitable setbacks of a career in clinical research?

Real life is about being refused things and carrying on anyway, so I have developed resilience. There was no academic training route when I started out, so I have had to forge my own way. People will always tell you that it cannot be done. You have to pursue the things you are passionate about.

Do you have any advice for junior doctors interested in doing research?

Work out what interests you, and then find the person who is going to help you do it. Being approached by an enthusiastic junior doctor is always well received, and once you have found the right senior person they can support you in achieving your goals. Do not lose heart if you don’t get an academic training post as they are not the only way into research. Some of the best research students I have worked with have not come through the standard path.

What would you say to doctors who have no interest in doing research?

I would argue that they may not be thinking broadly enough about what research actually is. Every clinician is responsible for evaluating their own practice, and to do that in a robust and meaningful way you need to use the tools of research. We all need to be able to critically review research done by others. For example, the guidelines used in everyday clinical practice are based on meta-analyses and systematic reviews. So I think all doctors need to be involved in research in some way, and that may be different for different people.

How can undertaking research help doctors in their careers?

It’s not just a help, it’s essential. There are few absolutes in science, and without inquiring minds medicine will stand still. Participation in research enables doctors to evaluate their practice objectively and to be involved in advancing their discipline. You can learn so many skills that make you a better clinician around appraising the evidence and thinking critically about a situation.

What are the benefits and downsides of doing research—both on a personal and professional level?

The benefits come from knowing you are contributing to the science of medicine as well as the art, and are able to question, evaluate, and test different approaches objectively. Everyone has a role in supporting research—many will contribute, and some will be research leaders.

As for downsides, life has ups and downs, and research is no different. You have to not be too disheartened when a grant application gets rejected. When you want to achieve something, you have to keep speaking to the powers that be until you find someone who can be an advocate.

How do you juggle the research, clinical, and leadership aspects of your working life?

It is a balance that is evolving all the time and that provides me with a huge stimulus. Every time I have been presented with an opportunity I have had to evaluate its potential effect on the other components of my work. I always say yes to the things that interest me and follow my muse. We are very privileged as doctors to have such a range of tremendous opportunities available to us.

Do you have a particular philosophy that has guided you in your career?

When life offers you an opportunity, do not turn it down. I believe you must do what grabs your interest, and if you are still doing it years later you know you made the right decision. When you lose the excitement, it is time for a change. The future lies with junior doctors, and you can be a part of shaping it in the way you think is right.

Is there anything you would do differently if you had your career again?

I would have much greater confidence to fight for something I believed in.

Competing interests: I have read and understood BMJ policy on declaration of interests and declare that I am the academic officer for the Paediatric Educators Special Interest Group of the Royal College of Paediatrics and Child Health.

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Why Is Medical Research Important?

Medical research has become an important part of the health care industry, and advances in technology have made it possible for much of it to be done on an outpatient basis, meaning that investigators sometimes don’t need to do extensive studies in a research facility. The field of medical research is one of the most interesting fields in all of science because of its focus on science and medicine in conjunction with a great deal of research.

Medical research covers a wide variety of studies, stretching from ‘baseline’ investigation, through systematic reviews and to the cutting-edge of medical science. It involves the study of all human diseases or may have only disease-specific research. For example, AIDS research includes both studying patients who have AIDS and those who do not, as well as studying children with AIDS and children without AIDS. Similarly, researchers may be investigating the causes of Parkinson’s disease in old age and Parkinson’s disease in young adulthood.

4 Phases of Medical Research Studies

The four phases of Medical Research Studies are experimental, comparative/expository, understudy, and last, analysis and validation/regression.

• Comparative/expository medical research compares experimental and comparative samples from which the study population is developed; compare post hoc comparisons with the initial data; evaluates associations among variables measured.  
• Understudy studies consist of data from observational studies and random chance sampling.
• Experimental refers to clinical trials that are done specifically to test a new medical product, device, or technique.  
• Finally, validation/ regression Research studies compare new designs or drugs to earlier designs and evaluate their effect on any association found.

There are many reasons why medical research is so valuable. Whether you aim to start a career in this field or to gain more knowledge about health conditions and their treatments, it’s important to understand the benefits that medical research provides. You can learn about medical research at http://hrmdresearch.com/ .

The Importance Of Medical Research

The breakthroughs that people enjoy today are virtually unimaginable without the knowledge gained through medical research. Here are some of the most important reasons medical research is important:

• Generate Valuable Insights

Medical research helps people learn more about themselves and their health. The knowledge gained by medical research is constantly improving.

• With new scientific information coming from medical studies, people will be able to take care of their health and well-being more effectively.
• It also seeks to understand the reasons for diseases, to discover new methods of preventing or controlling diseases, and to develop treatments for these diseases and their effects.

2. Development Of New Drugs

Medical research must be done to find a cure for diseases and illnesses. Without medical research, medicine and other medical innovations as we know it could not exist. Sometimes called pharmaceutical research, medical research encompasses a broad spectrum of scientific studies. It starts with the research and development of drugs, followed by treatments and procedures used in clinical practice.  

The process of new drug development may involve the following steps:

• It can be done in several different ways, including doing laboratory experiments in bioresources such as blood and cells, or cell culture, to studying the effects of chronic exposure to toxins, drugs, hormones, and other compounds in the environment.  
• Other research is directed toward understanding disease mechanisms, to find better ways of treating or preventing disease, and how disease progression is influenced by environmental factors.  

3. Improve The Quality Of Life

Medical researchers don’t just look for ways to manage the symptoms of diseases, they try their best to find a cure for a specific illness or a group of diseases. There are several ways drug research and testing improve the quality of life:

• Medical studies that aid in the development and administration of vaccines allow people to live without worrying about deadly diseases. An example will be the ongoing development and clinical trials for the COVID-19 vaccine which may help the world go back to normal.
• Some people can live with their conditions for years by understanding how to manage them properly. As time goes by, everyone is also learning how to prevent certain illnesses from occurring and even eliminate them.

Why is medical research so important? Medical research saves lives every day. Scientists and researchers work day and night to develop new treatments, drugs, and procedures. Without the help of dedicated scientists, doctors, and other medical professionals, the advances made would be slow and limited.  

When a patient participates in a trial, they must undergo several physical tests and provide some information about their lifestyle and diet. The findings and insights derived from these studies and trials are invaluable in coming up with treatments and cures for various health conditions.

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Be sceptical: The reasons why most healthcare research may be wrong

Posted on 12th May 2017 by Saul Crandon

Could it be that most healthcare research may be wrong? In this blog, Saul explores multiple, fundamental issues affecting research before discussing possible solutions to these issues….

As advancements in medicine become ever more sophisticated, our care of patients continues to improve. A reliable and solid evidence base enables the continuation of this progression. As a result, research is the very backbone of our clinical practice. This is confusing when we think about medical research as a whole and propose that, most of this research could be wrong…

Why most healthcare research may be wrong: The problems

Contradiction.

There are a number of reasons why much of the medical literature out there may be misleading. Firstly, it’s important to look at the vast contradiction of findings that exist. It seems like every other day we see an article in the news saying things like ‘ Tomatoes reduce cancer risk! ’ or ‘ Tomatoes increase cancer risk! ’ or ‘ Chocolate causes weight loss! ’ All of this confusion is disconcerting for both clinicians and patients. Researchers recognised this issue and carried out a large scale meta-analysis to assess the claims about an array of foods and their association with cancer risk  (1) . It found that many foods are claimed to increase or decrease the risk of cancer, however these are based on small studies and once tested via meta-analysis, these effects decrease significantly.

Illusion of high impact factors

The current hierarchy of publication outlets based on impact factor has been seen as a good way of sorting the good from the bad. Nevertheless, just because a study is published within a journal with a high impact factor, this shouldn’t automatically imply the study is perfect. For example, Cummings et al. highlighted the issue of error bars within experimental biology  (2) . Error bars can display things such as standard deviations, standard error of the mean, confidence intervals and more. It is therefore crucial they are labelled appropriately. In a particular issue of Nature , a well-respected, high-impact journal, it was found that seven items had error bars that were simply unlabelled  (3) . This is worrying given the importance of accurately understanding original research. This potentially misleading or careless error can often make readers question which other areas of that research might also be inaccurate.

Reproducibility crisis

The results of a 2015 reproducibility project titled “Estimating the reproducibility of psychological science” aimed to replicate 100 studies published in 3 psychology journals  (4) . Of the original 100 studies, 97% displayed a p -value of less than 0.05. In the repeat studies, only 36% found a p- value of less than 0.05. As p- values are arbitrarily set, the study also looked at the effect sizes and still concluded that less than half of the study results were adequately replicated. These findings don’t necessarily mean the original studies were wrong; the repeats could be false, or they both could be incorrect. What can be established is that there was great difficulty in replicating the original work. Research is always on the fringe of scientific knowledge and researchers try their best to control for various factors, but the process of new discovery is a challenging one.

Another catalyst to the issue of reproducibility is the lack of incentives to perform repeat studies. A strong pressure not to perform these types of studies exists, with many journals only publishing original work. Even if a journal accepts repeat studies, they are less likely to publish these ‘boring’ studies. The attitude of ‘we already know this’ or ‘this won’t attract excitement and readership’ still looms.

Translation of findings: bench-to-bedside

A 2003 review of ‘promising’ basic scientific discoveries assessed their translation from clinical research to clinical use  (5) . Over 20 years, only 27 of the 101 studies resulted in a clinical trial, whilst only 5 were licensed for clinical use. Of these, only 1 had widespread use throughout medical practice. This equates to a <1% translation rate for these ‘pivotal’ discoveries. This emphasises the problem of research being labelled incorrectly and the exaggeration of ‘promising’ findings.

Medical reversal

Medical reversal is the process whereby a methodologically improved randomised controlled trial (RCT) contradicts the standard practice of that time  (6) . For example, the COURAGE trial contradicted the routine stenting of stable coronary disease. A 2013 review identified that medical reversal is common across all aspects of medical research  (7) . The concept of reversal is dangerous given that patients may be unwillingly harmed using the previous treatment options, new trials can cause conflicts between practitioners that swear by traditional methods, and lastly, patients may lose faith with the medical system. It also raises the important question of ‘which practices that we use today will later be proven ineffective or harmful?’

Systematic bias is defined as an inherent problem in the study design that reduces that study’s internal validity. Examples include selection bias, attrition bias, response bias and many more. The definitions of these concepts are beyond the scope of this article, but useful information about these can be found on the Students 4 Best Evidence (S4BE) website. Sometimes, bias is unavoidable, such as in the cases of rare diseases (small samples) or during RCTs of certain surgical interventions (given an inability to fully blind surgeons or patients).

Publication bias is also an important issue when assessing the evidence base as a whole, such as in systematic reviews and meta-analyses. This is the type of bias whereby positive research (where a significant difference is observed) is more likely to be published compared to negative studies (where no significant difference is observed). Journals have a preference for positive studies to increase interest and readership of their articles. The underrepresentation of negative results makes it difficult to assess the counter arguments to various interventions. For example, there could be 10 robust RCTs that contradict the use of intervention X but 1 positive RCT. The positive RCT gets published whereas the 10 ‘uninteresting’ negative RCTs do not get published, and hence intervention X is adopted.

Statistical issues

Clinical research is founded upon probabilistic statistics. It is impossible to say with 100% certainty that a treatment works, so instead, we rely on strong statistical chance. As the widely accepted p- value of statistical significance is arbitrarily set at 0.05 (or 5%), this can lead to false positives (or a type 1 error). This still seems fairly high and many results could be due to chance, especially when multiple endpoints are assessed. The use of many endpoints or manipulating the data until the results drop below the golden 0.05, is known as data-dredging or p-hacking. This practice is frowned upon and should not be the basis of high quality evidence.

Conflicts of interest and unethical practice

A successful research career is deemed by seniority, obtained through publishing high volumes in high impact journals with shocking ‘new’ results. This can shift the emphasis away from the quality of research produced.

Secondly, pharmaceutical and medical device companies often sponsor studies about their products. The problem is, these companies have an interest in their profit margins, and consequently they require studies to support the products they are trying to sell. Occasionally, companies have been known to hire ghost writers so that the studies produced appear to be independent. The business of pharmaceuticals and medical devices is a massive, billion pound industry. An unfathomable quantity of money rides on these few studies and so the researchers have to ‘make-it-work’! This is usually achieved through producing the bare minimum, with lots of exclusion criteria to create a bigger effect in small, non-generalizable sample. Moreover, negative results about the products are unlikely to see the light of day for doctors and certainly not the public. This is often a double-edged sword, as without these companies and their investments and technology, modern medicine would not be able to take the steps forward that it has over the past century…

Additionally, a topic that is often not discussed regarding medical research is fraud. It does exist and some unethical practices are out there. This involves actions such as falsifying data, conducting research without informed consent of the participants, un-blinding themselves to treatment allocations and much more. This is clearly detrimental to the pursuit of truth and reliable clinical evidence in exchange for personal gain.

Cumulative effect

The problems discussed above may be small when assessing individual papers. It may be that many of the points raised are simply irrelevant to certain areas of research. However, when these problems are taken collectively and applied across the entirety of clinical research, it’s easy to see how much of the literature may produce false conclusions.

Improvements

Studies with negative results.

Negative studies and replication studies should be published more. An important step towards this ideal was the creation of the ‘Journal of Negative Results in Biomedicine’ (JNRBM) in 2002 8 . There is an increasing trend of journals committed to publishing negative results, which is fantastic for reducing publication bias. It is hoped these measures will help to produce an evidence base that is more representative of the science conducted.

Incentives for replication studies

Following on from the idea of publishing more negative studies, the same should be done for replication studies. This could be in the form of a dedicated journal or a new policy for existing journals to accept a certain quota of repeat studies. This will enable interventions to have a higher volume of evidence to support their use and improve the reliability of their findings. In turn, this will also improve the robustness and completeness of systematic reviews and meta-analyses.

Incentives for researchers

Academic success should be assessed on the quality of an individual’s research as opposed to the volume produced or the location where it was published. This will incentivise researchers to produce high quality, tangible evidence which is in the best interest for clinicians and patients alike.

Prospective registration

All studies should be prospectively registered with a reputable body, requiring approval. Just like systematic reviews and randomised controlled trials, all studies should be registered before the commencement of the work. This is useful to prevent researchers from deviating from their original methods, as well as p-hacking and other practices. In addition, if the study produces negative results, the study may not be written up for publication. This process can highlight these negative results and encourage their dissemination in outlets such as the JNRBM. This should go hand in hand with post-publication review, allowing other researchers to review papers and flaws that may be missed in peer review.

Improved education

Research skills are often not taught comprehensively in medical schools. Medical schools and postgraduate training programs should focus more heavily on improving research literacy to minimise common errors seen in clinical studies and improve the overall competence amongst all practitioners.

Retraction watch

Retraction watch is a blog that was created to feature important study retractions. It was founded on the principle that science should be self-correcting, eliminating mistakes that take us away from the real answers to health-related questions. It does a great job in increasing the publicity of retractions, which are typically not heard of and hence, practice can be altered in light of these retractions. The website also raises awareness of the issues discussed in this article as well as holding journals to high standards which should, in theory, improve the objectiveness of scientific publications across the board.

With the continual, rapid advancement of medical research and the importance placed upon evidence-based medicine, it is crucial now more than ever, that we remain sceptical of what we read.

• Schoenfeld JD, Ioannidis JP. Is everything we eat associated with cancer? A systematic cookbook review. The American journal of clinical nutrition. 2013;97(1):127-34.
• Cumming G, Fidler F, Vaux DL. Error bars in experimental biology . The Journal of Cell Biology. 2007;177(1):7-11.
• Vaux DL. Error message. Nature. 2004;428(6985):799-.
• Open Science Collaboration. Estimating the reproducibility of psychological science. Science. 2015;349(6251).
• Contopoulos-Ioannidis DG, Ntzani E, Ioannidis JP. Translation of highly promising basic science research into clinical applications. The American journal of medicine. 2003;114(6):477-84.
• Prasad V, Cifu A. Medical Reversal: Why We Must Raise the Bar Before Adopting New Technologies . The Yale Journal of Biology and Medicine. 2011;84(4):471-8.
• Prasad V, Vandross A, Toomey C, Cheung M, Rho J, Quinn S, et al. A decade of reversal: an analysis of 146 contradicted medical practices. Mayo Clinic proceedings. 2013;88(8):790-8.
• Journal of Negative Results in BioMedicine. About; Aims and Scope [01/05/2017]. Available from: https://jnrbm.biomedcentral.com/about .

Saul Crandon

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Human Subjects Office

Medical terms in lay language.

Please use these descriptions in place of medical jargon in consent documents, recruitment materials and other study documents. Note: These terms are not the only acceptable plain language alternatives for these vocabulary words.

This glossary of terms is derived from a list copyrighted by the University of Kentucky, Office of Research Integrity (1990).

For clinical research-specific definitions, see also the Clinical Research Glossary developed by the Multi-Regional Clinical Trials (MRCT) Center of Brigham and Women’s Hospital and Harvard  and the Clinical Data Interchange Standards Consortium (CDISC) .

Alternative Lay Language for Medical Terms for use in Informed Consent Documents

A   B   C   D   E   F   G   H   I  J  K   L   M   N   O   P   Q   R   S   T   U   V   W  X  Y  Z

ABDOMEN/ABDOMINAL body cavity below diaphragm that contains stomach, intestines, liver and other organs ABSORB take up fluids, take in ACIDOSIS condition when blood contains more acid than normal ACUITY clearness, keenness, esp. of vision and airways ACUTE new, recent, sudden, urgent ADENOPATHY swollen lymph nodes (glands) ADJUVANT helpful, assisting, aiding, supportive ADJUVANT TREATMENT added treatment (usually to a standard treatment) ANTIBIOTIC drug that kills bacteria and other germs ANTIMICROBIAL drug that kills bacteria and other germs ANTIRETROVIRAL drug that works against the growth of certain viruses ADVERSE EFFECT side effect, bad reaction, unwanted response ALLERGIC REACTION rash, hives, swelling, trouble breathing AMBULATE/AMBULATION/AMBULATORY walk, able to walk ANAPHYLAXIS serious, potentially life-threatening allergic reaction ANEMIA decreased red blood cells; low red cell blood count ANESTHETIC a drug or agent used to decrease the feeling of pain, or eliminate the feeling of pain by putting you to sleep ANGINA pain resulting from not enough blood flowing to the heart ANGINA PECTORIS pain resulting from not enough blood flowing to the heart ANOREXIA disorder in which person will not eat; lack of appetite ANTECUBITAL related to the inner side of the forearm ANTIBODY protein made in the body in response to foreign substance ANTICONVULSANT drug used to prevent seizures ANTILIPEMIC a drug that lowers fat levels in the blood ANTITUSSIVE a drug used to relieve coughing ARRHYTHMIA abnormal heartbeat; any change from the normal heartbeat ASPIRATION fluid entering the lungs, such as after vomiting ASSAY lab test ASSESS to learn about, measure, evaluate, look at ASTHMA lung disease associated with tightening of air passages, making breathing difficult ASYMPTOMATIC without symptoms AXILLA armpit

BENIGN not malignant, without serious consequences BID twice a day BINDING/BOUND carried by, to make stick together, transported BIOAVAILABILITY the extent to which a drug or other substance becomes available to the body BLOOD PROFILE series of blood tests BOLUS a large amount given all at once BONE MASS the amount of calcium and other minerals in a given amount of bone BRADYARRHYTHMIAS slow, irregular heartbeats BRADYCARDIA slow heartbeat BRONCHOSPASM breathing distress caused by narrowing of the airways

CARCINOGENIC cancer-causing CARCINOMA type of cancer CARDIAC related to the heart CARDIOVERSION return to normal heartbeat by electric shock CATHETER a tube for withdrawing or giving fluids CATHETER a tube placed near the spinal cord and used for anesthesia (indwelling epidural) during surgery CENTRAL NERVOUS SYSTEM (CNS) brain and spinal cord CEREBRAL TRAUMA damage to the brain CESSATION stopping CHD coronary heart disease CHEMOTHERAPY treatment of disease, usually cancer, by chemical agents CHRONIC continuing for a long time, ongoing CLINICAL pertaining to medical care CLINICAL TRIAL an experiment involving human subjects COMA unconscious state COMPLETE RESPONSE total disappearance of disease CONGENITAL present before birth CONJUNCTIVITIS redness and irritation of the thin membrane that covers the eye CONSOLIDATION PHASE treatment phase intended to make a remission permanent (follows induction phase) CONTROLLED TRIAL research study in which the experimental treatment or procedure is compared to a standard (control) treatment or procedure COOPERATIVE GROUP association of multiple institutions to perform clinical trials CORONARY related to the blood vessels that supply the heart, or to the heart itself CT SCAN (CAT) computerized series of x-rays (computerized tomography) CULTURE test for infection, or for organisms that could cause infection CUMULATIVE added together from the beginning CUTANEOUS relating to the skin CVA stroke (cerebrovascular accident)

DERMATOLOGIC pertaining to the skin DIASTOLIC lower number in a blood pressure reading DISTAL toward the end, away from the center of the body DIURETIC "water pill" or drug that causes increase in urination DOPPLER device using sound waves to diagnose or test DOUBLE BLIND study in which neither investigators nor subjects know what drug or treatment the subject is receiving DYSFUNCTION state of improper function DYSPLASIA abnormal cells

ECHOCARDIOGRAM sound wave test of the heart EDEMA excess fluid collecting in tissue EEG electric brain wave tracing (electroencephalogram) EFFICACY effectiveness ELECTROCARDIOGRAM electrical tracing of the heartbeat (ECG or EKG) ELECTROLYTE IMBALANCE an imbalance of minerals in the blood EMESIS vomiting EMPIRIC based on experience ENDOSCOPIC EXAMINATION viewing an  internal part of the body with a lighted tube  ENTERAL by way of the intestines EPIDURAL outside the spinal cord ERADICATE get rid of (such as disease) Page 2 of 7 EVALUATED, ASSESSED examined for a medical condition EXPEDITED REVIEW rapid review of a protocol by the IRB Chair without full committee approval, permitted with certain low-risk research studies EXTERNAL outside the body EXTRAVASATE to leak outside of a planned area, such as out of a blood vessel

FDA U.S. Food and Drug Administration, the branch of federal government that approves new drugs FIBROUS having many fibers, such as scar tissue FIBRILLATION irregular beat of the heart or other muscle

GENERAL ANESTHESIA pain prevention by giving drugs to cause loss of consciousness, as during surgery GESTATIONAL pertaining to pregnancy

HEMATOCRIT amount of red blood cells in the blood HEMATOMA a bruise, a black and blue mark HEMODYNAMIC MEASURING blood flow HEMOLYSIS breakdown in red blood cells HEPARIN LOCK needle placed in the arm with blood thinner to keep the blood from clotting HEPATOMA cancer or tumor of the liver HERITABLE DISEASE can be transmitted to one’s offspring, resulting in damage to future children HISTOPATHOLOGIC pertaining to the disease status of body tissues or cells HOLTER MONITOR a portable machine for recording heart beats HYPERCALCEMIA high blood calcium level HYPERKALEMIA high blood potassium level HYPERNATREMIA high blood sodium level HYPERTENSION high blood pressure HYPOCALCEMIA low blood calcium level HYPOKALEMIA low blood potassium level HYPONATREMIA low blood sodium level HYPOTENSION low blood pressure HYPOXEMIA a decrease of oxygen in the blood HYPOXIA a decrease of oxygen reaching body tissues HYSTERECTOMY surgical removal of the uterus, ovaries (female sex glands), or both uterus and ovaries

IATROGENIC caused by a physician or by treatment IDE investigational device exemption, the license to test an unapproved new medical device IDIOPATHIC of unknown cause IMMUNITY defense against, protection from IMMUNOGLOBIN a protein that makes antibodies IMMUNOSUPPRESSIVE drug which works against the body's immune (protective) response, often used in transplantation and diseases caused by immune system malfunction IMMUNOTHERAPY giving of drugs to help the body's immune (protective) system; usually used to destroy cancer cells IMPAIRED FUNCTION abnormal function IMPLANTED placed in the body IND investigational new drug, the license to test an unapproved new drug INDUCTION PHASE beginning phase or stage of a treatment INDURATION hardening INDWELLING remaining in a given location, such as a catheter INFARCT death of tissue due to lack of blood supply INFECTIOUS DISEASE transmitted from one person to the next INFLAMMATION swelling that is generally painful, red, and warm INFUSION slow injection of a substance into the body, usually into the blood by means of a catheter INGESTION eating; taking by mouth INTERFERON drug which acts against viruses; antiviral agent INTERMITTENT occurring (regularly or irregularly) between two time points; repeatedly stopping, then starting again INTERNAL within the body INTERIOR inside of the body INTRAMUSCULAR into the muscle; within the muscle INTRAPERITONEAL into the abdominal cavity INTRATHECAL into the spinal fluid INTRAVENOUS (IV) through the vein INTRAVESICAL in the bladder INTUBATE the placement of a tube into the airway INVASIVE PROCEDURE puncturing, opening, or cutting the skin INVESTIGATIONAL NEW DRUG (IND) a new drug that has not been approved by the FDA INVESTIGATIONAL METHOD a treatment method which has not been proven to be beneficial or has not been accepted as standard care ISCHEMIA decreased oxygen in a tissue (usually because of decreased blood flow)

LAPAROTOMY surgical procedure in which an incision is made in the abdominal wall to enable a doctor to look at the organs inside LESION wound or injury; a diseased patch of skin LETHARGY sleepiness, tiredness LEUKOPENIA low white blood cell count LIPID fat LIPID CONTENT fat content in the blood LIPID PROFILE (PANEL) fat and cholesterol levels in the blood LOCAL ANESTHESIA creation of insensitivity to pain in a small, local area of the body, usually by injection of numbing drugs LOCALIZED restricted to one area, limited to one area LUMEN the cavity of an organ or tube (e.g., blood vessel) LYMPHANGIOGRAPHY an x-ray of the lymph nodes or tissues after injecting dye into lymph vessels (e.g., in feet) LYMPHOCYTE a type of white blood cell important in immunity (protection) against infection LYMPHOMA a cancer of the lymph nodes (or tissues)

MALAISE a vague feeling of bodily discomfort, feeling badly MALFUNCTION condition in which something is not functioning properly MALIGNANCY cancer or other progressively enlarging and spreading tumor, usually fatal if not successfully treated MEDULLABLASTOMA a type of brain tumor MEGALOBLASTOSIS change in red blood cells METABOLIZE process of breaking down substances in the cells to obtain energy METASTASIS spread of cancer cells from one part of the body to another METRONIDAZOLE drug used to treat infections caused by parasites (invading organisms that take up living in the body) or other causes of anaerobic infection (not requiring oxygen to survive) MI myocardial infarction, heart attack MINIMAL slight MINIMIZE reduce as much as possible Page 4 of 7 MONITOR check on; keep track of; watch carefully MOBILITY ease of movement MORBIDITY undesired result or complication MORTALITY death MOTILITY the ability to move MRI magnetic resonance imaging, diagnostic pictures of the inside of the body, created using magnetic rather than x-ray energy MUCOSA, MUCOUS MEMBRANE moist lining of digestive, respiratory, reproductive, and urinary tracts MYALGIA muscle aches MYOCARDIAL pertaining to the heart muscle MYOCARDIAL INFARCTION heart attack

NASOGASTRIC TUBE placed in the nose, reaching to the stomach NCI the National Cancer Institute NECROSIS death of tissue NEOPLASIA/NEOPLASM tumor, may be benign or malignant NEUROBLASTOMA a cancer of nerve tissue NEUROLOGICAL pertaining to the nervous system NEUTROPENIA decrease in the main part of the white blood cells NIH the National Institutes of Health NONINVASIVE not breaking, cutting, or entering the skin NOSOCOMIAL acquired in the hospital

OCCLUSION closing; blockage; obstruction ONCOLOGY the study of tumors or cancer OPHTHALMIC pertaining to the eye OPTIMAL best, most favorable or desirable ORAL ADMINISTRATION by mouth ORTHOPEDIC pertaining to the bones OSTEOPETROSIS rare bone disorder characterized by dense bone OSTEOPOROSIS softening of the bones OVARIES female sex glands

PARENTERAL given by injection PATENCY condition of being open PATHOGENESIS development of a disease or unhealthy condition PERCUTANEOUS through the skin PERIPHERAL not central PER OS (PO) by mouth PHARMACOKINETICS the study of the way the body absorbs, distributes, and gets rid of a drug PHASE I first phase of study of a new drug in humans to determine action, safety, and proper dosing PHASE II second phase of study of a new drug in humans, intended to gather information about safety and effectiveness of the drug for certain uses PHASE III large-scale studies to confirm and expand information on safety and effectiveness of new drug for certain uses, and to study common side effects PHASE IV studies done after the drug is approved by the FDA, especially to compare it to standard care or to try it for new uses PHLEBITIS irritation or inflammation of the vein PLACEBO an inactive substance; a pill/liquid that contains no medicine PLACEBO EFFECT improvement seen with giving subjects a placebo, though it contains no active drug/treatment PLATELETS small particles in the blood that help with clotting POTENTIAL possible POTENTIATE increase or multiply the effect of a drug or toxin (poison) by giving another drug or toxin at the same time (sometimes an unintentional result) POTENTIATOR an agent that helps another agent work better PRENATAL before birth PROPHYLAXIS a drug given to prevent disease or infection PER OS (PO) by mouth PRN as needed PROGNOSIS outlook, probable outcomes PRONE lying on the stomach PROSPECTIVE STUDY following patients forward in time PROSTHESIS artificial part, most often limbs, such as arms or legs PROTOCOL plan of study PROXIMAL closer to the center of the body, away from the end PULMONARY pertaining to the lungs

QD every day; daily QID four times a day

RADIATION THERAPY x-ray or cobalt treatment RANDOM by chance (like the flip of a coin) RANDOMIZATION chance selection RBC red blood cell RECOMBINANT formation of new combinations of genes RECONSTITUTION putting back together the original parts or elements RECUR happen again REFRACTORY not responding to treatment REGENERATION re-growth of a structure or of lost tissue REGIMEN pattern of giving treatment RELAPSE the return of a disease REMISSION disappearance of evidence of cancer or other disease RENAL pertaining to the kidneys REPLICABLE possible to duplicate RESECT remove or cut out surgically RETROSPECTIVE STUDY looking back over past experience

SARCOMA a type of cancer SEDATIVE a drug to calm or make less anxious SEMINOMA a type of testicular cancer (found in the male sex glands) SEQUENTIALLY in a row, in order SOMNOLENCE sleepiness SPIROMETER an instrument to measure the amount of air taken into and exhaled from the lungs STAGING an evaluation of the extent of the disease STANDARD OF CARE a treatment plan that the majority of the medical community would accept as appropriate STENOSIS narrowing of a duct, tube, or one of the blood vessels in the heart STOMATITIS mouth sores, inflammation of the mouth STRATIFY arrange in groups for analysis of results (e.g., stratify by age, sex, etc.) STUPOR stunned state in which it is difficult to get a response or the attention of the subject SUBCLAVIAN under the collarbone SUBCUTANEOUS under the skin SUPINE lying on the back SUPPORTIVE CARE general medical care aimed at symptoms, not intended to improve or cure underlying disease SYMPTOMATIC having symptoms SYNDROME a condition characterized by a set of symptoms SYSTOLIC top number in blood pressure; pressure during active contraction of the heart

TERATOGENIC capable of causing malformations in a fetus (developing baby still inside the mother’s body) TESTES/TESTICLES male sex glands THROMBOSIS clotting THROMBUS blood clot TID three times a day TITRATION a method for deciding on the strength of a drug or solution; gradually increasing the dose T-LYMPHOCYTES type of white blood cells TOPICAL on the surface TOPICAL ANESTHETIC applied to a certain area of the skin and reducing pain only in the area to which applied TOXICITY side effects or undesirable effects of a drug or treatment TRANSDERMAL through the skin TRANSIENTLY temporarily TRAUMA injury; wound TREADMILL walking machine used to test heart function

UPTAKE absorbing and taking in of a substance by living tissue

VALVULOPLASTY plastic repair of a valve, especially a heart valve VARICES enlarged veins VASOSPASM narrowing of the blood vessels VECTOR a carrier that can transmit disease-causing microorganisms (germs and viruses) VENIPUNCTURE needle stick, blood draw, entering the skin with a needle VERTICAL TRANSMISSION spread of disease

WBC white blood cell

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Pharma’s digital Rx: Quantum computing in drug research and development

The development of molecular formulations that become drugs to treat or cure diseases is at the heart of the pharmaceutical industry. Development is so fundamental that pharma spends a full 15 percent of its sales on R&D—a huge sum that accounts for more than 20 percent of total R&D spending across all industries in the global economy. This investment goes hand in hand with innovation: constantly seeking to improve the R&D process, pharma companies have for decades been early adopters of computational chemistry’s digital tools, such as molecular dynamics (MD) simulations and density functional theory (DFT). More recently, pharma R&D has taken advantage of artificial intelligence (AI). The next digital frontier is quantum computing  (QC).

In a recent article , we analyzed the impact of QC on the chemical industry, which, similarly to pharma, relies on the development and manufacture of molecules, and concluded that it will be one of the first industries to benefit. In this article, we explain the profound impact that QC could have on the pharma industry and present use cases for its application. We also provide a set of strategic questions to get clarity on the path forward for industry players.

Pharma’s focus on molecular formations makes it well suited for QC

Identifying and developing small molecules and macromolecules that might help cure illnesses and diseases is the core activity of pharmaceutical companies. Given its focus on molecular formations, pharma as an industry is a natural candidate for quantum computing. The molecules (including those that might be used for drugs) are actually quantum systems; that is, systems that are based on quantum physics. QC is expected to be able to predict and simulate the structure, properties, and behavior (or reactivity) of these molecules more effectively than conventional computing can. Exact methods are computationally intractable for standard computers, and approximate methods are often not sufficiently accurate when interactions on the atomic level are critical, as is the case for many compounds. Theoretically, quantum computers have the capacity to efficiently simulate the complete problem, including interactions on the atomic level. As these quantum computers become more powerful, tremendous value will be at stake.

The basics of quantum computing

A conventional computer, built on transistor-based classical bits operated by voltages, can be in only one of two states: 0 or 1. A quantum computer, instead, uses systems based on quantum physics, such as superconducting loops or ions hovering in electromagnetic fields (ion traps), which are operated by microwave radiation or lasers, respectively. As a result of the laws of quantum mechanics, such systems can be held in a special physical state, called a quantum superposition, in which quantum bits (qubits) exist in a probabilistic combination of the two states—0 and 1—simultaneously.

The implications of these effects for QC are dramatic. Qubits can process far more information than conventional computers can. Qubits use the characteristics of quantum-mechanical systems to solve complex equations in a probabilistic manner, so a computation solved with a quantum algorithm enables sampling from the probabilistic distribution of being correct. The combination of greater speed with probabilistic solutions means that quantum computing fits well with a certain subset of computing needs and applications, such as optimization, the simulation of chemicals, and AI.

While the technology behind quantum computing is rather difficult to understand intuitively (see sidebar, “The basics of quantum computing”), its impact is much easier to grasp: it will handle certain kinds of computational tasks exponentially faster than today’s conventional computers do. Thus, once fully developed, QC could add value across the entire drug value chain—from discovery through development to registration and postmarketing.

QC’s biggest impact on pharma will be in the discovery phases

While QC may benefit the entire pharma value chain—from research across production through commercial and medical—its primary value lies in R&D (Exhibit 1).

Currently, pharma players process molecules with non-QC tools, such as MD and DFT, in a methodology called computer-assisted drug discovery (CADD). But the classical computers they rely on are sorely limited, and basic calculations predicting the behavior of medium-size drug molecules could take a lifetime to compute accurately. CADD on quantum computers could increase the scope of biological mechanisms amenable to CADD, shorten screening time, and reduce the number of times an empirically based development cycle must be run by eliminating some of the research-related “dead ends,” which add significant time and cost to the discovery phase. Exhibit 2 shows where QC-enhanced CADD would improve the development cycle.

QC could make current CADD tools more effective by helping to predict molecular properties with high accuracy. That can affect the development process in several ways, such as modeling how proteins fold and how drug candidates interact with biologically relevant proteins. Here, QC may allow researchers to screen computational libraries against multiple possible structures of the target in parallel. Current approaches usually restrict the structural flexibility of the target molecule due to a lack of computational power and a limited amount of time. These restrictions may reduce the chances of identifying the best drug candidates.

In the longer term, QC may improve generation and validation of hypotheses by using machine-learning (ML) algorithms to uncover new structure-property relationships. Once it has reached sufficient maturity, QC technology may be able to create new types of drug-candidate libraries that are no longer restricted to small molecules but also include peptides and antibodies. It could also enable a more automated approach to drug discovery, in which a large structural library of biologically relevant targets is automatically screened against drug-like molecules via high-throughput approaches.

One could even envision QC triggering a paradigm shift in pharmaceutical R&D, moving beyond today’s digitally enabled R&D toward simulation-based or in silico drug discoveries—a trend that has been seen in other industries as well.

The following QC use cases apply to different aspects of drug discovery and will emerge at different points over an extended timeline. All of them, however, may enable more accurate and efficient development of targeted compounds.

Target identification and validation

During target identification, QC can be leveraged to reliably predict the 3-D structures of proteins. Obtaining high-quality structural data is a lengthy process often leading to low-quality results. Despite all efforts, researchers have yet to crystallize many biologically important proteins—be it due to their size, solubility (for example, membrane proteins), or inability to express and purify in sufficient amount. Pharma companies sometimes develop drugs without even knowing the structure of a protein—accepting the risk of a trial-and-error approach in subsequent steps of drug development—because the business case for a given drug is potentially so strong.

AlphaFold, developed by Google’s DeepMind, was a breakthrough in AI-driven protein folding but has not resolved all of the challenges of classical computing-based simulation, including, for example, formation of protein complexes, protein-protein interactions, and protein-ligand interactions. It’s the interactions that are most difficult to classically solve and, thus, may benefit from QC, which allows for the explicit treatment of electrons. Additionally, QC may allow for strong computational efficiencies here given that Google’s AI model—which is trained on around 170,000 different structures of protein data—requires more than 120 high-end computers for several weeks.

Hit generation and validation

QC’s ability to parallel process complex phenomena would be particularly valuable during hit generation and validation. With existing computers, pharma companies can only use CADD on small to medium-size drug candidates and largely in a sequential manner. Computing power is the bottleneck. With powerful enough QC, pharma companies would be able to expand all use cases to selected biologics as well, for instance, semi-synthesized biologics or fusion proteins, and perform in silico search and validation experiments in a more high-throughput fashion. This use case would go beyond the identification of the protein and eventually encompass almost the entire known biological world. With a robust enough hit-generation and validation approach, this step would already deliver potential lead molecules that are much easier and quicker to optimize.

Lead optimization

During lead optimization, which is a top-three parameter to improve R&D productivity, 1 Steven M. Paul et al., “How to improve R&D productivity: The pharmaceutical industry’s grand challenge,” Nature Reviews Drug Discovery , March 2010, Volume 9, pp. 203–214, nature.com. QC may allow for enhanced absorption, distribution, metabolism, and excretion (ADME); more accurate activity and toxicity predictions for organ systems; dose and solubility optimization; and other safety issues.

Data linkage and generation

The metalevel of R&D very much consists of linking appropriate data together—for instance, creating sensible connections between data points through effective (semantic) management. The more complex the biological information that can be processed, the more extensive the graphs that inform the drug discovery research process become. There is currently research on “topological data analysis” under way that aims to identify “holes” and “connections” across large data sets. 2 Silvano Garnerone, Seth Lloyd, and Paolo Zanardi, “Quantum algorithms for topological and geometric analysis of data,” Nature Communications , January 2016, Volume 7, Article 10138, nature.com. This may at some point enable R&D specialists to identify concrete cases and “industry verticals” where such algorithms are applicable, for example, in identifying connections across brain cells in response to a drug.

Moreover, QC could be used to “deepfake” missing data points throughout the research process, that is, generate a type of fake data by using ML algorithms. This could be particularly useful wherever there is a scarcity of data, such as in rare diseases, that can then be mitigated through artificial data sets. QC will set a new bar here regarding speed in training ML models, amount of initial data needed, and level of accuracy.

Clinical trials

Clinical trials could be optimized through patient identification and stratification and population pharmacogenetic modeling. 3 Paul et al., 2010. In trial planning and execution, QC could optimize the selection of the trial sites. QC could also augment causality analyses for side effects to improve active safety surveillance.

Beyond research and development

While the potential value of QC in pharma R&D is immense, it will also likely play a role further down the value chain. In the production of active ingredients, QC may aid in the calculation of reaction rates, optimize catalytic processes, and, ultimately, create significant efficiencies in the development of new product formulations. In the business-related value pools, QC in pharma could include the optimization of logistics (for instance, the optimization of on-site flows of materials, heat, and waste in production facilities) and improvements in the supply chain. Finally, toward market access and commercial, QC may even enable automatic drug recommendations.

Rollout of QC in pharma R&D will occur over two clear time horizons, characterized by a gradual tech transition

The development of quantum computers began nearly four decades ago, but it is the gains in QC technology realized over the past few years that paved the way for practical applications in pharma. We see the key, value-adding QC activities in pharma unfolding over two distinct eras as the technology further matures (Exhibit 3):

• From 2020–30: Not fully error-corrected QC. Early commercial activities related to quantum computing are already under way as we leave the first horizon—which focused on quantum-inspired algorithms over the past 40 years—and enter the horizon of not fully error-corrected QC. Often referred to as “noisy intermediate-scale quantum” (NISQ), this phase describes the not-error-corrected characteristics of near-term devices that are based on an initially considerable number of quantum bits (qubits) to solve problems classic computers can’t solve yet and do not provide fault tolerance. The timeline for the development and implementation of QC technology, and its adoption across companies, is very much under debate. NISQ, as a class of probabilistic computers that still (mostly) produce error-prone results, may potentially provide a near-term solution for a limited set of use cases. Companies eyeing QC’s potential should take this uncertainty into consideration.
• Beyond 2030: Fully error-corrected QC. Beyond 2030, fully error-corrected QC is expected, in which full value through QC will be captured. In this horizon, QC gets implemented at scale, and later adopters also implement the technology. In other words, chemicals players may start creating value with QC by the mid-2020s ; pharma companies are expected to move more solidly into the space shortly thereafter. Compared with the chemical industry, pharma researchers primarily target more complex and larger molecular systems, which can’t be replicated with either high-performance computers or today’s limited quantum computers.

Exactly when a particular company begins to capture QC’s benefits will depend on its tech starting point (that is, its current level of R&D digitization) and its business focus: the number of small active pharmaceutical ingredients (APIs) in its portfolio. Pharma companies that have a strong footprint in CADD and focus their R&D on smaller molecules will be among the first to take advantage of emergent QC. Exhibit 4 maps key CADD methods along the drug-discovery continuum and offers an indication of the applicability of QC. It’s expected that QC will be mostly applicable in the discovery phase of hit generation, hit-to-lead, and also in lead optimization.

In the next five to ten years, we expect that the first QC tools pharma players deploy will rely on hybrid methodologies that use classical algorithms alongside QC subroutines when they can create additional value. The prominent examples are the imaginary time evolution (an algorithm to find the ground-state and excited-state energy of many-particle systems) and the variational quantum eigen-solver, or VQE (an algorithm to calculate the binding affinity between an API and a target receptor). The value that algorithms such as VQE will add depends on the size of the quantum hardware. Describing small-molecule drugs generally requires less-mature quantum computers, while biologicals will be tackled only as QC matures.

Taking steps now can position pharma players for QC success later

The pharma sector is well positioned to take full advantage of this opportunity. Its tech-ready culture already embraces a wide array of digital tools: CADD, AI, ML, and non-QC DFT- and MD-simulation tools already play a big role in the sector’s R&D. On top of this, pharma players are already working with quantum-chemical simulations, so the barrier to entry is quite low. Scientists will not have to change the way they develop drugs in any fundamental way—they will just be working with more capable tools.

That said, companies will make their own decisions regarding whether and how to move toward a QC-enabled business. Some pharma players may take a pass on deploying QC, others may wait and observe, while still others are going “all in,” ginning up early in-house development. Most pharma players, however, will likely undertake joint-development strategies with upstream players. No matter what, answering some key strategic questions will help companies make more informed decisions on their stance for QC.

Assess the opportunity

Pharmaceutical companies should assess QC now and potentially lay the groundwork to reap the benefits of the technology later. QC may give many of them a huge opportunity, yet each pharma player needs to figure out how much exposure it has and the size of its QC opportunity in the context of its current pace of development. Thus, pharma players should consider three key strategic questions to determine their optimal QC strategy (Exhibit 5):

• Will QC demonstrate promise to disrupt my area of play and reorganize the competitive landscape?
• Have I identified opportunities in my value chain where QC’s potential may translate into value and in which time horizon?
• Can I dedicate resources to investigate QC opportunities, and can I scale up capabilities?

Subject to the above answers, moving early can help secure valuable intellectual property for the algorithms that drive QC and can also address a key issue: pharma won’t be the first industry sector to benefit from QC, so late-moving players could face a lack of suitable talent.

Establish partnerships

Some pharmaceutical players have already realized the need to join forces on the topic of QC and have started to collaborate and/or form partnerships. For example, QuPharm formed in late 2019 by major pharmaceutical players to pool ideas and expertise around QC use cases. QuPharm also collaborates with the Quantum Economic Development Consortium (QED-C), which was created in 2018 by the US government as part of the National Quantum Initiative Act and aims to enable commercial QC use-case efforts. Additionally, the Pistoia Alliance is a life sciences membership organization, which was organized to facilitate precompetitive collaboration and foster R&D innovation.

Partnering with pure quantum players taps into their existing expertise to test early use cases and facilitate development. At the moment, there are more than 100 QC-focused companies—both start-ups and established firms—around the world, focusing on software, hardware, or enabling services. Approximately 25 companies are targeting applications in the pharma industry. Less than 15 focus on algorithms or solutions for pharma players, and very few are focusing exclusively on the needs of pharma players.

Develop capabilities

Digital talent gaps are already a reality, and QC may only exacerbate them. Unlike other important digital tools, such as AI, quantum computing depends on niche know-how. Pharma companies already struggle to attract people with capabilities in the less specialized digital technologies, and hiring quantum-computing experts may prove to be even more of a challenge.

Ensure organizational collaboration

A pharma company’s “way of working” will also be central to its success in QC. The traditional walls that separate the work of the organization’s various functions and units—for example, research, tech, business—will have to fall away. Cross-functional collaboration in both spirit and action will characterize the pharma companies that are able to take full advantage of QC.

Quantum computing could be the key to exponentially more efficient discovery of pharmaceutical cures and therapeutics as well as to hundreds of billions of dollars in value for the pharma industry. Experts predict, for example, that today’s $200 billion market for protein-based drugs could grow by 50 to 100 percent  in the medium term if better tools to develop them became available. Given QC’s vast potential, we expect global pharma spending on QC in R&D to be in the billions by 2030. Pharma companies would be well advised to assess the QC opportunity for themselves and begin laying the groundwork in securing their place in this new competitive and technological landscape.

Matthias Evers is a senior partner in McKinsey’s Hamburg office, and Anna Heid is a consultant in the Zurich office, where Ivan Ostojic is a partner.

The authors wish to thank Nicole Bellonzi, Matteo Biondi, Thomas Lehmann, Lorenzo Pautasso, Katarzyna Smietana, Matija Zesko, and the many industry/academia experts for their contributions to this article.

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• Open access
• Published: 01 July 2024

How does mentoring occupational therapists improve intervention fidelity in a randomised controlled trial? A realist evaluation

• Blanca De Dios Pérez 1 ,
• Jose Antonio Merchán-Baeza 2 , 3 ,
• Katie Powers 1 , 4 ,
• Kristelle Craven 1 ,
• Jain Holmes 1 ,
• Julie Phillips 1 ,
• Ruth Tyerman 1 &
• Kate Radford 1  

BMC Medical Research Methodology volume  24 , Article number:  142 ( 2024 ) Cite this article

Metrics details

Integrating complex interventions within healthcare settings can be challenging. Mentoring can be embedded within a randomised controlled trial (RCT) to upskill and support those delivering the intervention. This study aimed to understand, from a realist perspective, how mentoring worked to support implementation fidelity for occupational therapists (OTs) delivering a vocational rehabilitation (VR) intervention within the context of an RCT.

A realist evaluation using secondary data (emails, mentoring record forms, interviews) collected as part of an RCT. Three researchers coded the data following content analysis, focused on refining or refuting an initial programme theory by exploring the interactions between context, mechanisms, and outcomes. The research team met to further refine the programme theories.

Data from 584 emails, 184 mentoring record forms, and 25 interviews were analysed following a realist approach. We developed a programme theory consisting of two contexts (trial set-up, ongoing mentoring), nine mechanisms (collective understanding, monitoring, timely support, positive reinforcement, reflective practice, support data completeness, facilitation strategy, shared learning experience, management of research and clinical duties), and three outcomes (improved confidence, improved fidelity, reduced contamination).

Conclusions

Offering mentoring support to OTs delivering a VR intervention as part of an RCT improves intervention fidelity and reduces the risk of contamination. It improves OTs’ understanding of the differences between their clinical and research roles and increases their confidence and competence in trial paperwork completion and identification of potential contamination issues.

Peer Review reports

Introduction

Complex interventions are characterised by having multiple intervention components, involve behaviour change from several stakeholders and can influence multiple outcomes [ 1 ]. These are commonly used in health settings to influence important health outcomes [ 2 ]. One such intervention is vocational rehabilitation (VR), which focuses on supporting people with illness or disability to remain, return to, or find new employment [ 1 , 3 ].

Implementing complex interventions within healthcare systems is challenging and time-consuming [ 4 ]. Several barriers have been identified to deliver complex interventions with fidelity at organisational and professional levels [ 5 ]. In a previous systematic review [ 6 ], barriers to maintaining fidelity in the delivery of rehabilitation to people with long-term neurological conditions included a lack of training availability and therapists’ lack of confidence in offering new interventions, especially if there is a delay between training and the start of intervention delivery [ 5 , 6 ]. Implementing new interventions in clinical practice or a clinical trial context may require changes in staff knowledge, skills, confidence, and attitudes, and how they apply new learning in practice is a complex process [ 5 ].

To overcome some of these barriers, healthcare professionals delivering complex interventions rely on implementation strategies [ 7 ]. These can be defined as methods to enhance an intervention’s adoption, implementation, and sustainability [ 8 ]. For example, methods for training and supporting those delivering the intervention, such as mentoring, intervention-specific toolkits, checklists, algorithms, and formal practice protocols and guidelines [ 8 ].

Mentoring is an iterative process of intentional relationships between individuals dedicated to the professional and personal growth of one another within a structured program bound by a timeframe and defined objectives [ 9 , 10 ]. Previous studies have examined and demonstrated the effectiveness of mentoring in implementing complex interventions [ 9 , 10 ] and how mentoring supports intervention fidelity in the context of a trial [ 11 ]. However, the mechanisms underlying this learning process remain unclear.

Realist evaluations provide the methods to explore a programme’s context, mechanisms, and outcomes, which allow for determining how an intervention or programme works, for whom, and under what circumstances [ 12 , 13 ]. This approach enables an understanding of how the context influences behaviour towards an intervention, which, in turn, impacts the outcomes (i.e., participants’ responses) [ 12 ]. Evaluating a complex intervention can be challenging, and realist evaluations can be valuable for understanding implementation and which aspects of an intervention (in this case, mentoring) are effective or not [ 14 ]. Realist methods have been previously used to understand how complex interventions such as improving primary healthcare services [ 15 ], mentoring [ 16 ], and mental health rehabilitation services [ 17 ] work. Although more time-consuming than other methodologies (e.g., process evaluation), we selected a realist evaluation to identify the active ingredients of a complex intervention (i.e., mentoring) and gain insight into the factors (mechanisms, context) that underlie the effectiveness of mentoring [ 14 ].

This study uses realist evaluation methodology to explore the impact of embedded mentoring for clinical Occupational Therapists (OTs) working in the National Health Services (NHS) of the United Kingdom (UK) delivering an early stroke specialist vocational rehabilitation intervention (ESSVR) for stroke survivors as part of a randomised controlled trial (RCT) [ 18 ]. We are interested in understanding:

What are the underlying mechanisms by which Occupational Therapist-led mentoring supported the delivery of ESSVR for OTs in the RETAKE trial?

What are the conditions, in terms of context and mentoring structure, for whom mentoring works, how, and under what circumstances?

What other outcomes are influenced by mentoring for the OTs within the trial context?

We conducted a realist evaluation drawing on the reporting standards for realist evaluations (RAMESES II) [ 19 ].

The RETAKE [Return to Work after Stroke] trial involved the delivery of an early stroke specialist VR intervention (ESSVR) commencing within 12 weeks of stroke intended to support participants’ return to work and job retention at 12 months post-randomisation. ESSVR was individually tailored to the stroke survivor’s clinical, personal, and professional needs. ESSVR included assessment of the impact of a stroke at work, educating patients, employers and families about the impact of a stroke at work, identifying reasonable adjustments (e.g., written instructions, specialist equipment) to lessen the impact of stroke, work preparation and maintenance, and engagement of stakeholders (e.g., employer, healthcare professionals), amongst other support [ 18 ].

OTs delivered the intervention in the participants’ homes or workplaces, according to preference and need. Two OTs were recruited to deliver the RETAKE intervention in each of 16 trial sites [ 18 ]. The OTs recruited to deliver the ESSVR intervention adopted the role of mentees and received mentoring from senior OTs who were not involved in intervention delivery. The mentors were also OTs with stroke-specific knowledge and experience in VR and research processes (e.g., two had completed a PhD).

Mentees were based in different healthcare settings, with varying levels of VR and stroke expertise. OTs delivering the intervention completed an initial 2-day training session, followed by a third day six months later, to deliver the VR intervention and engaged in group monthly mentoring sessions delivered remotely [ 18 ].

Development of initial programme theory

Following the realist evaluation framework, we developed an initial programme theory using a context-mechanism-outcome (CMO) configuration through discussion with the research team [ 13 ]. While developing the initial programme theory, we conducted a face-to-face group meeting with the eight research team members (i.e., co-authors) to understand how mentoring was delivered during the trial and their thoughts on the impact of mentoring on the trial. A team member (BDP) led a discussion to understand what it was about the way mentoring was delivered, that made a difference to how the OTs delivered the intervention. The research team was encouraged to provide an explanation of how mentoring worked to test the initial theories the team provided, and refine them iteratively through discussion [ 20 , 21 ].

The team members had first-hand experience in the trial processes and in supporting the mentees with the implementation of ESSVR. The initial programme theory was:

If research OTs with limited research experience are provided with frequent mentoring during the trial (Context), then they will become more confident in delivering the intervention (Outcome) and deliver the intervention with improved fidelity (Outcome), because mentoring will help them develop an understanding of the need to adhere to the intervention process and trial (e.g., completion of forms) procedures (Mechanism).

We developed a series of secondary programme theories to explore the mechanisms by which mentoring brings about its change in more detail, which allowed us to create a code book for analysing the data. These are presented in additional file 1 .

Data Collection

This study involved secondary data analysis from the mentoring records collected during the trial. The methods used to embed the mentoring in the trial are published elsewhere [ 22 ]. The data was collected between March 2018 and April 2020 as part of the trial and included mentoring record forms ( n  = 184) (including content regarding implementation and clinical issues, challenges experienced by the OTs, and issues with the employer’s intervention), emails ( n  = 584) between the trial team and OTs, and interviews with mentors ( n  = 6) and mentees ( n  = 19) at the end of the trial to explore their views and experiences on the trial; these were not conducted following a realist perspective. We obtained informed consent from all participants.

The demographic characteristics of the mentors and mentees involved in the RETAKE trial are reported elsewhere [ 22 ].

Data analysis and synthesis

Interviews were audio-recorded, transcribed verbatim by an external company, and analysed following content analysis. All data (emails, interview transcripts, and mentoring record forms) were systematically coded following a realist evaluation framework. We developed a definition for each of the mechanisms identified in the initial programme theories to allow for consistency during the data coding process, and these were reviewed by the full research team.

Data from each data source (i.e., emails, mentoring record forms, interviews) were coded according to CMO configurations using Microsoft Word, and then data was merged in Excel for synthesis. The context refers to the background where the mentoring was implemented, including the trials and research site environment; the mechanisms refer to how the mentoring worked and what it triggered in the mentees (e.g., changes in feelings or thoughts), and the outcomes were the expected or unexpected consequences of the mechanisms acting in the given context. Only data related to the mentoring processes were extracted, using a bespoke data extraction form (additional file 2 ).

Three researchers (KP, JM, BDP) were involved in the data coding, and one author (BDP) oversaw the data coding and reviewed the data extraction forms. Discrepancies were discussed between the three researchers, and a fourth researcher (KR) was contacted to resolve discrepancies through discussion.

The first step in data analysis involved three researchers (KP, JM, BDP) reading and coding 10 emails independently to identify mechanisms involved in the mentoring process. The researchers met to discuss any discrepancies and distributed the data to code independently, arranging monthly meetings to discuss any issues with data extraction, new mechanisms identified, refine their definitions, and revise the programme theories.

Data were synthesised following the steps described by Wong et al. [ 23 ]. The CMO configurations coded were grouped based on the mechanisms that best explain the relationship between the context and outcomes of the mentoring support integrated within the trial. We developed “if-then-because” statements (i.e., “if” context, “then” outcome, “because” mechanism) to summarise the CMO configurations [ 23 ]. The data synthesis followed an iterative process to develop, support, refine, or refute the original programme theories based on the evidence from the mentoring records.

Team consultation

Following the data synthesis, the research team met to discuss the programme theories and refine them based on their knowledge and experiences of the mentoring and trial processes. Three authors (BDP, KP, JM) presented the programme theories to the rest of the research team who were involved in the trial to ascertain their views on the impact of mentoring on intervention delivery. The research team was presented with all the components of the programme theory and asked to reflect on whether the theories developed were valid or should be refined. Three authors (BDP, KP, JM) took notes on the views of the research team to refine the programme theories.

Development of a theoretical framework

The data from the mentoring records and consultation with the research team was synthesised to develop a programme theory using CMO configurations to explain how mentoring should be integrated within the context of future trials, which can be accommodated for different settings.

Ethical approval

The RETAKE Trial received full Ethical approval through the East Midlands–Nottingham 2 Research Ethics Committee (Ref: 18/EM/0019) and the NHS Health Research Authority. This study involves secondary analysis of anonymised data collected as part of RETAKE, and refinement of the programme theory through discussion with the research team involved in trial delivery and mentoring.

Data from 584 emails, 184 mentoring record forms, and 25 interviews were analysed. Data analysis generated two contexts, nine mechanisms, and three outcomes relevant to mentoring (Table  1 ). We present first the context relevant to mentoring, followed by the mechanisms and the resulting outcomes.

We identified two main themes within the context domains: trial set-up and ongoing mentoring sessions.

Trial set-up

Mentors started engaging with the mentees when a site was recruited to the trial. Some mentors were involved in training the mentees in ESSVR. These interactions were essential for the mentors to understand the mentees’ previous experiences (i.e., who had prior VR experience and who did not), clinical responsibilities at each site and the mentees’ critical areas for development.

Ongoing mentoring

During the trial, mentoring involved monthly group sessions and guidance to follow trial and ESSVR procedures. Mentors also provided ad hoc mentoring sessions for those who needed additional support. Mentees reported challenges around managing clinical and research requirements, such as insufficient time at work to deliver the intervention to trial patients, NHS managers expecting OTs to support the same number of patients as before the trial, and support needs in completing trial documentation and letters to other stakeholders (e.g., employers).

We elicited eight main mechanisms to describe how mentoring worked in the context of the RETAKE trial.

Collective understanding

One of the main mechanisms identified was “collective understanding”. Mentors supported mentees to understand the essential ESSVR components and tasks related to the documentation of the trial. Over time, mentors and mentees developed a relationship of trust that made mentees more likely to ask for support. This relationship matured as mentors shared examples from their experiences and were understanding and open-minded with the mentees’ questions.

As mentees developed a collective understanding of their research and clinical role, they became more accurate in identifying instances of potential contamination and delivered ESSVR with improved fidelity. Problems developing this collective understanding led to delays in study set-up, instances of contamination, and mentees lacking awareness of ESSVR procedures (e.g., how to discharge a participant). This mechanism was a driver for all other mechanisms within the trial.

This mechanism relates to the mentors’ ability to review progress made and provide long-term support to mentees during the trial.

At the trial set up stage, if the mentors engaged with the mentees to track progress on the sites, then this facilitated the identification of any changes in the trial sites that might lead to contamination (e.g., new service developments or services, identifying new or competing research studies, etc.). Mentors were then able to prepare the mentees to engage with the trial (e.g., access to trial systems and paperwork, data protection and Good Clinical Practice (GCP) training), and the mentors were able to identify those in need of further training. For this to occur, the mentors had to be proactive in developing trusting relationships with the mentees, potentially through the initial training that the mentees received. This was reinforced over the course of the trial due to further interactions during the mentoring sessions. This enabled the mentors to monitor progress, identify potential problems, and address the mentees’ concerns.

During the intervention delivery period, this mechanism related to mentors reassuring mentees that they were on the right track with the intervention delivery, which increased the mentees’ confidence in their ability to deliver the support, especially those who were new to VR. Mentors also shared summaries of the content discussed in the group mentoring sessions and arranged further 1-to-1 sessions for those who needed additional support. This allowed the mentees to have a re-accessible resource to review in their own time.

Timely support

In each group mentoring session, mentees were invited and actively encouraged to share details about their current caseloads. Mentees were especially encouraged to share instances and situations where they were struggling. Through sharing these struggles with the mentoring group, the mentees could seek advice from their mentors and peers and learn from their mistakes before integrating them into ESSVR delivery. Mentors were also able to identify their mentees’ further training needs in a timely way. This helped solidify skill development, increase confidence in delivering ESSVR, and ultimately helped facilitate fidelity to ESSVR.

Mentors reflected that even when mentees had developed greater confidence, the mentees still sought timely support, but were often looking for reassurance rather than solutions to a problem. The mentors also reflected that the more mentees engaged in disclosing their struggles in mentoring and subsequently received support, the more likely they were to disclose their struggles in future sessions.

It is important to consider that early identification of issues relied almost entirely on the mentee communicating their experience of delivering ESSVR. Throughout the trial process, situations arose where mentees required timely input from their mentors, often between mentoring sessions. When mentees were not able to disclose their struggles within their monthly mentoring session, mentors encouraged the mentees to contact them for individual support. In some circumstances, mentees did not engage in some of the monthly mentoring because of environmental factors, such as busy caseloads and personal circumstances. Mentors highlighted that, at times, providing timely support to mentees seeking individual support was difficult as the timeliness was dependent on the workload of the mentor and the mentee.

Positive reinforcement

When mentors provided reassurance about a mentee’s proposed course of action, mentees felt valued (and therefore disclosed more). Still, they were also reassured in their actions, which helped solidify their skill development, ESSVR knowledge, and confidence. When mentees are more confident in ESSVR delivery, they were more likely to go outside of their comfort zones to engage and liaise with employers.

Increases in mentees’ ESSVR delivery and research self-efficacy also increased the mentors’ confidence in the mentees’ abilities. Increased confidence in the mentees meant that the mentors could plan their time to give more support to less confident mentees. Mentors reflected that increased confidence among the mentees led to the group mentoring becoming more peer-led, which, in turn, led to the mentees feeling more valued.

Some mentees became more dependent on their mentors due to positive reinforcement. Mentors provided a safety net for mentees with little to no experience in VR or research. There was also a shared sentiment that, in some cases, mentees stopped coming to group mentoring, because they preferred the positive reinforcement and increased self-efficacy from one-to-one mentoring sessions. For these mentees, mentors reportedly had to delay their response rate to foster independence.

Reflective practice

ESSVR was a new intervention for the OTs in the RETAKE trial. Its components pushed the mentees beyond their comfort zones. In group and individual mentoring sessions, mentors provided a space for mentees to think about how they might approach ESSVR and other trial-related problems. Through evaluating the ESSVR process and trial procedures and discussing previous experiences, mentees were able to learn from each other and develop shared ‘best practice’. By sharing each other’s cases and reflecting on those cases, mentees were able to build their knowledge of how to individually-tailor ESSVR to their participants’ needs. This facilitated increased confidence and self-efficacy in both ESSVR delivery and trial procedures.

For many OTs, participating in a monthly, hour-long reflective practice session was an opportunity they did not have in their usual care roles, even though was written into some OTs’ contracts.

Support data completeness

This mechanism refers to support in completing forms, recording study data, and training and developing letter templates to communicate with participants and other stakeholders.

During mentoring sessions, mentors emphasised the importance of accurately completing study documentation and intervention records. They offered support with completing forms, which increased the mentees confidence and competence for accurate completion.

More reliable data were obtained from mentees who completed forms and reports immediately following ESSVR delivery. Mentees who completed forms later tended to rely on their clinical notes and were less accurate in their reporting.

Facilitation strategy

On numerous occasions, the mentees raised problems with the mentors that they did not know how to solve by themselves. For example, how to engage with managers, support recruitment or understand problems with how they were being paid to deliver the research. Their relationships with the mentor made them more likely to contact the mentors or other research team members to discuss issues and seek advice. For example, the mentors contacted the trials unit or the Chief Investigator to address complex trial issues, the mentors supported mentees on RETAKE administrative duties to relieve staff pressures, or mentors and mentees worked together to understand how to contain contamination at a site. This interaction improved intervention fidelity and allowed the development of a network of stakeholders with different skills to address each problem.

Overall, the mentors acted as case managers finding solutions to problems or identifying stakeholders who could address the problem. The mentees saw themselves as key members of the trial, with a role in ensuring the intervention was delivered as intended to ensure a robust trial outcome. Mentors themselves were able to address recurrent trial challenges such as low recruitment or staffing issues because they had gained this experience through the trial and knew who to contact for each problem.

Shared learning experience

This mechanism evolved over the study duration. The RETAKE trial lasted 6.5 years with 47 months of recruitment and an extra 12 months of ESSVR delivery. It was also impacted by the pandemic; thus, there were many changing circumstances that required shared learning to address problems. However, mentoring was seen as a highly acceptable process in the trial.

During the trial set-up, mentees got to know each other at the face-to-face intervention training and site initiation visit sessions. These trial set-up interactions, together with interactions in their own trial sites and during mentoring, allowed them to develop working relationships beyond their role in the trial.

During mentoring, mentors took a leading role and shared their own experiences and best VR practices with the mentees. Over time, mentees became more confident in offering each other support, creating an environment of peer support where they discussed common issues and potential solutions to barriers based on their experience. Mentees also discussed what they had learned and what they found most helpful. For example, mentees discussed how they learned by “doing” (i.e., delivering the intervention), and having a mentor to answer questions helped boost their confidence and knowledge in VR. Mentees were also grateful that other mentees were sharing initiatives and procedures followed at their site, which could be integrated into other sites to improve how services are delivered. This approach helped mentees learn from one another and build relationships over time.

Management of research and clinical duties

This was the only identified mechanism that affected delivery of the intervention with fidelity.

The Covid-19 pandemic had a direct impact on the mentees usual care clinical duties, which by extension, limited their time available to deliver ESSVR and engage in the mentoring. This was particularly challenging for mentees when either they or someone in their NHS teams contracted Covid-19, and were unable to work. The increased workload meant mentees could not deliver the intervention.

Mentees also experienced challenges associated with their NHS line managers being unsupportive of their research role. Despite mentees being paid indirectly via Excess Treatment Costs [ 24 ] to deliver ESSVR, within site transfer of these finances into therapy services’ budgets, research naivety in some NHS sites (in both line managers and research and innovation), together with local recruitment issues, often meant the OT mentees research time was not backfilled and some mentees were expected to deliver the research activity in addition to their usual clinical role. This resulted in mentees feeling overwhelmed.

If mentees were experiencing problems managing their clinical and research duties, they typically experienced problems with intervention delivery, and following research procedures.

We identified three main outcomes by integrating the mentoring sessions into the trial.

Improved confidence

Mentees became more confident in their ability to engage in research and deliver ESSVR as expected, developed skills to contact other stakeholders (e.g., employers, occupational health representatives, etc.), and engaged in conversations to problem-solve challenges arising during the intervention. This improved confidence resulted from the shared learning experience and open-minded mentor and mentee support. Mentors also gained confidence in the mentees ability, based on the questions they asked and their approach to solving identified problems. Mentees who overestimated their knowledge and ability to deliver ESSVR engaged in fewer mentoring sessions, and therefore, had fewer opportunities to reflect on their practice.

Improved fidelity

Through the mentoring sessions and contact with the mentors between sessions, mentees became more familiar with the clinical aspects of ESSVR delivery and research processes (e.g., how to record the intervention content). Therefore, they became more accurate in delivering and reporting ESSVR content. Therefore, they became more adherent to the individual components of ESSVR and more accurate in their reporting of ESSVR component delivery. OT mentors found fewer discrepancies between the intervention delivered and the intervention recorded, and OT mentees became more accurate in differentiating between intervention components and following procedures according to the different trial circumstances.

Reduced contamination

The topic of contamination was addressed during the trial set-up training sessions to allow mentees to identify potential issues that may arise during the lifetime of the trial.

As mentees became more familiar with the intervention manual and research processes, they became more aware of changes in their NHS services and local centres that may lead to contamination.

Mentees were responsive in communicating these changes to mentors and the research team, which allowed them to implement solutions to overcome contamination issues.

Revised Program Theory

Based on the data analysis, a visual representation of the revised programme theory representing the interaction between the different CMOs is presented in Fig.  1 .

Mentoring programme theory. Legend: Red arrows depict barriers to achieving outcomes

The context related to the “trial set-up” stage is at the programme theory outset. It refers to the starting point when the mentees and mentors got to know each other, shaping relationships and by extension, their perceptions of mentoring. Mentors received training on their role and expectations. All had worked as mentors on previous trials and had prior expertise in VR. The second context, “ongoing mentoring”, is located across the logic model to reflect changes over time.

The underpinning mechanisms of mentoring are presented as interacting with each other to reflect the ESSVR intervention and research learning throughout the trial.

The programme theory describes how embedding mentoring within the trial led to the proposed outcomes. One outcome (improved confidence) impacts at an individual level (mentees), and it is essential to achieve the intervention-related outcomes (improved fidelity and reduced contamination).

This study aimed to develop a realist programme theory to explain how mentoring supports implementation fidelity in a complex intervention trial. We identified nine mechanisms (collective understanding, monitoring, timely support, positive reinforcement, reflective practice, support data completeness, facilitation strategy, shared learning experience, management of research and clinical duties) and three outcomes (improved confidence, improved fidelity, reduced contamination) that describe how mentoring helped clinical OTsdeliver a complex VR intervention. The programme theory illustrates a process where mentees become more knowledgeable in ESSVR and trial processes, which helped them deliver the intervention with improved fidelity and identify problems (i.e., contamination).

Our previous research exploring the impact of mentoring in the context of the RETAKE trial showed that mentoring could improve fidelity and that it was valued by both mentors and mentees [ 5 ]. However, it was unclear how mentoring works in a trial context. This realist evaluation suggests mentoring helped the mentees gain confidence in their clinical and research skills. This enabled them to acknowledge when they needed further support and helped them identify possible deviations from the trial protocol. The relationship between mentor and mentees was important for the success of mentoring because mentees felt comfortable discussing the challenges they were facing with the mentors without feeling judged about their abilities.

Using realist evaluation has provided valuable insights into how trusting relationships between the mentors and mentees, which developed throughout the trial, exposed where mentees required further support to implement the intervention. Notably, the realist evaluation revealed that mentees faced greater challenges with the research-related aspects and balancing their clinical and research responsibilities than with delivering the VR itself. Additionally, mentors acted as support staff, managing the practicalities of combining research with clinical practice, which was essential for the OTs to deliver the trial intervention as intended. These insights into generative causal mechanisms may not have been exposed using other research methods [ 25 ].

Developing a collective understanding of the intervention was essential to the success of the trial. It is common for experienced OTs to make decisions in clinical practice based on their previous experiences and expert knowledge [ 26 ]. In the context of a trial, for the intervention to be delivered with fidelity, the OTs had to understand the research processes and deliver the intervention “as intended” following a predefined process. Mentors played a critical role in the development of a collective understanding by reiterating practices, and exploring, from the perspective of mentees what their challenges and fears were. This suggests that integration or collaboration between the research and the clinical team is a factor contributing to implementation fidelity, identifying instances of contamination, and development of a shared vision for trial success.

Mentoring in this trial also offered the OTs an opportunity for reflective practice. While this is an essential part of clinical practice [ 27 ] and a requirement of continuing professional development [ 23 ], it is poorly practised due to increasing workload pressures in routine care [ 27 ]. The RETAKE trial offered protected time for mentoring and reflection. The mentors also adopted a flexible and personalised approach that allowed OTs to seek advice outside the formal group mentoring sessions. This benefitted those OTs with high workloads related to the trial or participants with complex needs that needed further discussion.

The NHS constitution supports the idea of making research accessible to all patients accessing its services [ 28 ]. However, this is not always without challenges. Managing research and clinical duties was challenging for the clinical OTs, leading to barriers to delivering the intervention and threatening fidelity. This mechanism was present when the managers were not supportive of the research time because of the use of the clinical OT time on research instead of clinical duties or when the clinical demand was excessive. These are common findings in the literature that led to issues with recruitment and health professionals unaware of how to balance their research and clinical duties [ 29 , 30 ]. Therefore, it is important for trials to engage all key stakeholders, including NHS managers, in the pre-trial stage to set expectations and manage responsibilities.

Overall, the mechanisms and outcomes identified align with the literature on the topic. In fact, there is evidence that engaging in mentoring leads to intervention fidelity in the context of a trial [ 11 ]. There is also evidence that when healthcare professionals receive mentoring, they become more knowledgeable and skilled, and are more likely to follow clinical guidelines [ 31 ].

There were, however, barriers associated with attending the mentoring sessions. The most common issues were conflicting work schedules (i.e., clash with clinical duties or patient visits) and technological difficulties (i.e., lack of internet or telephone). Barriers to attending the mentoring sessions reflect the reality of competing clinical and research duties. To overcome these challenges in the trial, mentors offered flexible 1-to-1 support sessions for those who could not attend group sessions or needed additional support. The mentees found this approach beneficial to complement their training needs. This aligns with the literature that supports a combined approach to mentoring (group + individual sessions) to further develop healthcare professionals’ skills [ 32 ].

Strengths and limitations

This study’s main strength is the novel approach to exploring the impact of mentoring from a realist perspective and the extensive data available to understand how mentoring supports intervention delivery in the context of a trial.

Three researchers were involved in the data analysis and synthesis. Although the findings were discussed in detail with the research team, including several mentors involved in the trial, mentees were not contacted to verify the findings from their perspective. Another limitation relates to the generalisation of the findings, which are particular to acute stroke and stroke rehabilitation services.

Implications for practice and research

Clinical OTs might benefit from having protected time to engage in group sessions to reflect on their practice to learn from their errors and improve the quality of their services within the context of a trial.

Future trials should consider embedding mentoring to aid the early identification of issues and to support therapists in delivering interventions as intended. Future research should also explore what attributes lead to mentees benefitting more from group or individual mentoring sessions to tailor the mentoring to the mentees’ needs. Future research should also examine the long-term impact of mentoring and whether increased skills and confidence leads to OTs becoming more independent in their work t.

This study provides further evidence on the impact of mentoring in the context of a trial, by developing a theoretical understanding of how and why mentoring works. This realist evaluation offers insight into how clinical OTs can be upskilled in VR and research procedures, improving intervention fidelity, and reducing contamination.

The evidence suggests the need to build a relationship with clinical OTs delivering trial interventions before the trial to facilitate the study set-up and identify further training needs. There is also a need for continued and open communication between mentors and mentees to address questions and build their confidence in their ability to deliver the intervention and engage in the trial.

Embedding mentoring within a clinical trial has the potential to improve intervention fidelity. This is beneficial for improving the interpretation of research outcomes and facilitating the translation of research evidence into practice.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Context-Mechanism-Outcome

Early Stroke Specific Vocational Rehabilitation

National Healthcare Service

Occupational therapist

Randomised controlled trial

United Kingdom

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Acknowledgements

We would like to thank the occupational therapists involved in the delivery of the RETAKE trial for their involvement in the study.

This study is funded by the NIHR HTA programme (ref: 15/130/11). The views expressed herein are those of the authors, not necessarily the NIHR, the Department of Health and Social Care or the NHS.

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Blanca De Dios Pérez, Katie Powers, Kristelle Craven, Jain Holmes, Julie Phillips, Ruth Tyerman & Kate Radford

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Jose Antonio Merchán-Baeza

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K.R, B.D.P, J.M and K.P conceived the study and designed the protocol for the realist evaluation. B.D.P developed the data extraction forms. B.D.P, J.M, and K.P conducted the data analysis and synthesis. All authors (K.R, B.D.P, J.M, K.P, K.C, J.H, J.P, R.T) engaged in group discussions to develop the initial programme theory, met to synthesise the research findings, and read and approved the final version.

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Correspondence to Blanca De Dios Pérez .

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De Dios Pérez, B., Merchán-Baeza, J.A., Powers, K. et al. How does mentoring occupational therapists improve intervention fidelity in a randomised controlled trial? A realist evaluation. BMC Med Res Methodol 24 , 142 (2024). https://doi.org/10.1186/s12874-024-02269-4

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DOI : https://doi.org/10.1186/s12874-024-02269-4

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Med Research Topics: What Makes a Good One?

Several essential attributes characterize an excellent medical research topic. First and foremost, it should address a significant and relevant issue within the medical field. The topic must have practical implications, contributing to advancing medical knowledge and improving patient care. For example, researching a new treatment for a prevalent disease or understanding the underlying mechanisms of a standard physical and mental health condition can provide valuable insights that can be applied in clinical practice.

Furthermore, a robust medical research topic should be specific and well-defined, allowing for a focused investigation. Vague or overly broad issues can make formulating a straightforward research question and designing a robust study challenging. Interested researchers can delve deeper into the subject matter by narrowing the scope and producing more detailed and meaningful findings. For instance, instead of broadly studying "cancer and treatment options," a more defined topic like "the efficacy of a specific immunotherapy in treating melanoma" would yield more actionable results.

Another critical aspect of an excellent medical research topic is feasibility. Researchers need to consider the availability of resources, such as funding, equipment, and expertise, as well as ethical considerations. The topic should be practical to study within the given constraints and timeframe. The feasibility of interesting topics also encompasses recruiting sufficient participants if human subjects are involved, ensuring that the study can be conducted effectively and ethically.

Lastly, a compelling medical research topic should be innovative and contribute new knowledge. It should challenge existing paradigms, explore uncharted areas, or offer new perspectives on established concepts. Innovation drives progress in medicine, leading to breakthroughs that can revolutionize patient care and improve patient outcomes. By choosing a topic that pushes the boundaries of current knowledge, healthcare researchers can make a lasting impact on the medical community and beyond.

How to Pick a Good Medical Research Paper Topic

Selecting a good medical research paper topic involves carefully considering several key factors. Firstly, choosing a topic that addresses a significant and current issue in the medical field is essential. One such issue is healthcare access, which is crucial in addressing inequities and barriers leading to health disparities and injustices. This ensures that the research will be relevant and contribute valuable knowledge to ongoing discussions and advancements in oral health elsewhere. Reviewing recent literature on medical research topics and identifying gaps in existing research can help pinpoint areas that need further exploration.

Next, the chosen topic should be specific and focused. A narrow scope allows for a more in-depth investigation and produces more detailed and actionable findings. For example, instead of a broad topic like "diabetes management," focusing on "the impact of a specific diet on blood sugar levels in Type 2 diabetes patients" can yield more precise and practical insights.

Feasibility is another crucial aspect to consider. Ensure that the necessary resources, including time, funding, and access to data or study participants, are available to complete the research effectively. Ethical considerations should be addressed, mainly when human subjects are involved. This involves obtaining the appropriate approvals and ensuring the study design protects participants' rights and well-being.

Lastly, the topic should be innovative and advance medical knowledge or practice. Aim to explore new perspectives, challenge existing assumptions, or investigate novel treatments or interventions. By selecting a topic that pushes the boundaries of understanding herbal medicine, researchers can significantly impact trends in the field and contribute to meaningful advancements in medicine.

150 medical research topics for college students

• Impact of lifestyle changes on hypertension management
• Genetic predispositions to heart disease
• Advances in minimally invasive heart surgery
• Role of diet in preventing cardiovascular diseases
• Efficacy of new anticoagulants in stroke prevention
• Long-term effects of statins on heart health
• Emerging treatments for congestive heart failure
• Non-invasive techniques for detecting coronary artery disease
• Impact of mental health on cardiac health
• Role of inflammation in atherosclerosis development
• Immunotherapy for advanced melanoma
• Genetic markers for early cancer detection
• Impact of diet and lifestyle on cancer prognosis
• New targeted therapies for breast cancer
• Role of microRNA in cancer progression
• Advances in radiotherapy for brain tumors
• Psychological support for cancer patients
• Personalized medicine in oncology
• Impact of environmental toxins on cancer incidence
• Survivorship and quality of life post-cancer treatment
• New treatments for Alzheimer's disease
• Role of genetics in multiple sclerosis
• Advances in the understanding of Parkinson's disease
• Impact of sleep disorders on neurological health
• Efficacy of new migraine treatments
• Neuroplasticity in stroke recovery
• Role of gut microbiome in neurodegenerative diseases
• Emerging therapies for epilepsy
• Impact of chronic stress on brain health
• Non-pharmacological interventions for ADHD
• Vaccination and childhood disease prevention
• Impact of screen time on child development
• Pediatric obesity and associated health risks
• Advances in neonatal care
• Genetic disorders in children and early interventions
• Efficacy of behavioral therapies for autism
• Role of nutrition in childhood growth and development
• Preventing and treating pediatric asthma
• Long-term outcomes of premature birth
• Pediatric mental health and early intervention

Endocrinology

• New treatments for Type 1 diabetes
• Impact of thyroid disorders on overall health
• Advances in understanding insulin resistance
• Role of hormones in metabolic syndrome
• Long-term effects of hormone replacement therapy
• Efficacy of new medications for osteoporosis
• Relationship between stress and endocrine disorders
• Impact of endocrine disruptors on health
• Role of diet and exercise in managing diabetes
• Advances in adrenal gland disorder treatments

Infectious Diseases

• Impact of antibiotic resistance on public health
• New vaccines for emerging infectious diseases
• Role of climate change in disease spread
• Advances in HIV treatment and prevention
• Efficacy of antiviral therapies for hepatitis C
• Impact of global travel on infectious disease transmission
• Role of the microbiome in infection prevention
• Emerging zoonotic diseases
• Efficacy of new tuberculosis treatments
• Strategies for preventing hospital-acquired infections
• Advances in the treatment of depression
• Impact of social media on mental health
• Role of genetics in psychiatric disorders
• Efficacy of cognitive-behavioral therapy for anxiety
• Long-term effects of antipsychotic medications
• Role of Lifestyle changes in managing bipolar disorder
• Impact of trauma on mental health
• Emerging treatments for PTSD
• Role of neurobiology in addiction
• Efficacy of mindfulness-based therapies
• Insomnia effect on patients with mental health conditions

Public Health

• Impact of public health policies on smoking rates
• Role of community programs in obesity prevention
• Strategies for reducing health disparities
• Impact of urbanization on public health
• Efficacy of health education programs
• Role of public health in disaster preparedness
• Advances in global health initiatives
• Impact of socioeconomic status on health outcomes
• Role of vaccination in public health
• Efficacy of public health interventions for substance abuse
• Impact of public health regulations on social behavior and health outcomes amid COVID-19

Dermatology

• Advances in the treatment of psoriasis
• Role of diet in managing acne
• Efficacy of new therapies for eczema
• Impact of environmental factors on skin health
• Role of genetics in skin disorders
• Advances in melanoma detection
• Impact of skincare products on skin health
• Role of microbiome in skin diseases
• Efficacy of laser treatments for skin conditions
• Strategies for preventing skin cancer

Gastroenterology

• Impact of diet on gut health
• Advances in the treatment of inflammatory bowel disease
• Role of probiotics in digestive health
• Efficacy of new therapies for irritable bowel syndrome
• Effect of gut microbiome on overall health
• Role of genetics in gastrointestinal disorders
• Advances in colorectal cancer screening
• Efficacy of dietary interventions for celiac disease
• Impact of chronic stress on digestive health
• Strategies for managing liver diseases
• Impact of electronic health records on gastroenterology research

Pulmonology

• Advances in asthma management
• Role of genetics in lung diseases
• Impact of air pollution on respiratory health
• Efficacy of new treatments for COPD
• Role of Lifestyle changes in managing Sleep Apnea
• Advances in lung cancer treatment
• Effect of Smoking Cessation Programs
• Efficacy of pulmonary rehabilitation
• Role of diet in respiratory health
• Strategies for managing chronic bronchitis
• Advances in kidney transplant techniques
• Role of diet in managing kidney disease
• Impact of hypertension on kidney health
• Efficacy of new treatments for chronic kidney disease
• Role of genetics in nephrological disorders
• Advances in dialysis technology
• Impact of diabetes on kidney health
• Efficacy of lifestyle interventions for kidney stones
• Role of hydration in preventing kidney diseases
• Strategies for early detection of kidney disorders

Orthopedics

• Advances in joint replacement surgery
• Role of physical therapy in managing osteoarthritis
• Efficacy of new treatments for osteoporosis
• Impact of sports on musculoskeletal health
• Role of genetics in orthopedic disorders
• Advances in minimally invasive orthopedic surgery
• Efficacy of regenerative therapies for bone injuries
• Role of nutrition in bone health
• Strategies for preventing sports injuries
• Impact of aging on musculoskeletal health

Ophthalmology

• Advances in cataract surgery techniques
• Role of genetics in eye diseases
• Impact of screen time on vision health
• Efficacy of new treatments for glaucoma
• Role of diet in maintaining eye health
• Advances in retinal disease management
• Efficacy of laser eye surgery
• Strategies for preventing macular degeneration
• Role of lifestyle changes in managing dry eye syndrome
• Impact of environmental factors on eye health

Rheumatology

• Advances in the treatment of rheumatoid arthritis
• Role of genetics in autoimmune disorders
• Efficacy of new therapies for lupus
• Impact of diet on inflammatory conditions
• Role of physical activity in managing arthritis
• Advances in understanding fibromyalgia
• Efficacy of biologic drugs in rheumatology
• Impact of chronic inflammation on overall health
• Strategies for managing gout
• Role of complementary therapies in rheumatic diseases

Selecting a Medical Research Paper Topic

Choosing a good medical research paper topic is a critical first step in the research process, influencing the direction and impact of the study. A well-chosen topic should address a significant and current issue within the medical field, ensuring relevance and the potential to contribute valuable insights to ongoing medical discussions and advancements. By focusing research projects on areas of primary care that need further exploration, researchers can make meaningful contributions to the body of medical knowledge.

A specific and well-defined topic allows for a focused investigation, leading to detailed and actionable findings for future medical students and others. Narrowing the scope helps researchers delve deeper into the subject matter, enhancing the quality and precision of the research. This approach benefits the study and ensures that the results are practical and applicable in real-world medical scenarios. Additionally, the feasibility of the topic, considering available resources and ethical considerations, is crucial for completing the research.

Innovative research topics that push the boundaries of current understanding are essential for driving progress in medicine. Researchers can significantly impact the field by exploring new perspectives, challenging existing assumptions, and investigating novel treatments or interventions for chronic diseases. Such groundbreaking research has the potential to revolutionize patient care and improve health outcomes on a broader scale.

If you're embarking on your medical research journey, start by identifying a topic that not only fascinates you but also meets the criteria of significance, specificity, feasibility, and innovation. Dive into current literature, consult with experts, and consider the practical implications of your research. By choosing a compelling topic, you'll set the stage for a successful and impactful study that can contribute to advancing medical science and improving patient care. Don't hesitate to seek guidance and support from your peers and mentors throughout this process, as collaboration and feedback are invaluable in refining your research focus.

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Written by David Kidwell

David is one of those experienced content creators from the United Kingdom who has a high interest in social issues, culture, and entrepreneurship. He always says that reading, blogging, and staying aware of what happens in the world is what makes a person responsible. He likes to learn and share what he knows by making things inspiring and creative enough even for those students who dislike reading.

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Study Design in Medical Research

Bernd röhrig.

1 Institut für Medizinische Biometrie, Epidemiologie und Informatik (IMBEI), Johannes Gutenberg-Universität Mainz

Jean-Baptist du Prel

2 Zentrum Präventive Pädiatrie, Zentrum für Kinder- und Jugendmedizin, Johannes Gutenberg-Universität Mainz

Maria Blettner

The scientific value and informativeness of a medical study are determined to a major extent by the study design. Errors in study design cannot be corrected afterwards. Various aspects of study design are discussed in this article.

Six essential considerations in the planning and evaluation of medical research studies are presented and discussed in the light of selected scientific articles from the international literature as well as the authors’ own scientific expertise with regard to study design.

The six main considerations for study design are the question to be answered, the study population, the unit of analysis, the type of study, the measuring technique, and the calculation of sample size.

Conclusions

This article is intended to give the reader guidance in evaluating the design of studies in medical research. This should enable the reader to categorize medical studies better and to assess their scientific quality more accurately.

Medical research studies can be split into five phases—planning, performance, documentation, analysis, and publication ( 1 , 2 ). Aside from financial, organizational, logistical and personnel questions, scientific study design is the most important aspect of study planning. The significance of study design for subsequent quality, the relability of the conclusions, and the ability to publish a study are often underestimated ( 1 ). Long before the volunteers are recruited, the study design has set the points for fulfilling the study objectives. In contrast to errors in the statistical evaluation, errors in design cannot be corrected after the study has been completed. This is why the study design must be laid down carefully before starting and specified in the study protocol.

The term "study design" is not used consistently in the scientific literature. The term is often restricted to the use of a suitable type of study. However, the term can also mean the overall plan for all procedures involved in the study. If a study is properly planned, the factors which distort or bias the result of a test procedure can be minimized ( 3 , 4 ). We will use the term in a comprehensive sense in the present article. This will deal with the following six aspects of study design: the question to be answered, the study population, the type of study, the unit of analysis, the measuring technique, and the calculation of sample size—, on the basis of selected articles from the international literature and our own expertise. This is intended to help the reader to classify and evaluate the results in publications. Those who plan to perform their own studies must occupy themselves intensively with the issue of study design.

Question to be answered

The question to be answered by the research is of decisive importance for study planning. The research worker must be clear about the objectives. He must think very carefully about the question(s) to be answered by the study. This question must be operationalized, meaning that it must be converted into a measurable and evaluable form. This demands an adequate design and suitable measurement parameters. A distinction must be made between the main questions to be answered and secondary questions. The result of the study should be that open questions are answered and possibly that new hypotheses are generated. The following questions are important: Why? Who? What? How? When? Where? How many? The question to be answered also implies the target group and should therefore be very precisely formulated. For example, the question should not be "What is the quality of life?", but must specify the group of patients (e.g. age), the area (e.g. Germany), the disease (e.g. mammary carcinoma), the condition (e.g. tumor stage 3), perhaps also the intervention (e.g. after surgery), and what endpoint (in this case, quality of life) is to be determined with which method (e.g. the EORTC QLQ-C30 questionnaire) at what point in time. Scientific questions are often not only purely descriptive, but also include comparisons, for example, between two groups, or before and after the intervention. For example, it may be interesting to compare the quality of life of breast cancer patients with women of the same age without cancer.

The research worker specifies the question to be answered, and whether the study is to be evaluated in a descriptive, exploratory or confirmatory manner. Whereas in a descriptive study the units of analysis are to be described by the recorded variables (e.g. blood parameters or diagnosis), the aim in an exploratory analysis is to recognize connections between variables, to evaluate these and to formulate new hypotheses. On the other hand, confirmatory analyses are planned to provide statistical proofs by testing specified study hypotheses.

The question to be answered also determines the type and extent of the data to be recorded. This specifies which data are to be recorded at which point in time. In this case, less is often more. Data irrelevant to the question(s) to be answered should not be collected for the moment. If too many variables are recorded at too many time points, this can lead to low participation rates, high dropout rates, and poor compliance from the volunteers. The experience is then that not all data are evaluated.

The question to be answered and the strategy for evaluation must be specified in the study protocol before the study is started.

Study population

The question to be answered by the study implies that there is a target group for whom this is to be clarified. Nevertheless, the research worker is not primarily interested in the observed study population, but in whether the results can be transferred to the target population. Accordingly, statistical test procedures must be used to generalize the results from the sample for the whole population ( figure 1 ).

Connection between overall population and study population/data

The sample can be highly representative of the study population if it is properly selected. This can be attained with defined and selective inclusion and exclusion criteria, such as sex, age, and tumor stage. Study participants may be selected randomly, for example, by random selection through the residents’ registration office, or consecutively, for example, all patients in a clinical department in the course of one year.

With a selective sample, a statement can only be made about a population corresponding to these selection criteria. The possibility of generalizing the results may, for example, be greatly influenced by whether the patients come from a specialist practice, a specialized hospital department or from several different practices.

The possibility of generalization may also be influenced by the decision to perform the study at a single institution or site, or at several (multicenter study). The advantages of a multicenter study are that the required number of patients can be reached within a shorter period and that the results can more readily be generalized, as they are from different treatment centers. This raises the external validity.

Type of study

Before the study type is specified, the research worker must be clear about the category of research. There is a distinction in principle between research on primary data and research on secondary data.

Research on primary data means performing the actual scientific studies, recording the primary study data. This is intended to answer scientific questions and to gain new knowledge.

In contrast, research on secondary results involves the analysis of studies which have already been performed and published. This may include (renewed) analysis of recorded data, perhaps from a register, from population statistics, or from studies. Another objective may be to win a comprehensive overview of the current state of research and to come to appropriate conclusions. In secondary data research, a distinction is made between narrative reviews, systematic reviews, and meta-analyses.

The underlying question to be answered also influences the selection of the type of study. In primary research, experimental, clinical and epidemiological research are distinguished.

Experimental research includes applied studies, such as animal experiments, cell studies, biochemical and physiological investigations, and studies on material properties, as well as the development of analytical and biometric procedures.

Clinical research includes interventional and noninterventional studies. The objective of interventional clinical studies (clinical trials) is "to study or demonstrate the clinical or pharmacological activities of drugs" and "to provide convincing evidence of the safety or efficacy of drugs" (AMG, German Drugs Act §4) ( 5 ). In clinical studies, patients are randomly assigned to treatment groups. In contrast, noninterventional clinical studies are observational studies, in which patients are given an individually specified treatment ( 6 , 7 ).

Epidemiological research studies the distribution and changes with time of the frequency of diseases and of their causes. Experimental studies are distinguished from observational studies ( 7 , 8 ). Interventional studies (such as vaccination, addition of food additives, fluoride addition to drinking water) are of experimental character. Examples of observational epidemiological studies include cohort studies, case control studies, cross-sectional studies, and ecological studies.

A subsequent article will discuss the different study types in detail.

Unit of analysis

The unit of analysis (investigational unit) must be specified before starting a medical study. In a typical clinical study, the patient is the unit of analysis. However, the unit of analysis may also be a technical model, hereditary information, a cell, a cellular structure, an organ, an organ system, a single test individual (animal or man), or specified subgroup or the population of a region or of a country. In systematic reviews, the unit of analysis is a single study. The sample then includes the total of all units of analysis. The interesting information or data (observations, variables, characteristics) are recorded for the statistical units. For example, if the heart is being investigated in a patient (the unit of analysis), the heart rate may be measured as a characteristic of performance.

The selection of the unit of analysis influences the interpretation of the study results. It is therefore important for statistical reasons to know whether the units of analysis are dependent or independent of each other with respect to the outcome parameter. This distinction is not always easy. For example, if the teeth of test persons are the unit of analysis, it must be clarified whether these are independent with respect to the question to be answered (i.e. from different test persons) or dependent (i.e. from the same test person). Teeth in the mouth of a single test person are generally dependent, as specific factors, such as nutrition and teeth cleaning habits, act on all teeth in the mouth in the same way. On the other hand, extracted teeth are generally independent study objects, as there are no longer any shared factors which influence them. This is particularly the case when the teeth are subject to additional preparation, for example, cutting or grinding. On the other hand, if the observations are on tooth characteristics developed before extraction, these characteristics must be regarded as dependent.

Measuring technique

The term "measuring technique" includes the use of measuring instruments and the method of measurement.

Use of measuring instruments

Measuring instruments include instruments which specifically record measuring data (such as blood pressure or laboratory parameters), as well as data collection with standardized or self-designed questionnaires (for example, quality of life, depression, or satisfaction).

During the validation of a measuring instrument, its quality and practicability are evaluated using statistical parameters. Unfortunately, the nomenclature is not fully standardized and also depends on the special area (for example, chemical analysis, psychological studies with questionnaires, or diagnostic studies). It is always the case that a measuring instrument of high quality should be of high precision and validity.

Precision describes the extent to which a measuring technique consistently provides the same results if the measurement is repeated ( 9 ). The reliability (or precision) provides information on the precision or the occurrence of random errors. If the precision is low, the correlation coefficients are low, measurements are imprecise and a larger sample size is needed ( 9 ). On the other hand, the validity (accuracy of the mean or trueness) of a measuring instrument is high if it measures exactly what it is supposed to measure. Thus the validity provides information on the occurrence of systematic errors ( 10 ). Whereas the precision describes the difference (variance) between repeated measurements, the validity reflects the difference between the measured and true parameter ( 10 ). Figure 2 portrays the terms, using a target as a model.

Portrayal of the terms reliability (precision) and validity (trueness) using a target

Reliability and validity are subsumed in the term accuracy ( 11 , 12 ). The accuracy is only high when both the precision and the validity are high. Table 1 summarizes the important terms to validate a measurement method.

The problem is not only that the measurements may be invalid or false, but also that the measurements may lead to erroneous conclusions. External and internal validity can be distinguished ( 13 ). External validity means the possibility of generalizing the study results for the study population to the target population. The internal validity is the validity of a result for the actual question to be answered. This can be optimized by detailed planning, defined inclusion and exclusion criteria, and reduction of external interfering factors.

Measurement plan

The measurement plan describes the number and time points of the measurements to be performed. To obtain comparable and objective measurements, the measurement conditions must be standardized. For example, clinical study measurements such as blood pressure must always be performed at the same time, in the same room, in the same position, with the same instrument, and by the same person. If there are differences, for example in the investigator, measuring instrument, analytical laboratory or recording time, it must be established that the measurements are in agreement ( 10 , 13 ).

The type of scale used for the recorded parameter is also of decisive importance. Putting it simply, metric scales are superior to ordinal scales, which are superior to nominal scales. The type of scale is so important, as both descriptive statistics and statistical test procedures depend on it. Transformation from a higher to a lower scale type is in principle possible, although the converse is impossible. For example, the hemoglobin content may be determined with a metric scale (e.g. as g/dL). It can then be transformed to an ordinal scale (e.g. low, normal and high hemoglobin status), but not conversely.

Calculation of sample size

Whatever the study design, a calculation must be performed before the start of the study to estimate the necessary number of units of analysis (for example, patients) to answer the main study question ( 14 – 16 ). This requires calculation of sample size, exploiting knowledge of the expected effect (for example, the clinically relevant difference) and its scatter (for example, standard deviation). These may be determined in preliminary studies or from published information. It is generally true that a large sample is required to discover a small difference. The sample must also be large if the scatter of the outcome parameter is large in the study groups. Sample size planning helps to ensure that the study is large enough, but not excessively large. The sample size is often restricted by the available time and/or by the budget. This is not in accordance with good scientific practice. If the sample is small, the power will also be low, bringing the risk that real differences will not be identified ( 16 , 17 ). There are both ethical problems—stress to patients, possibly random allocation of therapy—and economic problems—financial, structural, and with regard to personnel—which make it difficult to justify a study which is either too large or not large enough ( 16 – 19 ). The research worker has to consider whether alternative procedures might be possible, such as increasing the time available, the personnel or the funding, or whether a multicenter study should be performed in collaboration with colleagues.

Planning, performance, documentation, analysis, and publication are the component parts of medical studies ( 1 , 2 ). Study design is of decisive importance in planning. This not only lays down the statistical analysis, but also ultimately the reliability of the conclusions and the significance and implementation of the study results ( 2 ). A six point checklist can be used for the rapid evaluation of the study design ( table 2 ).

According to Sackett, about two thirds of 56 typical errors in studies are connected to errors in design and performance ( 20 ). This cannot be corrected once the data have been collected. This makes the study less convincing. As a consequence, the design must be precisely planned before starting the study and this must be laid down in the study protocol. This requires a great deal of time.

In the final analysis, studies with poor design are unethical. Test persons (or animals) are subjected to unnecessary stress and research capacity is wasted ( 21 , 22 ). Medical studies must consider both individual ethics (protection of the individual) and collective ethics (benefit for society) ( 22 ). The size of medical studies is often too small, so that the power is also too small ( 23 ). For this reason, a real difference—for example, between the activity of two therapies—is either unidentified or only described imprecisely ( 24 ). Low power is the result if the study is too small, the difference between the study groups is too small, or the scatter of the measurements is too great. Sterne demands that the quality of studies should be increased by increasing their size and increasing the precision of measurement ( 25 ). On the other hand, if the study is too large, unnecessarily many test persons (or animals) are exposed to stress and resources (such as personnel or financial resources) are wasted. It is therefore necessary to evaluate the feasibility of a study during the planning phase by calculating the sample size. It may be necessary to take suitable measures to ensure that the power is adequate. The excuse that there is not enough time or money is misplaced. The power may be increased by reducing the heterogeneity, improving measurement precision, or by cooperation in multicenter studies. Much more new knowledge is won from a single accurately performed, well designed study of adequate size than from several inadequate studies.

Only adequately planned studies give results which can be published in high quality journals. Planning errors and inadequacies can no longer be corrected once the study has been completed. It is therefore advisable to consult an experienced biometrician during the planning phase of the study ( 1 , 16 , 17 , 18 ).

Acknowledgments

Translated from the original German by Rodney A. Yeates, M.A., Ph.D.

Conflict of interest statement

The authors declare that no conflict of interest exists according to the guidelines of the International Committee of Medical Journal Editors.