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Medical Research

How to conduct research as a medical student, this article will address how to conduct research as a medical student, including details on different types of research, how to go about constructing an idea and other practical advice., kevin seely, oms iv.

Student Doctor Seely attends the Rocky Vista University College of Osteopathic Medicine.

In addition to good grades, test performance, and notable characteristics, it is becoming increasingly important for medical students to participate in and publish research. Residency programs appreciate seeing that applicants are interested in improving the treatment landscape of medicine through the scientific method.

Many medical students also recognize that research is important. However, not all schools emphasize student participation in research or have associations with research labs. These factors, among others, often leave students wanting to do research but unsure of how to begin. This article will address how to conduct research as a medical student, including details on different types of research, how to go about constructing an idea, and other practical advice.

Types of research commonly conducted by medical students

This is not a comprehensive list, but rather, a starting point.

Case reports and case series

Case reports are detailed reports of the clinical course of an individual patient. They usually describe an unusual or novel occurrence or provide new evidence related to a specific pathological entity and its treatment. Advantages of case reports include a relatively fast timeline and little to no need for funding. A disadvantage, though, is that these contribute the most basic and least powerful scientific evidence and provide researchers with minimal exposure to the scientific process.

Case series, on the other hand, look at multiple patients retrospectively. In addition, statistical calculations can be performed to achieve significant conclusions, rendering these studies great for medical students to complete to get a full educational experience.

Clinical research

Clinical research is the peak of evidence-based medical research. Standard study designs include case-controlled trials, cohort studies or survey-based research. Clinical research requires IRB review, strict protocols and large sample sizes, thus requiring dedicated time and often funding. These can serve as barriers for medical students wanting to conduct this type of research. Be aware that the AOA offers students funding for certain research projects; you can learn more here . This year’s application window has closed, but you can always plan ahead and apply for the next grant cycle.

The advantages of clinical research include making a significant contribution to the body of medical knowledge and obtaining an understanding of what it takes to conduct clinical research. Some students take a dedicated research year to gain experience in this area.

Review articles

A literature review is a collection and summarization of literature on an unresolved, controversial or novel topic. There are different categories of reviews, including meta-analyses, systematic reviews and traditional literature reviews, offering very high, high and modest evidentiary value, respectively. Advantages of review articles include the possibility of remote collaboration and developing expertise on the subject matter. Disadvantages can include the time needed to complete the review and the difficulty of publishing this type of research.

Forming an idea

Research can be inspiring and intellectually stimulating or somewhat painful and dull. It’s helpful to first find an area of medicine in which you are interested and willing to invest time and energy. Then, search for research opportunities in this area. Doing so will make the research process more exciting and will motivate you to perform your best work. It will also demonstrate your commitment to your field of interest.

Think carefully before saying yes to studies that are too far outside your interests. Having completed research on a topic about which you are passionate will make it easier to recount your experience with enthusiasm and understanding in interviews. One way to refine your idea is by reading a recent literature review on your topic, which typically identifies gaps in current knowledge that need further investigation.

Finding a mentor

As medical students, we cannot be the primary investigator on certain types of research studies. So, you will need a mentor such as a DO, MD or PhD. If a professor approaches you about a research study, say yes if it’s something you can commit to and find interesting.

More commonly, however, students will need to approach a professor about starting a project. Asking a professor if they have research you can join is helpful, but approaching them with a well-thought-out idea is far better. Select a mentor whose area of interest aligns with that of your project. If they seem to think your idea has potential, ask them to mentor you. If they do not like your idea, it might open up an intellectual exchange that will refine your thinking. If you proceed with your idea, show initiative by completing the tasks they give you quickly, demonstrating that you are committed to the project.

Writing and publishing

Writing and publishing are essential components of the scientific process. Citation managers such as Zotero, Mendeley, and Connected Papers are free resources for keeping track of literature. Write using current scientific writing standards. If you are targeting a particular journal, you can look up their guidelines for writing and referencing. Writing is a team effort.

When it comes time to publish your work, consult with your mentor about publication. They may or may not be aware of an appropriate journal. If they’re not, Jane , the journal/author name estimator, is a free resource to start narrowing down your journal search. Beware of predatory publishing practices and aim to submit to verifiable publications indexed on vetted databases such as PubMed.

One great option for the osteopathic profession is the AOA’s Journal of Osteopathic Medicine (JOM). Learn more about submitting to JOM here .

My experience

As a second-year osteopathic medical student interested in surgery, my goal is to apply to residency with a solid research foundation. I genuinely enjoy research, and I am a member of my institution’s physician-scientist co-curricular track. With the help of amazing mentors and co-authors, I have been able to publish a literature review and a case-series study in medical school. I currently have some additional projects in the pipeline as well.

My board exams are fast approaching, so I will soon have to adjust the time I am currently committing to research. Once boards are done, though, you can bet I will be back on the research grind! I am so happy to be on this journey with all my peers and colleagues in medicine. Research is a great way to advance our profession and improve patient care.

 Keys to success

Research is a team effort. Strive to be a team player who communicates often and goes above and beyond to make the project a success. Be a finisher. Avoid joining a project if you are not fully committed, and employ resiliency to overcome failure along the way. Treat research not as a passive process, but as an active use of your intellectual capability. Push yourself to problem-solve and discover. You never know how big of an impact you might make.

Disclaimers:

Human subject-based research always requires authorization and institutional review before beginning. Be sure to follow your institution’s rules before engaging in any type of research.

This column was written from the perspective from a current medical student with the review and input from my COM’s director of research and scholarly activity, Amanda Brooks, PhD. 

Related reading:

H ow to find a mentor in medical school

Tips on surviving—and thriving—during your first year of medical school

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The best and worst states for doctors in 2024, making a splash, being a do in a heavily md residency program: what surprised me, 6 states in 12 months: a guide to life on the road during fourth year, business + medicine, how independent physician associations can make private practice more profitable, ‘let your light so shine … ‘, the 4th wave of osteopathic medicine: re-establishing osteopathic distinctiveness, more in training.

Fourth year is what you make it. Rachel Pray, OMS IV, shares how she embraced travel and adventure as much as possible during her fourth year.

I was incredibly nervous to join a large MD-dominant internal medicine residency, but I was pleasantly surprised by how much my osteopathic training helped me excel.

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Participating in Health Research Studies

What is health research.

• Is Health Research Safe?
• Is Health Research Right for Me?
• Types of Health Research

The term "health research," sometimes also called "medical research" or "clinical research," refers to research that is done to learn more about human health. Health research also aims to find better ways to prevent and treat disease. Health research is an important way to help improve the care and treatment of people worldwide.

Have you ever wondered how certain drugs can cure or help treat illness? For instance, you might have wondered how aspirin helps reduce pain. Well, health research begins with questions that have not been answered yet such as:

"Does a certain drug improve health?"

To gain more knowledge about illness and how the human body and mind work, volunteers can help researchers answer questions about health in studies of an illness. Studies might involve testing new drugs, vaccines, surgical procedures, or medical devices in clinical trials . For this reason, health research can involve known and unknown risks. To answer questions correctly, safely, and according to the best methods, researchers have detailed plans for the research and procedures that are part of any study. These procedures are called "protocols."

An example of a research protocol includes the process for determining participation in a study. A person might meet certain conditions, called "inclusion criteria," if they have the required characteristics for a study. A study on menopause may require participants to be female. On the other hand, a person might not be able to enroll in a study if they do not meet these criteria based on "exclusion criteria." A male may not be able to enroll in a study on menopause. These criteria are part of all research protocols. Study requirements are listed in the description of the study.

A Brief History

While a few studies of disease were done using a scientific approach as far back as the 14th Century, the era of modern health research started after World War II with early studies of antibiotics. Since then, health research and clinical trials have been essential for the development of more than 1,000 Food and Drug Administration (FDA) approved drugs. These drugs help treat infections, manage long term or chronic illness, and prolong the life of patients with cancer and HIV.

Sound research demands a clear consent process. Public knowledge of the potential abuses of medical research arose after the severe misconduct of research in Germany during World War II. This resulted in rules to ensure that volunteers freely agree, or give "consent," to any study they are involved in. To give consent, one should have clear knowledge about the study process explained by study staff. Additional safeguards for volunteers were also written in the Nuremberg Code and the Declaration of Helsinki .

New rules and regulations to protect research volunteers and to eliminate ethical violations have also been put in to place after the Tuskegee trial . In this unfortunate study, African American patients with syphilis were denied known treatment so that researchers could study the history of the illness. With these added protections, health research has brought new drugs and treatments to patients worldwide. Thus, health research has found cures to many diseases and helped manage many others.

Why is Health Research Important?

The development of new medical treatments and cures would not happen without health research and the active role of research volunteers. Behind every discovery of a new medicine and treatment are thousands of people who were involved in health research. Thanks to the advances in medical care and public health, we now live on average 10 years longer than in the 1960's and 20 years longer than in the 1930's. Without research, many diseases that can now be treated would cripple people or result in early death. New drugs, new ways to treat old and new illnesses, and new ways to prevent diseases in people at risk of developing them, can only result from health research.

Before health research was a part of health care, doctors would choose medical treatments based on their best guesses, and they were often wrong. Now, health research takes the guesswork out. In fact, the Food and Drug Administration (FDA) requires that all new medicines are fully tested before doctors can prescribe them. Many things that we now take for granted are the result of medical studies that have been done in the past. For instance, blood pressure pills, vaccines to prevent infectious diseases, transplant surgery, and chemotherapy are all the result of research.

Medical research often seems much like standard medical care, but it has a distinct goal. Medical care is the way that your doctors treat your illness or injury. Its only purpose is to make you feel better and you receive direct benefits. On the other hand, medical research studies are done to learn about and to improve current treatments. We all benefit from the new knowledge that is gained in the form of new drugs, vaccines, medical devices (such as pacemakers) and surgeries. However, it is crucial to know that volunteers do not always receive any direct benefits from being in a study. It is not known if the treatment or drug being studied is better, the same, or even worse than what is now used. If this was known, there would be no need for any medical studies.

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Types of Study in Medical Research

Bernd röhrig.

1 MDK Rheinland-Pfalz, Referat Rehabilitation/Biometrie, Alzey

Jean-Baptist du Prel

2 Zentrum für Präventive Pädiatrie, Zentrum für Kinder- und Jugendmedizin, Mainz

Daniel Wachtlin

3 Interdisziplinäres Zentrum Klinische Studien (IZKS), Fachbereich Medizin der Universität Mainz

Maria Blettner

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

The choice of study type is an important aspect of the design of medical studies. The study design and consequent study type are major determinants of a study’s scientific quality and clinical value.

This article describes the structured classification of studies into two types, primary and secondary, as well as a further subclassification of studies of primary type. This is done on the basis of a selective literature search concerning study types in medical research, in addition to the authors’ own experience.

Three main areas of medical research can be distinguished by study type: basic (experimental), clinical, and epidemiological research. Furthermore, clinical and epidemiological studies can be further subclassified as either interventional or noninterventional.

Conclusions

The study type that can best answer the particular research question at hand must be determined not only on a purely scientific basis, but also in view of the available financial resources, staffing, and practical feasibility (organization, medical prerequisites, number of patients, etc.).

The quality, reliability and possibility of publishing a study are decisively influenced by the selection of a proper study design. The study type is a component of the study design (see the article "Study Design in Medical Research") and must be specified before the study starts. The study type is determined by the question to be answered and decides how useful a scientific study is and how well it can be interpreted. If the wrong study type has been selected, this cannot be rectified once the study has started.

After an earlier publication dealing with aspects of study design, the present article deals with study types in primary and secondary research. The article focuses on study types in primary research. A special article will be devoted to study types in secondary research, such as meta-analyses and reviews. This article covers the classification of individual study types. The conception, implementation, advantages, disadvantages and possibilities of using the different study types are illustrated by examples. The article is based on a selective literature research on study types in medical research, as well as the authors’ own experience.

Classification of study types

In principle, medical research is classified into primary and secondary research. While secondary research summarizes available studies in the form of reviews and meta-analyses, the actual studies are performed in primary research. Three main areas are distinguished: basic medical research, clinical research, and epidemiological research. In individual cases, it may be difficult to classify individual studies to one of these three main categories or to the subcategories. In the interests of clarity and to avoid excessive length, the authors will dispense with discussing special areas of research, such as health services research, quality assurance, or clinical epidemiology. Figure 1 gives an overview of the different study types in medical research.

Classification of different study types

*1 , sometimes known as experimental research; *2 , analogous term: interventional; *3 , analogous term: noninterventional or nonexperimental

This scheme is intended to classify the study types as clearly as possible. In the interests of clarity, we have excluded clinical epidemiology — a subject which borders on both clinical and epidemiological research ( 3 ). The study types in this area can be found under clinical research and epidemiology.

Basic research

Basic medical research (otherwise known as experimental research) includes animal experiments, cell studies, biochemical, genetic and physiological investigations, and studies on the properties of drugs and materials. In almost all experiments, at least one independent variable is varied and the effects on the dependent variable are investigated. The procedure and the experimental design can be precisely specified and implemented ( 1 ). For example, the population, number of groups, case numbers, treatments and dosages can be exactly specified. It is also important that confounding factors should be specifically controlled or reduced. In experiments, specific hypotheses are investigated and causal statements are made. High internal validity (= unambiguity) is achieved by setting up standardized experimental conditions, with low variability in the units of observation (for example, cells, animals or materials). External validity is a more difficult issue. Laboratory conditions cannot always be directly transferred to normal clinical practice and processes in isolated cells or in animals are not equivalent to those in man (= generalizability) ( 2 ).

Basic research also includes the development and improvement of analytical procedures—such as analytical determination of enzymes, markers or genes—, imaging procedures—such as computed tomography or magnetic resonance imaging—, and gene sequencing—such as the link between eye color and specific gene sequences. The development of biometric procedures—such as statistical test procedures, modeling and statistical evaluation strategies—also belongs here.

Clinical studies

Clinical studies include both interventional (or experimental) studies and noninterventional (or observational) studies. A clinical drug study is an interventional clinical study, defined according to §4 Paragraph 23 of the Medicines Act [Arzneimittelgesetz; AMG] as "any study performed on man with the purpose of studying or demonstrating the clinical or pharmacological effects of drugs, to establish side effects, or to investigate absorption, distribution, metabolism or elimination, with the aim of providing clear evidence of the efficacy or safety of the drug."

Interventional studies also include studies on medical devices and studies in which surgical, physical or psychotherapeutic procedures are examined. In contrast to clinical studies, §4 Paragraph 23 of the AMG describes noninterventional studies as follows: "A noninterventional study is a study in the context of which knowledge from the treatment of persons with drugs in accordance with the instructions for use specified in their registration is analyzed using epidemiological methods. The diagnosis, treatment and monitoring are not performed according to a previously specified study protocol, but exclusively according to medical practice."

The aim of an interventional clinical study is to compare treatment procedures within a patient population, which should exhibit as few as possible internal differences, apart from the treatment ( 4 , e1 ). This is to be achieved by appropriate measures, particularly by random allocation of the patients to the groups, thus avoiding bias in the result. Possible therapies include a drug, an operation, the therapeutic use of a medical device such as a stent, or physiotherapy, acupuncture, psychosocial intervention, rehabilitation measures, training or diet. Vaccine studies also count as interventional studies in Germany and are performed as clinical studies according to the AMG.

Interventional clinical studies are subject to a variety of legal and ethical requirements, including the Medicines Act and the Law on Medical Devices. Studies with medical devices must be registered by the responsible authorities, who must also approve studies with drugs. Drug studies also require a favorable ruling from the responsible ethics committee. A study must be performed in accordance with the binding rules of Good Clinical Practice (GCP) ( 5 , e2 – e4 ). For clinical studies on persons capable of giving consent, it is absolutely essential that the patient should sign a declaration of consent (informed consent) ( e2 ). A control group is included in most clinical studies. This group receives another treatment regimen and/or placebo—a therapy without substantial efficacy. The selection of the control group must not only be ethically defensible, but also be suitable for answering the most important questions in the study ( e5 ).

Clinical studies should ideally include randomization, in which the patients are allocated by chance to the therapy arms. This procedure is performed with random numbers or computer algorithms ( 6 – 8 ). Randomization ensures that the patients will be allocated to the different groups in a balanced manner and that possible confounding factors—such as risk factors, comorbidities and genetic variabilities—will be distributed by chance between the groups (structural equivalence) ( 9 , 10 ). Randomization is intended to maximize homogeneity between the groups and prevent, for example, a specific therapy being reserved for patients with a particularly favorable prognosis (such as young patients in good physical condition) ( 11 ).

Blinding is another suitable method to avoid bias. A distinction is made between single and double blinding. With single blinding, the patient is unaware which treatment he is receiving, while, with double blinding, neither the patient nor the investigator knows which treatment is planned. Blinding the patient and investigator excludes possible subjective (even subconscious) influences on the evaluation of a specific therapy (e.g. drug administration versus placebo). Thus, double blinding ensures that the patient or therapy groups are both handled and observed in the same manner. The highest possible degree of blinding should always be selected. The study statistician should also remain blinded until the details of the evaluation have finally been specified.

A well designed clinical study must also include case number planning. This ensures that the assumed therapeutic effect can be recognized as such, with a previously specified statistical probability (statistical power) ( 4 , 6 , 12 ).

It is important for the performance of a clinical trial that it should be carefully planned and that the exact clinical details and methods should be specified in the study protocol ( 13 ). It is, however, also important that the implementation of the study according to the protocol, as well as data collection, must be monitored. For a first class study, data quality must be ensured by double data entry, programming plausibility tests, and evaluation by a biometrician. International recommendations for the reporting of randomized clinical studies can be found in the CONSORT statement (Consolidated Standards of Reporting Trials, www.consort-statement.org ) ( 14 ). Many journals make this an essential condition for publication.

For all the methodological reasons mentioned above and for ethical reasons, the randomized controlled and blinded clinical trial with case number planning is accepted as the gold standard for testing the efficacy and safety of therapies or drugs ( 4 , e1 , 15 ).

In contrast, noninterventional clinical studies (NIS) are patient-related observational studies, in which patients are given an individually specified therapy. The responsible physician specifies the therapy on the basis of the medical diagnosis and the patient’s wishes. NIS include noninterventional therapeutic studies, prognostic studies, observational drug studies, secondary data analyses, case series and single case analyses ( 13 , 16 ). Similarly to clinical studies, noninterventional therapy studies include comparison between therapies; however, the treatment is exclusively according to the physician’s discretion. The evaluation is often retrospective. Prognostic studies examine the influence of prognostic factors (such as tumor stage, functional state, or body mass index) on the further course of a disease. Diagnostic studies are another class of observational studies, in which either the quality of a diagnostic method is compared to an established method (ideally a gold standard), or an investigator is compared with one or several other investigators (inter-rater comparison) or with himself at different time points (intra-rater comparison) ( e1 ). If an event is very rare (such as a rare disease or an individual course of treatment), a single-case study, or a case series, are possibilities. A case series is a study on a larger patient group with a specific disease. For example, after the discovery of the AIDS virus, the Center for Disease Control (CDC) in the USA collected a case series of 1000 patients, in order to study frequent complications of this infection. The lack of a control group is a disadvantage of case series. For this reason, case series are primarily used for descriptive purposes ( 3 ).

Epidemiological studies

The main point of interest in epidemiological studies is to investigate the distribution and historical changes in the frequency of diseases and the causes for these. Analogously to clinical studies, a distinction is made between experimental and observational epidemiological studies ( 16 , 17 ).

Interventional studies are experimental in character and are further subdivided into field studies (sample from an area, such as a large region or a country) and group studies (sample from a specific group, such as a specific social or ethnic group). One example was the investigation of the iodine supplementation of cooking salt to prevent cretinism in a region with iodine deficiency. On the other hand, many interventions are unsuitable for randomized intervention studies, for ethical, social or political reasons, as the exposure may be harmful to the subjects ( 17 ).

Observational epidemiological studies can be further subdivided into cohort studies (follow-up studies), case control studies, cross-sectional studies (prevalence studies), and ecological studies (correlation studies or studies with aggregated data).

In contrast, studies with only descriptive evaluation are restricted to a simple depiction of the frequency (incidence and prevalence) and distribution of a disease within a population. The objective of the description may also be the regular recording of information (monitoring, surveillance). Registry data are also suited for the description of prevalence and incidence; for example, they are used for national health reports in Germany.

In the simplest case, cohort studies involve the observation of two healthy groups of subjects over time. One group is exposed to a specific substance (for example, workers in a chemical factory) and the other is not exposed. It is recorded prospectively (into the future) how often a specific disease (such as lung cancer) occurs in the two groups ( figure 2a ). The incidence for the occurrence of the disease can be determined for both groups. Moreover, the relative risk (quotient of the incidence rates) is a very important statistical parameter which can be calculated in cohort studies. For rare types of exposure, the general population can be used as controls ( e6 ). All evaluations naturally consider the age and gender distributions in the corresponding cohorts. The objective of cohort studies is to record detailed information on the exposure and on confounding factors, such as the duration of employment, the maximum and the cumulated exposure. One well known cohort study is the British Doctors Study, which prospectively examined the effect of smoking on mortality among British doctors over a period of decades ( e7 ). Cohort studies are well suited for detecting causal connections between exposure and the development of disease. On the other hand, cohort studies often demand a great deal of time, organization, and money. So-called historical cohort studies represent a special case. In this case, all data on exposure and effect (illness) are already available at the start of the study and are analyzed retrospectively. For example, studies of this sort are used to investigate occupational forms of cancer. They are usually cheaper ( 16 ).

Graphical depiction of a prospective cohort study (simplest case [2a]) and a retrospective case control study (2b)

In case control studies, cases are compared with controls. Cases are persons who fall ill from the disease in question. Controls are persons who are not ill, but are otherwise comparable to the cases. A retrospective analysis is performed to establish to what extent persons in the case and control groups were exposed ( figure 2b ). Possible exposure factors include smoking, nutrition and pollutant load. Care should be taken that the intensity and duration of the exposure is analyzed as carefully and in as detailed a manner as possible. If it is observed that ill people are more often exposed than healthy people, it may be concluded that there is a link between the illness and the risk factor. In case control studies, the most important statistical parameter is the odds ratio. Case control studies usually require less time and fewer resources than cohort studies ( 16 ). The disadvantage of case control studies is that the incidence rate (rate of new cases) cannot be calculated. There is also a great risk of bias from the selection of the study population ("selection bias") and from faulty recall ("recall bias") (see too the article "Avoiding Bias in Observational Studies"). Table 1 presents an overview of possible types of epidemiological study ( e8 ). Table 2 summarizes the advantages and disadvantages of observational studies ( 16 ).

1 = slight; 2 = moderate; 3 = high; N/A, not applicable.

*Individual cases may deviate from this pattern.

Selecting the correct study type is an important aspect of study design (see "Study Design in Medical Research" in volume 11/2009). However, the scientific questions can only be correctly answered if the study is planned and performed at a qualitatively high level ( e9 ). It is very important to consider or even eliminate possible interfering factors (or confounders), as otherwise the result cannot be adequately interpreted. Confounders are characteristics which influence the target parameters. Although this influence is not of primary interest, it can interfere with the connection between the target parameter and the factors that are of interest. The influence of confounders can be minimized or eliminated by standardizing the procedure, stratification ( 18 ), or adjustment ( 19 ).

The decision as to which study type is suitable to answer a specific primary research question must be based not only on scientific considerations, but also on issues related to resources (personnel and finances), hospital capacity, and practicability. Many epidemiological studies can only be implemented if there is access to registry data. The demands for planning, implementation, and statistical evaluation for observational studies should be just as high for observational studies as for experimental studies. There are particularly strict requirements, with legally based regulations (such as the Medicines Act and Good Clinical Practice), for the planning, implementation, and evaluation of clinical studies. A study protocol must be prepared for both interventional and noninterventional studies ( 6 , 13 ). The study protocol must contain information on the conditions, question to be answered (objective), the methods of measurement, the implementation, organization, study population, data management, case number planning, the biometric evaluation, and the clinical relevance of the question to be answered ( 13 ).

Important and justified ethical considerations may restrict studies with optimal scientific and statistical features. A randomized intervention study under strictly controlled conditions of the effect of exposure to harmful factors (such as smoking, radiation, or a fatty diet) is not possible and not permissible for ethical reasons. Observational studies are a possible alternative to interventional studies, even though observational studies are less reliable and less easy to control ( 17 ).

A medical study should always be published in a peer reviewed journal. Depending on the study type, there are recommendations and checklists for presenting the results. For example, these may include a description of the population, the procedure for missing values and confounders, and information on statistical parameters. Recommendations and guidelines are available for clinical studies ( 14 , 20 , e10 , e11 ), for diagnostic studies ( 21 , 22 , e12 ), and for epidemiological studies ( 23 , e13 ). Since 2004, the WHO has demanded that studies should be registered in a public registry, such as www.controlled-trials.com or www.clinicaltrials.gov . This demand is supported by the International Committee of Medical Journal Editors (ICMJE) ( 24 ), which specifies that the registration of the study before inclusion of the first subject is an essential condition for the publication of the study results ( e14 ).

When specifying the study type and study design for medical studies, it is essential to collaborate with an experienced biometrician. The quality and reliability of the study can be decisively improved if all important details are planned together ( 12 , 25 ).

Acknowledgments

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

Conflict of interest statement

The authors declare that there is no conflict of interest in the sense of the International Committee of Medical Journal Editors.

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• Published: 05 December 2019

Looking forward 25 years: the future of medicine

Nature Medicine volume  25 ,  pages 1804–1807 ( 2019 ) Cite this article

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This article has been updated

To celebrate the end of our 25th anniversary year, we asked thought leaders and experts in the field to answer one question: What will shape the next 25 years of medical research?

Core member and chair of the faculty, Broad Institute of MIT and Harvard; director, Klarman Cell Observatory, Broad Institute of MIT and Harvard; professor of biology, MIT; investigator, Howard Hughes Medical Institute; founding co-chair, Human Cell Atlas.

For many years, biology and disease appeared ‘too big’ to tackle on a broad level: with millions of genome variants, tens of thousands of disease-associated genes, thousands of cell types and an almost unimaginable number of ways they can combine, we had to approximate a best starting point—choose one target, guess the cell, simplify the experiment.

But we are now on the cusp of an inflection point, where the ‘bigness’ of biomedicine turns into an advantage. We are beginning to see advances towards these goals already, in polygenic risk scores, in understanding the cell and modules of action of genes through genome-wide association studies (GWAS), and in predicting the impact of combinations of interventions. Going forward, our success in harnessing bigness will rely on our ability to leverage structure, prediction and expanded data scale. Disease is highly structured at the molecular, genetic, gene program, cell and tissue levels; acknowledging and understanding this structure can help us reduce the overwhelming lists of genes and variants to a manageable number of meaningful gene modules . We cannot test every possible combination, so we need algorithms to make better computational predictions of experiments we have never performed in the lab or in clinical trials. But only when data are truly big, scaled massively and rich in content, will we have the most effective structuring and prediction power towards building a much-needed Roadmap of Disease for patients.

To achieve this, we need to invest in building the right initiatives—like the Human Cell Atlas and the International Common Disease Alliance—and in new experimental platforms: data platforms and algorithms. But we also need a broader ecosystem of partnerships in medicine that engages interaction between clinical experts and mathematicians, computer scientists and engineers who together will bring new approaches to drive experiments and algorithms to build this Roadmap.

PhD investigator, Howard Hughes Medical Institute; core member, Broad Institute of MIT and Harvard; James and Patricia Poitras Professor of Neuroscience, McGovern Institute for Brain Research, MIT.

Although it is difficult to pinpoint an exact value, it is safe to estimate that more than 250 patients have been treated with gene therapies for monogenic diseases for which there previously were no treatment options. Add in the patients who have received CAR-T therapy, and that number rises into the thousands. This is an enormous success, and it represents the beginning of a fundamental shift in medicine away from treating symptoms of disease and toward treating disease at its genetic roots.

Gene therapy has been under development for more than 30 years, but several recent major advances have tipped the scales toward clinical feasibility, including improved delivery methods and the development of robust molecular technologies for gene editing in human cells. In parallel, affordable genome sequencing has accelerated our ability to identify the genetic causes of disease. With these advances, the stage is set for the widespread use of gene therapy. Already, nearly 1,000 clinical trials testing gene therapies are ongoing, and the pace of clinical development is likely to accelerate.

To fulfil the potential of gene therapy and ensure that all patients have access to this revolutionary treatment, we will need to continue developing delivery approaches that are practical and widely usable, to refine molecular technologies for gene editing, to push our understanding of gene function in health and disease forward, and to engage with all members of society to openly discuss the risks and benefits of gene therapy.

Elizabeth Jaffee

Dana and Albert “Cubby” Broccoli Professor of Oncology, Johns Hopkins School of Medicine; deputy director, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins.

“An ounce of prevention is worth a pound of cure.” Benjamin Franklin said this in reference to fire safety, but it can easily be applied to health too. The twentieth century saw amazing advances aimed at preventing the onset of disease—including vaccines and risk-factor interventions—nearly doubling life expectancy worldwide. Only two decades into the twenty-first century, healthcare has already entered its next phase of rapid advancements. By using precision medicine technologies, genetic vulnerabilities to chronic and deadly diseases at the individual level can now be identified, potentially pre-empting disease decades later.

My hope for the next 25 years is that someday a single blood test could inform individuals of the diseases they are at risk of (diabetes, cancer, heart disease, etc.) and that safe interventions will be available. I am particularly excited about the possibility of developing cancer vaccines. Vaccines targeting the causative agents of cervical and hepatocellular cancers have already proven to be effective. With these technologies and the wealth of data that will become available as precision medicine becomes more routine, new discoveries identifying the earliest genetic and inflammatory changes occurring within a cell as it transitions into a pre-cancer can be expected. With these discoveries, the opportunities to develop vaccine approaches preventing cancers development will grow.

But, as is the case today, prevention technologies can only be fully successful if they are widely available, to reduce unnecessary morbidity and mortality and healthcare costs and further raise life expectancy. Global accessibility is key to reduce global disparities. For these strategies to work, funding agencies should consider prioritizing prevention strategies.

Jeremy Farrar

Director, Wellcome Trust.

Politics, demographics, economics, climate—how the world changes and interacts fundamentally affects all of us. Research is part of that and can help provide solutions to the great challenges we face, but only if the three pillars of science, innovation and society come together in an environment where people and teams can thrive. We must therefore take the opportunity today to shape how the culture of research will develop over the next 25 years.

Building a career in research can be incredibly rewarding, yet it often comes at a cost. The drive for research excellence—to which Wellcome has certainly contributed—has created a culture that cares more about what is achieved than how it is achieved. We can do better, and building a creative, inclusive and open research culture will unleash greater discoveries with greater impact.

Changing culture requires us to acknowledge the issue and then make a long-term commitment. As an independent foundation, Wellcome is able to acknowledge the issue and make that commitment. This is a permanent shift in our thinking. Working openly with, and as part of, the wider research community, we aim to make research inclusive, more inspiring, more fun, more rewarding. As a result, it will contribute even more to making the world a healthier place to live.

John Nkengasong

Director, Africa Centres for Disease Control and Prevention.

Population wise, Africa is the continent of the future. By 2050, it is estimated that its population will be 2.5 billion people. This means that one in every four persons in the world might be an African, with rapidly growing economies and a rising middle class. These demographic changes have important implications for both communicable and noncommunicable disease patterns, including emerging and re-emerging infectious diseases; resistance to antibiotics; and rising rates of cancers, diabetes, cardiovascular diseases and maternal and child deaths. To meet its health challenges by 2050, the continent will have to be innovative in order to leapfrog toward solutions in public health.

Precision medicine will need to take center stage in a new public health order—whereby a more precise and targeted approach to screening, diagnosis, treatment and, potentially, cure is based on each patient’s unique genetic and biologic make-up. For example, universal newborn screening and a more accurate analysis of causes of death in this age group could be established to curb under-five mortality; genetic screening programs could help avoid progression towards aggressive cancers; and medicine side effects could be reduced if tests could predict negative reactions and enable caregivers to proactively prescribe alternative treatments.

In Africa, precision medicine should not be seen from the lens of sequencing whole genomes, diagnosing DNA abnormalities and developing medications targeted to very small populations. Rather, African countries should begin pursuing policy approaches and partnerships to advance precision medicine to meet the African Union’s Agenda 2063 goals. This includes the integration of precision medicine approaches into national strategies to improve healthcare—including genomic data policy—and increase diagnostic capacity, and the creation of biobanks, such as H3Africa, that encompass both physical and bioinformatics facilities.

Executive vice-president, Scripps Research Institute; founder and director, Scripps Research Translational Institute.

Twenty-five years ago, the World Wide Web was just getting off the ground. Therefore, when thinking of the medical research landscape in 25 years, it is reasonable to think big and without limits.

In 2045, I hope we will have developed a planetary health infrastructure based on deep, longitudinal, multimodal human data, ideally collected from and accessible to as many as possible of the 9+ billion people projected to then inhabit the Earth.

This infrastructure, by using hybrid artificial intelligence (AI) models—including various deep neural networks, federated AI, nearest-neighbor analysis and systems yet to be developed—could provide individualized guidance for the prevention and optimal management of medical conditions, acting as a virtual medical coach for patients and a platform for clinicians to review a patient’s real-time, real-world, extensive and cumulative dataset.

Some have projected that, by this juncture, artificial general intelligence (AGI) will have been developed, giving machines enhanced capabilities to perform functions that are not feasible now. Notwithstanding that uncertainty, it is likely that machines’ ability to ingest and process biomedical text at scale—such as the corpus of the up-to-date medical literature—will be used routinely by physicians and patients. Accordingly, the concept of a learning health system will be redefined.

Linda Partridge

Professor, Max Planck Institute for Biology of Ageing.

Human life expectancy has increased over the past 170 years in many parts of the world. Unfortunately, the healthy lifespan has not, and the period of life when a person lives with disability and illness at the end of life is growing, especially in women.

But ageing is malleable, and mounting evidence suggests that late-life ill health can be combated. In laboratory animals, including mice and rhesus monkeys, genetic, lifestyle and pharmacological interventions can increase not only the lifespan, but also the healthspan. In humans, improvements in diet and the implementation of physical exercise regimes can effect major health improvements, but better lifestyle is not enough to prevent age-related diseases.

The big hope is that 25 years from now, medical sciences will have progressed enough to enable people to have healthier and more active lives almost up until their eventual death. Going forward, the direct targeting of mechanisms of ageing, including with existing drugs, presents an opportunity to reduce disability and illness in late life. Sirolimus, an mTORC1 inhibitor, extends the lifespan of laboratory animals and in clinical trials has proved to boost the immune response of older people to vaccination against influenza. Other drugs, such as the combination of desatinib and the BCL-2 inhibitor quercetin, which kill senescent cells, are farther from the clinic but show promise. Plasma from younger mice has been shown to have a beneficial effect on the stem cell function of several tissues in older mice; work to identify the natural metabolites responsible for this effect could open up avenues for translation to the clinic. Geroprotective drugs, which target the underlying molecular mechanisms of ageing, are coming over the scientific and clinical horizons, and may help to prevent the most intractable age-related disease, dementia.

Trevor Mundel

President of Global Health, Bill & Melinda Gates Foundation.

The most essential innovations in medical research over the next 25 years won’t just come from the explorations of bench scientists or the emergence of new technologies. They will come from what we do—as partners across the public and private sectors—to forge a new applied research ecosystem dedicated to the rapid discovery, development and delivery of life-changing tools that have been designed with the end user in mind.

This will mean finding new ways to share clinical data that are as open as possible and as closed as necessary. It will mean moving beyond drug donations toward a new era of corporate social responsibility that encourages biotechnology and pharmaceutical companies to offer their best minds and their most promising platforms. And it will mean working with governments and multilateral organizations much earlier in the product life cycle to finance the introduction of new interventions and to ensure the sustainable development of the health systems that will deliver them. If we focus on these goals, we can deliver on the promise of global health equity.

Josep Tabernero

Vall d’Hebron Institute of Oncology (VHIO); president, European Society for Medical Oncology (2018–2019).

Let’s briefly skip back 25 years. In oncology, who could have predicted that the stunning advances in genome sequencing would come to shape clinical decision-making? Who could have foreseen the increasing availability of genetic patient screenings or the promise of liquid biopsy policing of disease? Very few, which is why it is a fool’s errand to make sweeping predictions. But let’s try.

Over the next 25 years, genomic-driven analysis will continue to broaden the impact of personalized medicine in healthcare globally. Precision medicine will continue to deliver its new paradigm in cancer care and reach more patients. Immunotherapy will deliver on its promise to dismantle cancer’s armory across tumor types.

I also anticipate that AI will help guide the development of individually matched therapies, the harnessing and exchange of big data, and advances in telemedicine to bring crucial medical expertise to more patients everywhere. But the prospect is not all rosy. I worry about the exacerbating burden of comorbidities in cancer patients. We must collectively seek to strengthen and unify medical fields, with particular emphasis on oncology and cardiology. This is an emerging area for collaboration. Implementation research in the prevention and control of cancer will also be critical, as will be the shaping and strengthening of cancer policy-making at the global, national and regional levels.

With continued belief that scientific endeavors should be prioritized to respond to society’s and citizens’ needs, the scientific community must grasp future opportunities to uphold the very ethos of medicine as we continue to push boundaries in discovering new ways to extend and improve patients’ lives.

Pardis Sabeti

Professor, Harvard University & Harvard T.H. Chan School of Public Health and Broad Institute of MIT and Harvard; investigator, Howard Hughes Medical Institute.

A cataclysmic global pandemic is one of the greatest risks to humanity. Over the last 25 years, we have seen SARS, Ebola, Zika and other viruses spread undetected for months, leading to international emergencies and often devastating consequences. Even in the best US hospitals, most infectious diseases are not properly diagnosed or tracked.

But advances in two fields, genomics and information science, can transform our fight against viral threats. Ultrasensitive genome sequencing technologies are enabling the detection and characterization of viruses circulating under the radar. The advent of novel CRISPR, synthetic biology and microfluidic tools have allowed the development of rapid, ultrasensitive point-of-care diagnostics that can be deployed anywhere in the world. The resulting diagnostic and surveillance data can be integrated across healthcare nodes, from rural clinics to city hospitals, thanks to powerful new information systems. Together with advances from AI and other fields, these information systems can aid the rapid detection of infectious threats, to track their spread, and guide public health decision-making.

Over the next 25 years, the development and integration of these tools into an early-warning system embedded into healthcare systems around the world could revolutionize infectious disease detection and response. But this will only happen with a commitment from the global community.

Els Torreele

Executive director, Médecins Sans Frontières Access Campaign.

Of the many biomedical advances made by the scientific community, only those that can generate large financial profits are taken up for development by for-profit companies. This leaves many gaps—but also opportunities—in regard to developing new treatments to meet public health needs.

My hope is that the scientific community will step up and target efforts to develop innovative therapeutics and other health tools for populations across the world. This includes people affected by tuberculosis, hepatitis, Ebola, advanced HIV, neglected tropical diseases, vaccine-preventable diseases, antimicrobial resistance, snakebite—the list goes on. The creativity and brainpower of the global research community are required to find solutions addressing these grave human needs.

But to do this, we need a paradigm shift such that medicines are no longer lucrative market commodities but are global public health goods—available to all those who need them. This will require members of the scientific community to go beyond their role as researchers and actively engage in R&D policy reform mandating health research in the public interest and ensuring that the results of their work benefit many more people. The global research community can lead the way toward public-interest-driven health innovation, by undertaking collaborative open science and piloting not-for-profit R&D strategies that positively impact people’s lives globally.

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Looking forward 25 years: the future of medicine. Nat Med 25 , 1804–1807 (2019). https://doi.org/10.1038/s41591-019-0693-y

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Physician-Scientists

Physician-scientists are physicians (MDs or DOs with or without additional degrees) who devote regular components of their professional effort seeking new knowledge about health, disease, or delivery of patient care through research. While all physicians receive training in medical science, physician-scientists are those who are trained to conduct independent scientific investigation in the laboratory, clinic, or other setting. A physician scientist’s in-depth clinical knowledge of human health and disease, combined with skills in scientific investigation and analysis, make her uniquely resourceful. Physician-scientists are well prepared to detect new threats to human health; develop potential new therapies, treatments, or means of prevention; communicate knowledgeably across disciplines and to lead scientific teams or organizations; and, guide important policy decisions, such as in drug approval.

Historically, physicians were pioneers in medical science, and often relying on only informal scientific training coupled to their intellectual insight and curiosity. Today, however, most physician-scientists complete formal, usually intensive scientific training in addition to their medical education. There are vibrant examples of physician-scientist training programs that accommodate students entering science at different stages of their medical training or early career. At the same time, the knowledge and skills required for medical education and clinical specialization have also increased for all physicians. Beginning in the 1970s, prominent medical leaders publicly raised the question of whether any individuals could continue to master the growing complexities of both medicine and science, while being adequately sustained by medical institutions and health systems that were also changing. They raised such concerns not to sell their profession short, but to call for added attention and resources to the needs of students and early career physician-scientists. Those calls continue to this day, as the National of Institutes of Health finds that the number of younger physician scientists applying for research support is decreasing, and that the average age of these investigators, including first-time applicants, is increasing.

For those that become academic medical faculty, physician-scientists often teach, perform research, and provide clinical service, and embody in each individual the several missions of the academic medical center. The types of science” that physicians engage in has also broadened, from laboratory and clinical investigation, noted above, to research on health services and implementation, population health, community engagement, and health equity (we also expect a growing need for physicians with expert training in emerging data sciences). The AAMC is committed to the nurturing and growth of new physician-scientists.

AAMC Committee on Creating a Physician-Scientist Training and Career Development Home

The AAMC has convened an expert Committee to develop recommendations for medical schools and teaching hospitals to more comprehensively nurture physician-scientists across the continuum of training and early career development. For more information, visit the Committee Roster (PDF) and the Committee Charge (PDF) .

A National Institutes of Health working group recently concluded—confirming decades of earlier concerns—that the nation is failing to adequately renew and advance the physician-scientist workforce, as too few young physicians are attracted into scientific research or – if attracted—find necessary support or guidance lacking at key stages of their professional development. Several AAMC member institutions have begun to create physician-scientists “homes”, which integrate the support for new physician-scientists across career stages and departments. Such homes may be formal programs, networks, or other communities that support the training and development of individuals pursuing physician-scientist careers. The AAMC Committee will focus on constructive, systemic solutions for medical schools and teaching hospitals to ensure needed support.

In all its deliberations, the Committee embraces the variety of physician-scientist careers, from laboratory-based investigation to research in clinics, health systems, and communities, as well as the multiple training pathways, from integrated dual-degree programs to accumulated, distinct educational experiences, through which individuals attain these careers.

National MD-PhD Program Outcomes Study

A report from the AAMC's Group on Graduate Research, Education, and Training (GREAT) that tracks the careers of MD-PhD dual-degree program graduates over 50 years (1964–2014) and highlights results of a research project that explored their career paths.

NIH Advisory Committee to the Director Physician-Scientist Workforce Working Group

An NIH Advisory Committee to the Director Working Group on the Physician-Scientist Workforce issued a report with “recommendations for actions that NIH should take to support a sustainable and diverse clinical research infrastructure, as well as recommendations for actions needed by other relevant stakeholders.”

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The Guide to Becoming a Medical Researcher

• February 1, 2023

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As a medical researcher, your job is to conduct research to improve the health status and longevity of the population. The career revolves around understanding the causes, treatments, and prevention of diseases and medical conditions through rigorous clinical investigations, epidemiological studies, and laboratory experiments. As a medical researcher, simply gaining formal education won’t suffice. You also need to hone your communication, critical thinking, decision-making, data collecting, data analyzing and observational skills. These skill sets will enable you to create a competitive edge in the research industry. On a typical day, a medical researcher would be collecting, interpreting, and analyzing data from clinical trials, working alongside engineering, regulatory, and quality assurance experts to evaluate the risk of medical devices, or maybe even preparing and examining medical samples for causes or treatments of toxicity, disease, or pathogens.

How To Become a Medical Research Doctor?

The roadmap to medical research is a bit tricky to navigate, because it is a profession that demands distinctive skills and expertise along with mandatory formal education. If you harbor an interest in scientific exploration and a desire to break new ground in medical knowledge, the first step is to earn a bachelor’s degree in a related field, such as biology, chemistry, or biochemistry. After completing your undergraduate education, you will need to earn a Medical Degree ( MD ) or a Doctor of Osteopathic Medicine (DO) degree, from a quality institution such as the Windsor university school of Medicine.

After that, the newly minted doctor of medicine (MD) may choose to complete a three-year residency program in a specialty related to medical research, such as internal medicine, pediatrics, or neurology, in addition to a doctor of philosophy (PhD) degree—the part that provides the research expertise. In some  medical school  programs, students may pursue a dual MD-PhD at the same time, which provides training in both medicine and research. They are specifically designed for those who want to become research physicians. Last but not the least, all physician-scientists must pass the first two steps of the United States Medical Learning Examination (USMLE).

Use your fellowship years to hone the research skills necessary to carry out independent research. You may also take courses in epidemiology, biostatistics, and other related fields. In order to publish your research in peer-reviewed journals to establish yourself as a medical researcher. To apply for a faculty position at a medical school, research institute, or hospital. To maintain your position as a medical research doctor, you must publish your research and make significant contributions to the field.

How Much Do Medical Researchers Make?

Having a clear idea of what to earn when you become a medical researcher can help you decide if this is a good career choice for you. The salaries of Medical Researchers in the US range from $26,980 to $155,180, with a median salary of $82,240. There is also room for career advancement and higher earning potential as you gain experience.

The Most Popular Careers in Medical Research

• Medical Scientists  – conduct research and experiments to improve our understanding of diseases and to develop new treatments. They also develop new medical technologies and techniques.
• Biomedical engineers  – design medical devices, such as pacemakers, prosthetics, and imaging machines. They also develop and improve existing medical technologies.
• Clinical Trial Coordinators  – oversee and manage clinical trials, which test new drugs and treatments. They are responsible for recruiting participants, collecting and analyzing data, and ensuring the trial is conducted in compliance with ethical standards.
• Medical Laboratory Technicians  – analyze bodily fluids and tissues to diagnose diseases and conditions. They perform tests using specialized equipment and techniques, and report results to physicians.
• Biostatisticians  – collect statistics to analyze data and test hypotheses in medical research. They design and analyze clinical trials, and use statistical models to understand the causes and effects of diseases.
• Epidemiologists  – study the causes, distribution, and control of diseases in populations. They collect and analyze data, and use their findings to develop strategies for preventing and controlling diseases.
• Pathologists  – diagnose diseases by examining tissues and bodily fluids. They use microscopes and other diagnostic tools to identify and study the changes in tissues caused by disease.
• Genetic Counselors  – help individuals understand and manage the risks associated with inherited genetic disorders. They educate patients about genetic tests and help families make informed decisions about their health.
• Health Services Researchers  – study the delivery of healthcare and identify ways to improve it.
• Medical writers  – write articles, reports, and other materials related to medical research.
• Microbiologists  – study microorganisms, including bacteria and viruses, to understand their behavior and impact on human health.
• Neuroscientists  – study the brain and nervous system to understand the underlying causes of neurological conditions.
• Toxicologists  – study the effects of toxic substances on living organisms and the environment.

Skills You Need to Become a Medical Researcher?

To be a successful medical scientist, you need a range of soft and hard skills to excel in your work. First things first, medical researchers must be able to analyze data, identify patterns, and draw conclusions from their findings. They must be able to think critically, ask relevant questions, and design experiments to answer those questions. Additionally, you should also have the knack of articulating your findings clearly and effectively, be it writing research papers, grant proposals, or technical reports that are clear, concise, and free from errors.

Medical researchers must be proficient in using various computer programs and software to collect, manage, analyze and interpret research data. They must be able to use laboratory equipment and techniques, as well as statistical analysis software and other tools for data analysis. Since medical research involves precise and meticulous work, so you must also pay close attention to detail to ensure that your findings are accurate and reliable. Not to mention, medical researchers often work in teams, so it pays off if you are good at collaborating with others effectively, sharing ideas, and working together to solve complex problems.

Lastly, medical researchers must have a thorough understanding of regulations and ethical guidelines that govern research, such as obtaining informed consent from study participants, ensuring data confidentiality, and adhering to safety protocols.

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77 interesting medical research topics for 2024

Last updated

25 November 2023

Reviewed by

Brittany Ferri, PhD, OTR/L

Medical research is the gateway to improved patient care and expanding our available treatment options. However, finding a relevant and compelling research topic can be challenging.

Use this article as a jumping-off point to select an interesting medical research topic for your next paper or clinical study.

• How to choose a medical research topic

When choosing a research topic , it’s essential to consider a couple of things. What topics interest you? What unanswered questions do you want to address? 

During the decision-making and brainstorming process, here are a few helpful tips to help you pick the right medical research topic:

Focus on a particular field of study

The best medical research is specific to a particular area. Generalized studies are often too broad to produce meaningful results, so we advise picking a specific niche early in the process. 

Maybe a certain topic interests you, or your industry knowledge reveals areas of need.

Look into commonly researched topics

Once you’ve chosen your research field, do some preliminary research. What have other academics done in their papers and projects? 

From this list, you can focus on specific topics that interest you without accidentally creating a copycat project. This groundwork will also help you uncover any literature gaps—those may be beneficial areas for research.

Get curious and ask questions

Now you can get curious. Ask questions that start with why, how, or what. These questions are the starting point of your project design and will act as your guiding light throughout the process. 

For example: 

What impact does pollution have on children’s lung function in inner-city neighborhoods? 

Why is pollution-based asthma on the rise? 

How can we address pollution-induced asthma in young children? 

• 77 medical research topics worth exploring in 2023

Need some research inspiration for your upcoming paper or clinical study? We’ve compiled a list of 77 topical and in-demand medical research ideas. Let’s take a look. 

• Exciting new medical research topics

If you want to study cutting-edge topics, here are some exciting options:

COVID-19 and long COVID symptoms

Since 2020, COVID-19 has been a hot-button topic in medicine, along with the long-term symptoms in those with a history of COVID-19. 

Examples of COVID-19-related research topics worth exploring include:

The long-term impact of COVID-19 on cardiac and respiratory health

COVID-19 vaccination rates

The evolution of COVID-19 symptoms over time

New variants and strains of the COVID-19 virus

Changes in social behavior and public health regulations amid COVID-19

Vaccinations

Finding ways to cure or reduce the disease burden of chronic infectious diseases is a crucial research area. Vaccination is a powerful option and a great topic to research. 

Examples of vaccination-related research topics include:

mRNA vaccines for viral infections

Biomaterial vaccination capabilities

Vaccination rates based on location, ethnicity, or age

Public opinion about vaccination safety 

Artificial tissues fabrication

With the need for donor organs increasing, finding ways to fabricate artificial bioactive tissues (and possibly organs) is a popular research area. 

Examples of artificial tissue-related research topics you can study include:

The viability of artificially printed tissues

Tissue substrate and building block material studies

The ethics and efficacy of artificial tissue creation

• Medical research topics for medical students

For many medical students, research is a big driver for entering healthcare. If you’re a medical student looking for a research topic, here are some great ideas to work from:

Sleep disorders

Poor sleep quality is a growing problem, and it can significantly impact a person’s overall health. 

Examples of sleep disorder-related research topics include:

How stress affects sleep quality

The prevalence and impact of insomnia on patients with mental health conditions

Possible triggers for sleep disorder development

The impact of poor sleep quality on psychological and physical health

How melatonin supplements impact sleep quality

Alzheimer’s and dementia 

Cognitive conditions like dementia and Alzheimer’s disease are on the rise worldwide. They currently have no cure. As a result, research about these topics is in high demand. 

Examples of dementia-related research topics you could explore include:

The prevalence of Alzheimer’s disease in a chosen population

Early onset symptoms of dementia

Possible triggers or causes of cognitive decline with age

Treatment options for dementia-like conditions

The mental and physical burden of caregiving for patients with dementia

• Lifestyle habits and public health

Modern lifestyles have profoundly impacted the average person’s daily habits, and plenty of interesting topics explore its effects. 

Examples of lifestyle and public health-related research topics include:

The nutritional intake of college students

The impact of chronic work stress on overall health

The rise of upper back and neck pain from laptop use

Prevalence and cause of repetitive strain injuries (RSI)

• Controversial medical research paper topics

Medical research is a hotbed of controversial topics, content, and areas of study. 

If you want to explore a more niche (and attention-grabbing) concept, here are some controversial medical research topics worth looking into:

The benefits and risks of medical cannabis

Depending on where you live, the legalization and use of cannabis for medical conditions is controversial for the general public and healthcare providers.

Examples of medical cannabis-related research topics that might grab your attention include:

The legalization process of medical cannabis

The impact of cannabis use on developmental milestones in youth users

Cannabis and mental health diagnoses

CBD’s impact on chronic pain

Prevalence of cannabis use in young people

The impact of maternal cannabis use on fetal development 

Understanding how THC impacts cognitive function

Human genetics

The Human Genome Project identified, mapped, and sequenced all human DNA genes. Its completion in 2003 opened up a world of exciting and controversial studies in human genetics.

Examples of human genetics-related research topics worth delving into include:

Medical genetics and the incidence of genetic-based health disorders

Behavioral genetics differences between identical twins

Genetic risk factors for neurodegenerative disorders

Machine learning technologies for genetic research

Sexual health studies

Human sexuality and sexual health are important (yet often stigmatized) medical topics that need new research and analysis.

As a diverse field ranging from sexual orientation studies to sexual pathophysiology, examples of sexual health-related research topics include:

The incidence of sexually transmitted infections within a chosen population

Mental health conditions within the LGBTQIA+ community

The impact of untreated sexually transmitted infections

Access to safe sex resources (condoms, dental dams, etc.) in rural areas

• Health and wellness research topics

Human wellness and health are trendy topics in modern medicine as more people are interested in finding natural ways to live healthier lifestyles. 

If this field of study interests you, here are some big topics in the wellness space:

Gluten sensitivity

Gluten allergies and intolerances have risen over the past few decades. If you’re interested in exploring this topic, your options range in severity from mild gastrointestinal symptoms to full-blown anaphylaxis. 

Some examples of gluten sensitivity-related research topics include:

The pathophysiology and incidence of Celiac disease

Early onset symptoms of gluten intolerance

The prevalence of gluten allergies within a set population

Gluten allergies and the incidence of other gastrointestinal health conditions

Pollution and lung health

Living in large urban cities means regular exposure to high levels of pollutants. 

As more people become interested in protecting their lung health, examples of impactful lung health and pollution-related research topics include:

The extent of pollution in densely packed urban areas

The prevalence of pollution-based asthma in a set population

Lung capacity and function in young people

The benefits and risks of steroid therapy for asthma

Pollution risks based on geographical location

Plant-based diets

Plant-based diets like vegan and paleo diets are emerging trends in healthcare due to their limited supporting research. 

If you’re interested in learning more about the potential benefits or risks of holistic, diet-based medicine, examples of plant-based diet research topics to explore include:

Vegan and plant-based diets as part of disease management

Potential risks and benefits of specific plant-based diets

Plant-based diets and their impact on body mass index

The effect of diet and lifestyle on chronic disease management

Health supplements

Supplements are a multi-billion dollar industry. Many health-conscious people take supplements, including vitamins, minerals, herbal medicine, and more. 

Examples of health supplement-related research topics worth investigating include:

Omega-3 fish oil safety and efficacy for cardiac patients

The benefits and risks of regular vitamin D supplementation

Health supplementation regulation and product quality

The impact of social influencer marketing on consumer supplement practices

Analyzing added ingredients in protein powders

• Healthcare research topics

Working within the healthcare industry means you have insider knowledge and opportunity. Maybe you’d like to research the overall system, administration, and inherent biases that disrupt access to quality care. 

While these topics are essential to explore, it is important to note that these studies usually require approval and oversight from an Institutional Review Board (IRB). This ensures the study is ethical and does not harm any subjects. 

For this reason, the IRB sets protocols that require additional planning, so consider this when mapping out your study’s timeline. 

Here are some examples of trending healthcare research areas worth pursuing:

The pros and cons of electronic health records

The rise of electronic healthcare charting and records has forever changed how medical professionals and patients interact with their health data. 

Examples of electronic health record-related research topics include:

The number of medication errors reported during a software switch

Nurse sentiment analysis of electronic charting practices

Ethical and legal studies into encrypting and storing personal health data

Inequities within healthcare access

Many barriers inhibit people from accessing the quality medical care they need. These issues result in health disparities and injustices. 

Examples of research topics about health inequities include:

The impact of social determinants of health in a set population

Early and late-stage cancer stage diagnosis in urban vs. rural populations

Affordability of life-saving medications

Health insurance limitations and their impact on overall health

Diagnostic and treatment rates across ethnicities

People who belong to an ethnic minority are more likely to experience barriers and restrictions when trying to receive quality medical care. This is due to systemic healthcare racism and bias. 

As a result, diagnostic and treatment rates in minority populations are a hot-button field of research. Examples of ethnicity-based research topics include:

Cancer biopsy rates in BIPOC women

The prevalence of diabetes in Indigenous communities

Access inequalities in women’s health preventative screenings

The prevalence of undiagnosed hypertension in Black populations

• Pharmaceutical research topics

Large pharmaceutical companies are incredibly interested in investing in research to learn more about potential cures and treatments for diseases. 

If you’re interested in building a career in pharmaceutical research, here are a few examples of in-demand research topics:

Cancer treatment options

Clinical research is in high demand as pharmaceutical companies explore novel cancer treatment options outside of chemotherapy and radiation. 

Examples of cancer treatment-related research topics include:

Stem cell therapy for cancer

Oncogenic gene dysregulation and its impact on disease

Cancer-causing viral agents and their risks

Treatment efficacy based on early vs. late-stage cancer diagnosis

Cancer vaccines and targeted therapies

Immunotherapy for cancer

Pain medication alternatives

Historically, opioid medications were the primary treatment for short- and long-term pain. But, with the opioid epidemic getting worse, the need for alternative pain medications has never been more urgent. 

Examples of pain medication-related research topics include:

Opioid withdrawal symptoms and risks

Early signs of pain medication misuse

Anti-inflammatory medications for pain control

• Identify trends in your medical research with Dovetail

Are you interested in contributing life-changing research? Today’s medical research is part of the future of clinical patient care. 

As your go-to resource for speedy and accurate data analysis , we are proud to partner with healthcare researchers to innovate and improve the future of healthcare.

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April 23, 2024

Research in Context: Treating depression

Finding better approaches.

While effective treatments for major depression are available, there is still room for improvement. This special Research in Context feature explores the development of more effective ways to treat depression, including personalized treatment approaches and both old and new drugs.

Everyone has a bad day sometimes. People experience various types of stress in the course of everyday life. These stressors can cause sadness, anxiety, hopelessness, frustration, or guilt. You may not enjoy the activities you usually do. These feelings tend to be only temporary. Once circumstances change, and the source of stress goes away, your mood usually improves. But sometimes, these feelings don’t go away. When these feelings stick around for at least two weeks and interfere with your daily activities, it’s called major depression, or clinical depression.

In 2021, 8.3% of U.S. adults experienced major depression. That’s about 21 million people. Among adolescents, the prevalence was much greater—more than 20%. Major depression can bring decreased energy, difficulty thinking straight, sleep problems, loss of appetite, and even physical pain. People with major depression may become unable to meet their responsibilities at work or home. Depression can also lead people to use alcohol or drugs or engage in high-risk activities. In the most extreme cases, depression can drive people to self-harm or even suicide.

The good news is that effective treatments are available. But current treatments have limitations. That’s why NIH-funded researchers have been working to develop more effective ways to treat depression. These include finding ways to predict whether certain treatments will help a given patient. They're also trying to develop more effective drugs or, in some cases, find new uses for existing drugs.

Finding the right treatments

The most common treatments for depression include psychotherapy, medications, or a combination. Mild depression may be treated with psychotherapy. Moderate to severe depression often requires the addition of medication.

Several types of psychotherapy have been shown to help relieve depression symptoms. For example, cognitive behavioral therapy helps people to recognize harmful ways of thinking and teaches them how to change these. Some researchers are working to develop new therapies to enhance people’s positive emotions. But good psychotherapy can be hard to access due to the cost, scheduling difficulties, or lack of available providers. The recent growth of telehealth services for mental health has improved access in some cases.

There are many antidepressant drugs on the market. Different drugs will work best on different patients. But it can be challenging to predict which drugs will work for a given patient. And it can take anywhere from 6 to 12 weeks to know whether a drug is working. Finding an effective drug can involve a long period of trial and error, with no guarantee of results.

If depression doesn’t improve with psychotherapy or medications, brain stimulation therapies could be used. Electroconvulsive therapy, or ECT, uses electrodes to send electric current into the brain. A newer technique, transcranial magnetic stimulation (TMS), stimulates the brain using magnetic fields. These treatments must be administered by specially trained health professionals.

“A lot of patients, they kind of muddle along, treatment after treatment, with little idea whether something’s going to work,” says psychiatric researcher Dr. Amit Etkin.

One reason it’s difficult to know which antidepressant medications will work is that there are likely different biological mechanisms that can cause depression. Two people with similar symptoms may both be diagnosed with depression, but the causes of their symptoms could be different. As NIH depression researcher Dr. Carlos Zarate explains, “we believe that there’s not one depression, but hundreds of depressions.”

Depression may be due to many factors. Genetics can put certain people at risk for depression. Stressful situations, physical health conditions, and medications may contribute. And depression can also be part of a more complicated mental disorder, such as bipolar disorder. All of these can affect which treatment would be best to use.

Etkin has been developing methods to distinguish patients with different types of depression based on measurable biological features, or biomarkers. The idea is that different types of patients would respond differently to various treatments. Etkin calls this approach “precision psychiatry.”

One such type of biomarker is electrical activity in the brain. A technique called electroencephalography, or EEG, measures electrical activity using electrodes placed on the scalp. When Etkin was at Stanford University, he led a research team that developed a machine-learning algorithm to predict treatment response based on EEG signals. The team applied the algorithm to data from a clinical trial of the antidepressant sertraline (Zoloft) involving more than 300 people.

EEG data for the participants were collected at the outset. Participants were then randomly assigned to take either sertraline or an inactive placebo for eight weeks. The team found a specific set of signals that predicted the participants’ responses to sertraline. The same neural “signature” also predicted which patients with depression responded to medication in a separate group.

Etkin’s team also examined this neural signature in a set of patients who were treated with TMS and psychotherapy. People who were predicted to respond less to sertraline had a greater response to the TMS/psychotherapy combination.

Etkin continues to develop methods for personalized depression treatment through his company, Alto Neuroscience. He notes that EEG has the advantage of being low-cost and accessible; data can even be collected in a patient’s home. That’s important for being able to get personalized treatments to the large number of people they could help. He’s also working on developing antidepressant drugs targeted to specific EEG profiles. Candidate drugs are in clinical trials now.

“It’s not like a pie-in-the-sky future thing, 20-30 years from now,” Etkin explains. “This is something that could be in people's hands within the next five years.”

New tricks for old drugs

While some researchers focus on matching patients with their optimal treatments, others aim to find treatments that can work for many different patients. It turns out that some drugs we’ve known about for decades might be very effective antidepressants, but we didn’t recognize their antidepressant properties until recently.

One such drug is ketamine. Ketamine has been used as an anesthetic for more than 50 years. Around the turn of this century, researchers started to discover its potential as an antidepressant. Zarate and others have found that, unlike traditional antidepressants that can take weeks to take effect, ketamine can improve depression in as little as one day. And a single dose can have an effect for a week or more. In 2019, the FDA approved a form of ketamine for treating depression that is resistant to other treatments.

But ketamine has drawbacks of its own. It’s a dissociative drug, meaning that it can make people feel disconnected from their body and environment. It also has the potential for addiction and misuse. For these reasons, it’s a controlled substance and can only be administered in a doctor’s office or clinic.

Another class of drugs being studied as possible antidepressants are psychedelics. These include lysergic acid diethylamide (LSD) and psilocybin, the active ingredient in magic mushrooms. These drugs can temporarily alter a person’s mood, thoughts, and perceptions of reality. Some have historically been used for religious rituals, but they are also used recreationally.

In clinical studies, psychedelics are typically administered in combination with psychotherapy. This includes several preparatory sessions with a therapist in the weeks before getting the drug, and several sessions in the weeks following to help people process their experiences. The drugs are administered in a controlled setting.

Dr. Stephen Ross, co-director of the New York University Langone Health Center for Psychedelic Medicine, describes a typical session: “It takes place in a living room-like setting. The person is prepared, and they state their intention. They take the drug, they lie supine, they put on eye shades and preselected music, and two therapists monitor them.” Sessions last for as long as the acute effects of the drug last, which is typically several hours. This is a healthcare-intensive intervention given the time and personnel needed.

In 2016, Ross led a clinical trial examining whether psilocybin-assisted therapy could reduce depression and anxiety in people with cancer. According to Ross, as many as 40% of people with cancer have clinically significant anxiety and depression. The study showed that a single psilocybin session led to substantial reductions in anxiety and depression compared with a placebo. These reductions were evident as soon as one day after psilocybin administration. Six months later, 60-80% of participants still had reduced depression and anxiety.

Psychedelic drugs frequently trigger mystical experiences in the people who take them. “People can feel a sense…that their consciousness is part of a greater consciousness or that all energy is one,” Ross explains. “People can have an experience that for them feels more ‘real’ than regular reality. They can feel transported to a different dimension of reality.”

About three out of four participants in Ross’s study said it was among the most meaningful experiences of their lives. And the degree of mystical experience correlated with the drug’s therapeutic effect. A long-term follow-up study found that the effects of the treatment continued more than four years later.

If these results seem too good to be true, Ross is quick to point out that it was a small study, with only 29 participants, although similar studies from other groups have yielded similar results. Psychedelics haven’t yet been shown to be effective in a large, controlled clinical trial. Ross is now conducting a trial with 200 people to see if the results of his earlier study pan out in this larger group. For now, though, psychedelics remain experimental drugs—approved for testing, but not for routine medical use.

Unlike ketamine, psychedelics aren’t considered addictive. But they, too, carry risks, which certain conditions may increase. Psychedelics can cause cardiovascular complications. They can cause psychosis in people who are predisposed to it. In uncontrolled settings, they have the risk of causing anxiety, confusion, and paranoia—a so-called “bad trip”—that can lead the person taking the drug to harm themself or others. This is why psychedelic-assisted therapy takes place in such tightly controlled settings. That increases the cost and complexity of the therapy, which may prevent many people from having access to it.

Better, safer drugs

Despite the promise of ketamine or psychedelics, their drawbacks have led some researchers to look for drugs that work like them but with fewer side effects.

Depression is thought to be caused by the loss of connections between nerve cells, or neurons, in certain regions of the brain. Ketamine and psychedelics both promote the brain’s ability to repair these connections, a quality called plasticity. If we could understand how these drugs encourage plasticity, we might be able to design drugs that can do so without the side effects.

Dr. David Olson at the University of California, Davis studies how psychedelics work at the cellular and molecular levels. The drugs appear to promote plasticity by binding to a receptor in cells called the 5-hydroxytryptamine 2A receptor (5-HT2AR). But many other compounds also bind 5-HT2AR without promoting plasticity. In a recent NIH-funded study, Olson showed that 5-HT2AR can be found both inside and on the surface of the cell. Only compounds that bound to the receptor inside the cells promoted plasticity. This suggests that a drug has to be able to get into the cell to promote plasticity.

Moreover, not all drugs that bind 5-HT2AR have psychedelic effects. Olson’s team has developed a molecular sensor, called psychLight, that can identify which compounds that bind 5-HT2AR have psychedelic effects. Using psychLight, they identified compounds that are not psychedelic but still have rapid and long-lasting antidepressant effects in animal models. He’s founded a company, Delix Therapeutics, to further develop drugs that promote plasticity.

Meanwhile, Zarate and his colleagues have been investigating a compound related to ketamine called hydroxynorketamine (HNK). Ketamine is converted to HNK in the body, and this process appears to be required for ketamine’s antidepressant effects. Administering HNK directly produced antidepressant-like effects in mice. At the same time, it did not cause the dissociative side effects and addiction caused by ketamine. Zarate’s team has already completed phase I trials of HNK in people showing that it’s safe. Phase II trials to find out whether it’s effective are scheduled to begin soon.  

“What [ketamine and psychedelics] are doing for the field is they’re helping us realize that it is possible to move toward a repair model versus a symptom mitigation model,” Olson says. Unlike existing antidepressants, which just relieve the symptoms of depression, these drugs appear to fix the underlying causes. That’s likely why they work faster and produce longer-lasting effects. This research is bringing us closer to having safer antidepressants that only need to be taken once in a while, instead of every day.

—by Brian Doctrow, Ph.D.

Related Links

• How Psychedelic Drugs May Help with Depression
• Biosensor Advances Drug Discovery
• Neural Signature Predicts Antidepressant Response
• How Ketamine Relieves Symptoms of Depression
• Protein Structure Reveals How LSD Affects the Brain
• Predicting The Usefulness of Antidepressants
• Depression Screening and Treatment in Adults
• Serotonin Transporter Structure Revealed
• Placebo Effect in Depression Treatment
• When Sadness Lingers: Understanding and Treating Depression
• Psychedelic and Dissociative Drugs

References:  An electroencephalographic signature predicts antidepressant response in major depression.  Wu W, Zhang Y, Jiang J, Lucas MV, Fonzo GA, Rolle CE, Cooper C, Chin-Fatt C, Krepel N, Cornelssen CA, Wright R, Toll RT, Trivedi HM, Monuszko K, Caudle TL, Sarhadi K, Jha MK, Trombello JM, Deckersbach T, Adams P, McGrath PJ, Weissman MM, Fava M, Pizzagalli DA, Arns M, Trivedi MH, Etkin A.  Nat Biotechnol.  2020 Feb 10. doi: 10.1038/s41587-019-0397-3. Epub 2020 Feb 10. PMID: 32042166. Rapid and sustained symptom reduction following psilocybin treatment for anxiety and depression in patients with life-threatening cancer: a randomized controlled trial. Ross S, Bossis A, Guss J, Agin-Liebes G, Malone T, Cohen B, Mennenga SE, Belser A, Kalliontzi K, Babb J, Su Z, Corby P, Schmidt BL. J Psychopharmacol . 2016 Dec;30(12):1165-1180. doi: 10.1177/0269881116675512. PMID: 27909164. Long-term follow-up of psilocybin-assisted psychotherapy for psychiatric and existential distress in patients with life-threatening cancer. Agin-Liebes GI, Malone T, Yalch MM, Mennenga SE, Ponté KL, Guss J, Bossis AP, Grigsby J, Fischer S, Ross S. J Psychopharmacol . 2020 Feb;34(2):155-166. doi: 10.1177/0269881119897615. Epub 2020 Jan 9. PMID: 31916890. Psychedelics promote neuroplasticity through the activation of intracellular 5-HT2A receptors.  Vargas MV, Dunlap LE, Dong C, Carter SJ, Tombari RJ, Jami SA, Cameron LP, Patel SD, Hennessey JJ, Saeger HN, McCorvy JD, Gray JA, Tian L, Olson DE.  Science . 2023 Feb 17;379(6633):700-706. doi: 10.1126/science.adf0435. Epub 2023 Feb 16. PMID: 36795823. Psychedelic-inspired drug discovery using an engineered biosensor.  Dong C, Ly C, Dunlap LE, Vargas MV, Sun J, Hwang IW, Azinfar A, Oh WC, Wetsel WC, Olson DE, Tian L.  Cell . 2021 Apr 8: S0092-8674(21)00374-3. doi: 10.1016/j.cell.2021.03.043. Epub 2021 Apr 28. PMID: 33915107. NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Zanos P, Moaddel R, Morris PJ, Georgiou P, Fischell J, Elmer GI, Alkondon M, Yuan P, Pribut HJ, Singh NS, Dossou KS, Fang Y, Huang XP, Mayo CL, Wainer IW, Albuquerque EX, Thompson SM, Thomas CJ, Zarate CA Jr, Gould TD. Nature . 2016 May 26;533(7604):481-6. doi: 10.1038/nature17998. Epub 2016 May 4. PMID: 27144355.

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How to Become a Medical Researcher

Home / Medical / How to Become a Medical Researcher

Trending Careers

The medical industry heavily relies on the specialized work provided by Medical Researchers.

These professionals are at the forefront of medical advancements to develop treatments, medicines and possible cures for a variety of medical diseases and disorders.

Some common medical maladies and diseases Medical Researchers may study and investigate include: cancer, diabetes, Alzheimer’s and the medicines and treatments being developed for these disorders.

Individuals who want to become a Medical Researcher will need an extensive medical background, postsecondary degree and skills in data analysis in order to succeed in this profession.

Table of Contents

Education Requirements to Become a Medical Researcher

Medical researcher job description, national average salary, average salary by state.

These are the top 5 earning states in the field:

What does a medical researcher do?

How much does a medical researcher make, how much does it cost to become a medical researcher, what is the demand for medical researchers, how long does it take to become a medical researcher.

Individuals who want to become a Medical Researcher will need a strong background in medicine and complete required postsecondary degrees in order to enter this profession.

Medical Researchers will also have to attend medical school to attain a PhD in Biomedical Sciences or a Medical Degree (MD).

A medical license is a requirement for individuals who want to do medical research and treat patients.

As undergraduates, individuals who want to become a Medical Researcher will need pursue a degree in a science related field.

Some typical degrees individuals can seek include biology, chemistry and microbiology.

It is also highly recommended that undergraduates take classes in writing and English in order to develop skills useful in research and grant writing.

Other helpful courses include: mathematics, physical science and life sciences.

As graduate students, individuals who want to become a Medical Researcher have the option to pursue a PhD program or a dual program that combines a PhD and a medical degree.

Medical degree/PhD programs provide training in both research and medicine.

Under these dual programs, individuals can combine a PhD with the following degrees: Medical Doctor (M.D.), Doctor of Osteopathic Medicine (D.O.) or Doctor of Dental Medicine (DMD).

Traditional PhD programs are approximately 4 years in length and focus more on laboratory work and an individual’s own research.

During this phase, students will have the opportunity to focus on a specialization such as: cancers, neurology or gerontology.

Individuals will also be given the opportunity to supervise undergraduate students.

Students will also work in depth on their original research and prepare for a thesis reporting on their findings.

A thesis is a written hypothesis focusing on a student’s research that needs to be presented to a committee of professors.

Medical Researchers are highly educated professionals who work in the medical field providing research that help improve human health.

These professionals will spend their time researching medical problems, writing grants to keep their projects funded and write reports on their findings.

Some laboratory work includes developing and managing studies that help understand a variety of human ailments.

They will also investigate preventative care and treatment for the diseases they research.

They will work with medical samples and information to determine the causes and treatments.

Medical Researchers also work in conjunction with a variety of professionals such as industry experts, doctors and health departments to create programs that improve a population’s health.

Medical Researcher Salary and Career Path

In 2012, the median salary for Medical Researchers and Scientists was approximately $76,980 per year.

Exact wages will depend on a variety of factors including industry, level of experience and company size.

For example, Medical Researchers who work for state colleges, universities or professional schools earn an annual median salary of approximately $53,740 while individuals who work for pharmaceutical and medicine production companies earn a median income of approximately $92,940 per year.

The job outlook for Medical Researchers is expected to grow by 13 percent through the year 2022.

This job growth is expected to grow as fast as average when compared to other professions and is attributed to the increased demand for research into illnesses such as cancer, AIDS and Alzheimer’s.

In addition, Medical Researchers are also needed to study treatments and medicines such as resistance to antibiotics.

Clearly, this profession is one that many people depend on to help solve medical problems.

A career in Medical Research may be a great path for individuals who would like to work in medicine, but not directly treat patients.

This career gives individuals the opportunity to help make advancements in medicine, work in a challenging environment and work in one of the fastest growing industries.

The top earning state in the field is Massachusetts, where the average salary is $118,880.

The top earning state in the field is Massachusetts, where the average salary is $9,833.

The top earning state in the field is Massachusetts, where the average salary is $57.15.

Frequently Asked Questions

Medical researchers study diseases and try to find new treatments and ways of preventing illness in order to help improve human health.

They usually work in offices and laboratories and spend most of their time studying data and writing reports.

Medical researchers sometimes work with dangerous samples and chemicals and this is why they have to follow strict safety and sanitation procedures.

The exact job requirements vary depending on the field of employment.

Some medical researchers design and conduct studies to investigate a particular disease while others create and test medical devices.

As a medical researcher, you may also have to apply for funding for a particular research project.

To become a medical researcher you need not only a strong scientific background but also several important skills, such as dexterity, attention to detail, research, writing and communication skills.

According to the Bureau of Labor Statistics, the median annual wage for medical scientists, in general, was $84,810 as of May 2018.

However, salaries in this field vary widely depending on the field of employment.

For example, those who work from the pharmaceutical and manufacturing field earned a median wage of $115,450 a year, while those who work in hospitals earned a median wage of $87,060 a year as of May 2018.

In order to become a medical researcher, you will usually need a bachelor’s degree in biology, chemistry, biotechnology or a related field and a Ph.D. in the field in which you want to specialize.

A four-year bachelor’s degree program can cost you anywhere between $5,000 and more than $30,000 a year.

Ph.D. programs usually focus on teaching students how to interpret data and how to design a research project, skills that are very important for medical scientists.

Some schools also offer dual programs that teach both the clinical skills needed to become a physician and the research skills needed if you decide to work in a lab.

Research-based Ph.D. programs cost, on average, around $35,000-$40,000 a year but tuition costs vary widely depending on the school you choose.

According to the Bureau of Labor Statistics, employment of medical scientists is expected to grow 8 percent from 2018 to 2028, faster than the average for all occupations.

This growth is explained in part by the fact that more people are diagnosed with chronic conditions and rely on medical treatment to help control their illnesses.

Job prospects should be especially good for researchers who specialize in studying diseases such as Alzheimer’s disease, AIDS or cancer.

Medical researchers usually hold a bachelor’s degree in science and a Ph.D. in the field in their specialty.

While a bachelor’s degree can be earned after 4 years of post-secondary study, Ph.D. programs typically take 5-6 years.

This means that medical researchers may need up to 10 years of training beyond high school.

Related Careers

Clinical researchers plan and monitor trials to test how effective and safe new medical inventions are.

A cancer researcher conducts studies designed to answer specific questions about cancer.

Medical Assistant is responsible for a variety of patient care, technical, and clerical related functions.

Medical technicians, work closely with nurses to provide quality care for patients.

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How to Write a Medical Research Paper

Last Updated: February 5, 2024 Approved

This article was co-authored by Chris M. Matsko, MD . Dr. Chris M. Matsko is a retired physician based in Pittsburgh, Pennsylvania. With over 25 years of medical research experience, Dr. Matsko was awarded the Pittsburgh Cornell University Leadership Award for Excellence. He holds a BS in Nutritional Science from Cornell University and an MD from the Temple University School of Medicine in 2007. Dr. Matsko earned a Research Writing Certification from the American Medical Writers Association (AMWA) in 2016 and a Medical Writing & Editing Certification from the University of Chicago in 2017. wikiHow marks an article as reader-approved once it receives enough positive feedback. In this case, 89% of readers who voted found the article helpful, earning it our reader-approved status. This article has been viewed 202,216 times.

Writing a medical research paper is similar to writing other research papers in that you want to use reliable sources, write in a clear and organized style, and offer a strong argument for all conclusions you present. In some cases the research you discuss will be data you have actually collected to answer your research questions. Understanding proper formatting, citations, and style will help you write and informative and respected paper.

Researching Your Paper

• Pick something that really interests you to make the research more fun.
• Choose a topic that has unanswered questions and propose solutions.

• Quantitative studies consist of original research performed by the writer. These research papers will need to include sections like Hypothesis (or Research Question), Previous Findings, Method, Limitations, Results, Discussion, and Application.
• Synthesis papers review the research already published and analyze it. They find weaknesses and strengths in the research, apply it to a specific situation, and then indicate a direction for future research.

• Keep track of your sources. Write down all publication information necessary for citation: author, title of article, title of book or journal, publisher, edition, date published, volume number, issue number, page number, and anything else pertaining to your source. A program like Endnote can help you keep track of your sources.
• Take detailed notes as you read. Paraphrase information in your own words or if you copy directly from the article or book, indicate that these are direct quotes by using quotation marks to prevent plagiarism.
• Be sure to keep all of your notes with the correct source.
• Your professor and librarians can also help you find good resources.

• Keep all of your notes in a physical folder or in a digitized form on the computer.
• Start to form the basic outline of your paper using the notes you have collected.

Writing Your Paper

• Start with bullet points and then add in notes you've taken from references that support your ideas. [1] X Trustworthy Source PubMed Central Journal archive from the U.S. National Institutes of Health Go to source
• A common way to format research papers is to follow the IMRAD format. This dictates the structure of your paper in the following order: I ntroduction, M ethods, R esults, a nd D iscussion. [2] X Research source
• The outline is just the basic structure of your paper. Don't worry if you have to rearrange a few times to get it right.
• Ask others to look over your outline and get feedback on the organization.
• Know the audience you are writing for and adjust your style accordingly. [3] X Research source

• Use a standard font type and size, such as Times New Roman 12 point font.
• Double-space your paper.
• If necessary, create a cover page. Most schools require a cover page of some sort. Include your main title, running title (often a shortened version of your main title), author's name, course name, and semester.

• Break up information into sections and subsections and address one main point per section.
• Include any figures or data tables that support your main ideas.
• For a quantitative study, state the methods used to obtain results.

• Clearly state and summarize the main points of your research paper.
• Discuss how this research contributes to the field and why it is important. [4] X Research source
• Highlight potential applications of the theory if appropriate.
• Propose future directions that build upon the research you have presented. [5] X Research source
• Keep the introduction and discussion short, and spend more time explaining the methods and results.

• State why the problem is important to address.
• Discuss what is currently known and what is lacking in the field.
• State the objective of your paper.
• Keep the introduction short.

• Highlight the purpose of the paper and the main conclusions.
• State why your conclusions are important.
• Be concise in your summary of the paper.
• Show that you have a solid study design and a high-quality data set.
• Abstracts are usually one paragraph and between 250 – 500 words.

• Unless otherwise directed, use the American Medical Association (AMA) style guide to properly format citations.
• Add citations at end of a sentence to indicate that you are using someone else's idea. Use these throughout your research paper as needed. They include the author's last name, year of publication, and page number.
• Compile your reference list and add it to the end of your paper.
• Use a citation program if you have access to one to simplify the process.

• Continually revise your paper to make sure it is structured in a logical way.
• Proofread your paper for spelling and grammatical errors.
• Make sure you are following the proper formatting guidelines provided for the paper.
• Have others read your paper to proofread and check for clarity. Revise as needed.

Expert Q&A

• Ask your professor for help if you are stuck or confused about any part of your research paper. They are familiar with the style and structure of papers and can provide you with more resources. Thanks Helpful 0 Not Helpful 0
• Refer to your professor's specific guidelines. Some instructors modify parts of a research paper to better fit their assignment. Others may request supplementary details, such as a synopsis for your research project . Thanks Helpful 0 Not Helpful 0
• Set aside blocks of time specifically for writing each day. Thanks Helpful 0 Not Helpful 0

• Do not plagiarize. Plagiarism is using someone else's work, words, or ideas and presenting them as your own. It is important to cite all sources in your research paper, both through internal citations and on your reference page. Thanks Helpful 4 Not Helpful 2

You Might Also Like

• ↑ http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3178846/
• ↑ http://owl.excelsior.edu/research-and-citations/outlining/outlining-imrad/
• ↑ http://china.elsevier.com/ElsevierDNN/Portals/7/How%20to%20write%20a%20world-class%20paper.pdf
• ↑ http://intqhc.oxfordjournals.org/content/16/3/191
• ↑ http://www.ruf.rice.edu/~bioslabs/tools/report/reportform.html#form

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This paper is in the following e-collection/theme issue:

Published on 26.4.2024 in Vol 26 (2024)

Understanding Symptom Self-Monitoring Needs Among Postpartum Black Patients: Qualitative Interview Study

Authors of this article:

Original Paper

• Natalie Benda 1 , PhD   ; 
• Sydney Woode 2 , BSc   ; 
• Stephanie Niño de Rivera 1 , BS   ; 
• Robin B Kalish 3 , MD   ; 
• Laura E Riley 3 , MD   ; 
• Alison Hermann 4 , MD   ; 
• Ruth Masterson Creber 1 , MSc, PhD, RN   ; 
• Eric Costa Pimentel 5 , MS   ; 
• Jessica S Ancker 6 , MPH, PhD  

1 School of Nursing, Columbia University, New York, NY, United States

2 Department of Radiology, Early Lung and Cardiac Action Program, The Mount Sinai Health System, New York, NY, United States

3 Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, United States

4 Department of Psychiatry, Weill Cornell Medicine, New York, NY, United States

5 Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States

6 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States

Corresponding Author:

Natalie Benda, PhD

School of Nursing

Columbia University

560 West 168th Street

New York, NY, 10032

United States

Phone: 1 212 305 9547

Email: [email protected]

Background: Pregnancy-related death is on the rise in the United States, and there are significant disparities in outcomes for Black patients. Most solutions that address pregnancy-related death are hospital based, which rely on patients recognizing symptoms and seeking care from a health system, an area where many Black patients have reported experiencing bias. There is a need for patient-centered solutions that support and encourage postpartum people to seek care for severe symptoms.

Objective: We aimed to determine the design needs for a mobile health (mHealth) patient-reported outcomes and decision-support system to assist Black patients in assessing when to seek medical care for severe postpartum symptoms. These findings may also support different perinatal populations and minoritized groups in other clinical settings.

Methods: We conducted semistructured interviews with 36 participants—15 (42%) obstetric health professionals, 10 (28%) mental health professionals, and 11 (31%) postpartum Black patients. The interview questions included the following: current practices for symptom monitoring, barriers to and facilitators of effective monitoring, and design requirements for an mHealth system that supports monitoring for severe symptoms. Interviews were audio recorded and transcribed. We analyzed transcripts using directed content analysis and the constant comparative process. We adopted a thematic analysis approach, eliciting themes deductively using conceptual frameworks from health behavior and human information processing, while also allowing new themes to inductively arise from the data. Our team involved multiple coders to promote reliability through a consensus process.

Results: Our findings revealed considerations related to relevant symptom inputs for postpartum support, the drivers that may affect symptom processing, and the design needs for symptom self-monitoring and patient decision-support interventions. First, participants viewed both somatic and psychological symptom inputs as important to capture. Second, self-perception; previous experience; sociocultural, financial, environmental, and health systems–level factors were all perceived to impact how patients processed, made decisions about, and acted upon their symptoms. Third, participants provided recommendations for system design that involved allowing for user control and freedom. They also stressed the importance of careful wording of decision-support messages, such that messages that recommend them to seek care convey urgency but do not provoke anxiety. Alternatively, messages that recommend they may not need care should make the patient feel heard and reassured.

Conclusions: Future solutions for postpartum symptom monitoring should include both somatic and psychological symptoms, which may require combining existing measures to elicit symptoms in a nuanced manner. Solutions should allow for varied, safe interactions to suit individual needs. While mHealth or other apps may not be able to address all the social or financial needs of a person, they may at least provide information, so that patients can easily access other supportive resources.

Introduction

This study focused on designing a culturally congruent mobile health (mHealth) app to support postpartum symptom monitoring, as the current practice does not adequately support patients in identifying the warning signs of pregnancy-related death (PRD). First, we describe the public health case for symptom monitoring and decision support for PRD, specifically among US-based, Black patients, a group that faces severe disparities [ 1 , 2 ]. Next, we discuss why the current mechanisms for symptom monitoring and decision support are insufficient. We then outline the existing solutions while also emphasizing the need for new interventions, particularly why those using a combination of mHealth and patient-reported outcomes (PROs) may be appropriate. Finally, we introduce a conceptual model used to accomplish our study objectives.

PRD and Associated Health Disparities

The pregnancy-related mortality ratio has increased by >200% in the United States in the past 2 decades, and in a recent review of PRDs, experts estimated that 80% of the deaths were preventable [ 3 ]. The Centers for Disease Control and Prevention (CDC) defines PRD as “the death of a woman while pregnant or within 1 year of the end of pregnancy from any cause related to or aggravated by the pregnancy” [ 4 , 5 ]. Mental health conditions (22.7%), hemorrhage (13.7%), cardiac and coronary conditions (12.8%), infection (9.2%), thrombotic embolism (8.7%), and cardiomyopathy (8.5%) have been cited as the most common causes for PRD [ 3 ]. Although the global maternal mortality rate has declined, the global rates are still high with 287,000 people dying following childbirth in 2020. There are significant disparities in maternal mortality based on a country’s income, with almost 95% of the cases occurring in low- and middle-income countries [ 6 ]. Stark disparities in pregnancy-related outcomes in the United States, such as PRD, exist based on race. Specifically, Black or African American (henceforth, referred to as “Black”) perinatal patients experience PRD 3 times more than White perinatal patients [ 1 , 2 , 7 - 10 ].

The disparities in maternal health outcomes experienced by Black patients in the United States are based on inequitable access to care, biased treatment, and inadequate communication, driven by systemic racism and all the cascading effects it creates. Black perinatal patients are significantly more likely to be uninsured and significantly less likely to have a usual source of medical care (eg, a primary care clinician) than White patients [ 7 , 10 ]. When Black patients seek care, they face implicit biases that negatively affect care quality and health outcomes [ 1 , 7 , 10 - 12 ]. Unsurprisingly, these biases have led to reduced trust in the health care system among Black patients [ 13 - 17 ]. Black patients also receive less patient-centered communication and feel that they have poorer access to communication with their medical team [ 10 , 18 , 19 ]. Our study aimed to improve the patient centeredness of information and support for Black patients in the postpartum period through a participatory design, an approach by which representative end users are involved throughout the design process [ 20 - 23 ]. While this study focused on Black postpartum patients in the United States, we believe that our findings may provide insights for improving perinatal support for patients from minority groups globally.

Challenges to Supporting Symptom Recognition and Treatment Seeking Post Partum

Patients encounter several challenges recognizing concerning postpartum symptoms. First, the initial postpartum visit occurs 6 weeks after birth, and 86% of PRD cases occur within the first 6 weeks post partum [ 24 , 25 ]. Second, most strategies for improving postpartum outcomes focus on hospital-based solutions, which rely on people recognizing symptoms and contacting a health professional [ 7 ]. Most counseling regarding the warning signs of PRD occurs during the discharge process following delivery, when people are physically exhausted from childbirth and primarily focused on infant care [ 24 ]. As such, this is a suboptimal time for patient education about postpartum risk factors. Discharge nurses report spending <10 minutes on the warning signs of postpartum issues, and most nurses could not correctly identify the leading causes of PRD, making it unlikely that their patients could recognize the warning signs [ 26 ]. There are many measures for postpartum symptom reporting, but the most common instruments focus narrowly on specific mental health issues, many of which are not specific to postpartum mental health or postpartum health–related quality of life [ 27 ]. While these are helpful measures to use in a clinic or hospital setting, they do not provide real-time decision support regarding the full spectrum of severe symptoms that may be indicative of PRD.

Suitability of Different Solutions for Supporting Symptom Monitoring

mHealth can address the need for tailored, dynamic symptom monitoring and support. The Association of Women’s Health, Obstetric, and Neonatal Nurses and the CDC have developed 1-page summaries to help patients identify the warning signs of PRD, such as the Urgent Maternal Warning Signs (UWS) [ 28 , 29 ]. These tools represent a positive step toward improving symptom management, but these solutions do not provide real-time, tailored support. Telephone-based support staffed by health professionals has been demonstrated to decrease postpartum depression and improve maternal self-efficacy [ 30 - 33 ]. However, 24-hour hotlines can be resource intensive, and people may still experience bias when accessing these services. The goal of this study was to conduct a qualitative needs assessment for the Maternal Outcome Monitoring and Support app, an mHealth system using PROs to provide decision support for postpartum symptom monitoring.

Mobile phones offer a viable, inclusive option for intervention delivery for Black people of childbearing age. In 2020, data from the Pew Research Center indicate that 83% of Black people owned smartphones, which is comparable to smartphone ownership among White people (85%). Smartphone ownership is also higher among people aged <50 years (96%), which encompasses most postpartum patients [ 34 ]. However, Black people are twice as likely as White people to be dependent on smartphones for internet access [ 35 ]. mHealth-based apps for blood pressure and weight tracking during pregnancy have demonstrated success among diverse groups, providing evidence that mHealth may be an acceptable means for symptom reporting in the target population [ 36 - 38 ].

Symptom education and PRO-based interventions have demonstrated success in improving knowledge, self-efficacy, and outcomes. Use of PROs has improved symptom knowledge, health awareness, communication with health care professionals, and prioritization of symptoms in patients with chronic disease and cancer [ 39 - 44 ]. Multiple studies have also demonstrated that educational interventions regarding expected symptoms in the postpartum period can improve self-efficacy, resourcefulness, breastfeeding practices, and mental health [ 12 , 38 , 45 - 47 ]. However, given the issues related to trust and disparities in patient-centered communication, it is critical to understand Black patients’ perspectives about how such a system should be designed and implemented.

Conceptual Model

To study the issue of supporting symptom monitoring, we combined 2 theoretical frameworks ( Figure 1 ): the common sense model of self-regulation (health behavior) by Diefenbach and Leventhal [ 48 ] and the model of human information processing (human factors engineering) by Wickens [ 49 ]. The model by Diefenbach and Leventhal [ 48 ] depicts patients as active problem solvers with a mental model of their conditions. Patients process their symptoms, both cognitively and emotionally, and then evaluate whether action is needed [ 48 ]. The patient’s mental model of their condition, personal experiences, and sociocultural factors impact processing, evaluation, and action. In the information processing model by Wickens [ 49 ], action occurs in 2 steps—selection and execution [ 48 ]. Environmental or organizational factors also affect patients’ selection of actions and whether they can execute an action. For example, a patient may suspect that they should visit the emergency room but may not go because they do not have insurance, transportation, or childcare. Our qualitative inquiry investigated how to better support symptom processing and appropriate response selection, while also uncovering the barriers to action that may need to be mitigated.

The goal of this study was to identify the design and implementation needs of an mHealth-based symptom self-monitoring and decision-support system to support Black patients in determining when to seek care from a health professional for signs of PRD in the postpartum period. This tool will support both somatic and psychological symptoms given their complex, critical, and connected presentation. We used the described conceptual model in qualitative inquiry and pragmatic intervention design to provide contributions regarding the following: (1) relevant symptom inputs for postpartum support, (2) drivers that may affect symptom processing, and (3) how the previous 2 aspects highlight the design needs for symptom self-monitoring and patient decision support. To address our study objective, we conducted semistructured interviews with postpartum Black patients, obstetrics health professionals, and mental health professionals.

The study was conducted in 3 tertiary care hospitals and affiliated clinics within the same health system in New York City. The 3 hospitals, taken together, are involved in the delivery of >14,000 babies annually. All participants were either patients who received obstetric care in the included sites or health professionals affiliated with the sites.

Eligible patients were identified by the institutions’ research informatics team using electronic health record data. First, the patients’ providers consented to their patients being contacted, and patients’ charts were reviewed by the primary obstetrician or designate to ensure that the patient was eligible for the study and that they had a delivery experience that would allow them to participate in the interview without undue stress. Next, the patients were sent an invitation to participate via the email address listed in their record. We also posted fliers in 2 high-risk, outpatient obstetric clinics.

Obstetric and mental health professionals were eligible if they were affiliated with one of the institutions in the obstetrics or mental health department. Brief presentations were given at relevant faculty meetings, and participants were contacted individually via email or through departmental listserves.

Interested participants from all groups used a link to schedule a time to speak with a researcher.

Ethical Considerations

The study was approved by the affiliated medical schools’ institutional review board (protocol number 20-08022582). All participants provided written informed consent. Study data were coded (ie, all identifying information was removed) to protect participant privacy. Each participant was compensated US $50 for their time via a physical or electronic gift card.

Study Design and Sample

The study used semistructured interviews with 3 key stakeholder groups: recent postpartum Black patients, obstetric health professionals, and mental health professionals. Eligible patients were within 12 months post partum of a live birth, self-identified their race as Black or African American, and had at least 1 somatic or psychological high-risk feature associated with their pregnancy. High-risk features included attendance at a high-risk clinic for prenatal or postnatal care, inpatient hospitalization within 12 months post partum, a prescription of an antidepressant or benzodiazepine within 12 months of the pregnancy, or a new diagnosis of depression or anxiety within 12 months of the pregnancy. High-risk clinics treated various conditions, but the most common conditions were gestational hypertension and gestational diabetes.

We adopted an interpretivist qualitative research paradigm to study patient and health professionals’ perspectives of how symptom recognition and care seeking may be better supported [ 50 ]. Our methodological orientation involved directed content analysis, adopting an abductive reasoning approach. First, we used the previously specified conceptual model to construct questions and thematically categorize responses [ 48 ]. Then, we allowed unique subthemes to inductively emerge from the data collected [ 51 ].

Interview Guide Development

Interview guides were iteratively developed by our team of researchers with expertise in obstetrics, perinatal mental health, nursing, consumer informatics, inclusive design, and qualitative methods. The guide for each stakeholder group was reviewed and piloted before enrollment of the first participant. Interview guides were tailored for patients or health professionals but followed a similar structure, based on our conceptual model ( Figure 1 ), such that participants were first asked about barriers to and facilitators of processing symptoms cognitively and emotionally (eg, Do they notice the symptom or realize its severity?), making decisions about symptoms they are experiencing (ie, When to seek help from a health professional?), and taking action on problematic symptoms. Probing questions encouraged participants to elaborate on experiential, educational, sociocultural, organizational, environmental, or health systems–level drivers of patients’ symptom management. Then, participants were asked a series of questions related to their thoughts regarding the design of the mHealth system, including how to best report symptoms, the wording of system decision support, the desired level of involvement of the obstetrics health professionals, the means for facilitating outreach to a health professional, additional information resources, and preferences for sharing information included in the system with a trusted friend or family members. During this process, obstetrics and mental health professionals were also shown a handout that outlined the draft of the symptom management algorithm for the system being developed (CDC’s UWS) and asked if they would make any changes, additions, or deletions [ 29 ]. Full interview guides are included in Multimedia Appendix 1 .

Data Collection

All interviewees provided consent electronically before the interview. A PhD-trained qualitative research expert (NB) completing a postdoctoral study in health informatics and population health conducted all the interviews via Zoom (Zoom Video Communications) or telephone. Participants had the option to request an in-person interview, but none of them chose this option. Interviews lasted 30 to 60 minutes and were audio recorded. We explicitly described the study objectives to each participant before the interview. Following the interview, participants completed a demographics survey electronically. All electronic survey information was collected using REDCap (Research Electronic Data Capture; Vanderbilt University).

Data Preparation and Analysis

Audio recordings were converted into transcripts using an electronic software (NVivo Transcription; QSR International) and manually checked for accuracy by a study team member who did not conduct the initial interviews. We completed all data analyses using NVivo (versions 12 and 13), but we manually analyzed the data and did not use computer-aided techniques (eg, computerized emotion detection or autocoding).

Data were analyzed using thematic analysis and the constant comparative process [ 51 - 53 ]. Specifically, each analyst open coded the transcripts, by coding segments that pertained to the research questions, as opposed to coding all words and phrases. We used thematic analysis to detect the common and divergent needs for postpartum symptom monitoring. We chose this method over other approaches such as grounded theory or sentiment analysis because our needs were pragmatic to solution design, and we were not attempting to establish theory, describe phenomena, or represent collective feeling about a topic.

The first deductive analysis was conducted using an initial theoretical model derived from the common sense model by Diefenbach and Leventhal [ 48 ] and the model of human information processing by Wickens [ 49 ] ( Figure 1 ). To promote reliability, 2 coders in addition to the interviewer were involved in the analysis, and each transcript was first analyzed independently by at least 2 people (NB, SW, or SNdR), followed by meetings to resolve discrepancies based on consensus coding. The analysis team created initial codes based on the conceptual model and added new items to the codebook inductively (ie, post hoc instead of a priori, as they arose in the data). The team used NVivo to maintain a working codebook of themes, definitions, and relevant quotes derived from the data. The codebook was periodically presented to coinvestigators with expertise in obstetrics and perinatal psychiatry to improve external validity [ 51 , 52 ]. The sufficiency of sample size was assessed according to the theoretical saturation of themes encountered, specifically based on the need to add additional subthemes to the codebook [ 54 , 55 ]. After all the transcripts had been coded, at least 2 members of the coding team reviewed the data code by code to ensure that meaning remained consistent throughout the analysis and to derive key emerging themes [ 51 ].

Participant Characteristics

This study included 36 participants—15 (42%) obstetrics health professionals, 10 (28%) mental health professionals, and 11 (31%) recent postpartum Black patients. Table 1 presents the self-reported demographic information. As shown, 19% (7/36) of the health professionals and 11% (4/36) of the patients had missing data (ie, did not complete the questionnaire). Participants could also selectively choose not to answer questions. “Other” affiliations were possible for health professionals because those who had a secondary affiliation with one of the included sites but primary affiliation with another organization were eligible.

a N/A: not applicable.

b Health professionals’ self-reported role of resident psychiatrist, chief resident in psychiatry, psychologist, and patient care director was combined into the other category for analysis purposes.

Structure of Themes

Our initial theoretical model, derived from the common sense model by Diefenbach and Leventhal [ 48 ] and the model of human information processing by Wickens [ 49 ] ( Figure 1 ), described that patients experience some inputs (psychological and somatic symptoms of PRD). Then, there is a series of drivers that affect how patients cognitively and emotionally process (eg, notice and realize symptom severity), make decisions about, and act on symptoms they are experiencing. The nature of these symptoms, how they are processed, how decisions are made, and how they are acted upon then drive a conversation regarding the design needs for symptom monitoring and decision support for PRD. The emerging themes were organized into the following categories: (1) symptoms of PRD; (2) drivers of processing, decision-making, and action; and (3) design needs for a symptom-reporting and decision-support system. Quotes are labeled with study-specific identifiers: OB denotes obstetric health professional, MHP denotes mental health professional, and PT denotes patient.

Inputs: Psychological and Somatic Symptoms of PRD

Concerning and routine symptoms were reported both from a psychological and somatic perspective. Sometimes, the distinction between routine and concerning symptoms was clear. Other times, it was more challenging to differentiate routine versus concerning symptoms particularly because they were related to psychological health. Mental health professionals also noted the challenge that routine symptoms can progress to something more serious over time:

In my mind, like normal becomes abnormal, when there is any kind of functioning [loss] that like withstands two to three weeks. [MHP 04]

We really hear a lot about postpartum depression and stuff...A lot of women think...postpartum depression is you just don’t want to. You don’t have it. You go into depression where you can’t take care of your child and you don’t want to hold your child. You don’t feel connected to your child. And I learned...it can be so many different things. [PT 09]

A clear distinction was not always present between psychological and somatic symptoms:

If someone...has pain in their chest or shortness of breath, the first thing you want to think about is it sort of like clots and other kind of physiologic reasons for that. Those are also very implicated and sort of obviously [associated with] panic attacks and anxiety. So, I think though those symptoms are also relevant of physical symptoms, [they] are also relevant for mental health. [MHP 05]

Drivers of Processing, Decision-Making, and Action Based on the Symptoms Experienced

Several drivers were reported to affect symptom processing (ie, whether they noticed the symptom and its severity), patients’ capacity to decide what should be done (ie, make decisions), and whether they were able to act on concerning symptoms ( Table 2 ).

Table 2 presents exemplary quotes for emerging themes under a single driver, but many quotes were coded under multiple drivers in our analysis process. The following passage, for example, highlights how self-perception, sociocultural concerns, and the health system can overlap to present a complex set of factors that may prevent women from receiving the care they need for the symptoms they are experiencing:

A lot of times I think that does get overlooked because people feel like, well, you’re OK, you’re fine. But what research shows us is that especially for Black women, it really doesn’t matter how much money you make or your income level, like our postpartum and perinatal health outcomes are the same across the board, which is really detrimental. So, yeah, I think they get overlooked because of that. I think they get overlooked or we get overlooked in the health care system. But I also think we get overlooked by our family and friends because we’re the strong ones. So, if anybody can deal with this, it’s you. [MHP 10]

a MHP: mental health professional.

b PT: patient.

c OB: obstetric health professional.

Design Needs for a Symptom-Reporting and Decision-Support System

Obstetric health professionals, mental health professionals, and patients discussed multiple needs for improved PRD symptom reporting and decision support. The key design requirements are embedded and italicized in the following text.

Participants generally agreed that although the proposed system focuses on postpartum symptoms, it would be advantageous to introduce the system during pregnancy, particularly in the third trimester :

You have to reach women before they give birth. They might look, they might not look, they might look at it and be concerned. But then they might forget about it and not have time to call. Those first six weeks are really chaotic. [MHP 06]

I think in the third trimester would be great because often we don’t really have anything to talk about in the office. It’s very quick visits like blood pressure and you’re still pregnant and we’re just waiting. And so, I think and they start to have a lot of questions about like, well, when I get home and how’s this going to go? So, I think that time is a good time. We’re all kind of just waiting for labor to happen or full term to get there, and this kind of gives them something to feel like they can prepare for. [OB 08]

Patients were open to reminders regarding entering symptoms they were experiencing, and participants described a desire for just-in-time symptom reporting and decision support, so that they could get quick feedback as they were experiencing the symptoms:

When people get home so much in their life has changed. And it’s probably a very hectic time. So maybe I think that’s a great idea reaching out again, either a few days or a week later to make sure they’re really able to use it and engage with it to the extent that’s helpful to them. [OB 02]

I think it would be a good idea to have like a system where you can report whenever you want. [PT 03]

I think for me, I would say in the moment. But then also having something at the end of every week to just, you know, to check in with yourself. I think that would be good as well. [PT 09]

In addition to considerations about how symptoms would be recorded, participants stressed the importance of the wording of the decision-support messages that patients receive . For messages that inform the patient that their symptom did not seem to require immediate medical attention, it was important to ensure that the patient still felt heard and that they did not leave the interaction feeling stuck with nothing to do regarding a symptom that was concerning to them:

Reframe the message. You know...we apologize that you were experiencing this. We just want to reassure you that this is normal. [PT 01]

[You] don’t want to make anyone feel like their feelings aren’t valid because that’s a horrible thing, especially in health care, especially if a person is convinced that something is wrong with them and you’re telling them that it’s normal and is perfectly fine. So, in that situation, I would just, depending on what the issue is, I would also share information of what to look out for. [PT 05]

The first thing is that it’s normal, but also something that you want to be able to do for comfort. For me, I don’t have to do too much, especially if I’m having anxiety, like if I get a text back that says here are some things you can do in this very moment to handle it. And then also, here are some links or information that you can also look up. [PT 09]

In the events where a concerning symptom was reported and it was recommended that the patient should reach out to a health professional, importance of conveying a sense of urgency without scaring the patient:

You don’t want to scare people, but it’s kind of hard to get around that when something is serious, and you don’t want to dumb it down. [PT 01]

Participants wanted multiple, easy-to-do methods for connecting with their health professional team, including having the number to call pop up, scheduling a time for someone to call them, and being able to start a live web-based chat:

I like all the options, especially that form or chat you can have like, you know, those online chat where like you really chatting with someone for those who like the type. I’m the type of person I just want to make a phone call, right? So, like for me, [it] will be a call. Maybe say maybe if it’s five, five or ten minutes then that will be great. Like especially, it’s going to make me feel like, OK, there’s someone out there that will care about my health. [PT 06]

However, participants noted that they would prefer not to use a symptom-reporting and decision-support tool, but instead reach out directly via phone if they were experiencing issues.

Participants, particularly mental health professionals, described a need for improved nuance or details regarding the different psychological symptoms patients could experience that are indicative of severe mental health issues:

Thoughts of hurting yourself or someone else is a good one...I would say I would add difficulty bonding. It would add something about not being able to sleep, even if you could sleep, you know, like or your anxiety that doesn’t go away, that changes your behavior. So, it changes the way that you interact with the baby or kind of do childcare. I guess I would want to say something about. psychotic thoughts, like fear that someone else may be hurting you or...recurrent worries or anxieties that don’t go away. [MHP 02]

Patients had differing opinions regarding whether the system should be integrated with other health technologies, particularly the patient portal:

I love the patient portal. I was able to be traveling to reach out to my OB, to reach out to all, you know, the nurses and stuff like that and just experience things that I needed. [PT 09]

I feel like...it’s an integral part of my medical history. So, even if it may seem somewhat insignificant for whatever reason, I would still want to have access. [PT 09]

I didn’t find it [the patient portal] very helpful... [PT 03]

On the basis of the feedback from health professionals that it may be challenging for postpartum patients to process and recognize certain symptoms, especially those related to mental health, we explored whether patient participants would be open to sharing educational information about symptoms to expect (rather than sharing the actual symptom reports) with trusted friends or family members. Similar to other design considerations, results were mixed, but it seemed helpful to have a patient-driven option for sharing symptom-related educational information with chosen friends or family members :

I think that there’s so much going on it would help to have someone with a different perspective equipped with this information. [PT 02]

There’s a lot of shame that comes with this. I’m not sure people would actually want other people to know. I can’t speak for the majority, but I didn’t really want people to know because I don’t want the kind of energy that came with people knowing. [PT 05]

We also discovered the competing needs of balancing the patient’s desire for their health professionals to be involved in symptom reporting with the need to avoid significant increases to health professional workload :

I sort of wonder from the health care provider perspective, how involved is the provider in that in the app? Like, do they get like a PDF of all the information? Is that more work for the provider? How does the provider interpret that data? [MHP 03]

I feel like they [the health professional] should be super involved. Especially because I’m not just going off of my experience because, you know, I don’t want to feel like they’re not really like I’m experiencing. And so, it’s scaring me. So, I just want to know that, you know, you’re hands on with everything. [PT 01]

Finally, the participants desired information beyond PRD symptoms to entice them to use the system . They were supportive of including various types of information, such as breastfeeding support resources, milestones and information regarding their child, other websites and apps with trusted maternal and child health information, further support resources for how they feel mentally, and links to social services (eg, food, housing, or other assistance).

Principal Findings

In this qualitative study, we interviewed obstetric health professionals, mental health professionals, and Black postpartum patients. Our findings helped to identify the design and implementation needs of an mHealth-based, symptom self-monitoring and decision-support system designed to support Black patients in determining when to seek care from a health professional for signs of PRD in the postpartum period. We encountered important findings related to (1) inputs, including psychological and somatic symptoms; (2) drivers of processing, decision-making, and action based on the symptoms experienced; and (3) design needs for a symptom-reporting and decision-support system. We have discussed how our findings may be helpful to other postpartum populations as well as the implications of our study for patient decision-support in other clinical settings.

First, our findings related to symptom inputs revealed the challenges caused by the overlapping presentation of somatic and psychological symptoms. This provides support for our approach of including psychological and somatic issues in a single app, particularly given that mental health conditions are a leading cause of PRD. A 2021 review found 15 PRO measures for assessing postpartum recovery. The measures typically focused on mental health or health-related quality of life, but few included both psychological and somatic outcomes, and none were targeted for PRD, such as the system [ 56 ].

Moreover, related to symptom inputs, we found that current tools for pinpointing severe symptoms, such as the CDC’s UWS did not provide sufficient nuance for concerning psychological symptoms. Symptom-reporting tools for PRD will either need to consider incorporating structured assessments, such as the Edinburgh Postnatal Depression Scale (EPDS) [ 56 ], or incorporating additional symptoms. The latter approach may have advantages as the EPDS focuses on depression (while providing subscales for anxiety) and PROs evaluated for use with anxiety disorders have limitations [ 57 ]. Furthermore, the EPDS has been validated in in-person laboratory settings but not in community settings or for web-based entry [ 58 ]. We must also consider how mistrust in the health system may lead to less truthful answers. Issues expressed around stigma related to mental health indicate that the way in which these symptoms are elicited may require further assessment to promote the normalcy of the symptoms and improve candid reporting. Technology-based approaches for supporting perinatal mental health have been described as uniformly positive but having limited evidence for use [ 59 ], suggesting that further exploration is needed in this area, also considering how adding somatic issues may be perceived by patients.

Second, there were several drivers that affected symptom processing, decision-making, and action that cannot typically be solved through a symptom-reporting and decision-support system. Challenges related to self-perception and lack of experience or expectations may be addressed based on the wording for how the symptoms are elicited and by providing concise, easy-to-understand depictions of what should be expected versus what are the causes for concern. However, many of the other issues described related to sociocultural, financial, and environmental factors and the health systems’ systemic racism issues cannot be addressed directly in a simple PRO-based app and decision-support system. Directly addressing these issues will likely require more systematic, multipronged approaches. Therefore, it seems advisable to couple patient decision-support aids with other social support interventions for perinatal health [ 60 , 61 ].

Drivers of processing, decision-making, and action are still important contextual elements to be considered in the design of the system. Another study tailoring an mHealth app for Latina patients to support health during pregnancy also found it important to address issues related to financial barriers, social support, health care accessibility, and cultural differences [ 62 ]. Our best attempt to address these issues may be to promote information transparency and inclusive design. For example, there may be a “frequently asked questions” section of an app, where patients can explore things such as supportive resources for childcare while they seek medical attention or information they may show their friends or family members regarding postpartum symptoms of concern. The system may also use common human-computer interaction principles, such as information filtering [ 63 ] and organizing the suggested resources (eg, for mental health care) based on whether they accept the patient’s insurance. The built environment can also be changed through the system, but it may offer mechanisms for remote monitoring, such as telemedicine-based support or linking the system to a blood pressure cuff, when clinically appropriate [ 64 , 65 ]. As noted, the system obviously cannot address issues related to systematic racism directly [ 66 ]. Instead, we used a participatory design approach, with the hope that the nature of the information presented may be more patient centered, acceptable, and better aligned with the beliefs and values of Black patients [ 67 ]. Issues related to systematic racism have commonly been described in the US health care system, but structural inequities also exist on a global scale. Future studies should investigate how our findings regarding design needs may extend to other minoritized perinatal patient groups.

A systematic review of patient decision aids for socially disadvantaged populations across clinical settings found that such tools can improve knowledge, enhance patient-clinician communication, and reduce decisional conflict [ 68 ]. However, descriptions of patient decision aids focus on the type of tool (eg, paper vs digital), how it was delivered, when it was delivered, and by whom, as opposed to describing the content the aid provides. Therefore, it is challenging to determine how other decision-support tools have addressed information regarding environmental, financial, or health system–level factors that may affect care seeking based on the decision aid. Some tools seem to address sociocultural needs by tailoring to the target population, but the aforementioned systematic review did not find differential effects on outcomes when tools were tailored versus not tailored [ 16 ]. Future studies on patient decision aids may benefit from including non-symptom related information. Providing appropriate informational support may involve a deeper study of the systemic needs that patients may have, even if these needs may not directly be addressed by the decision aid.

Third, descriptions of the design needs for PRD symptom monitoring revealed that there is likely not a one-size-fits-all solution related to reminders, involvement of health professionals, and how the tool is incorporated with other systems (eg, the patient portal). “User control and freedom” and “flexibility of use” are two of the key items in commonly used heuristics for user interface design [ 69 ]; therefore, it is important to include options for customization and varied but safe pathways for interaction with the proposed system. For example, some participants described that they may not be likely to access the symptom-reporting system through the patient portal. Although there may be safety and convenience-related reasons for having the system as part of the patients’ medical record, if the patient chooses, the system could, on the front end, appear more like a stand-alone app than something that must be accessed through the patient portal. Patients also had varying opinions related to how they may want to reach out to a health professional if a problematic symptom was reported. These preferences may differ from instance to instance; therefore, it is helpful to ensure that patients have a choice regarding how to reach out, but system designers must also create workflows with feedback loop, so that patients who are reporting problematic symptoms are not missed (ie, if patients do not reach out themselves, they never receive attention). Patient-level customizations and options for interaction also respects patients as individuals and may promote patient-centered interactions.

Furthermore, related to design needs, participants indicated that the wording of the decision-support messages was critical. Specifically, for reports that did not include currently urgent symptoms, it was important that the message still conveyed support and validation, clarified that the patient could still reach out for help, and provided additional means for managing their symptoms, so the patient did not feel frustrated by their report [ 70 ]. Regarding messages that recommended patients to reach out to their health professional team, it was crucial to note what the symptom meant (eg, what kind of disease it could indicate), encourage the patient to reach out without increasing anxiety, and provide different avenues for easy outreach. Going forward, we plan to incorporate the aforementioned elements into the messages built into the system. We will then complete additional acceptance and comprehension testing with a larger sample of postpartum patients. These findings also indicate that care must be taken in translating such tools, and the translated materials should be reviewed with the target end user groups before implementation. This may mitigate unintended consequences or inadvertent inclusion of language that does not support the needs of minoritized groups.

Strengths and Limitations

Our study highlighted the limitations and areas that would benefit from further exploration. First, our study involved recruitment sites that were within a single health system in New York City. Second, while we achieved thematic saturation of qualitative themes (a means for determining sample sufficiency in qualitative studies) [ 54 , 55 ], our conclusions are based on a sample of 36 participants from 3 stakeholder groups. Third, given the documented disparities, we deliberately focused on the needs of Black postpartum patients, but this may not represent the needs of the postpartum patients of other races. Furthermore, our sample should not be viewed as encompassing the opinions of all Black postpartum patients. Our findings revealed the need for individual customization and varied interaction patterns on a case-by-case basis. Fourth, all interviews were conducted remotely (via Zoom or telephone), which can have effects on the interaction. On the one hand, it may be harder to connect with the interviewee, and on the other hand, people may feel more anonymous and comfortable with sharing information. Finally, although we attempted to promote external validity through the review of the coding scheme by a subject matter expert, we did not have the opportunity to perform triangulation of the findings by returning the results to participants. To address these limitations, it would be beneficial to survey a larger group of postpartum patients, powered to assess the differences based on race and ethnicity. This would allow us to come to a stronger consensus regarding design choices, assess whether there are differences in design needs or preferences, and gain feedback from patients in areas outside New York City. Future studies may also explore how other underserved groups, such as those with limited English proficiency, may benefit from tailored symptom self-monitoring and decision support.

Conclusions

In this qualitative study regarding postpartum symptom monitoring and decision support, we found that the current structured reporting measures do not include the combination of somatic and psychological symptoms that may be indicative of severe outcomes in the postpartum period. While not explicitly related to symptom reporting and decision support, patient decision aids, particularly those focusing on minoritized groups, should consider how the aids may be coupled with other structural support interventions or, at least, information about how other resources may be accessed. As stated in the commonly accepted design heuristics, we also found that user control and freedom unsurprisingly remain important for a patient decision-support aid for Black postpartum patients. Finally, decision aid–related phrases must take care to convey urgency without inducing anxiety when action may be indicated and consider respect and empathy for the patients’ symptoms when action may not be indicated to ensure that they do not feel unheard and are empowered to report new or worsening symptoms.

Acknowledgments

This study was supported by the National Institute on Minority Health and Health Disparities (K99MD015781; principal investigator: NB).

Data Availability

The data sets generated and analyzed during this study are not publicly available due to institutional review board regulations but are available from the corresponding author on reasonable request.

Authors' Contributions

NB conceptualized the study and acquired funding under the advisement of RBK, LER, AH, RMC, and JSA. NB collected the data. NB, SW, and SNdR analyzed the data with input from all other authors. ECP completed the literature review and descriptive analysis of participants’ characteristics. NB drafted the paper and received substantial inputs from all other authors.

Conflicts of Interest

LER is an Up to Date contributor and an advisory board member for the New English Journal of Medicine, and Contemporary OB/GYN. She has also been a speaker for Medscape is an an expert reviewer for Pfizer on the RSV Vaccine. AH is an Up to Date contributor, a co-founder and medical consultant for Iris Ob Health, and a consultant for Progyny.

Semistructured interview guide questions for patients and health professionals.

• Howell EA, Egorova NN, Janevic T, Brodman M, Balbierz A, Zeitlin J, et al. Race and ethnicity, medical insurance, and within-hospital severe maternal morbidity disparities. Obstet Gynecol. Feb 2020;135(2):285-293. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Wisner KL, Sit DK, McShea MC, Rizzo DM, Zoretich RA, Hughes CL, et al. Onset timing, thoughts of self-harm, and diagnoses in postpartum women with screen-positive depression findings. JAMA Psychiatry. May 01, 2013;70(5):490-498. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Pregnancy-related deaths: data from maternal mortality review committees in 36 US States, 2017-2019. Centers for Disease Control and Prevention. URL: https://www.cdc.gov/reproductivehealth/maternal-mortality/erase-mm/data-mmrc.html [accessed 2022-11-20]
• Pregnancy mortality surveillance system. Centers for Disease Control and Prevention. 2020. URL: https://tinyurl.com/356dwufh [accessed 2024-03-23]
• Creanga AA, Syverson C, Seed K, Callaghan WM. Pregnancy-related mortality in the United States, 2011-2013. Obstet Gynecol. Aug 2017;130(2):366-373. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Home page. World Health Organization. URL: https://www.who.int/ [accessed 2024-03-21]
• Troiano NH, Witcher PM. Maternal mortality and morbidity in the United States: classification, causes, preventability, and critical care obstetric implications. J Perinat Neonatal Nurs. 2018;32(3):222-231. [ CrossRef ] [ Medline ]
• Creanga AA, Berg CJ, Ko JY, Farr SL, Tong VT, Bruce FC, et al. Maternal mortality and morbidity in the United States: where are we now? J Womens Health (Larchmt). Jan 2014;23(1):3-9. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Campbell-Grossman C, Brage Hudson D, Keating-Lefler R, Ofe Fleck M. Community leaders' perceptions of single, low-income mothers' needs and concerns for social support. J Community Health Nurs. Dec 2005;22(4):241-257. [ CrossRef ] [ Medline ]
• New York State maternal mortality review report on pregnancy-associated deaths in 2018. New York State Department of Health. 2018. URL: https://www.health.ny.gov/community/adults/women/docs/maternal_mortality_review_2018.pdf [accessed 2024-03-23]
• Suplee PD, Kleppel L, Santa-Donato A, Bingham D. Improving postpartum education about warning signs of maternal morbidity and mortality. Nurs Womens Health. Dec 2017;20(6):552-567. [ CrossRef ] [ Medline ]
• Howell EA, Bodnar-Deren S, Balbierz A, Parides M, Bickell N. An intervention to extend breastfeeding among black and Latina mothers after delivery. Am J Obstet Gynecol. Mar 2014;210(3):239.e1-239.e5. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hall WJ, Chapman MV, Lee KM, Merino YM, Thomas TW, Payne BK, et al. Implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: a systematic review. Am J Public Health. Dec 2015;105(12):e60-e76. [ CrossRef ]
• Stepanikova I, Mollborn S, Cook KS, Thom DH, Kramer RM. Patients' race, ethnicity, language, and trust in a physician. J Health Soc Behav. Dec 24, 2006;47(4):390-405. [ CrossRef ] [ Medline ]
• Schwei RJ, Kadunc K, Nguyen AL, Jacobs EA. Impact of sociodemographic factors and previous interactions with the health care system on institutional trust in three racial/ethnic groups. Patient Educ Couns. Sep 2014;96(3):333-338. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Blair IV, Steiner JF, Fairclough DL, Hanratty R, Price DW, Hirsh HK, et al. Clinicians' implicit ethnic/racial bias and perceptions of care among Black and Latino patients. Ann Fam Med. 2013;11(1):43-52. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ayanian JZ, Zaslavsky AM, Guadagnoli E, Fuchs CS, Yost KJ, Creech CM, et al. Patients' perceptions of quality of care for colorectal cancer by race, ethnicity, and language. J Clin Oncol. Sep 20, 2005;23(27):6576-6586. [ CrossRef ] [ Medline ]
• Reyna VF, Nelson WL, Han PK, Dieckmann NF. How numeracy influences risk comprehension and medical decision making. Psychol Bull. Nov 2009;135(6):943-973. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Language use in the United States: 2011. United States Census Bureau. 2011. URL: https://www.census.gov/library/publications/2013/acs/acs-22.html [accessed 2024-03-23]
• Valdez RS, Brennan PF. Exploring patients' health information communication practices with social network members as a foundation for consumer health IT design. Int J Med Inform. May 2015;84(5):363-374. [ CrossRef ] [ Medline ]
• Valdez RS, Gibbons MC, Siegel ER, Kukafka R, Brennan PF. Designing consumer health IT to enhance usability among different racial and ethnic groups within the United States. Health Technol. Jul 13, 2012;2(4):225-233. [ CrossRef ]
• Valdez RS, Holden RJ. Health care human factors/ergonomics fieldwork in home and community settings. Ergon Des. Oct 2016;24(4):4-9. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Valdez RS, Holden RJ, Novak LL, Veinot TC. Transforming consumer health informatics through a patient work framework: connecting patients to context. J Am Med Inform Assoc. Jan 2015;22(1):2-10. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Bingham D, Suplee PD, Morris MH, McBride M. Healthcare strategies for reducing pregnancy-related morbidity and mortality in the postpartum period. J Perinat Neonatal Nurs. 2018;32(3):241-249. [ CrossRef ] [ Medline ]
• Creanga AA, Berg CJ, Syverson C, Seed K, Bruce FC, Callaghan WM. Pregnancy-related mortality in the United States, 2006-2010. Obstet Gynecol. Jan 2015;125(1):5-12. [ CrossRef ] [ Medline ]
• Suplee PD, Bingham D, Kleppel L. Nurses' knowledge and teaching of possible postpartum complications. MCN Am J Matern Child Nurs. 2017;42(6):338-344. [ CrossRef ] [ Medline ]
• O'Byrne LJ, Bodunde EO, Maher GM, Khashan AS, Greene RM, Browne JP, et al. Patient-reported outcome measures evaluating postpartum maternal health and well-being: a systematic review and evaluation of measurement properties. Am J Obstet Gynecol MFM. Nov 2022;4(6):100743. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Adler A, Conte TF, Illarraza T. Improvement of Postpartum Nursing Discharge Education Through Adaptation of AWHONN’s Post-Birth Education Program. J Obstet Gynecol Neonatal Nurs. Jun 2019;48(3):S54. [ CrossRef ]
• Urgent maternal warning signs. Centers for Disease Control and Prevention. URL: https://www.cdc.gov/hearher/maternal-warning-signs/index.html [accessed 2022-12-11]
• Hannan J. APN telephone follow up to low-income first time mothers. J Clin Nurs. Jan 30, 2013;22(1-2):262-270. [ CrossRef ] [ Medline ]
• Dennis CL, Kingston D. A systematic review of telephone support for women during pregnancy and the early postpartum period. J Obstet Gynecol Neonatal Nurs. May 2008;37(3):301-314. [ CrossRef ] [ Medline ]
• Letourneau N, Secco L, Colpitts J, Aldous S, Stewart M, Dennis CL. Quasi-experimental evaluation of a telephone-based peer support intervention for maternal depression. J Adv Nurs. Jul 23, 2015;71(7):1587-1599. [ CrossRef ] [ Medline ]
• Shamshiri Milani H, Azargashb E, Beyraghi N, Defaie S, Asbaghi T. Effect of telephone-based support on postpartum depression: a randomized controlled trial. Int J Fertil Steril. 2015;9(2):247-253. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Mobile fact sheet. Pew Research Center. URL: https://www.pewresearch.org/internet/fact-sheet/mobile/ [accessed 2023-02-22]
• Anderson M. Digital divide persists even as lower-income Americans make gains in tech adoption. Pew Research Center. URL: https:/​/www.​urbanismnext.org/​resources/​digital-divide-persists-even-as-lower-income-americans-make-gains-in-tech-adoption [accessed 2024-03-23]
• Drexler K, Cheu L, Donelan E, Kominiarek M. 415: Remote self-monitoring of perinatal weight and perinatal outcomes in low-risk women. Am J Obstet Gynecol. Jan 2020;222(1):S272-S273. [ CrossRef ]
• Marko KI, Ganju N, Krapf JM, Gaba ND, Brown JA, Benham JJ, et al. A mobile prenatal care app to reduce in-person visits: prospective controlled trial. JMIR Mhealth Uhealth. May 01, 2019;7(5):e10520. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Vernon MM, Yang FM. Implementing a self-monitoring application during pregnancy and postpartum for rural and underserved women: a qualitative needs assessment study. PLoS One. Jul 19, 2022;17(7):e0270190. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Berry DL, Blumenstein BA, Halpenny B, Wolpin S, Fann JR, Austin-Seymour M, et al. Enhancing patient-provider communication with the electronic self-report assessment for cancer: a randomized trial. J Clin Oncol. Mar 10, 2011;29(8):1029-1035. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Lordon RJ, Mikles SP, Kneale L, Evans HL, Munson SA, Backonja U, et al. How patient-generated health data and patient-reported outcomes affect patient-clinician relationships: a systematic review. Health Informatics J. Dec 20, 2020;26(4):2689-2706. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Todd BL, Feuerstein M, Gehrke A, Hydeman J, Beaupin L. Identifying the unmet needs of breast cancer patients post-primary treatment: the Cancer Survivor Profile (CSPro). J Cancer Surviv. Jun 29, 2015;9(2):137-160. [ CrossRef ] [ Medline ]
• Basch E, Deal AM, Dueck AC, Scher HI, Kris MG, Hudis C, et al. Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA. Jul 11, 2017;318(2):197-198. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Basch E, Deal AM, Kris MG, Scher HI, Hudis CA, Sabbatini P, et al. Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. J Clin Oncol. Feb 20, 2016;34(6):557-565. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Denis F, Basch E, Septans A, Bennouna J, Urban T, Dueck AC, et al. Two-year survival comparing web-based symptom monitoring vs routine surveillance following treatment for lung cancer. JAMA. Jan 22, 2019;321(3):306-307. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Howell EA, Balbierz A, Wang J, Parides M, Zlotnick C, Leventhal H. Reducing postpartum depressive symptoms among black and Latina mothers: a randomized controlled trial. Obstet Gynecol. May 2012;119(5):942-949. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Ngai FW, Chan SW, Ip WY. The effects of a childbirth psychoeducation program on learned resourcefulness, maternal role competence and perinatal depression: a quasi-experiment. Int J Nurs Stud. Oct 2009;46(10):1298-1306. [ CrossRef ] [ Medline ]
• Shorey S, Chan SW, Chong YS, He HG. A randomized controlled trial of the effectiveness of a postnatal psychoeducation programme on self-efficacy, social support and postnatal depression among primiparas. J Adv Nurs. Jun 15, 2015;71(6):1260-1273. [ CrossRef ] [ Medline ]
• Diefenbach MA, Leventhal H. The common-sense model of illness representation: theoretical and practical considerations. J Soc Distress Homeless. Jul 07, 2016;5(1):11-38. [ CrossRef ]
• Wickens CD. Multiple resources and mental workload. Hum Factors. Jun 2008;50(3):449-455. [ CrossRef ] [ Medline ]
• Gadamer HG. Philosophical Hermeneutics. Oakland, CA. University of California Press; 1976.
• Saldana J. The Coding Manual for Qualitative Researchers. Thousand Oaks, CA. Sage Publications; 2012.
• Huberman AM, Miles M, Saldana J. Qualitative Data Analysis: A Methods Sourcebook. Thousand Oaks, CA. Sage Publications; 2014.
• Pope C, Ziebland S, Mays N. Analysing qualitative data. In: Pope C, Mays N, editors. Qualitative Research in Health Care. Hoboken, NJ. John Wiley & Sons; 2006;63-81.
• Fusch PI, Ness LR. Are we there yet? Data saturation in qualitative research. Qual Rep. Sep 8, 2015;20(9):1408-1416. [ FREE Full text ] [ CrossRef ]
• Morse JM. The significance of saturation. Qual Health Res. Jul 01, 2016;5(2):147-149. [ CrossRef ]
• Sultan P, Sharawi N, Blake L, Ando K, Sultan E, Aghaeepour N, et al. Use of patient-reported outcome measures to assess outpatient postpartum recovery: a systematic review. JAMA Netw Open. May 03, 2021;4(5):e2111600. [ FREE Full text ] [ CrossRef ] [ Medline ]
• O'Carroll J, Ando K, Yun R, Panelli D, Nicklin A, Kennedy N, et al. A systematic review of patient-reported outcome measures used in maternal postpartum anxiety. Am J Obstet Gynecol MFM. Sep 2023;5(9):101076. [ CrossRef ] [ Medline ]
• Cox J. Thirty years with the Edinburgh postnatal depression scale: voices from the past and recommendations for the future. Br J Psychiatry. Mar 18, 2019;214(3):127-129. [ CrossRef ] [ Medline ]
• Novick AM, Kwitowski M, Dempsey J, Cooke DL, Dempsey AG. Technology-based approaches for supporting perinatal mental health. Curr Psychiatry Rep. Sep 23, 2022;24(9):419-429. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Guy Jr GP, Adams EK, Redd SK, Dunlop AL. Effects of Georgia's Medicaid family planning waiver on pregnancy characteristics and birth outcomes. Womens Health Issues. Dec 15, 2023. [ CrossRef ] [ Medline ]
• Zimmermann K, Haen LS, Desloge A, Handler A. The role of a local health department in advancing health equity: universal postpartum home visiting in a large urban setting. Health Equity. Oct 01, 2023;7(1):703-712. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Castillo AF, Davis AL, Krishnamurti T. Adapting a pregnancy app to address disparities in healthcare access among an emerging Latino community: qualitative study using implementation science frameworks. Research Square. Preprint posted online April 27, 2022. [ FREE Full text ] [ CrossRef ]
• Shneiderman B. The eyes have it: a task by data type taxonomy for information visualizations. In: Bederson BB, Shneiderman B, editors. The Craft of Information Visualization: Readings and Reflections. Burlington, MA. Morgan Kaufmann; 2003;364-371.
• White KM, Williamson C, Bergou N, Oetzmann C, de Angel V, Matcham F, et al. A systematic review of engagement reporting in remote measurement studies for health symptom tracking. NPJ Digit Med. Jun 29, 2022;5(1):82. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Walsh S, Golden E, Priebe S. Systematic review of patients' participation in and experiences of technology-based monitoring of mental health symptoms in the community. BMJ Open. Jun 21, 2016;6(6):e008362. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Davidson KW, Mangione CM, Barry MJ, Cabana MD, Caughey AB, Davis EM, et al. Actions to transform US preventive services task force methods to mitigate systemic racism in clinical preventive services. JAMA. Dec 21, 2021;326(23):2405-2411. [ CrossRef ] [ Medline ]
• Im EO, Chee W, Hu Y, Kim S, Choi H, Hamajima Y, et al. What to consider in a culturally tailored technology-based intervention? Comput Inform Nurs. Sep 2018;36(9):424-429. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Yen RW, Smith J, Engel J, Muscat DM, Smith SK, Mancini J, et al. A systematic review and meta-analysis of patient decision aids for socially disadvantaged populations: update from the international patient decision aid standards (IDPAS). Med Decis Making. Jun 21, 2021;41(7):870-896. [ CrossRef ]
• Nielsen J. 10 usability heuristics for user interface design. Nielsen Norman Group. 1994. URL: https://www.nngroup.com/articles/ten-usability-heuristics/ [accessed 2020-11-15]
• Ancker JS, Stabile C, Carter J, Chen LY, Stein D, Stetson PD, et al. Informing, reassuring, or alarming? Balancing patient needs in the development of a postsurgical symptom reporting system in cancer. AMIA Annu Symp Proc. 2018;2018:166-174. [ FREE Full text ] [ Medline ]

Abbreviations

Edited by A Mavragani; submitted 22.03.23; peer-reviewed by C Laranjeira; comments to author 15.01.24; revised version received 20.02.24; accepted 08.03.24; published 26.04.24.

©Natalie Benda, Sydney Woode, Stephanie Niño de Rivera, Robin B Kalish, Laura E Riley, Alison Hermann, Ruth Masterson Creber, Eric Costa Pimentel, Jessica S Ancker. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Do implicit bias trainings on race improve health care?

by Nao Hagiwara, The Conversation

There is increasing evidence that implicit bias—non-conscious attitudes toward specific groups—is a source of racial inequities in certain aspects of health care, and lawmakers are taking note.

Since the tragic murder of George Floyd in May 2020, wherein a Black man was killed by police, several U.S. federal and state legislators have introduced proposals declaring racism as a public health crisis . In March 2024, four U.S. senators led a resolution calling out the "implicit racial and ethnic biases within the health care system , which have an explicit impact on the quality of care experienced by members of racial and ethnic minority groups."

Following this reasoning, states like California and Massachusetts have enacted legislation mandating implicit bias training for health care providers. Health institutions have also focused on addressing implicit bias among the next generation of providers. For example, the American Medical Association's guidelines to address systemic racism in medicine includes requiring training that covers various forms of racial bias.

But is implicit bias training improving care quality for Black patients? We are a social and health psychologist and a health economist who are investigating the role that provider implicit bias plays in racial health care disparities. Our ongoing review of the existing evidence suggests the answer is: not yet.

What is implicit bias?

The first thing to understand is that implicit bias isn't just one thing. It involves multiple interconnected components that govern how someone interacts with specific groups or its members: affect, behavior and cognition.

Psychologists sometimes refer to those components as the ABCs.

The affective component of bias, also known as prejudice, is defined as having negative feelings towards a group or its members. The behavioral component of bias, or discrimination, involves negative or harmful actions towards a group or its members. Lastly, the cognitive component of bias, also known as stereotyping, refers to expectations and beliefs about a group.

One common misunderstanding is that implicit bias is inherently unconscious and people are unaware of their own negative feelings, beliefs and behaviors. In fact, research suggests that people are remarkably accurate in perceiving their own levels of implicit bias.

Each component of bias can operate at implicit and explicit levels. At the implicit level, the ABCs arise spontaneously and effortlessly, while ABCs operating at the explicit level are intentional and effortful. For example, the unease someone may feel when encountering a large Black man at night is an emotion triggered at the implicit level. Actively making an effort to replace those feelings of unease with neutral or positive feelings are emotions activated at the explicit level.

Why does implicit bias matter in health care?

Black and white people experience stark differences in treatment during medical interactions. A December 2023 survey from the Kaiser Family Foundation found that nearly 1 in 5 Black people reported experiencing unfair or disrespectful treatment from their health care providers in the past three years because of their race. Only 3% of white respondents reported similar treatment. Researchers have seen similar health inequities across race and ethnicity .

Extensive research over the past two decades indicates racial inequities in patient-provider communication stem largely from implicit prejudice among health care providers . This implicit prejudice manifests during medical interactions with Black patients through a wide range of communication behaviors . These include nonverbal behaviors, or how people move their bodies—such as eye contact and hand movements—and paraverbal behaviors, or how people deliver speech—such as their tone and volume. Both of these behaviors typically occur spontaneously.

For example, providers with higher levels of implicit prejudice tend to talk more and spend less time evaluating Black patients. They also display less positive and more negative affect and more frequently use anxiety-related words like "worry," "afraid" and "nervous."

Importantly, Black patients are adept at discerning these subtle negative communication behaviors. "It's petty, little things," a Black patient told the Kaiser Family Foundation. "When they call the nurse, they rush to come see the white people. They don't rush to see the Black people. I think it's racist." Consequently, Black patients report lower levels of satisfaction after interacting with providers with higher levels of implicit prejudice.

A common misconception is that implicit prejudice is a key driver of racial disparities in medical treatment. However, current research does not support the idea that providers with higher levels of implicit prejudice treat Black patients worse than white patients. Additionally, more research is needed to determine whether implicit stereotyping from providers—such as automatically associating the idea of being "medically uncooperative" with Black people—would also lead to negative communication behaviors or sub-optimal treatment decisions for Black patients.

What's wrong with implicit bias training?

Many researchers and clinicians see implicit bias training as an essential component of medical education. However, current programs have shortcomings that undermine their effectiveness.

To understand what typical implicit bias training is like, our ongoing systematic review looks at 77 studies on implicit bias training programs in U.S. health care institutions. Although the majority of the programs were designed to address implicit racial bias, a significant number also addressed other forms of bias including gender identity, sexual orientation and socioeconomic status. Most programs aim to educate health care workers and trainees on implicit bias and how it may affect their patient care, as well as increase awareness about their own biases. Most are single sessions that last about 5.5 hours on average.

However, the design of these training programs does not align with current scientific knowledge about implicit bias.

First, while awareness of one's biases is a necessary first step to mitigating implicit bias, it alone is not sufficient . Providers must also be personally invested in and have the mental capacity to address their biases.

Second, mitigating implicit bias requires repeated and consistent practice . Implicit bias is like a habit: it is deeply ingrained and operates without intentional control, making it challenging to recognize and change.

Third, training effectiveness is more accurately assessed through patient outcomes, such as care satisfaction, rather than self-reflection or implicit bias scores. Because providers may be concerned about how program facilitators will judge them , they may not provide honest feedback. Furthermore, changes in implicit bias scores do not necessarily result in decreased discriminatory behaviors, making it unclear how these programs can change the quality of care that Black patients experience.

How can health care systems better address implicit bias?

Developing and implementing effective implicit bias training in health care is a scientific endeavor that requires a strong supporting structure.

For example, the clinical and translational science, or CTS, framework , originally designed to help translate discoveries in the lab into treatments in the clinic, could also be applied to implicit bias training. This framework guides scientific progress across incremental stages, starting from confirming the mechanism behind an illness to developing and testing a new treatment for use in the broader community.

This framework is particularly relevant to the development and implementation of evidence-based implicit bias training. Researchers first focus on confirming the mechanisms that underlie implicit bias. Then, after developing and testing implicit bias training programs, they examine its effectiveness across institutions and among diverse health care professionals.

Applying a rigorous scientific process to the development of implicit bias training requires an institution's long-term commitment, robust support and substantial resources. We believe this investment is a small price to pay for the invaluable progress it promises in reshaping health care for the better for everyone.

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