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• Ethical Considerations in Research | Types & Examples

Ethical Considerations in Research | Types & Examples

Published on October 18, 2021 by Pritha Bhandari . Revised on May 9, 2024.

Ethical considerations in research are a set of principles that guide your research designs and practices. Scientists and researchers must always adhere to a certain code of conduct when collecting data from people.

The goals of human research often include understanding real-life phenomena, studying effective treatments, investigating behaviors, and improving lives in other ways. What you decide to research and how you conduct that research involve key ethical considerations.

These considerations work to

• protect the rights of research participants
• enhance research validity
• maintain scientific or academic integrity

Table of contents

Why do research ethics matter, getting ethical approval for your study, types of ethical issues, voluntary participation, informed consent, confidentiality, potential for harm, results communication, examples of ethical failures, other interesting articles, frequently asked questions about research ethics.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe for research subjects.

You’ll balance pursuing important research objectives with using ethical research methods and procedures. It’s always necessary to prevent permanent or excessive harm to participants, whether inadvertent or not.

Defying research ethics will also lower the credibility of your research because it’s hard for others to trust your data if your methods are morally questionable.

Even if a research idea is valuable to society, it doesn’t justify violating the human rights or dignity of your study participants.

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Before you start any study involving data collection with people, you’ll submit your research proposal to an institutional review board (IRB) .

An IRB is a committee that checks whether your research aims and research design are ethically acceptable and follow your institution’s code of conduct. They check that your research materials and procedures are up to code.

If successful, you’ll receive IRB approval, and you can begin collecting data according to the approved procedures. If you want to make any changes to your procedures or materials, you’ll need to submit a modification application to the IRB for approval.

If unsuccessful, you may be asked to re-submit with modifications or your research proposal may receive a rejection. To get IRB approval, it’s important to explicitly note how you’ll tackle each of the ethical issues that may arise in your study.

There are several ethical issues you should always pay attention to in your research design, and these issues can overlap with each other.

You’ll usually outline ways you’ll deal with each issue in your research proposal if you plan to collect data from participants.

Voluntary participation means that all research subjects are free to choose to participate without any pressure or coercion.

All participants are able to withdraw from, or leave, the study at any point without feeling an obligation to continue. Your participants don’t need to provide a reason for leaving the study.

It’s important to make it clear to participants that there are no negative consequences or repercussions to their refusal to participate. After all, they’re taking the time to help you in the research process , so you should respect their decisions without trying to change their minds.

Voluntary participation is an ethical principle protected by international law and many scientific codes of conduct.

Take special care to ensure there’s no pressure on participants when you’re working with vulnerable groups of people who may find it hard to stop the study even when they want to.

Informed consent refers to a situation in which all potential participants receive and understand all the information they need to decide whether they want to participate. This includes information about the study’s benefits, risks, funding, and institutional approval.

You make sure to provide all potential participants with all the relevant information about

• what the study is about
• the risks and benefits of taking part
• how long the study will take
• your supervisor’s contact information and the institution’s approval number

Usually, you’ll provide participants with a text for them to read and ask them if they have any questions. If they agree to participate, they can sign or initial the consent form. Note that this may not be sufficient for informed consent when you work with particularly vulnerable groups of people.

If you’re collecting data from people with low literacy, make sure to verbally explain the consent form to them before they agree to participate.

For participants with very limited English proficiency, you should always translate the study materials or work with an interpreter so they have all the information in their first language.

In research with children, you’ll often need informed permission for their participation from their parents or guardians. Although children cannot give informed consent, it’s best to also ask for their assent (agreement) to participate, depending on their age and maturity level.

Anonymity means that you don’t know who the participants are and you can’t link any individual participant to their data.

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, and videos.

In many cases, it may be impossible to truly anonymize data collection . For example, data collected in person or by phone cannot be considered fully anonymous because some personal identifiers (demographic information or phone numbers) are impossible to hide.

You’ll also need to collect some identifying information if you give your participants the option to withdraw their data at a later stage.

Data pseudonymization is an alternative method where you replace identifying information about participants with pseudonymous, or fake, identifiers. The data can still be linked to participants but it’s harder to do so because you separate personal information from the study data.

Confidentiality means that you know who the participants are, but you remove all identifying information from your report.

All participants have a right to privacy, so you should protect their personal data for as long as you store or use it. Even when you can’t collect data anonymously, you should secure confidentiality whenever you can.

Some research designs aren’t conducive to confidentiality, but it’s important to make all attempts and inform participants of the risks involved.

As a researcher, you have to consider all possible sources of harm to participants. Harm can come in many different forms.

• Psychological harm: Sensitive questions or tasks may trigger negative emotions such as shame or anxiety.
• Social harm: Participation can involve social risks, public embarrassment, or stigma.
• Physical harm: Pain or injury can result from the study procedures.
• Legal harm: Reporting sensitive data could lead to legal risks or a breach of privacy.

It’s best to consider every possible source of harm in your study as well as concrete ways to mitigate them. Involve your supervisor to discuss steps for harm reduction.

Make sure to disclose all possible risks of harm to participants before the study to get informed consent. If there is a risk of harm, prepare to provide participants with resources or counseling or medical services if needed.

Some of these questions may bring up negative emotions, so you inform participants about the sensitive nature of the survey and assure them that their responses will be confidential.

The way you communicate your research results can sometimes involve ethical issues. Good science communication is honest, reliable, and credible. It’s best to make your results as transparent as possible.

Take steps to actively avoid plagiarism and research misconduct wherever possible.

Plagiarism means submitting others’ works as your own. Although it can be unintentional, copying someone else’s work without proper credit amounts to stealing. It’s an ethical problem in research communication because you may benefit by harming other researchers.

Self-plagiarism is when you republish or re-submit parts of your own papers or reports without properly citing your original work.

This is problematic because you may benefit from presenting your ideas as new and original even though they’ve already been published elsewhere in the past. You may also be infringing on your previous publisher’s copyright, violating an ethical code, or wasting time and resources by doing so.

In extreme cases of self-plagiarism, entire datasets or papers are sometimes duplicated. These are major ethical violations because they can skew research findings if taken as original data.

You notice that two published studies have similar characteristics even though they are from different years. Their sample sizes, locations, treatments, and results are highly similar, and the studies share one author in common.

Research misconduct

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement about data analyses.

Research misconduct is a serious ethical issue because it can undermine academic integrity and institutional credibility. It leads to a waste of funding and resources that could have been used for alternative research.

Later investigations revealed that they fabricated and manipulated their data to show a nonexistent link between vaccines and autism. Wakefield also neglected to disclose important conflicts of interest, and his medical license was taken away.

This fraudulent work sparked vaccine hesitancy among parents and caregivers. The rate of MMR vaccinations in children fell sharply, and measles outbreaks became more common due to a lack of herd immunity.

Research scandals with ethical failures are littered throughout history, but some took place not that long ago.

Some scientists in positions of power have historically mistreated or even abused research participants to investigate research problems at any cost. These participants were prisoners, under their care, or otherwise trusted them to treat them with dignity.

To demonstrate the importance of research ethics, we’ll briefly review two research studies that violated human rights in modern history.

These experiments were inhumane and resulted in trauma, permanent disabilities, or death in many cases.

After some Nazi doctors were put on trial for their crimes, the Nuremberg Code of research ethics for human experimentation was developed in 1947 to establish a new standard for human experimentation in medical research.

In reality, the actual goal was to study the effects of the disease when left untreated, and the researchers never informed participants about their diagnoses or the research aims.

Although participants experienced severe health problems, including blindness and other complications, the researchers only pretended to provide medical care.

When treatment became possible in 1943, 11 years after the study began, none of the participants were offered it, despite their health conditions and high risk of death.

Ethical failures like these resulted in severe harm to participants, wasted resources, and lower trust in science and scientists. This is why all research institutions have strict ethical guidelines for performing research.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

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Annual Review of Ethics Case Studies

What are research ethics cases.

For additional information, please visit Resources for Research Ethics Education

Research Ethics Cases are a tool for discussing scientific integrity. Cases are designed to confront the readers with a specific problem that does not lend itself to easy answers. By providing a focus for discussion, cases help staff involved in research to define or refine their own standards, to appreciate alternative approaches to identifying and resolving ethical problems, and to develop skills for dealing with hard problems on their own.

Research Ethics Cases for Use by the NIH Community

• Theme 24 – Using AI in Research and Ethical Conduct of Clinical Trials (2024)
• Theme 23 – Authorship, Collaborations, and Mentoring (2023)
• Theme 22 – Use of Human Biospecimens and Informed Consent (2022)
• Theme 21 – Science Under Pressure (2021)
• Theme 20 – Data, Project and Lab Management, and Communication (2020)
• Theme 19 – Civility, Harassment and Inappropriate Conduct (2019)
• Theme 18 – Implicit and Explicit Biases in the Research Setting (2018)
• Theme 17 – Socially Responsible Science (2017)
• Theme 16 – Research Reproducibility (2016)
• Theme 15 – Authorship and Collaborative Science (2015)
• Theme 14 – Differentiating Between Honest Discourse and Research Misconduct and Introduction to Enhancing Reproducibility (2014)
• Theme 13 – Data Management, Whistleblowers, and Nepotism (2013)
• Theme 12 – Mentoring (2012)
• Theme 11 – Authorship (2011)
• Theme 10 – Science and Social Responsibility, continued (2010)
• Theme 9 – Science and Social Responsibility - Dual Use Research (2009)
• Theme 8 – Borrowing - Is It Plagiarism? (2008)
• Theme 7 – Data Management and Scientific Misconduct (2007)
• Theme 6 – Ethical Ambiguities (2006)
• Theme 5 – Data Management (2005)
• Theme 4 – Collaborative Science (2004)
• Theme 3 – Mentoring (2003)
• Theme 2 – Authorship (2002)
• Theme 1 – Scientific Misconduct (2001)

For Facilitators Leading Case Discussion

For the sake of time and clarity of purpose, it is essential that one individual have responsibility for leading the group discussion. As a minimum, this responsibility should include:

• Reading the case aloud.
• Defining, and re-defining as needed, the questions to be answered.
• Encouraging discussion that is “on topic”.
• Discouraging discussion that is “off topic”.
• Keeping the pace of discussion appropriate to the time available.
• Eliciting contributions from all members of the discussion group.
• Summarizing both majority and minority opinions at the end of the discussion.

How Should Cases be Analyzed?

Many of the skills necessary to analyze case studies can become tools for responding to real world problems. Cases, like the real world, contain uncertainties and ambiguities. Readers are encouraged to identify key issues, make assumptions as needed, and articulate options for resolution. In addition to the specific questions accompanying each case, readers should consider the following questions:

• Who are the affected parties (individuals, institutions, a field, society) in this situation?
• What interest(s) (material, financial, ethical, other) does each party have in the situation? Which interests are in conflict?
• Were the actions taken by each of the affected parties acceptable (ethical, legal, moral, or common sense)? If not, are there circumstances under which those actions would have been acceptable? Who should impose what sanction(s)?
• What other courses of action are open to each of the affected parties? What is the likely outcome of each course of action?
• For each party involved, what course of action would you take, and why?
• What actions could have been taken to avoid the conflict?

Is There a Right Answer?

Acceptable solutions.

Most problems will have several acceptable solutions or answers, but it will not always be the case that a perfect solution can be found. At times, even the best solution will still have some unsatisfactory consequences.

Unacceptable Solutions

While more than one acceptable solution may be possible, not all solutions are acceptable. For example, obvious violations of specific rules and regulations or of generally accepted standards of conduct would typically be unacceptable. However, it is also plausible that blind adherence to accepted rules or standards would sometimes be an unacceptable course of action.

Ethical Decision-Making

It should be noted that ethical decision-making is a process rather than a specific correct answer. In this sense, unethical behavior is defined by a failure to engage in the process of ethical decision-making. It is always unacceptable to have made no reasonable attempt to define a consistent and defensible basis for conduct.

This page was last updated on Friday, July 26, 2024

Ethical Issues in Research

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• First Online: 05 March 2021
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• Juwel Rana 2 , 3 , 4 ,
• Segufta Dilshad 2 &
• Md. Ali Ahsan 5  

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The most important human endeavor is the striving for morality in our actions. Our inner balance and even our very existence depend on it. Only morality in our actions can give beauty and dignity to life – Albert Einstein.

Ethics ; Methodology ; Mixed-method research ; Observation ; Qualitative research ; Quantitative research ; Research ; Research design ; Research ethics

Ethics is a set of standards, a code, or value system, worked out from human reason and experience, by which free human actions are determined as ultimately right or wrong, good, or evil. If acting agrees with these standards, it is ethical, otherwise unethical.

Scientific research refers to a persistent exercise towards producing new knowledge to unveil a new stream of ideas in academia for humankind.

Research ethics refer to some of the genres that researchers follow to protect the rights in developing research strategies and building a trusted relationship between the...

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Bulmer M (1982) Social Research Ethics: An Examination of the Merits of Covert Participant Observation. Holmes & Meier Publishers

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Butler I (2002) A Code of Ethics for Social Work and Social Care Research. Br J Soc Work [Internet]. 32(2):239–48. Available from: https://doi.org/10.1093/bjsw/32.2.239

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Hill J, Wright LT (2001) A qualitative research agenda for small to medium-sized enterprises. Mark Intell Plan 19(6):432–443

Homan R (1991) The ethics of social research. Addison-Wesley Longman Limited

Israel M, Hay I (2006) Research ethics for social scientists. Sage

Kimmel AJ (1988) Ethics and values in applied social research. 1st ed. SAGE Publications Inc

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Department of Public Health, School of Health and Life Sciences, North South University, Dhaka, Bangladesh

Juwel Rana & Segufta Dilshad

Department of Biostatistics and Epidemiology, School of Health and Health Sciences, University of Massachusetts Amherst, Amherst, MA, USA

Department of Research and Innovation, South Asia Institute for Social Transformation (SAIST), Dhaka, Bangladesh

Space and Environment Research Center (SERC), Rajshahi, Bangladesh

Md. Ali Ahsan

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Rana, J., Dilshad, S., Ahsan, M.A. (2021). Ethical Issues in Research. In: Farazmand, A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-31816-5_462-1

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Received : 01 February 2021

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Research Design Review

A discussion of qualitative & quantitative research design, ethical considerations in case-centered qualitative research.

The following is a modified excerpt from Applied Qualitative Research Design: A Total Quality Framework Approach (Roller & Lavrakas, 2015, pp. 304-305)

Ethical considerations are important in every research method involving human subjects but they take on added significance in case-centered research where researchers often work closely with research participants over a period of time and frequently in the face-to-face mode (where researcher-participant relationships play an important role in the research outcomes).  Both case study and narrative research gather a great deal of highly detailed information on each case, e.g., a case study may collect a detailed account of a particular social program; or a narrative inquiry may result in long, very personal stories associated with a chronic illness.  Beyond the ethical dilemma associated with drawing interpretations of narratives outside their temporal and social contexts (Brinkmann & Kvale, 2008), case-centered studies run the risk of of inadvertently exposing participants’ identities (without their permission) unless preventive measures are taken.

This is why the use of informed and voluntary consent as well as approval from institutional review boards (when required) is critical in case-centered research.  Consent involves disclosing the various aspects of the research, emphasizing the voluntary component, promising to keep participants safe, and paying particular attention to vulnerable population segments (e.g., children).  Yet these efforts need to go further.  Case-centered researchers must also effectively communicate the confidential nature of the research and take extra precautions to ensure participants’ right to privacy – which can be particularly challenging when only one case is the focal point of the research (e.g., a city social program).  For this reason, it is not uncommon for case study and narrative researchers to maintain participants’ anonymity in their final reports by changing participants’ names as well as the names of the characters and places revealed in the course of the research.

The path that these ethical considerations – consent and anonymity – take in the research design is also important.  The skilled researcher will think carefully about how and when to incorporate these ethical standards while maintaining the quality and integrity of the data.  For instance, narrative researchers are reluctant to reveal “too much” regarding the study objectives at the onset of an interview in fear of biasing the participant’s narrative. The thinking tends to be that “the ‘scholarly good’ of framing the study in a way that makes possible the kind of narration the researcher needs outweighs the ‘moral’ good of telling the participant the exact nature of the study” (Josselson, 2007, p. 540). Many of these researchers balance the ethical obligation of informed consent with the need for quality outcomes by, among other things, gaining consent twice, i.e., before the interview and again at the completion of the interview, and by conducting a thoughtful debriefing with each participant.

Case-centered researchers also need to give thoughtful attention to anonymity and its impact on the final outcomes.  Specifically, researchers must address questions such as: How will anonymizing the data introduce bias or error by way of changing context?  and How will de-identifying the data alter its interpretation?  These are important questions because the answers may determine how or if the data is used.

Ethical considerations revolve around transparency and safety, with safety broadly defined in terms of both physical and psychological harm, including the potential harm associated with the invasion of privacy and confidentiality.  However, ethical considerations cannot (should not) be contemplated in a vacuum.  Researchers – particularly case-centered researchers – need to carefully incorporate these ethics while also ensuring the quality of the research results.

Brinkmann, S., & Kvale, S. (2008). Ethics in qualitative psychological research. In C. Willig & W. Stainton-Rogers (Eds.), The Sage handbook of qualitative psychology (pp. 263–279). London: Sage Publications.

Josselson, R. (2007). The ethical attitude in narrative research: Principles and practicalities. In D. J. Clandinin (Ed.), Handbook of narrative inquiry (pp. 537–566). Thousand Oaks, CA: Sage Publications.

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• Pingback: Generalizability in Case Study Research | Research Design Review

In qualitative research, ethical principles are primarily centered on protecting research participants and the guiding foundation of “do no harm”.

Following is a list of core ethical principles that are important in qualitative research:

Respect for persons – Respect the autonomy, decision-making and dignity of participants.

Beneficence – Minimizing the risks (physically, psychologically and socially) and maximizing the benefits to research participants.

Justice – Participants should be selected from groups of people whom the research may benefit.

Respect for communities – Protect and respect the values and interests of the community as a whole and protect the community from harm.

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Ethical Considerations In Psychology Research

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Ethics refers to the correct rules of conduct necessary when carrying out research. We have a moral responsibility to protect research participants from harm.

However important the issue under investigation, psychologists must remember that they have a duty to respect the rights and dignity of research participants. This means that they must abide by certain moral principles and rules of conduct.

What are Ethical Guidelines?

In Britain, ethical guidelines for research are published by the British Psychological Society, and in America, by the American Psychological Association. The purpose of these codes of conduct is to protect research participants, the reputation of psychology, and psychologists themselves.

Moral issues rarely yield a simple, unambiguous, right or wrong answer. It is, therefore, often a matter of judgment whether the research is justified or not.

For example, it might be that a study causes psychological or physical discomfort to participants; maybe they suffer pain or perhaps even come to serious harm.

On the other hand, the investigation could lead to discoveries that benefit the participants themselves or even have the potential to increase the sum of human happiness.

Rosenthal and Rosnow (1984) also discuss the potential costs of failing to carry out certain research. Who is to weigh up these costs and benefits? Who is to judge whether the ends justify the means?

Finally, if you are ever in doubt as to whether research is ethical or not, it is worthwhile remembering that if there is a conflict of interest between the participants and the researcher, it is the interests of the subjects that should take priority.

Studies must now undergo an extensive review by an institutional review board (US) or ethics committee (UK) before they are implemented. All UK research requires ethical approval by one or more of the following:

• Department Ethics Committee (DEC) : for most routine research.
• Institutional Ethics Committee (IEC) : for non-routine research.
• External Ethics Committee (EEC) : for research that s externally regulated (e.g., NHS research).

Committees review proposals to assess if the potential benefits of the research are justifiable in light of the possible risk of physical or psychological harm.

These committees may request researchers make changes to the study’s design or procedure or, in extreme cases, deny approval of the study altogether.

The British Psychological Society (BPS) and American Psychological Association (APA) have issued a code of ethics in psychology that provides guidelines for conducting research.  Some of the more important ethical issues are as follows:

Informed Consent

Before the study begins, the researcher must outline to the participants what the research is about and then ask for their consent (i.e., permission) to participate.

An adult (18 years +) capable of being permitted to participate in a study can provide consent. Parents/legal guardians of minors can also provide consent to allow their children to participate in a study.

Whenever possible, investigators should obtain the consent of participants. In practice, this means it is not sufficient to get potential participants to say “Yes.”

They also need to know what it is that they agree to. In other words, the psychologist should, so far as is practicable, explain what is involved in advance and obtain the informed consent of participants.

Informed consent must be informed, voluntary, and rational. Participants must be given relevant details to make an informed decision, including the purpose, procedures, risks, and benefits. Consent must be given voluntarily without undue coercion. And participants must have the capacity to rationally weigh the decision.

Components of informed consent include clearly explaining the risks and expected benefits, addressing potential therapeutic misconceptions about experimental treatments, allowing participants to ask questions, and describing methods to minimize risks like emotional distress.

Investigators should tailor the consent language and process appropriately for the study population. Obtaining meaningful informed consent is an ethical imperative for human subjects research.

The voluntary nature of participation should not be compromised through coercion or undue influence. Inducements should be fair and not excessive/inappropriate.

However, it is not always possible to gain informed consent.  Where the researcher can’t ask the actual participants, a similar group of people can be asked how they would feel about participating.

If they think it would be OK, then it can be assumed that the real participants will also find it acceptable. This is known as presumptive consent.

However, a problem with this method is that there might be a mismatch between how people think they would feel/behave and how they actually feel and behave during a study.

In order for consent to be ‘informed,’ consent forms may need to be accompanied by an information sheet for participants’ setting out information about the proposed study (in lay terms), along with details about the investigators and how they can be contacted.

Special considerations exist when obtaining consent from vulnerable populations with decisional impairments, such as psychiatric patients, intellectually disabled persons, and children/adolescents. Capacity can vary widely so should be assessed individually, but interventions to improve comprehension may help. Legally authorized representatives usually must provide consent for children.

Participants must be given information relating to the following:

• A statement that participation is voluntary and that refusal to participate will not result in any consequences or any loss of benefits that the person is otherwise entitled to receive.
• Purpose of the research.
• All foreseeable risks and discomforts to the participant (if there are any). These include not only physical injury but also possible psychological.
• Procedures involved in the research.
• Benefits of the research to society and possibly to the individual human subject.
• Length of time the subject is expected to participate.
• Person to contact for answers to questions or in the event of injury or emergency.
• Subjects” right to confidentiality and the right to withdraw from the study at any time without any consequences.

Debriefing after a study involves informing participants about the purpose, providing an opportunity to ask questions, and addressing any harm from participation. Debriefing serves an educational function and allows researchers to correct misconceptions. It is an ethical imperative.

After the research is over, the participant should be able to discuss the procedure and the findings with the psychologist. They must be given a general idea of what the researcher was investigating and why, and their part in the research should be explained.

Participants must be told if they have been deceived and given reasons why. They must be asked if they have any questions, which should be answered honestly and as fully as possible.

Debriefing should occur as soon as possible and be as full as possible; experimenters should take reasonable steps to ensure that participants understand debriefing.

“The purpose of debriefing is to remove any misconceptions and anxieties that the participants have about the research and to leave them with a sense of dignity, knowledge, and a perception of time not wasted” (Harris, 1998).

The debriefing aims to provide information and help the participant leave the experimental situation in a similar frame of mind as when he/she entered it (Aronson, 1988).

Exceptions may exist if debriefing seriously compromises study validity or causes harm itself, like negative emotions in children. Consultation with an institutional review board guides exceptions.

Debriefing indicates investigators’ commitment to participant welfare. Harms may not be raised in the debriefing itself, so responsibility continues after data collection. Following up demonstrates respect and protects persons in human subjects research.

Protection of Participants

Researchers must ensure that those participating in research will not be caused distress. They must be protected from physical and mental harm. This means you must not embarrass, frighten, offend or harm participants.

Normally, the risk of harm must be no greater than in ordinary life, i.e., participants should not be exposed to risks greater than or additional to those encountered in their normal lifestyles.

The researcher must also ensure that if vulnerable groups are to be used (elderly, disabled, children, etc.), they must receive special care. For example, if studying children, ensure their participation is brief as they get tired easily and have a limited attention span.

Researchers are not always accurately able to predict the risks of taking part in a study, and in some cases, a therapeutic debriefing may be necessary if participants have become disturbed during the research (as happened to some participants in Zimbardo’s prisoners/guards study ).

Deception research involves purposely misleading participants or withholding information that could influence their participation decision. This method is controversial because it limits informed consent and autonomy, but can provide otherwise unobtainable valuable knowledge.

Types of deception include (i) deliberate misleading, e.g. using confederates, staged manipulations in field settings, deceptive instructions; (ii) deception by omission, e.g., failure to disclose full information about the study, or creating ambiguity.

The researcher should avoid deceiving participants about the nature of the research unless there is no alternative – and even then, this would need to be judged acceptable by an independent expert. However, some types of research cannot be carried out without at least some element of deception.

For example, in Milgram’s study of obedience , the participants thought they were giving electric shocks to a learner when they answered a question wrongly. In reality, no shocks were given, and the learners were confederates of Milgram.

This is sometimes necessary to avoid demand characteristics (i.e., the clues in an experiment that lead participants to think they know what the researcher is looking for).

Another common example is when a stooge or confederate of the experimenter is used (this was the case in both the experiments carried out by Asch ).

According to ethics codes, deception must have strong scientific justification, and non-deceptive alternatives should not be feasible. Deception that causes significant harm is prohibited. Investigators should carefully weigh whether deception is necessary and ethical for their research.

However, participants must be deceived as little as possible, and any deception must not cause distress.  Researchers can determine whether participants are likely distressed when deception is disclosed by consulting culturally relevant groups.

Participants should immediately be informed of the deception without compromising the study’s integrity. Reactions to learning of deception can range from understanding to anger. Debriefing should explain the scientific rationale and social benefits to minimize negative reactions.

If the participant is likely to object or be distressed once they discover the true nature of the research at debriefing, then the study is unacceptable.

If you have gained participants’ informed consent by deception, then they will have agreed to take part without actually knowing what they were consenting to.  The true nature of the research should be revealed at the earliest possible opportunity or at least during debriefing.

Some researchers argue that deception can never be justified and object to this practice as it (i) violates an individual’s right to choose to participate; (ii) is a questionable basis on which to build a discipline; and (iii) leads to distrust of psychology in the community.

Confidentiality

Protecting participant confidentiality is an ethical imperative that demonstrates respect, ensures honest participation, and prevents harms like embarrassment or legal issues. Methods like data encryption, coding systems, and secure storage should match the research methodology.

Participants and the data gained from them must be kept anonymous unless they give their full consent.  No names must be used in a lab report .

Researchers must clearly describe to participants the limits of confidentiality and methods to protect privacy. With internet research, threats exist like third-party data access; security measures like encryption should be explained. For non-internet research, other protections should be noted too, like coding systems and restricted data access.

High-profile data breaches have eroded public trust. Methods that minimize identifiable information can further guard confidentiality. For example, researchers can consider whether birthdates are necessary or just ages.

Generally, reducing personal details collected and limiting accessibility safeguards participants. Following strong confidentiality protections demonstrates respect for persons in human subjects research.

What do we do if we discover something that should be disclosed (e.g., a criminal act)? Researchers have no legal obligation to disclose criminal acts and must determine the most important consideration: their duty to the participant vs. their duty to the wider community.

Ultimately, decisions to disclose information must be set in the context of the research aims.

Withdrawal from an Investigation

Participants should be able to leave a study anytime if they feel uncomfortable. They should also be allowed to withdraw their data. They should be told at the start of the study that they have the right to withdraw.

They should not have pressure placed upon them to continue if they do not want to (a guideline flouted in Milgram’s research).

Participants may feel they shouldn’t withdraw as this may ‘spoil’ the study. Many participants are paid or receive course credits; they may worry they won’t get this if they withdraw.

Even at the end of the study, the participant has a final opportunity to withdraw the data they have provided for the research.

Ethical Issues in Psychology & Socially Sensitive Research

There has been an assumption over the years by many psychologists that provided they follow the BPS or APA guidelines when using human participants and that all leave in a similar state of mind to how they turned up, not having been deceived or humiliated, given a debrief, and not having had their confidentiality breached, that there are no ethical concerns with their research.

But consider the following examples:

a) Caughy et al. 1994 found that middle-class children in daycare at an early age generally score less on cognitive tests than children from similar families reared in the home.

Assuming all guidelines were followed, neither the parents nor the children participating would have been unduly affected by this research. Nobody would have been deceived, consent would have been obtained, and no harm would have been caused.

However, consider the wider implications of this study when the results are published, particularly for parents of middle-class infants who are considering placing their young children in daycare or those who recently have!

b)  IQ tests administered to black Americans show that they typically score 15 points below the average white score.

When black Americans are given these tests, they presumably complete them willingly and are not harmed as individuals. However, when published, findings of this sort seek to reinforce racial stereotypes and are used to discriminate against the black population in the job market, etc.

Sieber & Stanley (1988) (the main names for Socially Sensitive Research (SSR) outline 4 groups that may be affected by psychological research: It is the first group of people that we are most concerned with!

• Members of the social group being studied, such as racial or ethnic group. For example, early research on IQ was used to discriminate against US Blacks.
• Friends and relatives of those participating in the study, particularly in case studies, where individuals may become famous or infamous. Cases that spring to mind would include Genie’s mother.
• The research team. There are examples of researchers being intimidated because of the line of research they are in.
• The institution in which the research is conducted.

salso suggest there are 4 main ethical concerns when conducting SSR:

• The research question or hypothesis.
• The treatment of individual participants.
• The institutional context.
• How the findings of the research are interpreted and applied.

Ethical Guidelines For Carrying Out SSR

Sieber and Stanley suggest the following ethical guidelines for carrying out SSR. There is some overlap between these and research on human participants in general.

Privacy : This refers to people rather than data. Asking people questions of a personal nature (e.g., about sexuality) could offend.

Confidentiality: This refers to data. Information (e.g., about H.I.V. status) leaked to others may affect the participant’s life.

Sound & valid methodology : This is even more vital when the research topic is socially sensitive. Academics can detect flaws in methods, but the lay public and the media often don’t.

When research findings are publicized, people are likely to consider them fact, and policies may be based on them. Examples are Bowlby’s maternal deprivation studies and intelligence testing.

Deception : Causing the wider public to believe something, which isn’t true by the findings, you report (e.g., that parents are responsible for how their children turn out).

Informed consent : Participants should be made aware of how participating in the research may affect them.

Justice & equitable treatment : Examples of unjust treatment are (i) publicizing an idea, which creates a prejudice against a group, & (ii) withholding a treatment, which you believe is beneficial, from some participants so that you can use them as controls.

Scientific freedom : Science should not be censored, but there should be some monitoring of sensitive research. The researcher should weigh their responsibilities against their rights to do the research.

Ownership of data : When research findings could be used to make social policies, which affect people’s lives, should they be publicly accessible? Sometimes, a party commissions research with their interests in mind (e.g., an industry, an advertising agency, a political party, or the military).

Some people argue that scientists should be compelled to disclose their results so that other scientists can re-analyze them. If this had happened in Burt’s day, there might not have been such widespread belief in the genetic transmission of intelligence. George Miller (Miller’s Magic 7) famously argued that we should give psychology away.

The values of social scientists : Psychologists can be divided into two main groups: those who advocate a humanistic approach (individuals are important and worthy of study, quality of life is important, intuition is useful) and those advocating a scientific approach (rigorous methodology, objective data).

The researcher’s values may conflict with those of the participant/institution. For example, if someone with a scientific approach was evaluating a counseling technique based on a humanistic approach, they would judge it on criteria that those giving & receiving the therapy may not consider important.

Cost/benefit analysis : It is unethical if the costs outweigh the potential/actual benefits. However, it isn’t easy to assess costs & benefits accurately & the participants themselves rarely benefit from research.

Sieber & Stanley advise that researchers should not avoid researching socially sensitive issues. Scientists have a responsibility to society to find useful knowledge.

• They need to take more care over consent, debriefing, etc. when the issue is sensitive.
• They should be aware of how their findings may be interpreted & used by others.
• They should make explicit the assumptions underlying their research so that the public can consider whether they agree with these.
• They should make the limitations of their research explicit (e.g., ‘the study was only carried out on white middle-class American male students,’ ‘the study is based on questionnaire data, which may be inaccurate,’ etc.
• They should be careful how they communicate with the media and policymakers.
• They should be aware of the balance between their obligations to participants and those to society (e.g. if the participant tells them something which they feel they should tell the police/social services).
• They should be aware of their own values and biases and those of the participants.

Arguments for SSR

• Psychologists have devised methods to resolve the issues raised.
• SSR is the most scrutinized research in psychology. Ethical committees reject more SSR than any other form of research.
• By gaining a better understanding of issues such as gender, race, and sexuality, we are able to gain greater acceptance and reduce prejudice.
• SSR has been of benefit to society, for example, EWT. This has made us aware that EWT can be flawed and should not be used without corroboration. It has also made us aware that the EWT of children is every bit as reliable as that of adults.
• Most research is still on white middle-class Americans (about 90% of research is quoted in texts!). SSR is helping to redress the balance and make us more aware of other cultures and outlooks.

Arguments against SSR

• Flawed research has been used to dictate social policy and put certain groups at a disadvantage.
• Research has been used to discriminate against groups in society, such as the sterilization of people in the USA between 1910 and 1920 because they were of low intelligence, criminal, or suffered from psychological illness.
• The guidelines used by psychologists to control SSR lack power and, as a result, are unable to prevent indefensible research from being carried out.

American Psychological Association. (2002). American Psychological Association ethical principles of psychologists and code of conduct. www.apa.org/ethics/code2002.html

Baumrind, D. (1964). Some thoughts on ethics of research: After reading Milgram’s” Behavioral study of obedience.”.  American Psychologist ,  19 (6), 421.

Caughy, M. O. B., DiPietro, J. A., & Strobino, D. M. (1994). Day‐care participation as a protective factor in the cognitive development of low‐income children.  Child development ,  65 (2), 457-471.

Harris, B. (1988). Key words: A history of debriefing in social psychology. In J. Morawski (Ed.), The rise of experimentation in American psychology (pp. 188-212). New York: Oxford University Press.

Rosenthal, R., & Rosnow, R. L. (1984). Applying Hamlet’s question to the ethical conduct of research: A conceptual addendum. American Psychologist, 39(5) , 561.

Sieber, J. E., & Stanley, B. (1988). Ethical and professional dimensions of socially sensitive research.  American psychologist ,  43 (1), 49.

The British Psychological Society. (2010). Code of Human Research Ethics. www.bps.org.uk/sites/default/files/documents/code_of_human_research_ethics.pdf

Further Information

• MIT Psychology Ethics Lecture Slides

BPS Documents

• Code of Ethics and Conduct (2018)
• Good Practice Guidelines for the Conduct of Psychological Research within the NHS
• Guidelines for Psychologists Working with Animals
• Guidelines for ethical practice in psychological research online

APA Documents

APA Ethical Principles of Psychologists and Code of Conduct

Ethical considerations in research: Best practices and examples

To conduct responsible research, you’ve got to think about ethics. They protect participants’ rights and their well-being - and they ensure your findings are valid and reliable. This isn’t just a box for you to tick. It’s a crucial consideration that can make all the difference to the outcome of your research.

In this article, we'll explore the meaning and importance of research ethics in today's research landscape. You'll learn best practices to conduct ethical and impactful research.

Examples of ethical considerations in research

As a researcher, you're responsible for ethical research alongside your organization. Fulfilling ethical guidelines is critical. Organizations must ensure employees follow best practices to protect participants' rights and well-being.

Keep these things in mind when it comes to ethical considerations in research:

Voluntary participation

Voluntary participation is key. Nobody should feel like they're being forced to participate or pressured into doing anything they don't want to. That means giving people a choice and the ability to opt out at any time, even if they've already agreed to take part in the study.

Informed consent

Informed consent isn't just an ethical consideration. It's a legal requirement as well. Participants must fully understand what they're agreeing to, including potential risks and benefits.

The best way to go about this is by using a consent form. Make sure you include:

• A brief description of the study and research methods.
• The potential benefits and risks of participating.
• The length of the study.
• Contact information for the researcher and/or sponsor.
• Reiteration of the participant’s right to withdraw from the research project at any time without penalty.

Anonymity means that participants aren't identifiable in any way. This includes:

• Email address
• Photographs
• Video footage

You need a way to anonymize research data so that it can't be traced back to individual participants. This may involve creating a new digital ID for participants that can’t be linked back to their original identity using numerical codes.

Confidentiality

Information gathered during a study must be kept confidential. Confidentiality helps to protect the privacy of research participants. It also ensures that their information isn't disclosed to unauthorized individuals.

Some ways to ensure confidentiality include:

• Using a secure server to store data.
• Removing identifying information from databases that contain sensitive data.
• Using a third-party company to process and manage research participant data.
• Not keeping participant records for longer than necessary.
• Avoiding discussion of research findings in public forums.

Potential for harm

​​The potential for harm is a crucial factor in deciding whether a research study should proceed. It can manifest in various forms, such as:

• Psychological harm
• Social harm
• Physical harm

Conduct an ethical review to identify possible harms. Be prepared to explain how you’ll minimize these harms and what support is available in case they do happen.

Fair payment

One of the most crucial aspects of setting up a research study is deciding on fair compensation for your participants. Underpayment is a common ethical issue that shouldn't be overlooked. Properly rewarding participants' time is critical for boosting engagement and obtaining high-quality data. While Prolific requires a minimum payment of £6.00 / $8.00 per hour, there are other factors you need to consider when deciding on a fair payment.

First, check your institution's reimbursement guidelines to see if they already have a minimum or maximum hourly rate. You can also use the national minimum wage as a reference point.

Next, think about the amount of work you're asking participants to do. The level of effort required for a task, such as producing a video recording versus a short survey, should correspond with the reward offered.

You also need to consider the population you're targeting. To attract research subjects with specific characteristics or high-paying jobs, you may need to offer more as an incentive.

We recommend a minimum payment of £9.00 / $12.00 per hour, but we understand that payment rates can vary depending on a range of factors. Whatever payment you choose should reflect the amount of effort participants are required to put in and be fair to everyone involved.

Ethical research made easy with Prolific

At Prolific, we believe in making ethical research easy and accessible. The findings from the Fairwork Cloudwork report speak for themselves. Prolific was given the top score out of all competitors for minimum standards of fair work.

With over 25,000 researchers in our community, we're leading the way in revolutionizing the research industry. If you're interested in learning more about how we can support your research journey, sign up to get started now.

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Ethical issues in mental health research: the case for community engagement

DuBois, James M a ; Bailey-Burch, Brendolyn b ; Bustillos, Dan a ; Campbell, Jean b ; Cottler, Linda c ; Fisher, Celia B d ; Hadley, Whitney B a ; Hoop, Jinger G e ; Roberts, Laura f ; Salter, Erica K a ; Sieber, Joan E g ; Stevenson, Richard D h

a Gnaegi Center for Healthcare Ethics, Saint Louis University, St Louis, Missouri, USA

b Missouri Institute of Mental Health, USA

c Department of Psychiatry at Washington University School of Medicine, Center for Community Based Research, St Louis, Missouri, USA

d Marie Ward Doty University Chair, Center for Ethics Education, Fordham University, New York City, New York, USA

e Mental Health Service Line, Edward Hines Jr Veteran's Administration Hospital, Hines, Illinois, USA

f Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, USA

g California State University, East Bay, Hayward, California, USA

h Alliance on Mental Illness, NAMI St Louis, St Louis, USA

Correspondence to James M. DuBois, Gnaegi Center for Healthcare Ethics, Salus 5th floor, Saint Louis University, 3545 Lafayette Avenue, St Louis, MO 63104, USA Tel: +1 314 977 6663; fax: +1 314 977 5150; e-mail: [email protected]

Purpose of review 

To describe community-engaged research (CEnR) and how it may improve the quality of a research study while addressing ethical concerns that communities may have with mental health and substance abuse research. This article includes a review of the literature as well as recommendations from an expert panel convened with funding from the US National Institute of Mental Health.

Recent findings 

CEnR represents a broad spectrum of practices, including representation on institutional ethics committees, attitude research with individuals from the study population, engaging community advisory boards, forming research partnerships with community organizations, and including community members as co-investigators.

Summary 

CEnR poses some challenges; for example, it requires funding and training for researchers and community members. However, it offers many benefits to researchers and communities, and some form of CEnR is appropriate and feasible in nearly every study involving human participants.

Introduction

Research has the potential not only to yield tremendous benefits, but also to inflict significant harms. Consider the example of genetic research on the relationship between schizophrenia and substance abuse. Such research may be undertaken with the legitimate goals of better understanding pathophysiology and comorbidity, seeking new modes of treatment, identifying causative environmental factors, and identifying high-risk individuals who might benefit from preventive interventions [1] . However, such research also generates concerns such as possible insurance or employment discrimination if confidentiality is breached; concerns about negative psychological consequences of learning of a genetic risk; and questions regarding the appropriateness of sharing information pertinent to biological relatives [2–4,5••,6] . Complicating the resolution of these ethical issues, the field of psychiatric genetics is ‘haunted by memories of the eugenics movement of the early 1900s, which targeted psychiatric patients and others considered “genetically inferior” for forced sterilization and death [ [2] , p. 322].’ When abuse by researchers occurs in a community, mistrust may occur and people may be less willing to participate in research or even to seek help from the healthcare community, possibly exacerbating health disparities [7] .

Although we may tend to think of individuals as those who are harmed or benefited by research endeavors, communities may feel that they too are directly affected for better or for worse when researchers study their members. In particular, they may be highly susceptible to stigmatization [8•] . For example, the term ‘scarlet genes’ has been coined to refer to the stigmatization of groups when popular media report on genetic predispositions to alcoholism or drug abuse within minority populations [9] .

In this paper, we review what is community-engaged research (CEnR), how CEnR may improve our ability to address such ethical and social issues, and how CEnR may improve the quality of science. This article builds upon a National Institute of Mental Health-funded scientific meeting held in St Louis in June 2009 that reviewed the literature and recent studies at the intersection of research ethics and CEnR in mental health research. The authors served as panelists and include ethicists, mental health researchers, and community representatives, all of whom have played some role in CEnR in the areas of mental health or drug addiction research.

The panel strongly endorses the idea that CEnR is an essential and beneficial component of human research; however, CEnR is not easy. To that point, we have added ‘caveat’ sections to raise awareness of some of the more significant challenges that arise in CEnR. Table 1 uses the example of genetic research on comorbid schizophrenia and substance abuse to illustrate the application of concepts found throughout the paper.

What is community-engaged research?

CEnR is research that provides communities with a voice and role in the research process beyond providing access to research participants [10–12] . Clearly, this can be done to greater or lesser degrees. The forms of engagement may range from studying the views of community members regarding research protocols [13,14••] to incorporating community members as coinvestigators [11,14••,15,16•] .

Table 2 provides a description of nine forms of engaging community members. Each of the approaches listed goes beyond international requirements that Institutional Review Boards (IRBs) or Institutional Ethics Committees (IECs) include at least one member who is a nonscientist and unaffiliated with the institution [20,47] . The various forms of CEnR provide ways of ensuring that a key stakeholder group is represented in the research enterprise as more than just a subject pool. In determining the degree to which communities are involved, key questions include the following:

• How many individuals from the community are provided with a voice (e.g., one representative, a small group of gatekeepers, or a random sample)?
• Do community members have authority to advise on the research protocol or to make key decisions regarding the research protocol?
• Are community members elevated to the level of coinvestigators? Do they share resources and play an investigative role in the conduct research? Do they participate in data interpretation and dissemination?

Community engagement in mental health research may involve interaction with individuals from any of the following groups: people with mental health disorders; people who are recovering; family members or caregivers; people at risk; clinicians, healthcare providers, service agencies, and insurers; government or industry funding representatives; and advocates. CEnR also involves members of communities who are affected by mental disorders, including employers, educators, prisoners, students, and minority members within any of these groups. CEnR may vary radically depending on whether, for example, mental health consumers are approached by researchers or, rather, initiate a research study themselves, with or without the collaboration of an academic center [45] .

Different kinds and degrees of engagement may depend on how well certain values are embraced, how educated the researchers are regarding community engagement (techniques and benefits), time and financial resources, and also on the type of science (e.g., how much ‘scientific flexibility’ they have) and the funding source, which may mandate CEnR or make it more difficult. Figure 1 provides a hierarchy of forms of CEnR with the baseline representing forms that are minimally burdensome and should be integrated into most human participant research.

For a group to constitute a community, it must possess structure and leadership. In some cases, a clear community exists prior to a research study; in other cases, researchers must collaborate with group members to establish a community structure [49••] . The boundaries of communities are not always well defined and communities may range from fairly homogeneous to heterogeneous. Not all community members may wish to engage with researchers, and resources may limit the number of community members who can be engaged. The interests of the larger community may not always be congruent with the best interests or research goals of vulnerable groups within the community who will be recruited to participate in the research [50] . Thus, one never fully engages a community.

Rather, community engagement is an ideal that may be more or less embodied by a study.

Why is community engagement important?

Researchers inevitably affect the communities they study and frequently leave a lasting impression: positive or negative. So-called ‘helicopter’ projects, in which researchers fly in and quickly fly out with data, may leave the impression that communities are simply used rather than valued. Research that does not address the knowledge or health priorities of communities may contribute to research fatigue and an unwillingness to participate in research [51,52] .

Engaging communities in appropriate ways is a form of showing respect for community members as persons. It provides a voice to individuals who are often disenfranchised [16•] . The American Psychological Association has asserted that community engagement is a requirement of any ethical research with minority communities [53] .

CEnR may also provide significant benefits to community members. Our researcher panelists believe that CEnR improves T3 or curbside translation of the results of health research. To the extent that decreasing health disparities is a health priority [54] , we should increase CEnR efforts toward cultural competence, the recruitment of minorities, and the dissemination of health information among minority communities. CEnR may also provide significant peripheral benefits to community members. For example, mental health service users have reported that participatory research offered them opportunities to gain knowledge and to share their unique perspectives, increased their self-esteem, provided them with an opportunity for employment, and gave them a chance to give back to society and help others [45] .

CEnR may also improve the quality of science insofar as it may assist researchers in recruitment and retention [49••,55,56] . The Framingham Heart study would not have been nearly as successful without intense engagement of the local community, including efforts to adapt the study in response to community concerns [57] . CEnR may additionally contribute to the recruitment of participants who are genuinely representative of the larger community. Given that 6.7% of the population suffers from depression [58] and 3.8% from substance abuse disorders at any given time [58] (with a life-long prevalence of 16.2% [59] and 14.6% [60] , respectively), a study that wishes to have a truly representative sample should refrain from excluding individuals with such diagnoses; in fact, extra efforts should be made to include them [61] . CEnR methods have proven successful in recruiting marginalized populations into traditional clinical trials [62] .

Moreover, community members may bring novel perspectives to questions of research design and recruitment; they may raise concerns or suggest useful strategies that may be unfamiliar to researchers [45] . Indeed, in early HIV trials, not only was CEnR essential to obtaining the cooperation of the participant community, but some community members suggested improvements to the statistical analysis of the data [63] . In other cases, the scientific expertise may be largely qualitative. For example, whereas researchers often focus on ‘objective’ outcomes of studies, mental health consumers may encourage a focus on subjective outcomes such as a sense of well being and empowerment or of sadness and hopelessness.

CEnR may also serve to foster trust in science and to improve institutional public relations. Although trust and trustworthiness are to be valued for their own sake, they are also prerequisites to any successful research enterprise [45] .

Further, compliance with international policies requires at least some degree of CEnR. For example, 45 Code of Federal Regulations, part 46 (the US ‘common rule’) and European guidelines for good clinical practice require IRBs and IECs to have at least one member who is a nonscientist and unaffiliated with the institution [20] . National Institutes of Health requires all Clinical and Translational Science Award programs to have a community engagement program. Finally, in certain kinds of research, such as research in emergency medicine when informed consent cannot be obtained (e.g., from unconscious patients), US regulations require investigators to consult with communities [64] .

As Emanuel et al. [65] note, to be ethical, research must be scientifically valid [66] . Invalid research benefits no one and wastes resources. CEnR must be conducted in ways that do not compromise the quality of science. Although CEnR can improve recruitment, retention, and the quality of participation, it can also compromise the quality of science if done poorly [67] .

What are characteristics of successful community engagement?

The quality of a CEnR process depends in part upon the traits that the researchers and community members bring to the encounter. Some of the traits that panelists (engaged researchers and community members) considered ideal are as follows:

• Listen and learn
• Ask questions
• Educate and share their expertise (e.g., about science or community concerns and priorities)
• Be flexible and creative
• Demonstrate empathy, courtesy, and cultural sensitivity
• Be diverse in their backgrounds and thinking

While the panel first attempted to identify separately the ideal traits of researchers and community members, it became apparent that the ideal traits are shared, although the specific kinds of expertise that they provide will differ.

Although not all forms of CEnR involve including community members as members of the research team (co-investigators), this would be considered the most robust and also most complex form of CEnR. A group of mental health consumer researchers have identified a list of requirements for appropriate involvement of consumers on the research team: payment for work; equal treatment; involvement in all stages of research; acknowledgement of power differentials; regular feedback on their work; safe work environment, including emotional support; and sufficient training [68] .

Successful CEnR requires the ability to translate the community's values and research priorities to the audience of funding agencies and grant reviewers. This can be challenging when researchers and community members have different priorities and expectations [69••] . In these cases, mediation skills (listening, paraphrasing, seeking compromises, etc.) can be beneficial [70] .

The success of CEnR in research should be measured in terms of all the potential benefits of CEnR identified above, including enhancing relationships with community members and facilitating high-quality research.

Successful CEnR takes time to develop. Initially, it may be difficult to recruit diverse community members to engage researchers; failure to do so may inappropriately empower one or a few individuals to set the agenda for a community. It may take time for researchers to adapt their frame of mind to appreciate the different values and the different kind of expertise that community members may bring to a project, just as it may take time for community members to understand the rules of science and research funding, which set limits to the accommodations that can be made within a research protocol. Further, when community members are integrated into the research team, they may, ironically, lose their ability to represent accurately the views of the community; community advisory boards may retain a significant role even in robust forms of CEnR.

What is required to foster community-engaged research?

Among the many resources needed to sustain CEnR, we believe two deserve particular attention: the need for training and funding. Successful CEnR requires training for community members to increase knowledge of the research process and of basic human participant protections, as well as training of researchers on strategies for respectful engagement of communities [69••,71,72••,73] . However, too few opportunities for such training exist, especially at the local level.

Although some forms of CEnR (such as exit interviews on participant satisfaction) are very affordable and low burden, other more robust forms of CEnR require budgetary support. Expenses may include the following: hiring diverse staff, translating documents, disseminating results to the community, and tracking hard-to-reach participants [11] . The biggest funding challenge is typically faced at the conclusion of a particular project when bridge funding is required to sustain community-research partnerships [74] .

Researchers frequently equate CEnR with community-based participatory research, which can be highly beneficial for researchers, science, and communities, but can also require significant training, resources, and commitment. Researchers would do well to recognize there are many forms of CEnR, including some that are relatively low burden, and that some forms of CEnR can enrich virtually any research program involving human participants.

Acknowledgement

The present study was made possible by grant 1R13MH079690 from National Institutes of Health (NIH)-National Institute of Mental Health and grant UL1 RR024992 from the NIH-National Center for Research Resources.

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

• of special interest

•• of outstanding interest

Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 259).

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Youssef A , Nichol AA , Martinez-Martin N, et al. Ethical Considerations in the Design and Conduct of Clinical Trials of Artificial Intelligence. JAMA Netw Open. 2024;7(9):e2432482. doi:10.1001/jamanetworkopen.2024.32482

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Ethical Considerations in the Design and Conduct of Clinical Trials of Artificial Intelligence

• 1 Departments of Radiology, Stanford University School of Medicine, Stanford, California
• 2 Center for Biomedical Ethics, Stanford University School of Medicine, Stanford, California
• 3 Department of Psychiatry, Stanford University School of Medicine, Stanford, California
• 4 Department of Ophthalmology and Visual Sciences, University of Iowa Hospital and Clinics, Iowa City
• 5 Electrical and Computer Engineering, University of Iowa, Iowa City
• 6 Division of Endocrinology, Department of Pediatrics, The Johns Hopkins School of Medicine, Baltimore, Maryland
• 7 Department of Anesthesiology, Division of Pediatric Cardiac Anesthesia, Stanford, California

Question   How generalizable are current National Institutes of Health (NIH) ethical principles for conduct of clinical trials to clinical trials of artificial intelligence (AI), and what unique ethical considerations arise in trials of AI?

Findings   In this qualitative study, interviews with 11 investigators involved in clinical trials of AI for diabetic retinopathy screening confirmed the applicability of current ethical principles but also identified unique challenges, including assessing social value, ensuring scientific validity, fair participant selection, evaluation of risk-to-benefit ratio in underrepresented groups, and navigating complex consent processes.

Meaning   These results suggest ethical challenges unique to clinical trials of AI, which may provide important guidance for empirical and normative ethical efforts to enhance the conduct of AI clinical trials.

Importance   Safe integration of artificial intelligence (AI) into clinical settings often requires randomized clinical trials (RCT) to compare AI efficacy with conventional care. Diabetic retinopathy (DR) screening is at the forefront of clinical AI applications, marked by the first US Food and Drug Administration (FDA) De Novo authorization for an autonomous AI for such use.

Objective   To determine the generalizability of the 7 ethical research principles for clinical trials endorsed by the National Institute of Health (NIH), and identify ethical concerns unique to clinical trials of AI.

Design, Setting, and Participants   This qualitative study included semistructured interviews conducted with 11 investigators engaged in the design and implementation of clinical trials of AI for DR screening from November 11, 2022, to February 20, 2023. The study was a collaboration with the ACCESS (AI for Children’s Diabetic Eye Exams) trial, the first clinical trial of autonomous AI in pediatrics. Participant recruitment initially utilized purposeful sampling, and later expanded with snowball sampling. Study methodology for analysis combined a deductive approach to explore investigators’ perspectives of the 7 ethical principles for clinical research endorsed by the NIH and an inductive approach to uncover the broader ethical considerations implementing clinical trials of AI within care delivery.

Results   A total of 11 participants (mean [SD] age, 47.5 [12.0] years; 7 male [64%], 4 female [36%]; 3 Asian [27%], 8 White [73%]) were included, with diverse expertise in ethics, ophthalmology, translational medicine, biostatistics, and AI development. Key themes revealed several ethical challenges unique to clinical trials of AI. These themes included difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across various patient subgroups, and addressing the complexities inherent in the data use terms of informed consent.

Conclusions and Relevance   This qualitative study identified practical ethical challenges that investigators need to consider and negotiate when conducting AI clinical trials, exemplified by the DR screening use-case. These considerations call for further guidance on where to focus empirical and normative ethical efforts to best support conduct clinical trials of AI and minimize unintended harm to trial participants.

The integration of artificial intelligence (AI) into health care promises to address long-standing challenges, offering innovative solutions to improve patient outcomes, health equity, clinician productivity, and system efficiency. 1 , 2 As the deployment of AI interventions expands, clinical evidence becomes increasingly crucial in validating their efficacy and safety. 3 - 7 However, there exists a notable gap between the extensive theoretical research on ethical concerns in AI applications in health care and the practical challenges encountered by clinical investigators in clinical settings. 8 This empirical study aims to bridge this gap by examining the practical ethical considerations in the design and implementation of clinical trials involving AI.

Early detection of diabetic retinopathy (DR) is a vanguard area in clinical AI; the first US Food and Drug Administration (FDA) De Novo–authorized autonomous AI was for diabetic eye examinations. 9 We collaborated with investigators from the first National Institutes of Health (NIH)-funded randomized clinical trial (RCT) of autonomous AI, the AI for Children’s Diabetic Eye Exams Study (ACCESS), which was designed to determine the efficacy of autonomous AI screening for DR in a diverse population of youth with diabetes. 10

Ethical frameworks for clinical research, shaped by landmark documents such as the Nuremberg Code, Declaration of Helsinki, Belmont Report, CIOMS guidelines, and the US Common Rule, form the bedrock of research ethics. 11 - 13 Emanuel et al 12 have further delineated 7 core principles for clinical trial ethics, endorsed by the NIH: social and clinical value, scientific validity, fair participant selection, favorable risk-benefit ratio, independent review, informed consent, and respect for human participants. 14 However, the complexities inherent to AI, such as clinical efficacy, algorithmic fairness, and reproducibility of results, pose unique challenges. 15 - 17 Systematic reviews have highlighted significant limitations in AI clinical trials, such as the absence of clinically relevant endpoints and a high risk of bias, raising questions about the suitability of traditional ethical frameworks in AI contexts. 4 , 18 - 21 While there is a consensus on the necessity for increased transparency of randomized clinical trials of AI (AI-RCTs), current guidelines primarily focus on standardized reporting and fall short from addressing ethical considerations in the design of these clinical trials. 22 , 23

This qualitative study aimed to address 2 primary research questions: (1) To what extent are the 7 NIH ethical principles 14 created by Emanuel and Grady 12 generalizable to clinical trials of AI? and (2) What are the ethical considerations that may be unique to clinical trials of AI?

This qualitative study was approved by the Johns Hopkins Medicine institutional review board. All study participants were informed about the waiver of written consent and provided verbal consent to participate voluntarily, without financial compensation. We followed the Consolidated Criteria for Reporting Qualitative Research ( COREQ ) reporting guidelines.

We employed both a deductive and an inductive approach to data collection. We used a deductive approach described to test the applicability of the NIH’s 7 core ethical principles—clinical and social value, scientific validity, fair participant selection, favorable risk-benefit ratio, independent review, informed consent, and respect for human participants. 24 We also utilized a modified grounded theory approach for the discovery of novel themes. 25

Participants in this study included clinical investigators, institutional review ethicists, and clinical trialists involved in autonomous AI trials for diabetic retinopathy screening. The selection criteria were aligned with the study’s aim of examining ethical challenges in the design and conduct of AI-based clinical trials. Initially, purposive, nonprobabilistic sampling was used to recruit 6 participants from the ACCESS study ( NCT05131451 ). 10 Two authors (R.W. and D.C.) invited investigators from the ACCESS study to participate in this study. To enhance the generalizability of our findings, we employed snowball sampling method to identify participants involved in concurrent RCTs of AI for diabetic retinopathy screening in low-income countries, resulting in the inclusion of 3 participants from a nonprofit organization and 2 from the private sector.

Data collection occurred from November 2022 to February 2023. Interviews were conducted in English via video call (Zoom) by a qualitative research scientist (A.Y.) with over 7 years of experience in qualitative research. Interviews ranged from 30 to 60 minutes and were guided by a set of questions addressing demographic questions, the 7 ethical principles endorsed by the NIH—clinical and social value, scientific validity, fair participant selection, favorable risk-benefit ratio, independent review, informed consent, and respect for human participants—and open-ended questions to explore additional ethical considerations (eAppendix in Supplement 1 ). All interviews were transcribed by a professional service, and MAXQDA version 2022.2 software (VERBI GmbH) was used for managing and analyzing the data.

Following initial transcript analysis, a study coauthor (A.Y.) developed a codebook for systematic independent coding. Two authors (A.Y. and A.N.) independently coded all interviews, achieving a Cohen κ score greater than 0.8 for interrater reliability. Discrepancies were resolved through consensus coding with 3 coauthors (R.W., N.M., and D.C.). Theoretical saturation was achieved after the tenth interview, as no new insights emerged from the eleventh interview. To maintain reflexivity, we kept a detailed audit trail (A.Y.). This trail included reflections on both the interviewees’ and interviewer’s perceptions. These reflections were critically examined in weekly research meetings with all authors, challenging emerging hypotheses to reduce confirmation bias and ensure theme credibility. 26

We conducted interviews with 11 investigators with experience conducting AI-RCT for DR screening, with a mean (SD) age of 47.5 (12.0) years (7 male [64%], 4 female [36%]; 3 Asian [27%], 8 White [73%]) ( Table 1 ). Participants came from academia, the nonprofit sector, and industry, bringing diverse expertise in ethics, ophthalmology, translational medicine, biostatistics, AI development and deployment, and policy.

While recognizing the importance of the 7 ethical principles in AI clinical trials, participants identified unique ethical challenges specific to AI trials. These challenges demand a nuanced understanding of how to appropriately apply these principles in the context of AI clinical trials. Table 2 outlines participants’ perspectives on the 7 principles within the context of AI clinical trials. Table 3 presents novel ethical considerations that emerged from the inductive analysis, highlighting specific challenges faced during the implementation of these trials.

When applied to clinical trials of AI in clinical settings, participants identified several unique applications of the 7 ethical principles. Common themes across principles included the added difficulty in accounting for equitable access to care and the need for transparency with patients.

Participants recognized AI’s potential to improve clinical outcomes, comparable with the potential outcomes of non-AI based RCTs (ie, drugs or medical devices). Specifically, in this RCT focused on DR, they perceived AI’s potential to reduce health disparities as a clear metric for social value. However, they expressed uncertainty defining and quantifying the social value of an AI intervention compared with its clinical benefits.

Participants recognized RCTs as a criterion standard for demonstrating clinical efficacy of the AI intervention. However, they identified unique challenges specific to AI RCTs. One participant questioned the appropriateness of prioritizing individualized outcome parameters—such as patient outcome—rather than outcomes for groups or populations. They noted the difficulty of comparing AI interventions with the variable criterion standard of usual care, which can differ significantly across clinical settings.

Fair participant selection in AI clinical trials emerged as a significant topic, particularly regarding the accurate representation of the patient population of focus. Study participants highlighted the challenges in evaluating the efficacy of the AI intervention across patient subgroups, who are often affected by limited access to care and can be underrepresented in clinical trials. One participant pointed out the complexities of ensuring equitable access studying the impact of AI screening on patient groups that may access less regular diabetes screening and care.

Participants recognized the complexity of balancing the risks and benefits of AI interventions across diverse patient groups. They noted the difficulty in estimating the harm-to-benefit ratio of AI interventions relative to the known risks of standard care, a challenge exacerbated by limited representation of patient groups facing health inequities in retrospective standalone studies of algorithm performance.

Participants identified key ethical concerns presented in AI clinical trials, emphasizing the need for transparent communication about the risk and benefits of an AI intervention tailored to patients with varying levels of health literacy. They questioned whether patients fully understand the extent toward which their data might be used beyond the trial itself. Additionally, concerns were raised about the adequacy of current informed consent processes and institutional ethical review readiness to assess the risks and benefits of AI interventions.

Participants highlighted additional ethical challenges beyond the established 7 ethical principles ( Table 3 ). These included: (1) Whose values prevail in AI systems design and implementation? (2) Can AI integration enhance clinical workflows without compromising patient safety? (3) How to balance the economic incentives with the ethical obligations to adopt effective AI intervention that can improve patients’ outcomes? (4) What are the ethical implications of expanding DR screening without enhancing treatment access?

Participants critiqued the broadly defined term “value,” noting its varied interpretations across different stakeholders including health systems, clinicians, and patients. They questioned whose values are prioritized during the design and implementation of AI systems. Additionally, concerns were raised about AI’s adaptability to individual patient needs. For instance, while clinicians can adjust treatments to ensure affordability and effectiveness, AI systems may lack this flexibility due to their predefined operational parameters and potential downstream effects.

Said a participant who specializes in informatics, “So patient value can take all what people really, really, really care about, which includes spiritual and religious issues which do not go into health services research considerations, don’t go into societal considerations…so the very word value I would bet is not well-defined.” A participant with a research focus in ophthalmology pointed out that cost of care varied by community, “Somebody who had very limited resources couldn’t afford to pay $60 a month for drops.…So, the decision that we make about how much quality we can afford needs to be made with respect to local economic scales.”

From the participants’ perspective, integrating AI tools into clinical workflows introduces a significant tension. There is a drive for AI to enhance clinical workflows, but this drive carries the inherent risk of complicating an already complex workflow, especially when the definitive clinical benefits of AI are still unclear. This tension is further amplified when contemplating potential risks to research participants during clinical trials. “I think part of it, to not be able to do an RCT with an AI tool, would come down to just clinical workflow,” said a participant working in optometry. “If you’re trying to interject something into a workflow that’s already overloaded and pretty strapped.…I think that’s a limitation when it comes to implementing these because you have to set up, you know, both arms. You have to then set up multiple workflows and you’re already…you’re already trying to interject a new workflow where it hadn’t been before, which can be complicated.”

“I think the clinical value is that there’s quite a bit of hype about AI and we know that for sure AI can do certain things better than humans in many different contexts, but just because AI is better than humans that do certain things doesn’t mean if we incorporate AI will it necessarily improve the outcomes or the metrics that we’re interested in,” said a respondent specializing in ophthalmology and machine learning. “So I think it’s very important to, in clinical trial[s] involving AI, to show that it improves outcomes. That’s a completely open question by now that we don’t know for the most part whether incorporating AI in clinical workflow improves outcome, so I think this is a very important question to answer. And you could only answer that using [a] randomized clinical trial.”

Participants highlighted a critical tension in developing and validating AI tools in health care, balancing economic pressures with ethical imperatives. The ethical mandate to make these tools universally accessible clashes with the high costs associated with conducting RCTs, deemed the criterion standard for validation, particularly in the US and Europe. This economic challenge has prompted AI developers to shift RCTs to developing countries, raising concerns about potentially deepening health care inequities.

One participant who is both an AI developer and clinician-scientist expressed the dilemma facing AI developers and health systems: “If you don’t get creators and people like me and investors excited about the potential return, it will stop. That’s just the way it is. I was struggling as a developer, what is the balance between making…so if you see that more access and better outcomes is good and you expect people to pay for that, how do you put a charge so that you don’t make a charge too high?” The same participant also added insight on payment models for AI, suggesting a focus on health equity. “How should we be paying for AI?” he said. “If as a taxpayer or society you’re paying for something, then health equity should be the main guiding star.”

One participant in ophthalmology criticized the inherently high costs associated with RCTs: “Randomized control trials…there’s sort of an inherent assumption that they have to cost 40 million dollars. I just think that’s unethical. We have to come up with a way of delivering the kind of evidence, the high-quality evidence that can provide in a way that’s affordable for lower middle-income countries.”

Finally, the practical implications of AI were discussed. “If you’re improving the screening, then that in and of itself is sufficient to understand this is something that benefits patients,” said a participant working in AI and machine learning in health care. “Now whether a system is willing to pay for such an [AI solution], that’s a different question.”

A stated goal of AI is to broaden the reach of ophthalmology screening to populations currently underserved, thereby reducing their risk of blindness from DR. However, participants highlighted a complex array of clinical and ethical questions associated with this proposed use of AI. One concern is whether merely expanding access to DR screening without simultaneously improving access to treatment might create ethical dilemmas downstream.

“If someone’s not accessing services for diabetes in general regularly and not coming in for their well visits,…they’re not controlling their condition in the first place, they’re probably coming in less, they’re less likely to get the AI screening even if it’s available to them in their clinic and they’re more at risk for diabetic retinopathy because they’re not [accessing care],” said a researcher specializing in biostatistics and clinical trials. “If we’re trying to target and reduce those disparities, I think it would be important then to see where they’re falling off and why they’re not getting screened, or are they getting screened and not going for follow-ups.”

One participant emphasized the potential benefits of AI for the “bottom billion,” a uniquely underserved population, highlighting the slower arrival of such technologies to these groups. Another noted the generalization issues that can arise if AI models are trained on data from a narrow demographic. “I’ve been pleasantly surprised at how well the generalization has shown so far,” he said. “But I also think that if you only train for people from one small part of the world, then you would have a generalization problem.”

Finally, the cost-effectiveness of AI diagnostics was questioned, particularly in contexts where the financial burden might outweigh the clinical benefits. “If the AI is efficacious, it’s an accurate diagnostic, but is this cost-effective if it costs a million dollars to run?” asked one participant. “Whether a system is willing to pay for such a product is another question.”

This study is, to our knowledge, the first to explore the practical ethical considerations involved in designing and executing AI clinical trials. We draw on the experiences of investigators conducting the first NIH-funded RCT of an autonomous AI for DR screening, along with related trials. While we found consensus among stakeholders regarding generalizability of the NIH’s 7 ethical principles to clinical trials of AI, we identified important areas of uncertainty regarding social value, scientific validity, fair participant selection, favorable benefit-risk ratio, and informed consent ( Table 2 ). Thematic analysis of participants’ experiences in DR screening trials across various settings also highlighted novel ethical considerations specific to AI clinical trials, independent of the 7 principles.

When discussing the 7 ethical principles, defining and measuring the social value of AI in clinical trials proved to be complex. Perspectives ranged from prioritizing patient views to measurable reduction in health care inequities. Moreover, participants struggled to generalize social value across trials due to its context-dependent nature and the lack of defined metrics to measure the social impact of AI interventions. While the clinical value of AI in improving patient outcomes is similar to that of traditional drug or device trials, evaluating AI introduces additional complexities as it functions as both a cognitive tool and a workflow intervention. Establishing a control, typically defined as the standard of care, can vary significantly across different clinical environments. This variability may limit the generalizability of AI interventions, as an AI system validated in one setting might not perform effectively in another setting.

In addition, the goal of using an AI to expand access for populations with limited access presents an ethical tension between the desirable social value of reducing access inequity with the limitations of an AI with biased training data (at least until better access for all groups is delivered) while outcomes are still being evaluated. For future trials, it will be crucial for researchers to clearly define the desired social value and establish specific, measurable outcomes that demonstrate the AI intervention efficacy achieving this value.

Participants also expressed nuanced concerns about ensuring a favorable benefit-to-risk ratio and obtaining true informed consent for AI interventions. While uncertainty is inherent in clinical research, balancing the unknown risks of AI screening against the known risks of untreated DR presented unique challenges. Interviewees noted that different population subgroups likely had different risk-benefit ratios when AI risks are compared with current screening methods or the absence of screening. Moreover, challenges in ensuring fair patient selection were noted, particularly in scenarios where patients facing health disparities are less likely to access care. Ensuring informed consent emerged as a significant challenge, particularly in communicating the benefits, risks, and data use terms for AI interventions to participants with varying levels of health literacy.

The exploration of novel ethical considerations in the context of AI clinical trials revealed several critical issues ( Table 3 ). Participants expressed concerns about whose values are prioritized in the design and implementation of AI systems, emphasizing that current definitions fail to capture the diverse needs and priorities of all stakeholders, including patients, clinicians, and health systems. An ethical challenge is emerging in trials of AI around value capture; if a desired outcome of an AI tool is “value” (cost, labor, or access savings), who decides what outcome value is prioritized and how value savings are redistributed within a health care system or community is unknown. 27 This uncertainty presents a crucial ethical knowledge gap in ensuring that AI trials are responsive to clinical contexts.

The integration of AI into clinical workflows also generated tension. RCT investigators aimed to evaluate AI effectiveness without compromising patient safety or disrupting established workflows with proven efficacy. Clinicians expressed concern that modifying care workflows to accommodate AI could unintentionally affect patient care or increase staff workload. Therefore, it is crucial to carefully assess the impact of AI on clinical workflows before implementation.

Participants also raised ethical concerns about using AI to improve access and equity without a clear financial incentive. They questioned what would incentivize a health system to invest in such technologies. Participants expressed concern around using AI to improve screening access in resource-constrained settings. For example, in the context of an AI clinical trial for DR screening, the AI system may be tested in a well-resourced clinical setting where patient can immediately receive follow-up treatment from an ophthalmologist if diagnosed with DR. However, if this AI system is later to be deployed in an underresourced setting, even if it accurately identifies patients needing treatment, the lack of access to follow-up care might prevent these patients from receiving the necessary interventions. This raises an ethical question: Is it appropriate to evaluate the AI’s efficacy in a controlled environment with follow-up care, knowing that in its clincial application, such care might be inaccessible?

Findings from this study suggest that the concept of equipoise—the ethical balance necessary in clinical trials—is more complex in AI interventions. AI, as a systems intervention, not only affects individual patient care but also integrates with and transforms health care workflows and system operations, complicating the evaluation of its effectiveness in clinical trials.

This study had several limitations. The participant pool was relatively small, comprising 11 individuals from 4 US academic institutions, and was restricted to investigators involved in AI clinical trials. While the deductive approach allowed us to systematically apply the 7 ethical principles to our data, it may inherently have limited the scope of conclusions by focusing on predefined frameworks. However, the inductive components of our study enabled us to explore novel insights and themes that emerged directly from the data, thereby enriching our understanding and identification of ethical issues beyond the initial framework. Although the theoretical concepts uncovered may be applicable to AI clinical trials in other areas, the scope of this study was limited to clinical trials of AI in diabetic retinopathy screening. Thus, the generalizability of these findings requires further validation in future studies. Furthermore, it is important to note that the 7 principles centered in this article have been criticized as being parochial, or at least Western-centric. 28 , 29 The potential vulnerability of the 7 principles raised by this criticism is magnified as AI development for health care is occurring globally.

This study addresses an important gap in practical understanding of how clinical investigators actually navigate ethical considerations arising with the design and conduct of AI clinical trials. It reveals a general consensus on the utility of NIH’s 7 ethical principles for clinical trials of AI but also important areas of uncertainty in social value, scientific validity, fair participant selection, favorable risk-benefit ratio, and informed consent. These findings highlight important considerations that should be addressed in future iterations of ethical guidance for AI trials. As Emanuel and Grady 12 aptly noted, “Like a constitution, these requirements can be reinterpreted, refined, and revised.…Yet these requirements must all be considered and met to ensure that clinical research, wherever practiced, is ethical.”

Accepted for Publication: July 15, 2024.

Published: September 6, 2024. doi:10.1001/jamanetworkopen.2024.32482

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2024 Youssef A et al. JAMA Network Open .

Corresponding Author: Alaa Youssef, PhD, Department of Radiology, Stanford University School of Medicine, Stanford Center for Artificial Intelligence and Medical Imaging, 1701 Page Mill Rd, Mail code 5467, Stanford, CA 94304 ( [email protected] ).

Author Contributions : Drs Youssef and Char had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Youssef, Abramoff, Wolf, Char.

Acquisition, analysis, or interpretation of data: Youssef, Nichol, Martinez-Martin, Larson, Wolf, Char.

Drafting of the manuscript: Youssef, Nichol, Abramoff, Wolf, Char.

Critical review of the manuscript for important intellectual content: Youssef, Martinez-Martin, Larson, Wolf, Char.

Statistical analysis: Youssef, Nichol, Abramoff.

Obtained funding: Wolf, Char.

Administrative, technical, or material support: Nichol, Wolf, Char.

Supervision: Larson, Abramoff, Wolf, Char.

Conflict of Interest Disclosures: Dr Larson reported holding shares in Bunker Hill Health Shareholder outside the submitted work; he reported receiving research support from Siemens Healthineers and the Gordon and Betty Moore Foundation outside the submitted work. Dr Abramoff reported work as director and consultant with Digital Diagnostics Inc outside the submitted work, where he also holds equity and has patent application assigned; he reported chairing the Healthcare AI Coalition Foundational Principles of AI Collaborative Community for Ophtalmic Imgaing and serving as committee member of the American Academy of Ophthalmology AI Committee, AI Workgroup Digital Medicine Payment Advisory Group, and the Collaborative Community for Ophthalmic Imaging. Dr Wolf reported grants from Novo Nordisk as primary investigator for a clinical research site outside the submitted work. No other disclosures were reported.

Funding/Support: This study was funded by the National Eye Institute (R01EY033233-01).

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: We extend our sincere gratitude to the ACCESS study team and all participating individuals. Their invaluable contributions, dedicated time, and willingness to share their insights have been fundamental to the success of this research. We are deeply grateful for their openness and the rich perspectives they have provided.

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Understanding Ethical Issues of Research Participation from the Perspective of Participating Children and Adolescents: A Systematic Review

Stacey crane.

Predoctoral Fellow, Indiana University School of Nursing, 1111 Middle Dr., NU345, Indianapolis, IN, 46202, 513-508-3936

Marion E. Broome

Ruby F. Wilson Distinguished Professor and Dean, Vice-Chancellor for Nursing Affairs, Duke University School of Nursing, 307 Trent Drive, Durham, NC, 27710, 919-684-9444

Associated Data

TABLE S2. Articles Included in Sample: Methodologies Used

TABLE S3. Articles Included in Sample: Demographics of Participating Children and Adolescents

The past twenty years have seen distinct shifts in the way the participation of children and adolescents in research is viewed. This has been emphasized by the growing pediatric research enterprise. Additional information on children’s and adolescents’ experiences during research participation is needed to better inform researchers on the ethical conduct of research with this vulnerable population.

The objective of this analysis was to examine ethical issues in research with children and adolescents from their perspective as participants, including: assent, parental consent, risk perception, impact of research participation, and incentives.

This systematic review was conducted per the Long et al. framework by means of an iterative searching process. Using the key words ‘research ethics’ and ‘child or pediatric or adolescent’, PubMed, CINAHL, and EBSCOhost databases were searched to identify articles. Limitations placed on the original searches were: English language, year of publication between 2003–2014, humans, abstract available, and age birth–18 years.

Twenty-three empiric studies were identified and formed the sample. Included studies represented a diverse range of areas of research, methods, settings, sample demographics, authors, and journals.

Even young children demonstrated the ability to understand essential elements of research, although there is variability in children’s level of understanding. Trust was a significant contributing factor to children’s and adolescents’ participation in research, and also shaped their assessments of risk. Research participation was mainly beneficial for children and adolescents. Incentives were mainly viewed positively, although concerns of possible undue influence were expressed.

Linking Evidence to Action

This systematic review highlights the importance of including the perspectives of children and adolescents and provides researchers and nurse clinicians with best practices for involving children in research.

Introduction

In 2004, the Institute of Medicine published a report, ‘Ethical Conduct of Clinical Research Involving Children’, the purpose of which was to review federal regulations, reports and research and make recommendations about ethical research involving children ( Institute of Medicine, 2004 ). Themes of the report included the need for:

• Well-designed and executed research with children to improve the health of children and future generations worldwide;
• Children to not be either burdened or excluded from participation in research;
• A robust system for protecting child and adolescent research participants, including additional resources like experts in physiology and development, to recognize and address unique ethical issues.

In the ensuing years, researchers have continued to recognize the need to balance the inherent vulnerability of children and adolescents with the necessity to research their unique needs and perspectives ( Broome, Kodish, Geller, & Siminoff, 2003 ; Hurst, 2008 ; Levine et al., 2004 ; Solomon, 2013 ). There have been new research investigations with child and adolescent participants, outside of traditional clinical research settings and those using more novel designs. More child/adolescent populations have been identified as vulnerable within the research context; indeed the current prevalence of vulnerable populations has compromised our understanding of the unique needs of any particular vulnerable population ( Levine et al., 2004 ). As the research enterprise continues to evolve it is important to better inform researchers about the unique needs that should inform the ethical conduct of research with children and adolescents.

Much of our understanding of the conduct of ethical research with children and adolescents has been formulated based on general ethical principles, without consideration of the heterogeneity of children and adolescents research participants ( Carter, 2009 ; Hurst, 2008 ; Levine et al., 2004 ). It is unclear what, if any, voice children and adolescents have had in the development of these ethical guidelines. The objective of this systematic review was to examine ethical issues surrounding research with children and adolescents from their perspective as participants. Specific questions that guided this review were:

• What research methods have been used to understand children’s and adolescents’ experiences of participating in research?
• What has been learned from children and adolescents about assent and parental consent for research participation?
• How do children and adolescents perceive the risks inherent with research participation?
• What impact have children and adolescents identified as a result of their research participation?
• What has been learned from child and adolescent research participants regarding the use of incentives?

This systematic review was conducted using the framework described by Long, Godfrey, Randall, Brettle, and Grant (2002) . An iterative searching process was used including three stages: scoping, refinement and confirmation ( Long et al., 2002 ). After a broad search and relevance check on initially identified studies, inclusion and exclusion criteria were refined and questions refocused. Searches were then rerun. References cited in included studies were reviewed to identify further relevant studies. A PRISMA flowchart was used to graphically represent search procedures ( Moher, Liberati, Tetzlaff, & Altman, 2009 ).

Search Methods

Using the key words ‘research ethics’ and ‘child or pediatric or adolescent’, PubMed, CINAHL, and EBSCOhost (including Academic Search Premier, Health Source, PsycINFO, SocINDEX, Family & Society Studies Worldwide, MasterFILE Premier, Biomedical Reference Collection, Applied Science & Technology Source, Historical Abstracts) databases were searched to identify potentially relevant published articles. Limitations placed on the original searches were: English language, year of publication between 2003 and 2014, humans, abstract available, and age birth – 18 years. Due to the high volume of articles initially retrieved (PubMed = 2,240 and EBSCOhost = 3,313) additional limitations were placed on searches. Explicitly, in PubMed a limitation was added for the MeSH search term ‘Ethics, research’ and in EBSCOhost a limitation was placed using ‘Research ethics’ as a major concept. Using this process, these searches yielded a combined total of 1,424 potentially relevant published articles (including 56 duplicates).

Search Outcomes

Articles were then reviewed to select those that met criteria for inclusion. Inclusion criteria included: 1) empiric research studies from the child/adolescent perspective; 2) articles considering ethical issues in research with children/adolescents or child/adolescent perspectives of research participation; and 3) ethical issues as the primary focus of the paper. Exclusion criteria included articles that focused solely on: 1) broad medical ethics or bioethics, or 2) research procedures or regulatory approval processes. From the original search 19 articles met these criteria. Manual searching yielded four further articles meeting the criteria for inclusion. In the end, 23 articles provided the sample for this analysis. Table 1 lists the included articles. Figure 1 illustrates the search results and screening procedures.

PRISMA Diagram of Search Results and Screening

Articles Included in Sample

Quality Appraisal

All articles in the sample were evaluated using an instrument to assess overall quality; the Evaluative Tool for Quantitative Research Studies ( Long et al., 2002 ) or the Critical Review Form for Qualitative Research ( Letts et al., 2007 ). Mixed methods studies were assessed using both instruments. These tools were used to ensure the overall quality of studies within the sample, to summarize study findings, and as a method for ensuring inter-rater agreement between the two authors. Both authors independently completed assessments of 14 articles in the sample, three articles at a time, comparing results until substantive agreement was achieved. The nine remaining articles were then assessed by the first author, with the second author performing a secondary confirmation. All articles included in the sample met a minimum of 80% of the instruments’ criteria. The potential for bias in the quality appraisal was minimal as both authors are trained in research ethics and experienced in conducting research with pediatric and adolescent participants.

Data Abstraction and Synthesis

Data abstracted from the articles included: journal, country of publication, purpose, approach, method, data collection techniques, research context, sample size, sample characteristics (ages, health, and research experience), method of child assent and parent consent, and findings.

For further details of the articles in the sample, including their findings, journal and country of publication, research methodologies used, and demographics of the children and adolescents studied in each article, see Tables S1 through S3 online.

Characteristics of Reviewed Studies

The sample reflected a variety of different methods and settings. Of the 23 articles, 11 used a descriptive, quantitative design, eight used a descriptive qualitative design, two used mixed methods, and two used a quantitative design that involved testing an intervention. Eleven of the articles involved retrospective reflection on a research experience and one involved a prospective, longitudinal design. The remaining 11 articles considered participants’ current views on research issues. In terms of setting, 10 of the articles involved studies conducted at or through a hospital, nine at schools, three were community based, and one did not indicate the study site.

Children and adolescents were asked to either reflect on their personal experience as a research participant, on research in general, or on a specific hypothetical research situation. Hypothetical scenarios reflected a variety of medical treatments, clinical trials, diagnostic procedures, collection of laboratory samples and/or descriptive research studies.. In other studies children were asked to reflect on their experiences as part of a study they just participated in including those studying exposure to violence, depression, oncology, pain, drug testing, sociometric testing, and health screening. In most cases these reflections were obtained at the end of their participation in the study. In five of the studies children were asked to reflect on their overall impressions of research participation.

Methods for data collection varied. Four of the studies involved either semi-structured or unstructured individual interviews, one involved a focus group, and two studies used a combination of focus groups and interviews. Eight of the studies used written instruments completed at home, school, hospital, or juvenile justice program settings. Seven studies involved structured quantitative instruments that were completed in individual interviews. One study involved a structured quantitative survey conducted orally in a classroom.

Obtaining Assent and Parental Consent

Per the Declaration of Helsinki, “when a potential research subject who is deemed incapable of giving informed consent is able to give assent to decisions about participation in research, the [researcher] must seek that assent in addition to the consent of the legally authorized representative” ( World Medical Association, 2013 ). When conducting research with children and adolescents, when and how to obtain assent versus informed consent (for adolescents) and parental consent has been ethically debated ( Giesbertz, Bredenoord, & van Delden, 2014 ; Lambert & Glacken, 2011 ). In general, literature and policies support researchers seeking assent from all child and adolescent participants in addition to parental consent. In this sample of 23 articles, seven indicated assent was obtained from the participating children/adolescents although the method was not discussed, seven obtained assent using a written form, and three obtained assent verbally. Two articles took the completion of written survey instruments as an indication of implied consent, and the remaining seven articles did not discuss assent procedures.

The majority of child and adolescent research participants were able to comprehend the purpose and nature of research, research risks and benefits, and the voluntary nature of research participation. Comprehension increased with grade level, with 15 – 16 year olds having a similar understanding of research as adults ( Bruzzese & Fisher, 2003 ; Unguru, Sill, & Kamani, 2010 ). However, while even young children could understand complex concepts like research risks and benefits, there remained a significant minority of children under around the age of 10 who had difficulties understanding research concepts ( Bruzzese & Fisher, 2003 ; Burke, Abramovitch, & Zlotkin, 2005 ). In addition, cultural factors, including race, influenced children’s interpretation of research information ( Traube, Cederbaum, Kerkorian, Bhupali, & McKay, 2013 ; Unguru et al., 2010 ).

Noteworthy challenges to children’s comprehension, including their inability to specify any risks associated with previously collected data or samples, were found in a multi-year longitudinal study. This highlights the need to view assent as an ongoing process to be reaffirmed in studies with research activities at more than one time point ( Swartling, Hansson, Ludvigsson, & Nordgren, 2011 ). In addition, challenges were found in children’s ability to understand clinical trials despite researchers’ explanations; with children’s expectations for clinical improvement as a result of clinical trial participation sometimes being unrealistically high ( Unguru et al., 2010 ; Wagner, Martinez, & Joiner, 2006 ).

Most children preferred a shared decision-making model when deciding to participate in research, where they were actively involved and supported by parents, doctors, and researchers ( Swartling, Helgesson, Ludvigsson, Hansson, & Nordgren, 2014 ; Unguru et al., 2010 ). One challenging situation, however, was indicated by children with cancer who did not feel free to dissent to clinical trial enrollment ( Unguru et al., 2010 ). In another, homeless adolescents felt strongly that they should be able to independently consent to participate in research, without requiring parental approval ( Ensign, 2006 ).

An important consideration is the type of parental consent processes that should be used in research with children and adolescents. Three studies specified that parental consent was obtained but did not indicate a method, eight of the articles obtained consent from parents using a written form, three obtained verbal parental consent, and three articles did not discuss parental consent processes. Other processes used included passive parental consent (1), implied parental consent (1), and not obtaining any parental consent (2). Of the two articles that did not obtain any parental consent one was conducted with homeless adolescents, and the other involved a survey completed at school ( Ellonen & Pösö, 2011 ; Ensign, 2006 ). For this latter study, the children aged 12–16 years decided whether they wished to participate in the study and parents were notified afterwards regarding their child’s participation. Participation rates were lower when active parental consent processes were used in school-based research ( Langhinrichsen-Rohling, Arata, O’Brien, Bowers, & Klibert, 2006 ). One article demonstrated that an active vs. passive parental consent procedure did not reduce the risk of adolescents completing a survey of high-risk behavior feeling upset ( Langhinrichsen-Rohling et al., 2006 ). However, other findings suggested that whether parents were present during the assent discussion impacted whether adolescents perceived their decision to participate in research to be autonomous ( Cohn, Ginsburg, Kassam-Adams, & Fein, 2005 ).

Specific suggestions from children and adolescents on improving assent processes included: for researchers to speak directly to children about research participation – not simply through their parents, ensuring written materials are written in a way that is appealing and understandable, and providing written information instead of using e-mails or websites ( Brawner, Volpe, Stewart, & Gomes, 2013 ; Burke et al., 2005 ; Swartling et al., 2011 ; Swartling et al., 2014 ; Unguru et al., 2010 ). Specific tools that were demonstrated to enhance children’s and adolescents’ comprehension of research included an assent quiz, and a specific lesson on research rights ( Bruzzese & Fisher, 2003 ; Chu, DePrince, & Weinzierl, 2008 ).

Perception of Research Risks

The presence or absence of trust was perceived by children as a contributing factor to being involved in research, and also shaped their assessments of risk ( Brawner et al., 2013 ; Traube et al., 2013 ; Woodgate & Edwards, 2010 ). Findings in the sample of articles suggested that children and adolescents are most willing to participate in research when they feel safe ( Brawner et al., 2013 ; O’Reilly, Karim, Taylor, & Dogra, 2012 ; Swartling et al., 2011 ; Traube et al., 2013 ). Most children and adolescents expected that researchers and their parents would protect them during their research participation ( Brawner et al., 2013 ; Woodgate & Edwards, 2010 ). Children tended to believe that if a researcher behaved unethically or caused harm, the researcher would suffer consequences professionally and personally ( Traube et al., 2013 ). When asked in one study to identify factors that shaped their perceptions and assessments of risks in research children identified: the potential for harm to the child; the potential for good for the child and children in general; the burden to the child and family; and the trust experienced by the child and their parents ( Woodgate & Edwards, 2010 ).

However, weighing of risks and benefits may be age dependent in children, with young children more likely to choose options they are familiar with, and older children paying more attention to the advantages and disadvantages of each option ( Burke et al., 2005 ). In addition, Traube et al. (2013) found that both race and relationship of the researchers to participants impacted children’s trust of researchers, with African-American children having more trust in researchers who weren’t from their own community, and the most trust in Caucasian researchers who had no connection to their community.

There was also evidence that research participants interpreted and used risk information subjectively, based on their personal experiences, and may overlook risk probability information ( Reynolds & Nelson, 2007 ). One article demonstrated that adolescents and adults evaluate risks using a similar process where first the magnitude of the risks are considered, followed by consideration of the probability of the risks ( Reynolds & Nelson, 2007 ). If the magnitude was acceptable, adolescents were willing to tolerate the stated or perceived risks of a research procedure, regardless of probability.

Adolescents were very concerned regarding how their information and samples would be used, and in particular whether information would be shared with their parents ( Brawner et al., 2013 ). Adolescents and parents were found to have different opinions about research disclosures; parents often wanted to receive their children’s research information, but adolescents reported wanting to withhold private and sensitive findings ( Brawner et al., 2013 ). Specific suggestions adolescents made to researchers included allowing their parents and/or friends to attend data collection visits, being able to participate in research along with their friends, and in research where blood, urine, or other biological samples are taken to explicitly inform the adolescent whether or whether not pregnancy, sexually transmitted disease, or drug testing would be performed ( Brawner et al., 2013 ).

Impact of Research Participation Experiences

Twelve studies examined children’s feelings about their own research participation. When asked how the participation affected them, overall the majority of ratings and reports were positive. Specific benefits reported by children/adolescents included: 1) learned something new, 2) helped others, 3) helped other people learn something new, 4) felt ‘empowered’, 5) liked talking about themselves to someone else, 6) enjoyed the procedures, 7) thought filling out forms was ‘fun’, 8) trusted in researchers, 9) thought they experienced ‘clinical improvement’, and 10) would be willing to participate in another study ( Bruzzese & Fisher, 2003 ; Chu et al., 2008 ; Ensign, 2006 ; Fernandez et al., 2009 ; Reynolds & Nelson, 2007 ; Swartling et al., 2014 ; Wagner et al., 2006 ).

In the studies asking about positive aspects of participation there were always some children who did not report positive experiences. The percentages in those studies who reported negative experiences ranged from 4% – 6.1% ( Cohn et al., 2005 ; Ellonen & Pösö, 2011 ). Negative reports associated with research participation included: anxiety, feeling upset, being bored, worry about being identified as high risk for disease, and inconvenient or painful (i.e. blood draws) procedures ( Bruzzese & Fisher, 2003 ; Wagner et al., 2006 ). In some cases, those who rated aspects of research experiences more negatively also rated other aspects positively, indicating an overall positive cost-benefit ratio of research participation ( Cohn et al., 2005 ). Interestingly, of the few studies that examined factors associated with negative or positive appraisals of research participation, only one found that a demographic variable, namely the child’s level of emotional problems, was associated with their appraisals (i.e. there was a positive association between emotional problems and negative feelings towards research participation) ( Cohn et al., 2005 ; Ellonen & Pösö, 2011 ; Swartling et al., 2011 ). No other demographic variables –including age, gender, data collection strategy, type of precipitating event that lead to inclusion in the study (i.e. violence), or anxiety - were reported as significantly associated with children’s appraisals.

Use of Incentives

In seven of the articles a cash incentive of between $10 and $50 was provided to participants. Other incentives used included: small tokens or prizes, $10 phone cards, movie gift certificates, psychology course credits, and a raffle for a gift certificate). Three articles did not provide incentive to participants. Twelve articles did not discuss whether participants were provided with incentives. One article where studies were conducted at schools provided the school with $1 per participant recruited to the study.

There was an interesting range of opinions expressed by children and adolescents about the usefulness of incentives. In five of the studies, at least some of the participants thought cash incentives were a preferred form of incentive ( Brawner et al., 2013 ; Bruzzese & Fisher, 2003 ; Ensign, 2006 ; Fernandez et al., 2009 ; Langhinrichsen-Rohling et al., 2006 ). Rationale for this included: justice, pleasure associated with receiving cash, and compensation for time spent, discomfort experienced, and effort expended. In a few studies the issue of ‘how much is too much’, in terms of cash incentives as a coercive factor, was explored with children and adolescents. In one study, some adolescents voiced concerns that disproportionately large amounts of cash could be coercive for homeless youth ( Ensign, 2006 ). In another, ethnic minority children were concerned that financial incentives could potentially undermine altruistic motivations, or even tempt youth into providing false information ( Mayeux, Underwood, & Risser, 2007 ). In another study, adolescents felt that cash was not coercive for older children who had a better understanding of the role of incentives ( Vitiello et al., 2007 ).

Although parental consent for participation remains the first step in involving children and adolescents in most research, researchers and human research ethics committees are now taking assent to participate in children aged 7–12 and consent from adolescents aged 13–18 far more seriously. This systematic review confirms that obtaining children’s and adolescents’ assent to participate in research is valid and important, as even young children have demonstrated the ability to understand the essential elements of research ( Burke et al., 2005 ; Unguru et al., 2010 ). Some of the variability in levels of understanding reported in studies with children likely reflects how assent forms were written, as opposed to developmental differences ( Burke et al., 2005 ). The challenge for researchers is to find better ways to get information across to children. This problem, while relevant for all research participants, is especially pertinent in younger children who have less life experience and are challenged with a less developed ability to understand new experiences ( Brawner et al., 2013 ; Swartling et al., 2014 ). Assent processes and instruments need to be created with the assistance of child development specialists and piloted with children before being used in a research study ( Burke et al., 2005 ). Researchers should also consider using quizzes to assess children’s understanding of assent information. In addition to setting an empirical standard for assessing understanding, assent quizzes also provide additional opportunities to interact with children about assent information ( Chu et al., 2008 ).

The decision-making model used in research consent and assent processes needs to reflect the context. With the adolescent population, in particular, there is a need to balance the desire for privacy and autonomy with inclusion of parents ( Cohn et al., 2005 ; Fisher, 2003 ). Both adolescents and parents are sympathetic to the ethical dilemmas researchers face when conducting sensitive research with adolescents ( Fisher, 2003 ). A priori consultation with representative adolescents and parents can provide guidance for the selection of consent and assent procedures within challenging contexts ( Fisher, 2003 ). While this type of consultation may seem burdensome for researchers, it demonstrates that researchers respect local norms regarding parental decision-making and do not wish to inadvertently undermine the parent–child relationship ( Fisher, 2003 ).

A key gap in the findings of this review is consideration of whether children and adolescents, beyond simply understanding their research rights, are capable of applying this knowledge and of actually exerting their research rights ( Bruzzese & Fisher, 2003 ; Unguru et al., 2010 ). For example, is a child truly capable of asserting and following through on their desire to stop participating in a research study or dissenting to participate?

Findings of this systematic review demonstrate that children and adolescents have a realistic perception of research risks, and that trust - towards both parents and researchers - is essential in establishing a safe environment for children and adolescents to participate in research. As a result, researchers must establish a mutual respect with child and adolescent participants; if their trust is eroded this could have implications for both the researcher-child and the parent-child relationship ( Woodgate & Edwards, 2010 ). In addition, when performing sensitive research with adolescents, researchers should consider obtaining a federal-wide assurance to protect all data collected for use solely in research, and in particular to prevent data from being used in legal proceedings ( Langhinrichsen-Rohling et al., 2006 ).

Researchers need to appreciate that the assessment of risk is an ongoing process throughout a research study, beyond simply explanations provided when obtaining assent, and that ethnicity and context play important roles in children’s and adolescents’ perceptions of risk. In a study of African-American children, it was found that children were more likely to trust researchers from outside their neighborhood, in particular Caucasian researchers, over and above researchers they knew from their own community ( Traube et al., 2013 ). Children in this study seemed to be fearful that a researcher from their own neighborhood might tell their parents what they shared ( Traube et al., 2013 ). This is particularly interesting as the same sample of children reported that during consent processes they believed the veracity of information provided from African-American researchers over that of Caucasian researchers ( Traube et al., 2013 ).

Impact of Research Participation

Findings from this review provide evidence that research participation can be beneficial for children and adolescents. The overwhelming majority of participants confirmed a willingness to participate in research again. Children and adolescents also identified reasons for participation in research as including altruistic motivations to help others and their own learning.

This review confirmed that most children prefer to be involved in the decision-making of whether they will participate in research. In addition, soliciting children’s and adolescents’ opinions about their involvement in illness management decision-making has been found to be related to adherence to care regimens ( Miller & Jawad, 2014 ). This decision-making involvement could also be important in intervention research where children’s participation is important to the integrity of the intervention.

All research with children and adolescents could benefit from inclusion of a short interview or survey with participants to gauge their degree of satisfaction with the study. If this were done it should be formative rather than summative. That is, the responses from participants early in the study could help shape aspects of the study to enhance the experience for future participants. Talking with children and adolescents about the process of research participation, beyond the actual study, may also be useful in enhancing engagement and future participation in research.

In this review, a common reason children and adolescents gave for participating in research was incentives. Incentives for the most part were viewed positively, although some children did share that the amount of cash incentives should be carefully considered by researchers. Based on findings from this review the age of the child and their vulnerability status needs to be considered when developing plans for incentives. Younger children do not have the same understanding of monetary incentives and could be better suited to more age appropriate incentives such as toys, books, and movie passes. Researchers could consider consulting parents or adolescents from the target population when designing a study to obtain their perceptions about the timing, type, and amount of incentives. Children and adolescents who are homeless or very financially disadvantaged require special consideration, as these participants may weigh incentives differently from those who are more advantaged. For all children and adolescents, per the findings of this integrative review, when obtaining assent/consent researchers should include non-monetary elements as a benefit of study participation including: helping other children learn things, learning something new themselves, and making others’ lives better.

Conclusions

Although there have been many studies on obtaining informed consent and assent when conducting research with ill children, historically there has been much less emphasis placed on children who are involved in research in other contexts. In addition, few studies have focused on the perspectives of children and adolescents themselves. The objective of this systematic review was to examine ethical issues in research with children and adolescents from their perspective as participants, related to assent, parental consent, risk perception, impact of research participation, and incentives. This systematic review highlights the importance of including the voice of children and adolescents in the debate regarding the ethical conduct of research. Children and adolescents are a vulnerable population in the research context, formed of diverse individuals with unique, varying needs. The wide variety of strategies used in the studies described herein exemplifies that in addition to primary research studies of children’s and adolescents’ perspectives of research participation, secondary objectives related to examining their experience as participants can feasibly be added into any pediatric research study. This analysis highlights how researchers and nurses working with children and adolescents enrolled in research can expand their voice and encourage the children to share their experiences in terms of benefits, risks and challenges. It is through linking the evidence found in these studies with their own practice that researchers can improve the experience of and benefits to child and adolescent research participants.

• Assent processes and instruments need to be created with the assistance of child development specialists and piloted with children before being used.
• A priori consultation with representative adolescents and parents can provide guidance for developing consent and assent procedures within challenging contexts.
• A key gap is consideration of whether children and adolescents, beyond simply understanding their research rights, are capable of applying this knowledge and of actually exerting their research rights.
• Researchers need to appreciate that the assessment of risk is an ongoing process throughout a research study, beyond simply explanations provided when obtaining assent and/or consent.
• All research with children and adolescents could benefit from inclusion of a short, formative, off-study interview or survey with participants to gauge their experience in the study.
• The age of the child and their vulnerability status needs to be considered when selecting incentives.

Supplementary Material

Supplemental tables.

TABLE S1. Articles Included in Sample: Summary and Characteristics

Contributor Information

Stacey Crane, Predoctoral Fellow, Indiana University School of Nursing, 1111 Middle Dr., NU345, Indianapolis, IN, 46202, 513-508-3936.

Marion E. Broome, Ruby F. Wilson Distinguished Professor and Dean, Vice-Chancellor for Nursing Affairs, Duke University School of Nursing, 307 Trent Drive, Durham, NC, 27710, 919-684-9444.

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