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Ethical Considerations – Types, Examples and Writing Guide

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Ethical Considerations

Ethical considerations in research refer to the principles and guidelines that researchers must follow to ensure that their studies are conducted in an ethical and responsible manner. These considerations are designed to protect the rights, safety, and well-being of research participants, as well as the integrity and credibility of the research itself

Some of the key ethical considerations in research include:

• Informed consent: Researchers must obtain informed consent from study participants, which means they must inform participants about the study’s purpose, procedures, risks, benefits, and their right to withdraw at any time.
• Privacy and confidentiality : Researchers must ensure that participants’ privacy and confidentiality are protected. This means that personal information should be kept confidential and not shared without the participant’s consent.
• Harm reduction : Researchers must ensure that the study does not harm the participants physically or psychologically. They must take steps to minimize the risks associated with the study.
• Fairness and equity : Researchers must ensure that the study does not discriminate against any particular group or individual. They should treat all participants equally and fairly.
• Use of deception: Researchers must use deception only if it is necessary to achieve the study’s objectives. They must inform participants of the deception as soon as possible.
• Use of vulnerable populations : Researchers must be especially cautious when working with vulnerable populations, such as children, pregnant women, prisoners, and individuals with cognitive or intellectual disabilities.
• Conflict of interest : Researchers must disclose any potential conflicts of interest that may affect the study’s integrity. This includes financial or personal relationships that could influence the study’s results.
• Data manipulation: Researchers must not manipulate data to support a particular hypothesis or agenda. They should report the results of the study objectively, even if the findings are not consistent with their expectations.
• Intellectual property: Researchers must respect intellectual property rights and give credit to previous studies and research.
• Cultural sensitivity : Researchers must be sensitive to the cultural norms and beliefs of the participants. They should avoid imposing their values and beliefs on the participants and should be respectful of their cultural practices.

Types of Ethical Considerations

Types of Ethical Considerations are as follows:

Research Ethics:

This includes ethical principles and guidelines that govern research involving human or animal subjects, ensuring that the research is conducted in an ethical and responsible manner.

Business Ethics :

This refers to ethical principles and standards that guide business practices and decision-making, such as transparency, honesty, fairness, and social responsibility.

Medical Ethics :

This refers to ethical principles and standards that govern the practice of medicine, including the duty to protect patient autonomy, informed consent, confidentiality, and non-maleficence.

Environmental Ethics :

This involves ethical principles and values that guide our interactions with the natural world, including the obligation to protect the environment, minimize harm, and promote sustainability.

Legal Ethics

This involves ethical principles and standards that guide the conduct of legal professionals, including issues such as confidentiality, conflicts of interest, and professional competence.

Social Ethics

This involves ethical principles and values that guide our interactions with other individuals and society as a whole, including issues such as justice, fairness, and human rights.

Information Ethics

This involves ethical principles and values that govern the use and dissemination of information, including issues such as privacy, accuracy, and intellectual property.

Cultural Ethics

This involves ethical principles and values that govern the relationship between different cultures and communities, including issues such as respect for diversity, cultural sensitivity, and inclusivity.

Technological Ethics

This refers to ethical principles and guidelines that govern the development, use, and impact of technology, including issues such as privacy, security, and social responsibility.

Journalism Ethics

This involves ethical principles and standards that guide the practice of journalism, including issues such as accuracy, fairness, and the public interest.

Educational Ethics

This refers to ethical principles and standards that guide the practice of education, including issues such as academic integrity, fairness, and respect for diversity.

Political Ethics

This involves ethical principles and values that guide political decision-making and behavior, including issues such as accountability, transparency, and the protection of civil liberties.

Professional Ethics

This refers to ethical principles and standards that guide the conduct of professionals in various fields, including issues such as honesty, integrity, and competence.

Personal Ethics

This involves ethical principles and values that guide individual behavior and decision-making, including issues such as personal responsibility, honesty, and respect for others.

Global Ethics

This involves ethical principles and values that guide our interactions with other nations and the global community, including issues such as human rights, environmental protection, and social justice.

Applications of Ethical Considerations

Ethical considerations are important in many areas of society, including medicine, business, law, and technology. Here are some specific applications of ethical considerations:

• Medical research : Ethical considerations are crucial in medical research, particularly when human subjects are involved. Researchers must ensure that their studies are conducted in a way that does not harm participants and that participants give informed consent before participating.
• Business practices: Ethical considerations are also important in business, where companies must make decisions that are socially responsible and avoid activities that are harmful to society. For example, companies must ensure that their products are safe for consumers and that they do not engage in exploitative labor practices.
• Environmental protection: Ethical considerations play a crucial role in environmental protection, as companies and governments must weigh the benefits of economic development against the potential harm to the environment. Decisions about land use, resource allocation, and pollution must be made in an ethical manner that takes into account the long-term consequences for the planet and future generations.
• Technology development : As technology continues to advance rapidly, ethical considerations become increasingly important in areas such as artificial intelligence, robotics, and genetic engineering. Developers must ensure that their creations do not harm humans or the environment and that they are developed in a way that is fair and equitable.
• Legal system : The legal system relies on ethical considerations to ensure that justice is served and that individuals are treated fairly. Lawyers and judges must abide by ethical standards to maintain the integrity of the legal system and to protect the rights of all individuals involved.

Examples of Ethical Considerations

Here are a few examples of ethical considerations in different contexts:

• In healthcare : A doctor must ensure that they provide the best possible care to their patients and avoid causing them harm. They must respect the autonomy of their patients, and obtain informed consent before administering any treatment or procedure. They must also ensure that they maintain patient confidentiality and avoid any conflicts of interest.
• In the workplace: An employer must ensure that they treat their employees fairly and with respect, provide them with a safe working environment, and pay them a fair wage. They must also avoid any discrimination based on race, gender, religion, or any other characteristic protected by law.
• In the media : Journalists must ensure that they report the news accurately and without bias. They must respect the privacy of individuals and avoid causing harm or distress. They must also be transparent about their sources and avoid any conflicts of interest.
• In research: Researchers must ensure that they conduct their studies ethically and with integrity. They must obtain informed consent from participants, protect their privacy, and avoid any harm or discomfort. They must also ensure that their findings are reported accurately and without bias.
• In personal relationships : People must ensure that they treat others with respect and kindness, and avoid causing harm or distress. They must respect the autonomy of others and avoid any actions that would be considered unethical, such as lying or cheating. They must also respect the confidentiality of others and maintain their privacy.

How to Write Ethical Considerations

When writing about research involving human subjects or animals, it is essential to include ethical considerations to ensure that the study is conducted in a manner that is morally responsible and in accordance with professional standards. Here are some steps to help you write ethical considerations:

• Describe the ethical principles: Start by explaining the ethical principles that will guide the research. These could include principles such as respect for persons, beneficence, and justice.
• Discuss informed consent : Informed consent is a critical ethical consideration when conducting research. Explain how you will obtain informed consent from participants, including how you will explain the purpose of the study, potential risks and benefits, and how you will protect their privacy.
• Address confidentiality : Describe how you will protect the confidentiality of the participants’ personal information and data, including any measures you will take to ensure that the data is kept secure and confidential.
• Consider potential risks and benefits : Describe any potential risks or harms to participants that could result from the study and how you will minimize those risks. Also, discuss the potential benefits of the study, both to the participants and to society.
• Discuss the use of animals : If the research involves the use of animals, address the ethical considerations related to animal welfare. Explain how you will minimize any potential harm to the animals and ensure that they are treated ethically.
• Mention the ethical approval : Finally, it’s essential to acknowledge that the research has received ethical approval from the relevant institutional review board or ethics committee. State the name of the committee, the date of approval, and any specific conditions or requirements that were imposed.

When to Write Ethical Considerations

Ethical considerations should be written whenever research involves human subjects or has the potential to impact human beings, animals, or the environment in some way. Ethical considerations are also important when research involves sensitive topics, such as mental health, sexuality, or religion.

In general, ethical considerations should be an integral part of any research project, regardless of the field or subject matter. This means that they should be considered at every stage of the research process, from the initial planning and design phase to data collection, analysis, and dissemination.

Ethical considerations should also be written in accordance with the guidelines and standards set by the relevant regulatory bodies and professional associations. These guidelines may vary depending on the discipline, so it is important to be familiar with the specific requirements of your field.

Purpose of Ethical Considerations

Ethical considerations are an essential aspect of many areas of life, including business, healthcare, research, and social interactions. The primary purposes of ethical considerations are:

• Protection of human rights: Ethical considerations help ensure that people’s rights are respected and protected. This includes respecting their autonomy, ensuring their privacy is respected, and ensuring that they are not subjected to harm or exploitation.
• Promoting fairness and justice: Ethical considerations help ensure that people are treated fairly and justly, without discrimination or bias. This includes ensuring that everyone has equal access to resources and opportunities, and that decisions are made based on merit rather than personal biases or prejudices.
• Promoting honesty and transparency : Ethical considerations help ensure that people are truthful and transparent in their actions and decisions. This includes being open and honest about conflicts of interest, disclosing potential risks, and communicating clearly with others.
• Maintaining public trust: Ethical considerations help maintain public trust in institutions and individuals. This is important for building and maintaining relationships with customers, patients, colleagues, and other stakeholders.
• Ensuring responsible conduct: Ethical considerations help ensure that people act responsibly and are accountable for their actions. This includes adhering to professional standards and codes of conduct, following laws and regulations, and avoiding behaviors that could harm others or damage the environment.

Advantages of Ethical Considerations

Here are some of the advantages of ethical considerations:

• Builds Trust : When individuals or organizations follow ethical considerations, it creates a sense of trust among stakeholders, including customers, clients, and employees. This trust can lead to stronger relationships and long-term loyalty.
• Reputation and Brand Image : Ethical considerations are often linked to a company’s brand image and reputation. By following ethical practices, a company can establish a positive image and reputation that can enhance its brand value.
• Avoids Legal Issues: Ethical considerations can help individuals and organizations avoid legal issues and penalties. By adhering to ethical principles, companies can reduce the risk of facing lawsuits, regulatory investigations, and fines.
• Increases Employee Retention and Motivation: Employees tend to be more satisfied and motivated when they work for an organization that values ethics. Companies that prioritize ethical considerations tend to have higher employee retention rates, leading to lower recruitment costs.
• Enhances Decision-making: Ethical considerations help individuals and organizations make better decisions. By considering the ethical implications of their actions, decision-makers can evaluate the potential consequences and choose the best course of action.
• Positive Impact on Society: Ethical considerations have a positive impact on society as a whole. By following ethical practices, companies can contribute to social and environmental causes, leading to a more sustainable and equitable society.

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• Ethical Considerations in Research | Types & Examples

Ethical Considerations in Research | Types & Examples

Published on 7 May 2022 by Pritha Bhandari . Revised on 6 July 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 behaviours, 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 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, 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 aims 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.

Prevent plagiarism, run a free check.

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.

• 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 anonymise 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 pseudonymisation 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, counselling, 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 scientific 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.

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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Smith PG, Morrow RH, Ross DA, editors. Field Trials of Health Interventions: A Toolbox. 3rd edition. Oxford (UK): OUP Oxford; 2015 Jun 1.

Field Trials of Health Interventions: A Toolbox. 3rd edition.

Chapter 6 ethical considerations, 1. introduction to ethical considerations.

For any research investigation involving human subjects, there must be careful consideration of ethical issues that may arise in the planning, conduct, and reporting of the study. With very few exceptions, such research is not permitted unless the study has been approved by at least one formal ethics review committee (ERC). All research funding agencies require approval of the research by the appropriate ERC(s) before they will confirm an award for an intervention study. Often ethical review will be required from more than one such committee, for example, by both an institutional and a national ethics review committee, and/or in each of the countries involved in a trial. The ethics committee(s) will not only review the study protocol but usually will require full details of the study plan and procedures and will usually have specific application forms that must be completed. They may require payment of an administration fee for considering an application, irrespective of the outcome of the application. The committee will pay particular attention to informed consent documents and how consent to take part in the research will be obtained from potential study participants. Any significant changes in the study plan, either before it starts or during the conduct of the study, such as adding new objectives, extending the trial catchment area, or adding/removing inclusion or exclusion criteria, require approval by the ERC.

It is important that the ethical aspects of a research study are considered from its inception; for that reason, this chapter is placed early in the book. An underlying philosophy in this chapter is that it is difficult, and often inappropriate, to lay down ethical rules that apply to all studies in all places; each study should be judged in the context of the circumstances in which it will be conducted. A study judged unethical in one place might be considered ethical in another, and both of these might be ‘correct’ judgements.

Most ethical issues arise from conflicts between competing sets of values. For example, the medical practitioner is dedicated to the provision of the best medical care for an individual who is his or her patient. However, this dedication may be in direct conflict with that of the public health professional whose goal is to achieve maximum health benefits in a community with the limited resources available, which may entail restricting resources available to any one patient. Consuming large amounts of resources on one patient may deprive others of benefit. The appropriate balance between benefit for the individual and benefit for the community depends very much on the particular situation. The conflict is most obvious in situations of poverty and deprivation—just those conditions in which most field trials are conducted in LMICs. Those conducting field trials of interventions against diseases associated with poverty are likely therefore to be faced with especially difficult ethical dilemmas. Resolution of such dilemmas often depends upon where the investigators place their horizon of responsibility. If they consider their responsibility is confined to the participants in a trial, then some studies to resolve important public health issues might be viewed as unethical. But to assess the likely public health impact of an intervention in the wider community, it may be important to continue a trial beyond the point when it is established that one intervention is superior to another, in order to obtain a better estimate of the magnitude of the beneficial effect. Knowledge of the extent of benefit is needed, in order to make an informed decision about whether the benefit is sufficient to introduce the intervention on a widespread basis, especially if it is more expensive than the intervention that is currently available. If the investigators consider their responsibility is extended to the entire population, then they may regard it as unethical to stop a trial before a reasonable estimate of that benefit is obtained.

It is important to recognize that the primary purpose of an intervention trial is not to benefit the specific participants in the trial, but rather to obtain information about the effects of the intervention that will inform decisions about whether the intervention should be introduced on a widespread basis. Although trial participants may derive benefit, for example, they might receive better medical care in the trial than they would with the normal medical services, this is incidental to the main purposes of the trial.

Although intervention trials are not conducted with the prime aim of benefiting those in the trial, investigators have a specific responsibility for participants in a trial and must ensure that they are not harmed as a consequence of taking part in the trial and might derive some benefit. In so far as is possible, at a minimum, participants in a trial should be placed in no worse a situation than would have been the case had they not participated in the trial. It is, of course, not always possible to guarantee this, as sometimes there may be unexpected adverse events associated with an intervention, but it is important to minimize the possibility of harm to trial participants.

There is sometimes a conflict between what is best for the ‘future population’ and what is best for those participating in a trial. Such conflicts may pose serious ethical dilemmas, for which there are few ‘cookbook’ solutions. Each situation has to be considered individually and preferably during the planning of the trial, so that potential ethical issues can be thought through in advance and, where necessary, guidance can be sought from properly constituted ethics committees. This issue is discussed further in Section 2 .

It is not the purpose of this chapter to provide comprehensive guidance on all of the ethical considerations that must be considered in designing and conducting a field trial. Substantial sets of ethical guidelines have been published by a number of international bodies, and we give reference to these in the chapter, especially in Section 2.8 . Rather we highlight some of the basic ethical principles related to randomized trials in Section 2 and then focus on some of the particularly difficult, and sometimes controversial, issues that arise in field trials in LMICs.

2. Widely accepted ethical principles concerning research on human subjects

The ethical principles related to medical research involving human subjects were summarized in the Declaration of Helsinki. This declaration was first formulated in 1964 and has subsequently been debated and revised a number of times, most recently in 2008 ( World Medical Association, 2008 ). While some parts of the declaration remain hotly debated, the basic principles are generally accepted. They were reproduced and further elaborated with special reference to LMICs by the Council for International Organizations of Medical Sciences (CIOMS) ( Council for International Organizations of Medical Sciences, 2009 ). The main principles are the following.

2.1. Scientific merit

To be ethical, research must have scientific merit, preferably in the judgement of an independent scientific committee, rather than only by the researchers themselves. This assessment will generally be made in the peer review process employed by funding agencies. The methods of the research should be appropriate to the aims of the research, and results from any relevant previous or ongoing research should be taken into account in its design. Over the last decade or so, there has been much greater insistence by research funding bodies and ethics committees, as well as research journal editors, that some kind of systematic review of prior research on a topic is conducted before further research on the topic is planned. This is to avoid unnecessary duplication of research where a new study needlessly addresses research questions that have been effectively answered previously. An outline of how to conduct systematic reviews is given in Chapter 3 . Anyone proposing a trial should also review the clinical trial registers (see Chapter 7 , Section 5 ), so that they are aware of trials that are already under way which might be addressing similar issues.

The investigator is also obliged to design and conduct the research in such a way that the results from the study are likely to provide answers to the questions being addressed. This includes attention to the appropriate size and duration of the study, as well as to other aspects of its design. For example, a study that is too small to address properly the principal research question may be deemed to be unethical. Furthermore, for research concerning interventions, achievement of the trial objectives must be linked, directly or indirectly, to some kind of action that is expected to lead to improved health for the population, or future population, of which the trial participants are in some way representative. Not all research findings will have immediate health consequences for the population, but the research should be on the pathway that is expected to lead ultimately to such benefit.

2.2. Equitable selection of subjects

The potential benefits of research and the risks and burdens associated with the research should be distributed equitably among communities and among individuals within communities. The economically and socially deprived are often at the highest risk of disease. There is, on the one hand, an imperative to ensure that the appropriate research is conducted in such groups and, on the other hand, an imperative to ensure that they are not exploited in research that will mainly benefit the more wealthy and privileged. For example, it would generally be deemed unacceptable to conduct a trial of an expensive treatment in a deprived group, unless it was expected that the cost of the treatment was likely to be reduced in the immediate future to a level that could be afforded by the community or that, even if there was no reduction in cost, the treatment would at least be made accessible to those in the community in which the trial was conducted, should it be found to be efficacious. Such treatment should not be restricted solely to those who had participated in the trial but should also be provided to those in similar circumstances in the community. Whether the ‘community’ is the local population in the trial area or a much larger, possibly national, group will often be an important aspect to consider before a trial is started.

2.3. Voluntariness

Voluntariness implies that individuals and communities enrol, continue, or withdraw from the study of their own free will, with full knowledge of the consequences of their participation or withdrawal. They should not be forced or coerced by investigators, officials, family, or friends, enticed by financial or other rewards. Nor should their decisions be constrained by socio-economic or political conditions. The principle of voluntariness is a key component of the informed consent process. Voluntariness, however, applies only as far as community leaders, adult individuals, or legal guardians of children are at liberty to make free choices. In some LMICs, researchers must take extra efforts to understand, for example, the influence that unequal gender relations might have on voluntariness and design information and procedures to minimize this influence. Illiteracy is another factor that may influence voluntariness when the information channels for the study favour those who can read over those who cannot. Any monetary compensation for participants’ time or transport fares should be of a level that does not interfere with their freedom of choice, i.e. it should be sufficient to cover the actual costs, but not be an undue inducement to participate in the study (see Section 3.3 ). Particular attention should be paid to thanking potential participants who want to participate in a trial but are excluded because they are found not to meet the inclusion criteria.

2.4. Informed consent

It is now an established principle that ‘informed consent’ must be obtained from all participants in a medical or social research investigation on human subjects. Where the participant is not able to give informed consent for themselves, it is usually acceptable to request this from their parent or legal guardian.

Each potential participant should be given a comprehensive explanation as to why the research is being conducted, why they are being invited to participate, what possible benefits, risks, and burdens may arise for them personally as a result of participating in the research, and what benefits are expected to accrue to them and to the community as a result of the research. Translating these goals into a set of procedures that will be used to convey this information in a specific study is often challenging. Special problems arise with respect to field trials in LMICs, commonly involving large numbers of subjects, in obtaining assurance that all individuals are properly informed about these aspects.

Often, a research funding body or ERC will require the use of a consent form that participants must sign in the presence of a witness. The form must give full details of the study, with respect to the aspects outlined in Sections 2.1 to 2.3 . It is becoming more widely recognized, however, that, in some societies, the insistence on obtaining a witnessed signature, or thumbprint, on such a form may not guarantee that the consent was fully informed, especially in communities where many are not literate. Moreover, in some societies, the requirement to sign a consent form may actually cause undue fear and anxiety, as when people in the local culture would typically sign or mark documents only in connection with legal transactions such as transferring property or if they were to be arrested. The ethical review process may include an option to request a waiver of signed consent, provided that certain other protective conditions are met. With or without the collection of a signature, what is most important is the consent process, through which study personnel have a conversation with prospective participants to make sure that they understand all the key points of information, have an opportunity to ask questions, and understand that they are free to say ‘no’. It is always the investigator’s responsibility to ensure that subjects are properly informed of the potential risks and benefits of participation in a study. It is common practice, in some trials, to include a short ‘test’ to check that the potential study participant has understood the key information before they are asked to sign the consent form, with the opportunity to receive further explanation of points that they do not fully understand.

Lema et al. (2009) conducted a systematic review on consent procedures in clinical trials in Africa and reported that consent often was not truly voluntary; consent procedures are difficult to implement, due to cultural factors and low literacy, and local ethical review committees may be weak or ill-equipped. These findings are reinforced by a study of informed consent for HIV testing in South Africa that found that, although all women had given informed consent for the testing, they were coerced in direct and indirect ways into providing consent, and many felt they did not, in fact, have a choice ( Groves et al., 2010 ). It is therefore very important that investigators endeavour to ensure that consent is truly informed and non-coercive.

Special provisions must be made for potential participants who are not competent to provide informed consent such as children or patients who are comatose. Such persons require an advocate who is legally and morally responsible for decisions taken on their behalf. Even when the advocate provides consent, the subject should have the right to refuse, if he or she is able to, but, in practice, it may be difficult, for example, for a young child to exercise that right. In general, research procedures should not be conducted on children, unless they have already been demonstrated to be safe in adults and, if appropriate, efficacious in adults also.

The information provided to potential participants to obtain consent for taking part in a trial would be expected to include that listed in Box 6.1 .

Information that should be provided to potential participants to seek consent for taking part in a trial.

The checklist in Box 6.1 was drawn up in the context of trials in HICs, but the same principles apply for trials in LMICs. In the latter, however, it may be necessary to go to some lengths to give the required explanations and in ways that will be comprehensible in the context of the local attitudes and beliefs in the communities in which the trial will be undertaken. Often investigators will first meet with community leaders to explain the trial and to seek permission to conduct the investigation. This might be followed by community meetings at which the trial investigators explain the trial and the procedures to be followed and then answer any questions. After that, potential participants might be given further information, often in written form, that they can take home and discuss with neighbours, friends, and others advisors in the community, before they are asked to provide informed consent. Although key steps of the informed consent process should usually be done face-to-face, it is sometimes effective to get a prospective participant to watch a video or listen to an audio message that explains aspects the study. And sometimes photographs or diagrams can be very useful to supplement a verbal explanation.

2.5. Confidentiality

The confidentiality of all information collected in a research investigation must be maintained and only released to others with the explicit consent of all those concerned. The proportion of individuals who agree to participate in a study, especially one in which sensitive information is being collected (for example, whether or not an individual is infected with HIV), may be increased if careful explanations are given as to how confidentiality will be maintained and who within the study team will have access to such information. In many studies, it will be appropriate to identify individuals on record forms by a code number only, with the list linking names to the codes being kept separately in a secure place, with access limited to only those who must be able to link trial data back to specific individuals.

2.6. Coercion

In general, there are fewer legal and institutional safeguards to protect the rights of individuals in LMICs than there are in most HICs. When research workers are employed by, or identified with, the state authorities or with those who provide medical care, there is a danger that they might be tempted to exploit this position, with greater or lesser degrees of subtlety, to coerce subjects to participate in a study. Coercion and deception, even when rationalized as being for the ‘greater good’, are unacceptable. Full and open explanations of all study procedures, with the explicit understanding that participation is voluntary and those who decline will not be penalized, may be time-consuming, but this is the only acceptable approach.

2.7. Review and approval by ethics committees

Most research investigations must go through several levels of scientific and ethical review to assess their acceptability. The number of levels will depend on the nature of the research, national regulations, and from which agencies support for the research is being sought.

All ethical review bodies will require that each individual participant in a study is provided with sufficient information on potential risks and benefits to enable them to make an informed decision on whether or not to participate. Illiteracy and differing cultural concepts of health and disease do not alter the basic requirements for informed consent. If permission to approach and recruit individual members of the population has been obtained by virtue of a communal decision, individual informed consent is still necessary, and the research worker and the ethics committee must assure themselves that there is no coercion on individuals to participate. The principles that consent must be given by each individual, rather than assumed, and that all prospective participants have the right of refusal must be regarded as the minimal safeguards.

As well as being acceptable to individual participants, a trial may be reviewed at a community level through either a formal or an informal review committee. In addition, there may be local and national ethical and scientific review bodies to satisfy. If funding for a study is sought from an international agency, there may be a further level of ethical review. For example, research proposals submitted to the WHO are reviewed by the WHO Research Ethics Review Committee (WHO ERC). The committee will only review proposals that have first been approved by national and, if appropriate, local ethics committees. Given all these potential steps, it is very important that investigators allow sufficient time for research and ethics approval. Although many are much faster, it is not uncommon for some ethics committees to take as long as 6 months to review a proposal.

In the case of multicountry studies, it is common that the ethics committees review a master protocol and then subsequently individual or country-specific protocols. The latter are needed to describe how the master protocol was adapted to local reality and resources. The review of protocols for additional study sites is usually more straightforward, given that the main ethical and methodological issues of the study have already been reviewed. In some cases, a centralized ethics committee has been used to review multicentre studies, but generally ERCs are reluctant to delegate responsibility for review to a committee outside of their own country.

Ethics committees should be properly constituted and operating under defined standard operating procedures (SOPs) (see first reference in Section 2.8 ). Their main role is to ensure that ethical principles, as established by universal guidelines, are applied in the research and the rights, safety, well-being, and confidentiality of participants are protected. The committee review should focus on ethical and quality assurance aspects of the protocol, addressing its relevance, risks (physical, psychological, social, economic), and potential benefits. In some cases, the trial does not bring immediate benefit to the participants, but the knowledge generated will be for the benefit of broader society. In local committees, the inclusion of members representing the group of patients or communities under study enables a better understanding of the social and cultural aspects involved. Ideally, the members of ethics committees comprise a multidisciplinary group with experience in research and should include lay persons who can bring a non-medical perspective to the review. As the focus of review is on fairness and ethical issues, in most cases, there is no need for all members to be knowledgeable about the medical or scientific aspects. However, it is also helpful that a medical or scientific member be available to explain in more detail the rationale or concept for the procedures to be carried out and products to be administered.

The protocol should include copies of case report forms, examples of questionnaires to be used, as well as a model of informed consent in the committee’s working language and in the local language, as it is going to be applied. Social sciences methodologies, such as focus group discussions, or in-depth interviews, also require proper description and a list of the topics that will be covered in the protocol.

It is common that, before approval, the ethics committee requests additional information or description of procedures not fully detailed in the protocol, so investigators should endeavour to be comprehensive in their initial application. The queries or deliberations of the ethics committee are transmitted by the secretary to the PIs or sponsor, who should submit a revised version of the protocol with amendments and clarification, following the instructions of the committee. The more complete and detailed the protocol is, the less time will be required for reviewing. However, very often, a resubmission is needed, and the investigator should allow for time for clearance.

Some ethics committees require reports during a trial to ensure compliance with procedures and to evaluate any protocol deviations or to follow up AEs. Serious adverse reactions occurring during a trial that are considered related to the intervention should be reported to the ethics committee, and the balance between risks and benefits should be continually reassessed by the investigators (or by the Data and Safety Monitoring Board, (DSMB) on behalf of the investigators; see Chapter 7 , Section 4 ). Frequency and procedures for reports and review of trial operations and data are laid down by the committee on a case-by-case basis.

Ethics committees pay special attention to studies involving vulnerable individuals, and the protocol should ensure that there is no undue inducement to participate. Vulnerable individuals, according to Good Clinical Practice (GCP) guidelines ( International Conference on Harmonisation, 1996 ), are individuals whose willingness to volunteer in a clinical trial may be unduly influenced by the expectation, whether justified or not, of benefits associated with participation or of a retaliatory response from senior members of a hierarchy in case of refusal to participate. Other vulnerable subjects include children (commonly defined as all those below 18 years of age, but this varies between countries), patients with incurable diseases, persons in nursing homes, unemployed or impoverished persons, patients in emergency situations, ethnic minority groups, homeless persons, nomads, refugees, prisoners, and those incapable of giving consent. In some countries, there are special regulations regarding research involving indigenous populations.

Before initiating a trial, the investigator should have written approval of the protocol, written informed consent documents, subject recruitment procedures, and any other written information to be given to participants. The investigator is responsible for complying with the study protocol that was approved by the ethics committee and agreed by the sponsor and regulatory authority (if appropriate).

A clinical trial legal and financial liability insurance, which is compulsory in some countries, provides the participants and sponsor financial protection against specific contingencies such as death, disability, or other health-related complications that may occur from the participation in a trial. In most cases, liability is product-related, and lawsuits against pharmaceutical companies have increased over the years, as more careful pharmaco-epidemiological studies have been able to identify adverse effects of new products when used in a large number of people or over a long period of time. Some ethics committees will not review a protocol without having a copy of the clinical trial insurance certificate.

2.8. Useful guidance documents

Research involving human subjects is conducted in countries with widely varying socio-economic, health, and research ethics infrastructure. However, irrespective of where the research is conducted, for the ethics infrastructure to be effective, it must have officially recognized regulations or guidelines, a system for oversight and monitoring, and well-functioning research ethics committees. Many LMICs lack laws or regulations governing ethics in research and face the challenge of deciding which international guidelines to use. These guidelines are increasing in number, are not harmonized, and require interpretation or adaptation to local circumstances. Many ethics committees also face the challenge of ensuring adequate ethical review of research protocols.

The following is a selection of the most important guidance documents.

2.8.1. Operational guidelines for ethics committees that review biomedical research

These were produced by the WHO Tropical Diseases Research Programme in 2000. They set out operational guidelines for ethics committees, in order to facilitate, support, and ensure quality of the ethical review of biomedical research in all countries of the world. Targeted for use by national and local bodies, these guidelines define the role and constituents of an ethics committee and detail the requirements for submitting an application for review. The review procedure and details of the decision-making process are provided, together with necessary follow-up and documentation procedures. They can be downloaded from < http://www.who.int/tdr >.

2.8.2. International conference on harmonisation/WHO good clinical practice standards

This document ( International conference on harmonisation, 1996 ) provides a unified standard for the European Union, Japan, the USA, Australia, Canada, the Nordic countries, and the WHO. Thus, any country that adopts this guideline technically follows this same standard.

2.8.3. The Declaration of Helsinki—ethical principles for medical research involving human subjects

The Declaration of Helsinki is a statement of ethical principles for medical research involving human subjects, including research on identifiable human material and data. It was adopted in 1964 and has since undergone several amendments, including one in 2008 (available at < http://www.wma.net/en/30publications/10policies/b3/17c.pdf >.

2.8.4. International Ethical Guidelines for Epidemiological Studies

In 2009, the CIOMS published its revised guidelines ( Council for International Organizations of Medical Sciences, 2009 ). The book contains ethical guidance on how epidemiologists—as well as those who sponsor, review, or participate in the studies they conduct—should identify and respond to the ethical issues that are raised by the research process. The book can be ordered from WHO through e-mail: tni.ohw@smoic .

2.8.5. The ethics of research related to health care in developing countries

This book was produced in 2002 ( Nuffield Council on Bioethics, 2002 ) and updated in 2005 ( Nuffield Council on Bioethics, 2005 ). It defines the ethical standards for health care research in LMICs (< http://www.nuffieldbioethics.org/research-developing-countries >).

2.8.6. Consolidated Standards of Reporting Trials (CONSORT)

CONSORT 2010 provides a checklist of information to include when reporting a randomized trial. It includes a flow diagram of the process through the phases of a randomized trial. Diligent adherence to these guidelines facilitates clarity, comprehensiveness, and transparency of reporting ( Schulz et al., 2010 ).

2.8.7. Extending the CONSORT statement to randomized trials of non-pharmacologic treatments

The CONSORT statement has been extended to address specific issues that apply to trials of non-pharmacologic treatments and behavioural intervention ( Boutron et al., 2008 ).

2.8.8. Other useful background documents

The Belmont report: ethical principles and guidelines for the protection of human subjects of research (< http://www ​.hhs.gov/ohrp ​/humansubjects/guidance/belmont.html >)

The common rule, title 45 (public welfare), code of federal regulations, part 46 (protection of human subjects) , subparts A–D; The international ethical guidelines for biomedical research involving human subjects. (CIOMS) (< http://www ​.hhs.gov/ohrp ​/humansubjects/guidance/45cfr46.html >)

Canada: Tri-council policy statement: ethical conduct for research involving humans (< http://www ​.pre.ethics ​.gc.ca/pdf/eng/tcps2/TCPS_2_FINAL_Web ​.pdf >)

Indian Council of Medical Research: Ethical guidelines for biomedical research on human participants (< http://icmr ​.nic.in/ethical_guidelines ​.pdf >)

Finally, see the very useful international compilation of human subjects protections maintained by the US Office for Human Research Protections (OHRP) (< http://www ​.hhs.gov/ohrp ​/international/index.html >).

3. Special issues in field trials in low- and middle-income countries

Trials of an intervention should be undertaken only when there is uncertainty about the balance of potential benefit and potential harm, with respect to the intervention. The assessment of the extent of such uncertainty will be a critical factor in deciding whether or not it is justifiable to conduct a trial. If one trial provides good evidence of a beneficial effect, further trials of the same agent or procedure, even under very different epidemiological circumstances, will be more difficult to justify than if the first trial had not been conducted. Only if there are good reasons to believe that the results might be different under these different circumstances would further trials be indicated, and indeed a case could be made that it would be unethical not to conduct a further trial in such circumstances.

In communities which are poor and deprived and whose inhabitants may be at substantial risk of premature death and serious disease from many causes, the balance between the potential benefits of an intervention and the risk of harm may be different from that which might apply in a more privileged community. For example, a higher level of vaccine-related adverse effects might be acceptable in a trial of a vaccine against a disease that was responsible for many deaths and considerable disability in a community than would be acceptable in a study in a community in which the disease was rarely fatal and rarely caused severe disability.

In general, it is easier to persuade those who are sick than those who are well to participate in a medical research investigation. Field trials of preventive measures often involve those in the latter category and, unlike most clinical trials, take place in the community, rather than in a clinic or hospital. The task of obtaining consent for the conduct of a study in such a setting involves some special issues discussed in Section 3.1 .

3.1. Obtaining communal and individual consent

In communities in many LMICs, decisions about participation in a particular project may be taken initially at a communal level. The permission of community leaders needs to be sought for a research investigation to take place in their community. Only once such approval has been granted is it appropriate to seek approval at a household, and then an individual, level. Thus, permission to conduct a research project may be obtained first through trusted and respected community leaders, rather than through individual community members or through the heads of households. Although such procedures may seem strange and be unnecessary in many HICs and might even be regarded as challenging the right of an individual to make autonomous decisions, they are part of the cultural norm in many other societies.

In a clinical trial conducted in a hospital or clinic setting, the investigator may be able to take considerable time to explain the nature of the trial to each participant, as usually the total number of subjects in a study is relatively small. Field trials of some interventions (for example, vaccines) may be large, sometimes involving thousands, or even tens of thousands of participants, and it is more challenging to explain the trial in detail to all participants. Some of the potential methods for informing potential participants about the study have been outlined in Section 2.4 . It is important to note that obtaining ‘communal consent’ does not dispense with the need to also seek and gain individual informed consent. However, those from whom communal consent is sought should be able to represent properly the participants and to protect their interests. In reality, judgements about whether or not to participate in a research investigation depend greatly on the level of trust that investigators enjoy in a community. If a participant trusts an investigator to protect their interests, then they are more likely to agree to take part in the research. Participants will generally expect community leaders to protect their interests also and thus the importance of communal consent, as well as individual consent.

Before a community is approached regarding the possible participation of members of the community in a trial, it will usually be necessary to seek permission from the relevant local health authority, including those responsible for the medical care of the population. Subsequently, the initial approach to a community is likely to be best made to those recognized as leaders in the community. Generally, field trials are likely to be carried out by, or in direct co-operation with, the Ministry of Health and local health authorities. In such circumstances, it will usually be appropriate for discussions with community leaders to be initiated by such authorities, or at least to include their active participation. The extent of such discussions, and precisely who within a community should be involved, depends on the nature of the intervention that is to be studied. Most communities are heterogeneous, and sometimes there are factions within a community that have their own leaders whose co-operation must be sought. The people may not recognize those who are considered as the ‘official’ leaders, and others must be brought into discussions. Public notices and public meetings may also be useful.

It must be re-emphasized that obtaining communal consent for a study does not relieve investigators of their responsibility to explain the study procedures and the potential risks and benefits to those individuals who are being invited to participate, and those individuals must also be informed and be aware that they are free to refuse to participate or to withdraw from the investigation at any time without penalty of any kind.

It is also important to stress that consent to participate in a research investigation is not a one-off event in which the ethical requirements are satisfied, for example, once a signature is appended to the informed consent document. Consent to participate in a trial requires an ongoing dialogue between investigators and participants from the start of a trial through to its end. Investigators must take pains to keep participants informed of the progress of a trial, unexpected developments, and other findings, possibly from parallel studies that may impact on the trial.

3.2. Potential benefit and the risk of harm

The simple Hippocratic caveat ‘do no harm’ is not a sufficient guide to ethical decisions concerning trials of interventions. The introduction of a new intervention requires the demonstration of benefit. Furthermore, since almost any intervention procedure involves some risk of harm, albeit usually small, it is necessary to assess in intervention trials the balance of benefits against risks. In general, ethical review committees are disinclined to approve studies in which healthy persons will be exposed to more than very small risks in the context of a research investigation. Thus, it may be unacceptable to carry out a trial using a vaccine associated with serious side effects, even if it offers protection against a disease that is more serious than the side effects. For example, if one person dies as a result of vaccination for every ten persons who are saved from dying, it is unlikely that such a product would be used, even though the ‘public health’ balance appears to be in favour of the vaccine. More weight is given to harm that results from a deliberate medical intervention than is given to the harm done by the ‘natural’ disease against which the intervention protects. Furthermore, legal concerns of litigation may sometimes be given greater weight than would seem appropriate from a strictly public health viewpoint.

A proposed research investigation should be viewed within the context of the overall problems facing the community in which it is to be conducted. The community should have a reasonable expectation of benefiting from the research in both the short and long term. The effects of the conduct of a field trial in a community may be immediate and evident or may be quite subtle. Even the mere presence of the research workers in a community may have side effects (for example, increased cash flow, availability of transport to other centres), and the impact of such effects should be considered in planning the research.

The possibility of long-term harm must be considered, even if there are short-term benefits.

3.3. Incentives

In some circumstances, it may be reasonable to provide direct incentives as an encouragement to participation in a research project. If this is done, it must be recognized that there may be a fine line between compensating individuals for time and income lost as a result of participation in the study and ‘bribing’ subjects to take part. It may be considered reasonable to give a small snack after a blood sample has been taken, or to repay bus or taxi fares to participants who travel to a research centre, or to give simple medications for minor ailments, but monetary payments to encourage individuals to participate in a trial that are greater than the wages they forego or the expenses they incurred will usually be viewed as a form of undue inducement. It is difficult to lay down any absolute rules as to what is acceptable, and it is necessary to review each situation on its merits in the local context. The level of compensation to be offered will generally be considered carefully by the local ERC, whose concern will be that the level proposed does not constitute undue inducement for individuals to participate in the research.

3.4. Standard of care

There are two aspects of standard of care that have been much debated in the context of trials in LMICs. The first is with respect to the choice of the control intervention against which the effects of some new intervention is to be compared. This is discussed in Section 3.5 . The second is the standard of medical and other care offered to all the participants in a trial. When a trial is conducted in a poor community, the resources available for the trial (including additional medical personnel) may enable the standard of medical care to trial participants to be greatly improved over what would be available in the absence of the trial. Some such improvements may be essential for the scientific purposes of the trial such as improving the diagnostic facilities for detection of the disease that is the primary focus of the trial. However, the extent to which the general medical care provided to trial participants should be enhanced will need to be carefully considered in the context of each specific trial. Introducing improvements that cannot be sustained beyond the duration of the trial may, in the long run, be damaging to local communities or provoke unrealistic expectations of the local medical services. To the extent possible, improvements implemented during a trial should be designed so that they can be maintained with the resources available to the local medical service after the trial. This may involve specific training of local staff, introducing improvements in the routine medical records system, rather than setting up a parallel system, or ensuring a regular supply of drugs and other treatments that could be maintained by the local medical service after the trial. Inevitably, however, there will be some enhancements that are introduced that may be difficult to maintain after the trial. The aim should be that these are not disproportionate. In general, the provision of health care for a community is the responsibility of the national or local health services, and the research should neither usurp nor undermine existing services. It is essential therefore that the organizers of a field trial develop and maintain close links with those responsible for the normal provision of health care. Discussion of these aspects is an essential component of the submission for permission to conduct the trial to the local ethics committee.

3.5. Choice of ‘control’ interventions

The Declaration of Helsinki states that ‘the benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best current proven intervention’. Using this principle, comparison with a placebo is acceptable only if there is no convincing evidence that any intervention is effective. This principle of comparing a new intervention with the best current proven intervention seems reasonable at first sight, but it has given rise to much controversy. The controversy has centred on global ‘best’ interventions that are neither currently available nor likely to become available to the population in which the trial is being conducted, either because of their cost or because of the feasibility of implementing the intervention (for example, radiotherapy for conditions in countries in which there is little or no provision for such treatment). The ‘purists’ hold that, if the global ‘best’ intervention is not included as the control arm, then the trial is unethical and should not be conducted. The pragmatists, who often have experience of conducting trials in LMICs, hold that this position is itself ‘unethical’, as it prevents research investigations that may lead to important public health benefits in deprived populations. There is no space to expand on these arguments in detail here, but the issue is discussed at some length in other publications (for example, Council for International Organizations of Medical Sciences, 2009 ; Nuffield Council on Bioethics, 2002 ; Rid et al., 2014 ). The view of the pragmatists, including ourselves, is that, if an effective intervention is known, but its cost is beyond that which would make it feasible to introduce it into the local health care system (and there is little prospect that the cost can be reduced by means such as shifting production of pharmaceuticals to generic manufacturers), then it may well be acceptable to exclude it from consideration as a possible comparison intervention in a trial. In some circumstances, it may be acceptable to try to test a new intervention that might be, at best, equivalent to an existing intervention or may even be inferior to it if, for example, it is cheaper or simpler to apply, or more stable, or associated with fewer adverse reactions, or is more acceptable to the community than the existing intervention. In such circumstances, the purpose of the trial might be to show that the efficacy of the intervention was ‘equally good or not much worse than’ the existing intervention.

3.6. Choosing the primary endpoint

The choice of the primary endpoint for a trial, which will usually determine the necessary minimum size and duration of the trial, will generally depend on scientific, rather than ethical, considerations. Generally, the most important endpoints, in terms of assessing the impact of an intervention, will be in the reduction of severe disease or death. However, in a trial with either of these as the primary endpoint, there may be less severe outcomes, which occur with greater frequency than the severe forms of disease. The benefits of the intervention against these, often chosen as secondary, endpoints may become apparent, before sufficient cases of the more severe primary trial outcome have accumulated to reliably assess the impact of the intervention on the primary outcome. For example, in a trial of a vaccine to measure the impact of the vaccine on the incidence of severe malaria (primary trial outcome), the impact on milder malaria (secondary trial outcome) may be apparent much sooner than the impact on severe disease. Having demonstrated impact on the secondary trial outcome, some may argue that it is unethical to continue the trial, because there is no longer ‘equipoise’ between the effects of the control and the new intervention. There is no simple answer to such debates, but it is very important that careful consideration is given to such possibilities at the time the trial is designed, so that a clear decision can be taken at that stage, rather than being taken ‘on the hoof’ when the situation emerges. Sometimes, this may result in some secondary outcomes not being measured so as to avoid the potential problem! Alternatively, the decision may be taken not to break the allocation code for secondary trial outcomes until the end of the trial, or the interim results may be made available only to the DSMC, and not to the trial investigators. Alternatively, the prior decision may be taken to continue the trial until the numbers necessary to satisfy the primary trial outcome have been achieved, because of the public health importance of knowing the impact on severe disease or death. These aspects should be clearly presented to the relevant ethics committees when they consider the trial. Also relevant is what feedback will be given to trial participants of results that become available during the conduct of the trial, so that they can assess whether or not they wish to withdraw from the trial.

3.7. Duration and size of a trial

In field trials, it may be necessary to establish the efficacy of the intervention not only in the population as a whole, but also in special subgroups. This may involve the measurement of efficacy in persons of certain ages or for persons with underlying or associated conditions such as malnutrition. It will also be necessary to determine the duration of efficacy and to have a reasonably precise estimate of the degree of efficacy.

It may be argued therefore that the appropriate point at which to stop a trial should be when sufficient evidence has been collected to support, or reject, the introduction of the intervention by the health services generally, rather than at the point when the difference in response in intervention and control groups is first established beyond reasonable doubt. For many interventions, it is important to establish both the degree and the duration of protection. Thus, a trial might be continued beyond the point at which protection is first established to determine if there is long-lasting protection. For example, it may be established in the first 6 months of a malaria vaccine trial that the vaccine is protective, but, to be of public health value, it may be necessary to demonstrate that long-lasting protection is achieved. This may necessitate continuing the trial for at least 2 or 3 years with the maintenance for this period of an unvaccinated group or of a group whose members had received an inferior vaccine. In some circumstances, this will be considered acceptable, but, in others, it will not. Again, each situation must be considered on its own merits, and much will depend on how far the investigators extend their horizon of responsibility, with respect to the public health use of the intervention they are evaluating.

Often, the most important outcome in a trial may not be observed until a considerable time after the intervention has been applied, but there may be intermediate outcomes against which the intervention is also assessed. For example, a vaccine may produce a good antibody response long before any protection against disease is shown. Demonstration of efficacy against the intermediate outcome (antibody response) might be considered grounds for ending a trial if it is reasonable to assume that the effect observed on the intermediate outcome would necessarily carry over to the more distant trial outcome (protection against disease), even though efficacy against that outcome had not been formally demonstrated. What is ‘reasonable to assume’ is often a matter of considerable debate, and the ethics of continuing a trial, once protection against intermediate endpoints has been established, must be argued in the particular circumstances surrounding a trial. Immunological measures which are thought to correlate with protection against clinical disease may not so do. For example, in one trial in which this aspect was examined, the protection that BCG conferred against TB did not correlate well with the induction by the vaccine of sensitivity to a tuberculin skin test ( D’Arcy Hart et al., 1967 ), even though it was possible to put forward plausible immunological arguments for believing that such a correlation should exist.

An example of the ethical difficulties that may arise is provided by trials of malaria vaccines. Early treatment with appropriate anti-malarials is normally curative for falciparum malaria, and, in a trial, it would be unethical to withhold such treatment from those with clinical malaria. Yet the main purpose of such a vaccine is the prevention of death from malaria, not of infection, nor even the prevention of minor malaria illness. Indeed, it is conceivable that there may not be a good correlation between the protection of a vaccine against the last two outcomes and the protection against death as the outcome. The dilemma is that, in most of Africa where malaria continues to kill hundreds of thousands of children annually, medical services are not adequate to provide the level of curative care that would be provided in a trial, nor are they likely to be so in the near future. Because malaria is a treatable disease and effective treatment should be made available to all those who are diagnosed with malaria during a trial, it is likely that mortality from malaria in a trial would be at a very low level—too low to allow this to be a primary outcome in a reasonably sized trial—and therefore the primary outcome may have to be either clinical malaria or severe disease (which may also be at a lower level, because of the treatment and care provided in the context of the trial). The assumption would have to be made that any efficacy demonstrated against clinical malaria and/or against severe disease would be likely to carry over into the prevention of malaria mortality. It may not be possible to address the impact on mortality until the vaccine is in public health use, and assessment might be made through specially set-up surveillance or Phase IV studies (see Chapter 22 ). Such studies may be set up to be very large, such that it would only be realistic to leave the treatment of cases of malaria to the existing system of medical care.

There are very strong reasons for conducting early trials of a new intervention to assess the impact of the intervention against the outcomes which are of greatest public health importance, rather than starting with trials against intermediate outcomes, if, by studying intermediate outcomes, further trials against more important outcomes may be compromised. Sometimes, knowledge from other studies may be sufficient to be confident that, if effects are demonstrated against intermediate outcomes, then impacts on more important outcomes will necessarily follow, but all too often, such an assumption is not warranted.

There are strong reasons for conducting very large trials of interventions that are likely to be used on large numbers of people in the future if the interventions are effective, much larger than would initially seem necessary to achieve only a statistically significant difference in outcome. The results of very large trials, if the trials have been adequately managed, can be much more convincing and are more likely to lead to the implementation of the intervention in disease control programmes than are the results of small trials.

Again, part of the dilemma relates to where the investigator places the horizon of responsibility. If the view is taken that the investigator, by taking on the responsibility of a field study, also takes on responsibility to provide full medical care of the subjects under study, then a study of a malaria vaccine with prevention of death as the endpoint could not be undertaken. If the view is taken that the horizon of responsibility extends to all those who are at risk of dying from malaria, including those who would not be included in the trial but who may benefit eventually from the vaccine, then a trial might be conducted with death as an endpoint, but the design of such a trial would be challenging!

3.8. Monitoring safety during a trial

All clinical studies require safety monitoring throughout the duration of the trial and, in some cases, for a defined period after the completion of the study. Investigators are responsible for the detection and reporting of adverse events or serious adverse events and to the sponsor, the ethics committee, and regulatory authorities, according to the time period and procedures specified in the protocol (see Chapters 7 and 12 ).

The ethics committee should review a study when serious and unexpected adverse events related to the conduct of a study or study product are reported, as the events may affect the benefit/risk balance of the study. Refer to the International conference on harmonisation guideline for clinical safety data management: definitions and standards for expedited reporting for more detail (< http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500002749.pdf >).

3.9. Special ethical issues in cluster randomized trials

In addition to ethical issues common to all randomized trials, additional ethical concerns can arise in cluster or group randomized trials ( Edwards et al., 1999 ).

Most ethical issues specific to cluster trials are related to: (1) the legitimacy of informed consent when sought at group level, (2) the potential conflicts between individual autonomy vs group consent, and (3) the differential benefit that one cluster may have over another in some trials.

Most of the issues concerning informed consent in cluster randomized trials are discussed in Section 3.1 . These include the identification of different levels at which consent can, or should be, sought and who has the legitimacy to determine whether researchers may approach groups or communities.

A potential issue in cluster randomized trials is when the request for individual consent is obtained after randomization and allocation of the cluster to the intervention or control arm of the trial. This should not cause an ethical concern per se, but it could lead to bias in the nature of the consent in the different intervention groups and thus be of scientific concern.

3.10. Reporting and feedback of results

At the completion of an investigation, there is a responsibility to inform the community in which a trial has been conducted of the results of the study in such a way that its members can understand the implications of the findings. Indeed, such feedback should be ongoing, as the research progresses. Not only is it important ethically that participants should be kept informed of the progress of the research, but, if this is done, it is also likely to encourage their continued participation. The procedures to ensure this feedback takes place should be planned from the start of an investigation.

There is also a responsibility to feed back the results of the research to the relevant local or national health services and disease control programmes, so that these groups can assess the implications of the findings for their own activities.

These issues are discussed in greater detail in Chapter 23 .

The anonymity of participants in a trial should always be respected, and there should be no danger that any of them will be identified through any publication of the results of a trial. The same rights of confidentiality should be considered for communities, as well as for individuals. It will sometimes be appropriate to keep the identity of the community anonymous, particularly if sensitive issues are discussed, such as hygiene practices or sexual or other practices that are sometimes condemned by other cultures (such as female genital cutting, infanticide, or anal sex). Sometimes, it is not possible to disguise a particular location, and, in some circumstances, it may be important that the community be identified to aid interpretation of the study results. Indeed, communities are sometimes proud to be associated with a particular research programme, and the name of the community or place may be used as the title of the project (for example, the Garki malaria project ( Molineaux and Gramiccia, 1980 )).

3.11. What happens after the trial?

The closure of a trial presents special challenges, especially when the intervention group receives significant improvements in the quality of care, while the control group receives usual care, which, in many LMICs, will be suboptimal care or even no care. The challenges are even greater when the intervention has been shown to be successful. Should the benefits of the intervention be sustained in the study group and, if so, how and with whose resources? Should the intervention be extended to the control group (at the minimum), and possibly to the whole community in which the trial was conducted? If yes, how and with whose resources? These are often difficult questions and should be addressed from the inception of the trial, and the implications included in any discussions with the trial funder and trial sponsor. How they are tackled will depend on the setting, the nature of the intervention, the strength of the health system, and the availability of other partners working the study area. If the intervention can be mainstreamed into the health or other services of the community, this should be explored with the relevant decision makers. If, for example, the intervention concerns children and there is a United Nations Children's Fund (UNICEF) programme in the area that can help to extend it to the communities, these alliances should be established. If there is an opportunity for the local health administration to apply for a local, regional, or international grant to help extend the intervention, the trial team should help with preparing this grant. If the trial team plans to take responsibility for extending the intervention, appropriate funding and timelines should be reflected in the project plan and budget.

3.12. Special ethical issues in Phase IV (post-licensure) studies

Phase IV studies with drugs and vaccines are needed to evaluate effectiveness, long-term safety, and potential drug interactions. For safety surveillance, or pharmacovigilance, a system should be in place for collecting, monitoring, and evaluating information from health care providers and patients on AEs that may be associated with medications and biological products. These issues are discussed in greater detail in Chapter 22 .

Ethical concerns, as well as quality of data, should be carefully examined in relation to the physician’s relationship with the sponsors, marketing of products, incentives, and biased observations. Special informed consent is not always needed when the intervention under study is already part of the routine public health system. However, if participants are asked for more detailed follow-up than would usually be required, to answer specific questionnaires or to perform additional examinations, special informed consent for research may be needed and ethical review of the Phase IV study protocol required.

Post-licensing studies are also used to explore new routes, formulations, and new or modified indications or drug associations of a registered product. In the case of evaluation for a new indication for a known product (label extension studies), the development protocols and ethics review should follow the same path as for a new product.

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• Cite this Page Smith PG, Morrow RH, Ross DA, editors. Field Trials of Health Interventions: A Toolbox. 3rd edition. Oxford (UK): OUP Oxford; 2015 Jun 1. Chapter 6, Ethical considerations.
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Frequently asked questions

What are ethical considerations in research.

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.

Frequently asked questions: Methodology

Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

• Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

• If there is no sampling frame available (e.g., people with a rare disease)
• If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
• If the research focuses on a sensitive topic (e.g., extramarital affairs)

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

• Reproducing research entails reanalyzing the existing data in the same manner.
• Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 
• A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
• A successful replication shows that the reliability of the results is high.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity , and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

• Convergent validity : The extent to which your measure corresponds to measures of related constructs
• Discriminant validity : The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as “people watching” with a purpose.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation).

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

• Open-ended and flexible
• Impossible to answer with “yes” or “no” (questions that start with “why” or “how” are often best)
• Unambiguous, getting straight to the point while still stimulating discussion
• Unbiased and neutral

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when: 

• You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
• You are constrained in terms of time or resources and need to analyze your data quickly and efficiently.
• Your research question depends on strong parity between participants, with environmental conditions held constant.

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
• Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions.
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
• You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses.
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts.

The four most common types of interviews are:

• Structured interviews : The questions are predetermined in both topic and order. 
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
• Unstructured interviews : None of the questions are predetermined.
• Focus group interviews : The questions are presented to a group instead of one individual.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

• Inductive generalization : You use observations about a sample to come to a conclusion about the population it came from.
• Statistical generalization: You use specific numbers about samples to make statements about populations.
• Causal reasoning: You make cause-and-effect links between different things.
• Sign reasoning: You make a conclusion about a correlational relationship between different things.
• Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Triangulation can help:

• Reduce research bias that comes from using a single method, theory, or investigator
• Enhance validity by approaching the same topic with different tools
• Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

• It’s time-consuming and labor-intensive, often involving an interdisciplinary team.
• Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

• Data triangulation : Using data from different times, spaces, and people
• Investigator triangulation : Involving multiple researchers in collecting or analyzing data
• Theory triangulation : Using varying theoretical perspectives in your research
• Methodological triangulation : Using different methodologies to approach the same topic

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure. 

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps: 

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to author, or 
• Send it onward to the selected peer reviewer(s) 
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made. 
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Every dataset requires different techniques to clean dirty data , but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.

These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimize or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.

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 but a serious ethical failure.

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.

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.

In multistage sampling , you can use probability or non-probability sampling methods .

For a probability sample, you have to conduct probability sampling at every stage.

You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.

To find the slope of the line, you’ll need to perform a regression analysis .

Correlation coefficients always range between -1 and 1.

The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.

The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.

These are the assumptions your data must meet if you want to use Pearson’s r :

• Both variables are on an interval or ratio level of measurement
• Data from both variables follow normal distributions
• Your data have no outliers
• Your data is from a random or representative sample
• You expect a linear relationship between the two variables

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your sampling methods or criteria for selecting subjects
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Correlation describes an association between variables : when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.

Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.

While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy .

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

• In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
• In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

• A positive correlation means that both variables change in the same direction.
• A negative correlation means that the variables change in opposite directions.
• A zero correlation means there’s no relationship between the variables.

Random error  is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables .

You can avoid systematic error through careful design of your sampling , data collection , and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment ; and apply masking (blinding) where possible.

Systematic error is generally a bigger problem in research.

With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample , the errors in different directions will cancel each other out.

Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions ( Type I and II errors ) about the relationship between the variables you’re studying.

Random and systematic error are two types of measurement error.

Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).

Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).

On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.

• If you have quantitative variables , use a scatterplot or a line graph.
• If your response variable is categorical, use a scatterplot or a line graph.
• If your explanatory variable is categorical, use a bar graph.

The term “ explanatory variable ” is sometimes preferred over “ independent variable ” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.

The difference between explanatory and response variables is simple:

• An explanatory variable is the expected cause, and it explains the results.
• A response variable is the expected effect, and it responds to other variables.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment.
• Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

There are 4 main types of extraneous variables :

• Demand characteristics : environmental cues that encourage participants to conform to researchers’ expectations.
• Experimenter effects : unintentional actions by researchers that influence study outcomes.
• Situational variables : environmental variables that alter participants’ behaviors.
• Participant variables : any characteristic or aspect of a participant’s background that could affect study results.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

• Only requires small samples
• Statistically powerful
• Removes the effects of individual differences on the outcomes

Disadvantages:

• Internal validity threats reduce the likelihood of establishing a direct relationship between variables
• Time-related effects, such as growth, can influence the outcomes
• Carryover effects mean that the specific order of different treatments affect the outcomes

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

• Prevents carryover effects of learning and fatigue.
• Shorter study duration.
• Needs larger samples for high power.
• Uses more resources to recruit participants, administer sessions, cover costs, etc.
• Individual differences may be an alternative explanation for results.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

• It’s caused by the independent variable .
• It influences the dependent variable
• When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

There are three key steps in systematic sampling :

• Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
• Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
• Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

• In single-stage sampling , you collect data from every unit within the selected clusters.
• In double-stage sampling , you select a random sample of units from within the clusters.
• In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.

Blinding is important to reduce research bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

• In a single-blind study , only the participants are blinded.
• In a double-blind study , both participants and experimenters are blinded.
• In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
• You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

• The type of soda – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Using careful research design and sampling procedures can help you avoid sampling bias . Oversampling can be used to correct undercoverage bias .

Some common types of sampling bias include self-selection bias , nonresponse bias , undercoverage bias , survivorship bias , pre-screening or advertising bias, and healthy user bias.

Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).

The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g. the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g. water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Ethical considerations in research

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This chapter provides the principles on which ethical decisions are based. It describes the processes required to obtain informed consent. The chapter includes exercises with practical work on observation and note taking. In the UK, ethical standards are enforced by a national framework of local research ethics committees in combination with a set of regional multicentre research ethics committees. Ethical decisions in research are also subject to the dictates of scientific validity. Studies are carried out and given ethical approval even though informed consent has not been sought, because to do so would influence the outcome of the trial. The principles are derived from the ethical approaches. There are four principles: autonomy, non-maleficence, beneficence and justice. Like the ethical principles on which the rules are based, there are four. They are veracity, privacy, confidentiality and fidelity. Gaining informed consent from a patient is an essential part of any research. The setting and timing when seeking informed consent is obviously crucial.

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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 and Regulatory Aspects of Clinical Research

This course is offered to anyone interested or involved in the ethics of clinical research with human subjects. Participants represent multiple disciplines including research teams, IRB members, physicians, psychologists, nurses, social workers, administrative staff, students, and others.

Course Objectives

Upon completion of this course, you should be able to:

• Utilize a systematic framework for evaluating the ethics of a clinical research protocol.
• Identify, define, and consider ethical issues in the conduct of human subject research
• Apply appropriate codes, regulations, and other documents governing the ethical conduct of human subject research to their own research.
• Describe the purpose, function, and challenges of IRBs
• Identify the critical elements of informed consent and strategies for implementing informed consent for clinical research.
• Identify and apply relevant considerations for assessment of research risks and benefits
• Explore the ethical requirement of fair subject selection and its application.
• Identify challenges and opportunities related to genetics research and research with stored samples
• Appreciate the perspective of individuals who have participated in research
• Appreciate ethical challenges with conducting international collaborative research in low- and middle-income countries

Course Syllabus

View a DRAFT version of the course syllabus.

Background Requirements

There are no background requirements in terms of education, knowledge, or experience, just an interest in clinical research with human subjects. This course is readily accessible to the non-medically trained as well as to those in the field of scientific research. As a rule, background education includes a mix of MD, PhD, RN, MPH, MSW, MPH, and BA/BS.

There is no fee for this course, but a textbook, The Ethical and Regulatory Aspects of Clinical Research (JHU Press) is required. The course textbook is "Ethical and Regulatory Aspects of Clinical Research: Readings and Commentaries (JHU Press, ISBN 9780801878138)." You can order the book online from the FAES Bookstore @ NIH or other online purveyors of books.

Lecture Only

If your plan is to only watch/review the lectures (i.e. you are not looking to earn a certificate of completion) you do not have to register on Canvas. Just tune in at 8:30-11:30 am Eastern Standard Time at NIH VideoCast or watch on your own time once the recording is posted on the NIH VideoCast archive or Department of Bioethics website . Recordings are posted within 48 hours after each class session.

Certificate of Completion

In order to receive a Certificate of Completion you must self-enroll in the course and self-register .

Step 1: Self-enroll . If you self-enroll you will have access to course materials (e.g. readings) posted in Canvas. Self-enroll .

Self-enrollment ends at 11:59 pm Eastern time on Wednesday, October 16, 2024.

If you want a Certificate of Completion you must also self-register .

Step 2: Self-Register. The Self Registration Quiz is posted on the Homepage for the course as well as under the TAB labeled Quizzes.

Self-Registration ends at 11:59 pm Eastern time on Wednesday, October 9, 2024

The course meets 7 times (7 sessions). There is a Session Quiz for each session. To receive a basic Certificate of Completion you must complete at least 3 Session Quizzes .

If you want to receive credit for the Clinical Research Curriculum* (for those employed by the NIH as staff, trainee or contractor) credits you must be registered for the course and

complete at least 6 of the 7 Session Quizzes by November 20, 2024 .

** Successful completion of this course is required for the Clinical Research Curriculum Certificate. View more information .

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In the past, we facilitated the enrollment of groups of learners who complete the course as a group off site. We will not be offering this option this year. Direct learners to self-enroll and self-register (see above). Learners who complete 3 sessions will receive a Certificate of Completion. For questions email [email protected].

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2024 Course Information

Our annual Ethical and Regulatory Aspects of Clinical Research course will be offered in Fall 2024 (September 25–November 6). Materials from previous years can be viewed at the links below.

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Ethics considerations for precision medicine research and genetic testing in low- and middle-income countries

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Sondos Mubarak 1 and Mohamed Ashraf 2

Background : Genetic data transfer within multicentre clinical trials conducted in low- and middle-income countries is common and must be communicated to study participants as part of ethical requirements.

Aims : To analyse ethics practices in precision medicine research in low- and middle-income countries and make useful recommendations.

Methods : We conducted a narrative review of published literature and existing ethics frameworks regarding under-representation of low- and middle-income countries in genomic databases, informed consent and data security discussions, as well as the potential for exploitation and limited access to benefits.

Results : The findings highlight the need for increased diversity in research participation, robust ethical frameworks, and knowledge sharing between developed and developing countries. The findings show that strengthening national research ethics committees and fostering collaboration can help low- and middle-income countries in addressing unique challenges and harnessing the potential of precision medicine while ensuring ethical conduct and equitable access for all. Our review emphasizes the importance of ethical considerations in precision medicine research to ensure that its benefits reach all affected populations, promoting a more just and more equitable healthcare future.

Conclusion : There is a need to ensure that research participants are accorded the rights, whether in the ownership of their samples or the right to know what type of genetic studies have been conducted on their samples. It is important to have binding agreements that will allow clinical trial participants to access drugs that proof effective based on the trials they participated in.

Keywords : precision medicine research, research equity, low- and middle-income countries, ethics principles, ethics committees, ethical considerations, clinical trials

Citation: Mubarak S, Ashraf M. Ethics considerations for precision medicine research and genetic testing in low- and middle-income countries. East Mediterr Health J. 2024;30(6):455–460. https://doi.org/10.26719/2024.30.6.455.

Received: 31/07/23; Accepted: 15/01/24

Copyright: © Authors 2024; Licensee: World Health Organization. EMHJ is an open access journal. All papers published in EMHJ are available under the Creative Commons Attribution Non-Commercial ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo).

Introduction

Do we need innovative concepts in biomedical ethics to maintain pace with genomics innovations, or are we compelled to tailor genomics and its applications, such as pharmacogenomics and precision medicine research, to fit into existing ethical frameworks? Should additional protections be established for so-called vulnerable populations residing in low- and middle-income countries (LMICs)? What are the ethical implications governing research in an international context and recruiting populations from developing countries and LMICs, as defined by the World Bank (1)?

Ethical considerations for the inclusion of different populations in genetic research include assessing all ethical implications regarding privacy, beneficence, confidentiality, non-maleficence and autonomy (2). Genetic data transfer during multicentre clinical trials conducted in LMICs is common practice and must be communicated as a part of the informed consent process.

The concept of personalised medicine is controversial, and is defined as “the use of drugs and procedures to provide the optimal treatment for every individual patient” (1). Pharmacogenetics is an advanced area of personalized medicine, which aims to reduce adverse drug reactions and achieve a better response by tailoring the pharmaceutical regimen to the individual genome of the patient. Many such approaches have been used to treat cancer patients. Pharmacogenomics has been used to treat infectious diseases such as hepatitis to avoid severe adverse drug events in patients who are genetically more sensitive to standard treatments (3). The discovery of the Goldilocks gene, which plays a role in the inflammatory response to tuberculosis, could have a major impact on medical practice in developing countries for predicting the risk of contracting tuberculosis and identifying who will benefit from steroids (3). Given the pace of development of precision medicine, it is only a matter of time before other benefits for socioeconomically underserved populations can be identified (4). In this article, we address the lack of diversity in genomics databases, which is a barrier to translating precision medicine research into practice. We also explore the concept of privacy and its associated ethical standards. Precision medicine research in LMICs necessitates a nuanced approach that balances the potential benefits with ethical considerations, including informed consent, data security and ensuring equitable access to the advancements for all populations.

Addressing evidence limitation related to precision medicine

Patients should be well educated about all the options of precision medicine and the potential results so that they can make informed decisions. Educational materials should be tailored to the awareness of different populations. It is important to support communication with families when there is an identifiable family risk because, for example, first-degree relatives have a 50% chance of inheriting conditions such as Lynch syndrome. Clinicians have an ethical duty to inform patients about this kind of risk and to encourage family members to undergo testing. However, it is arguable how far this duty of clinicians extends and whether it ends with telling the patient, who then has to inform their family (5).

The other aspect under consideration pertains to the implementation of clinical innovation in small or rural clinics and hospitals. It is imperative to ensure equitable access to the advantages of precision medicine for all individuals. Notably, while conducting research and implementing innovations in academic medical centres and larger healthcare facilities, these endeavours can function as instructive templates for the broader integration of genomic medicine (6).

Situation analysis

As previously described by Landry et al. in 2018, “Precision medicine is predicted to revolutionize the clinical practice of medicine by using molecular biomarkers to assess a patient's prognosis, risk, and therapeutic modalities more precisely” (2). However, dependence on biomarkers may create challenges for countries that are not equitably represented in precision medicine research. The representation of different populations in genomic studies listed in the following 2 public databases has been investigated: the genome-wide association study catalog and the database of genotypes and phenotypes (2). The findings showed fewer studies among African, Latin American and Asian than European populations. These patterns were consistent across various information types. Although the number of genomic research studies that include non-European populations is increasing, the overall number is still low, “and action is needed to implement the changes necessary for realising the promise of precision medicine for all” (2).

There is a lack of genetic counselling for prenatal genetic testing in LMICs, and clinicians use negative language to influence the decisions significantly more than in higher-income countries. Genetic counselling should involve reducing the fear and anxiety related to genetic testing and the need for support to achieve the maximum benefit of counselling (7).

There are many organizations that control biobanks, such as the International Society for Biological and Environmental Repositories, which produces guidelines to guarantee high-quality specimens, and the European, Middle Eastern and African Society for Biopreservation and Biobanking, which aims to improve sharing of biological specimens (7). The use of human blood and tissue is critical to biomedical research; however, there are no clearly defined regulations regarding the ownership of human tissue specimens and who controls their fate. Hence, there is a need to address this issue at the national level to ensure that policies are compliant with local cultural customs and beliefs, rather than relying on external agencies to address underlying issues related to national security and privacy of data.

As Ramsay mentioned in 2012, the genomic composition of African populations is poorly understood and there is considerable variation between ethnolinguistic groups (8). The unique genomic dynamics among African populations have an important role to play in understanding human health and susceptibility to disease (9). Extensive genomic analyses have been conducted among Europeans to examine associations with complex traits but few such studies have been conducted among Africans (8). This is mainly because of lack of funding, poor healthcare infrastructure and public health facilities, and a small pool of trained scientists (10). Africa is currently host to several international genomics research and biobanking consortia; each with a mandate to advance genomics research and biobanking in the continent. However, many of these consortia have yet to specify exactly how they plan to revolutionise international health research in Africa, despite their ambitious claims (10). When African researchers were interviewed, 2 major concerns about being part of these collaborative initiatives were voiced: (1) that there is a possibility of exploitation of African researchers and their countries; and (2) a lack of sustainable measures for research capacity building to allow researchers to begin conducting the research themselves (10).

The 4 principles of Beauchamp and Childress: principles of biomedical ethics

The principles of biomedical ethics were first published in 1979. They have become one of the best-known theories of bioethics and are practiced worldwide in medical research. Here, we use them to analyse questions related to the use of emergent techniques and areas of research related to the human genome, the investigation of precision medicine, and incorporating developing nations into these research frameworks (11).

Examination of the principles of biomedical ethics in the context of genetic research and marginalised populations

Respect for autonomy

Vulnerable populations in LMICs do not practice autonomous decision-making in the same way that western populations do (12); therefore, further consideration of what autonomy means in such vulnerable communities is needed. One should consider how they perceive the offer to participate in a clinical trial or any kind of data collection. For them, it may be considered a way to improve health care provision, which may not necessarily be the case. One could argue that health literacy issues hinder the practice of such concepts as autonomy and informed decision-making among these populations. As defined by WHO, during the 7th Global Conference on Health Promotion, “Health literacy is the cognitive and social skills which determine the motivation and ability of individuals to get access to, perceive and use information in ways which promote and maintain good health” (13). Health literacy means more than being able to read and browse pamphlets successfully and make doctors’ appointments, and goes beyond the concepts of health education and individual behaviour-oriented communication. Health education properly applied through the effective participation of healthcare teams and patients could slowly close the communication gap between them and reduce the level of paternalism practiced by healthcare providers. This could lead to further health literacy, resulting in effective community action and development of social capital (13).

Non-maleficence

Non-maleficence is the principle of not doing harm. Beneficence is an action that is taken, whereas non-maleficence is avoidance of an action. For research that is externally sponsored (conducted in a country and funded by sponsors from another), international guidelines advise that independent ethics committees in both countries should approve the research to ensure that the ethical standards of both countries are met, and avoid exploitation arising from potential imbalances of power and resources. The non-maleficence principle, which emphasizes avoiding harm, may be challenged when selecting certain populations for research. This could be the case if these populations lack the same level of health care as developed nations, making them unfamiliar with the specific experimental drugs being tested.

Beneficence

The bodies that regulate clinical trials (such as the United States Food and Drug Administration, European Medicines Agency, and Medicines and Healthcare Products Regulatory Agency in the United Kingdom of Great Britain and Norther Ireland) should ensure that pharmaceutical companies register their drugs after trial completion and that the drugs have been proven safe. The drugs should be registered in countries where the trials were conducted. This would form a post-clinical trial agreement that would benefit the populations that participated in the trial. If genetic tests for future exploratory studies are requested during clinical trials, participants must be informed of the purpose of the study, what type of tests will be conducted, how long any data or biological specimens will be kept, and whether they will be informed of any new findings related to their data or specimens.

Professional–patient relationship

Examining privacy parameters.

The concept of privacy has long played a central role in human rights law. Worldwide, various bodies have enacted several binding and nonbinding regulations for physicians and researchers to protect the autonomy, dignity and privacy of patients and research subjects (14). With the development of new technology, the right to privacy has gained a new perspective: the right to protection of personal data.

According to Carrieri et al., “Genomic research has the potential to generate incidental findings, that is, findings that were not an intended objective of the study but were discovered as a consequence of the current technologies employed in this field” (15). Although institutional review boards expect doctors and researchers to discuss the return of research findings to participants in their research, this is something that does not usually happen in developing countries.

The importance of data protection has increased in the European Union (EU). Data protection laws are considered crucial to regulate the use of health data in medical research and research related to biobanks (16). In May 2018, the EU released the EU General Data Protection Regulation, which is considered the most important change in data privacy regulations over the past 20 years. The EU Charter includes explicit rules for handling human biological samples and personal data, requiring informed consent from the sample donors and research participants, or with regard to data, some other legal basis has been laid down. Similar provisions should be made for research in developing countries, especially for cross-border transfer of health data or biological samples, to protect the privacy of citizens (14).

Data sharing in the era of precision medicine research

Data sharing is an important component in scientific research. However, it is a challenge in genetic research because of the nature of the research itself and the genome is an identifiable feature of the participants (17). In studies involving humans, consent from donors must be obtained to use their data for research.

There have been claims about differences in human research practice in relation to standards in western countries and other parts of the world. There is an argument that what are called western standards are actually international standards and should be respected everywhere. In contrast, opponents of this view state that there is a need to tailor standards to the context and cultural perspectives in particular countries (18). Protection of communities is an important element of research; however, the potential harm to communities of individuals' participation in research has not been fully considered.

One study that actually addressed this issue was a genetic study of Askhenazi Jews, whose findings illustrated how it is possible for a research study to put the whole community at risk (18). There have been frequent reports of a particular mutation (185delAG) in the BRCA1 gene among Ashkenazi Jews, which results in a high risk of ovarian and breast cancer. The study samples were collected from the data banks established in association with Tay–Sachs disease and cystic fibrosis screening. The National Institutes of Health Review Committee required no individual informed consent because all the identifiers were erased from the samples. The results showed that 0.9% of Ashkenazi Jews carried the mutation, at a higher rate than among the general population. Another study found that 6.1% of Jews had the I1307K mutation of the APC gene, which is related to susceptibility to colon cancer, but it was not found in the non-Jewish population (17). This study also used anonymous samples from a Tay–Sachs database. In both the above studies, any identifying information was removed from the DNA samples, thus there was no risk to individuals' participation in the studies. However, the results of these studies could have a substantial impact on the wider Ashkenazi Jewish community. The results give credibility to the suggestion that Jews are more susceptible to malignant diseases, such as breast cancer, and this in turn could lead to discrimination (18).

Potential threats and benefits to the populations of LMICs

Precision medicine faces several challenges that need to be addressed. There are foreseeable benefits and threats to the populations of LMICs. We are examining the challenges and opportunities facing developing countries as they begin to harness genomics for the benefit of their populations, in genetic research and development of treatment options.

The main role of institutional review boards is to help researchers protect the rights and welfare of study participants through periodic independent review of different ethical proposals for human research. The diverse membership of the boards includes scientists, nonscientists and institutional members, which allows the boards to systematically evaluate each study to ensure that the rights and welfare of participants are adequately protected by the study objectives. Each member of the board has the opportunity to contribute their concerns and life experiences to the discussion.

There are gaps between developed and developing countries in terms of adequate research infrastructure and equipment, and in applying the results of research and any lessons to be learned. Insufficient technology can make it difficult for researchers in developing countries to communicate their findings with researchers in similar fields in other countries (19).

Who will have ownership of research data is an important question; whether it should be governments or the institutions and companies responsible for conducting the research. In the United States of America, it is noteworthy that the Food and Drug Administration has stopped companies from allowing individuals to access their own genetic information (19).

Gene sequencing and precision medicine generate huge amounts of personal data that require massive infrastructure for storage and further analysis, and create concerns for data security and privacy. It is possible that organizations involved in research and sponsors of trials could support the establishment of such infrastructure as part of a moral duty towards the host country. Such support could be compensated through tax exemptions for any agencies working in a particular country, such as multinational pharmaceutical companies (19).

Precision medicine could improve the cost-effectiveness of health care, as developing countries have scarce resources to meet the need for provision of health care to all. Pharmacogenomics research could result in substantial cost savings by enabling the introduction of drugs that are effective for particular targeted populations in developing countries.

Countries should consider how their citizens' personal information can be shared or disclosed among different parties, such as police officers and national security services. There is a need to prevent abuse of information for unintended purposes, such as screening potential partners, or racial discrimination based on genetics (19).

We do not know all the implications of precision medicine and the discussion is ongoing, although there are many benefits and threats to populations in LMICs.

One issue that arises when considering whether it is appropriate to conduct a specific study in a developing country is whether the intervention is likely to be affordable in that country if it is shown to be effective (19). This will often not be a straightforward issue. For example, there is a need for technology-driven tools that help integrate different healthcare facilities and communities in Africa, as well as investigate knowledge, attitudes and barriers surrounding precision medicine (20). The role, scope and perception of genetic testing have changed because of technological advances. Genomic testing has yielded advances in diagnosis and prediction of diseases; however, it has also brought an increased chance of uncertain or unexpected findings that may have an impact on several members of a person’s family. Previously, genetic testing was unable to provide results rapidly but its progressive development has resulted in the ability to achieve rapid accurate results that can aid appropriate decision-making (21).

This review highlights several issues to address when considering the way forward in trying to resolve the ethical dilemmas surrounding precision medicine research in humans. Some countries consider that such research is an infringement of national security and makes their populations vulnerable to harm. One possibility is to establish national research ethics committees to conduct proper reviews of research, provide clear regulations and determine the post-trial benefits. Effective ethical review of medical research is essential in developed and developing countries to ensure that unethical practice is not allowed, and to protect the population from exploitation. There is a need to ensure that research participants are accorded their rights, whether in the ownership of their samples or the right to know what type of genetic studies will be conducted using their samples. There must be binding agreements for clinical trial participants to have access to any drugs that prove effective during trials in which they participated.

Funding : None.

Competing interests : None declared.

Considérations éthiques relatives à la recherche en médecine de précision et aux tests génétiques dans les pays à revenu faible et intermédiaire

Contexte  : Le transfert de données génétiques dans le cadre d'essais cliniques multicentriques menés dans des pays à revenu faible et intermédiaire est courant et les participants à l'étude doivent en être informés conformément aux exigences éthiques.

Objectifs  : Analyser les pratiques éthiques relatives à la recherche en médecine de précision dans les pays à revenu faible et intermédiaire, et formuler des recommandations utiles.

Méthodes  : Nous avons mené une revue narrative de la littérature publiée et des cadres éthiques existants concernant la sous-représentation des pays à revenu faible et intermédiaire dans les bases de données génomiques, les discussions sur le consentement éclairé et la sécurité des données, ainsi que le potentiel d'exploitation et l'accès limité aux avantages de cette discipline.

Résultats  : Les résultats mettent en évidence la nécessité d'accroître la diversité des participants à la recherche, de définir des cadres éthiques solides et de promouvoir le partage des connaissances entre les pays développés et les pays en développement. Ils montrent que le renforcement des comités nationaux d'éthique de la recherche ainsi qu'une meilleure collaboration peuvent aider les pays à revenu faible et intermédiaire à relever des défis spécifiques et à exploiter le potentiel de la médecine de précision, tout en garantissant une conduite éthique et un accès équitable pour tous. Notre examen souligne l'importance de prendre en compte les considérations éthiques dans la recherche en médecine de précision afin de permettre à toutes les populations concernées de bénéficier de ses avantages et de promouvoir un avenir plus juste et plus équitable en matière de soins de santé.

Conclusion  : Il est nécessaire de veiller à ce que les participants à la recherche puissent jouir de leurs droits, qu'il s'agisse de la propriété de leurs échantillons ou du droit de savoir quels types d'études génétiques ont été menés sur ces derniers. La mise en place d'accords contraignants, autorisant les participants à des essais cliniques à avoir accès aux médicaments dont l'efficacité sera prouvée par lesdits essais auxquels ils ont pris part, est essentielle.

الاعتبارات الأخلاقية المتعلقة ببحوث طب الدقة والاختبارات الجينية في البلدان ذات الدخل المنخفض والمتوسط

محمد أشرف، سندس مبارك

الخلفية : يُعد نقل البيانات الجينية في إطار التجارب السريرية المتعددة المراكز التي تُجرى في البلدان ذات الدخل المنخفض والمتوسط أمرًا شائعًا، ويجب إبلاغ المشاركين في الدراسة به بوصفه جزءًا من المتطلبات الأخلاقية.

الأهداف : هدفت هذه الدراسة إلى تحليل الممارسات الأخلاقية في بحوث طب الدقة في البلدان ذات الدخل المنخفض والمتوسط وتقديم توصيات مفيدة.

طرق البحث : أجرينا استعراضًا سرديًّا للمؤلفات المنشورة والأطر الأخلاقية القائمة فيما يتعلق بنقص تمثيل البلدان ذات الدخل المنخفض والمتوسط في قواعد البيانات الجينومية، والمناقشات بشأن الموافقات المستنيرة وأمن البيانات، وكذلك إمكانية الاستغلال ومحدودية الحصول على الفوائد.

النتائج : تُبرِز نتائجُ الدراسة الحاجةَ إلى زيادة التنوع في المشاركة في البحوث، ووجود أُطر أخلاقية قوية، وتبادل المعلومات بين البلدان المتقدِّمة والنامية. وتُظهِر النتائجُ أن تقوية اللجان الوطنية لأخلاقيات البحوث وتشجيع التعاون من شأنهما أن يساعدا البلدان ذات الدخل المنخفض والمتوسط على التصدي للتحديات الفريدة، وتسخير إمكانات طب الدقة مع ضمان السلوك الأخلاقي والإتاحة المنصفة للجميع. ويؤكد الاستعراض الذي أجريناه أهمية الاعتبارات الأخلاقية في بحوث طب الدقة، لضمان وصول فوائدها إلى جميع الفئات السكانية المتضررة، وهو ما يعزز تحقيق مستقبل أكثر عدلًا وإنصافًا للرعاية الصحية.

الاستنتاجات : ثمة حاجة إلى ضمان منح المشاركين في البحوث حقوقهم، سواء في ملكية عيناتهم أو في معرفة نوع الدراسات الجينية التي أُجريت على عيناتهم. ومن المهم كذلك إبرام اتفاقات مُلزِمة تتيح للمشاركين في التجارب السريرية الحصول على الأدوية التي تثبت فعاليتها استنادًا إلى التجارب التي شاركوا فيها.

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Ethical aspects of human genome research in sports—a narrative review.

1. Introduction

3.1. evolution and athletic talent and identification and ethical challenges in sports genetics, 3.2. human rights and legal frameworks, 3.3. the role of international declarations: the human genome project and its ethical implications, 3.4. ethical considerations on genetic doping in sports, 3.5. ethical debate on performance enhancement, 3.6. ensuring informed consent and data protection, genetic data sharing (gds), 3.7. patentability and intellectual property issues, 3.8. ethical considerations surrounding the use of genetic technologies in sports, 3.9. human genome research in sports: implications of genetic advancements in athletics and the integrity of sports, 3.10. seeking new study areas not yet addressed, 4. conclusions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Bojarczuk, A. Ethical Aspects of Human Genome Research in Sports—A Narrative Review. Genes 2024 , 15 , 1216. https://doi.org/10.3390/genes15091216

Bojarczuk A. Ethical Aspects of Human Genome Research in Sports—A Narrative Review. Genes . 2024; 15(9):1216. https://doi.org/10.3390/genes15091216

Bojarczuk, Aleksandra. 2024. "Ethical Aspects of Human Genome Research in Sports—A Narrative Review" Genes 15, no. 9: 1216. https://doi.org/10.3390/genes15091216

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Diversity, Equity, and Inclusion in Clinical Research

• Meghan Hosely Marketing Content Manager;

Achieving diversity, equity, and inclusion (DEI) in clinical trials is crucial for producing comprehensive and effective medical research benefitting all communities. DEI ensures clinical research encompasses diverse populations, considering variations in gender, race, ethnicity, socioeconomic status, and more. This helps to generate inclusive data essential for regulatory review and developing treatments effective for everyone.

Importance of DEI in Clinical Trials

Clinical trials are a cornerstone of medical research, contributing to the development of new drugs and treatments. However, historical underrepresentation of marginalized communities has often led to incomplete or biased data. For example, treatments working well for one group may not be effective or could even be harmful to another group due to differences in genetics, lifestyle, or environment. This highlights the need for diverse participation in clinical trials to ensure all populations benefit from medical advancements.

The U.S. Food and Drug Administration (FDA) emphasizes the need for equal representation in clinical trials to generate useful and inclusive data. The agency’s draft guidance calls for Diversity Action Plans to ensure diverse participants are enrolled, which is critical for developing safe and effective drugs and medical devices for everyone.

The National Institute on Minority Health and Health Disparities emphasizes DEI in research goes beyond race and ethnicity , but should also face for the diverse lived experiences of different populations considering factors such as:

• Socioeconomic status
• Biological status
• Pregnancy status
• Unhealthy behaviors (such as substance use)
• Environmental conditions (such as pollution)
• Underlying medical conditions or comorbidities

Challenges to Achieving DEI in Clinical Research

Achieving DEI in clinical research is not without challenges. Some common barriers to diverse clinical trial enrollment include:

• Mistrust: Historical mistreatment by medical professionals, such as the Tuskegee Syphilis Study and the mishandling of genetic information from the Havasupai Tribe, has led to a deep mistrust of clinical trials among certain communities. Overcoming this requires significant education and outreach to build trust and inform people about the safety and importance of participating in clinical trials.
• Lack of awareness and education: Many potential participants may not understand what clinical trials entail, their purpose, or the protections in place to ensure safety. More educational efforts are needed to demystify important clinical research and encourage participation.
• Environmental barriers: Physical barriers such as distance from research sites, lack of transportation, and time constraints can prevent potential participants from enrolling in clinical trials. To address this, creating research sites within underserved communities or employing decentralized clinical trial models can help improve accessibility and encourage diverse participation.
• Community engagement: Building relationships with communities is crucial for understanding their unique needs and concerns. Engaging community leaders and providing transparency throughout the trial process can help foster trust and encourage participation.

Strategies for Promoting DEI in Clinical Trials

To address these challenges, several strategies can be employed:

• Community outreach and education: Building relationships with community leaders and organizations can help promote understanding and trust. This involves going beyond traditional healthcare settings and engaging in places like community centers, faith-based organizations, and local health fairs.
• Culturally competent communication: Effective communication tailored to different cultural and linguistic groups is essential for encouraging diverse participation. Ensuring clinical trial information is accessible and understandable can help break down enrollment barriers.
• Diverse research staff and investigators: Having a diverse team of researchers and investigators who reflect the communities they serve can help foster trust and increase enrollment from underrepresented groups. Potential participants are more likely to trust and engage with study staff who share similar backgrounds or experiences.
• Decentralized clinical trials: By employing decentralized models, which can include home visits, remote monitoring, or using local healthcare facilities, clinical trials can become more accessible to participants who may face geographic or logistical barriers.

Regulatory and Ethical Considerations

To ensure ethical standards are upheld, regulatory frameworks such as the Belmont Report and the Declaration of Helsinki guide the ethical conduct of clinical research. These guidelines stress the importance of informed consent, respect for persons, and equitable participant selection. Regulatory bodies like institutional review boards (IRBs) are crucial for reviewing and approving research studies, ensuring they meet ethical standards and protect participant rights.

Other guidelines include:

Promoting diversity, equity, and inclusion in clinical research is essential for developing safe, effective, and equitable treatments. Overcoming historical mistrust, improving accessibility, and engaging communities are key steps toward achieving this goal. By prioritizing DEI, clinical trials can provide more comprehensive and relevant data designed to benefits all individuals, ensuring the medical advancements of tomorrow are built on a foundation of inclusivity and fairness.

Tagged in: DEI , diversity

Meghan Hosely creates educational content for Advarra, such as blogs, eBooks, white papers, and more.

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Research Agenda of Ethical Recommender Systems based on Explainable AI

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Ethical Considerations

• First Online: 24 March 2020

Cite this chapter

• Hesta Friedrich-Nel 2 &
• Aarthi Ramlaul 3  

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Ethical principles and considerations that need to be made when undertaking research studies are covered in this chapter. A brief history and timeline of ethics are provided. There is clarification of which studies require formal ethical review and approval as well as the need for rigour in research work underpinned by professional attributes and expectations as healthcare professionals. Areas and topics, which occasionally cause issues in relation to applications and review for ethics/research and development (R&D) approval, are highlighted and presented using a glossary style to enable readers to utilise this section as a quick answer to a query. A panacea for ethical review is not presented as the focus is an overview of some areas where problems may arise. Common errors made on ethics application forms are discussed. Good practice tips on dealing with reviewer feedback are provided. For ease of writing the term ‘participant’ is used to cover all individuals or groups (including patients) who act as subjects, respondents, interviewees, informants, within any type of research design, whether it be quantitative or qualitative in nature.

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Department of Clinical Sciences, Central University of Technology, Bloemfontein, South Africa

Hesta Friedrich-Nel

Diagnostic Radiography and Imaging, School of Health and Social Work, University of Hertfordshire, Hatfield, Hertfordshire, UK

Aarthi Ramlaul

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Friedrich-Nel, H., Ramlaul, A. (2020). Ethical Considerations. In: Ramlaul, A. (eds) Medical Imaging and Radiotherapy Research: Skills and Strategies. Springer, Cham. https://doi.org/10.1007/978-3-030-37944-5_6

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DOI : https://doi.org/10.1007/978-3-030-37944-5_6

Published : 24 March 2020

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