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Ethical Considerations – Types, Examples and Writing Guide

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Ethical Considerations

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.

About the author

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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Ethical considerations in research: Best practices and examples

October 2023

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.


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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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 .


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


  • 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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Book cover

The Application of Content Analysis in Nursing Science Research pp 49–69 Cite as

Qualitative Research: Ethical Considerations

  • Anna-Maija Pietilä 4 ,
  • Sanna-Maria Nurmi 4 ,
  • Arja Halkoaho 4 , 5 &
  • Helvi Kyngäs 6  
  • First Online: 01 November 2019

9485 Accesses

7 Citations

2 Altmetric

Ethical aspects include perspectives of subject protection and conducting research based on ethical standards. This chapter aims to highlight the ethical aspects of qualitative research, with particular emphasis on content analysis. The chapter begins by presenting four ethical principles—autonomy, non-maleficence, beneficence, and justice—that were first brought to attention by Beauchamp and Childress (Principles of biomedical ethics. Oxford University Press, New York, 2013). These principles form the basis for the protection of the subject in qualitative research. Next, Shamoon and Resnik’s (Responsible conduct of research. Oxford University Press, New York, 2015) principles for responsible research conduct are described. The ethical framework presented by Emanuel et al. (J Infect Dis 189:930–937, 2000; JAMA 283:2701–2711, 2004), which includes eight ethical requirements, is then introduced, and later used to explore the ethical aspects of content analysis based on an example of qualitative research. The chapter concludes by discussing several challenges that researchers may face when applying content analysis to qualitative research.

  • Research ethics
  • Ethical principles
  • Ethical framework
  • Qualitative research
  • Content analysis

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Pietilä, AM., Nurmi, SM., Halkoaho, A., Kyngäs, H. (2020). Qualitative Research: Ethical Considerations. In: Kyngäs, H., Mikkonen, K., Kääriäinen, M. (eds) The Application of Content Analysis in Nursing Science Research. Springer, Cham. https://doi.org/10.1007/978-3-030-30199-6_6

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What Are the Ethical Considerations in Research Design?

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When I began my work on the thesis I was always focused on my research. However, once I began to make my way through research, I realized that research ethics is a core aspect of the research work and the foundation of research design.

Research ethics play a crucial role in ensuring the responsible conduct of research. Here are some key reasons why research ethics matter:

Why Research Ethics Matter

Let us look into some of the major ethical considerations in research design.

Ethical Issues in Research

There are many organizations, like the Committee on Publication Ethics , dedicated to promoting ethics in scientific research. These organizations agree that ethics is not an afterthought or side note to the research study. It is an integral aspect of research that needs to remain at the forefront of our work.

The research design must address specific research questions. Hence, the conclusions of the study must correlate to the questions posed and the results. Also, research ethics demands that the methods used must relate specifically to the research questions.

Voluntary Participation and Consent

An individual should at no point feel any coercion to participate in a study. This includes any type of persuasion or deception in attempting to gain an individual’s trust.

Informed consent states that an individual must give their explicit consent to participate in the study. You can think of consent form as an agreement of trust between the researcher and the participants.

Sampling is the first step in research design . You will need to explain why you want a particular group of participants. You will have to explain why you left out certain people or groups. In addition, if your sample includes children or special needs individuals, you will have additional requirements to address like parental permission.


The third ethics principle of the Economic and Social Research Council (ESRC) states that: “The confidentiality of the information supplied by research subjects and the anonymity of respondents must be respected.” However, sometimes confidentiality is limited. For example, if a participant is at risk of harm, we must protect them. This might require releasing confidential information.

Risk of Harm

We should do everything in our power to protect study participants. For this, we should focus on the risk to benefit ratio. If possible risks outweigh the benefits, then we should abandon or redesign the study. Risk of harm also requires us to measure the risk to benefit ratio as the study progresses.

Research Methods

We know there are numerous research methods. However, when it comes to ethical considerations, some key questions can help us find the right approach for our studies.

i. Which methods most effectively fit the aims of your research?

ii. What are the strengths and restrictions of a particular method?

iii. Are there potential risks when using a particular research method?

For more guidance, you can refer to the ESRC Framework for Research Ethics .

Ethical issues in research can arise at various stages of the research process and involve different aspects of the study. Here are some common examples of ethical issues in research:

Examples of Ethical Issues in Research

Institutional Review Boards

The importance of ethics in research cannot be understated. Following ethical guidelines will ensure your study’s validity and promote its contribution to scientific study. On a personal level, you will strengthen your research and increase your opportunities to gain funding.

To address the need for ethical considerations, most institutions have their own Institutional Review Board (IRB). An IRB secures the safety of human participants and prevents violation of human rights. It reviews the research aims and methodologies to ensure ethical practices are followed. If a research design does not follow the set ethical guidelines, then the  researcher will have to amend their study.

Applying for Ethical Approval

Applications for ethical approval will differ across institutions. Regardless, they focus on the benefits of your research and the risk to benefit ratio concerning participants. Therefore, you need to effectively address both in order to get ethical clearence.


It is vital that you make it clear that individuals are provided with sufficient information in order to make an informed decision on their participation. In addition, you need to demonstrate that the ethical issues of consent, risk of harm, and confidentiality are clearly defined.

Benefits of the Study

You need to prove to the panel that your work is essential and will yield results that contribute to the scientific community. For this, you should demonstrate the following:

i. The conduct of research guarantees the quality and integrity of results.

ii. The research will be properly distributed.

iii. The aims of the research are clear and the methodology is appropriate.

Integrity and transparency are vital in the research. Ethics committees expect you to share any actual or potential conflicts of interest that could affect your work. In addition, you have to be honest and transparent throughout the approval process and the research process.

The Dangers of Unethical Practices

There is a reason to  follow ethical guidelines. Without these guidelines, our research will suffer. Moreover, more importantly, people could suffer.

The following are just two examples of infamous cases of unethical research practices that demonstrate the importance of adhering to ethical standards:

  • The Stanford Prison Experiment (1971) aimed to investigate the psychological effects of power using the relationship between prisoners and prison officers. Those assigned the role of “prison officers” embraced measures that exposed “prisoners” to psychological and physical harm. In this case, there was voluntary participation. However, there was disregard for  welfare of the participants.
  • Recently, Chinese scientist He Jiankui announced his work on genetically edited babies . Over 100 Chinese scientists denounced this research, calling it “crazy” and “shocking and unacceptable.” This research shows a troubling attitude of “do first, debate later” and a disregard for the ethical concerns of manipulating the human body Wang Yuedan, a professor of immunology at Peking University, calls this “an ethics disaster for the world” and demands strict punishments for this type of ethics violation.

What are your experiences with research ethics? How have you developed an ethical approach to research design? Please share your thoughts with us in the comments section below.

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Ethical considerations associated with Qualitative Research methods


This high-level guidance has been developed by the UK Statistics Authority’s Centre for Applied Data Ethics (CADE), and the UK Government Data Quality Hub (DQHub), based at the Office for National Statistics (ONS). The guidance can be used as a practical resource to help researchers identify different ethical issues when conducting qualitative research.  

This guidance is not exhaustive but aims to support researchers navigating the ethical issues surrounding qualitative research projects (particularly in relation to primary data collection). It brings together existing literature on qualitative research methods and their ethical concerns. Links to further resources are provided if you would like to read about aspects in more detail.  

The guidance has been created for researchers using qualitative methods within the ONS . However, the ethical considerations discussed, and the mitigations for these, can be more widely applied to all types of qualitative research.  

The guidance is divided into several parts.    

  • An introduction to qualitative research and why ethics matters in this space.   
  • An overview of some of the ethical considerations associated with qualitative research methods, and some potential mitigations for these issues. This includes an overview of some of the qualitative methods used within the ONS.  
  • An ethics checklist which summarises the main points covered in this guidance.    
  • A list of helpful links to further resources.   


Ethical Considerations

Ethical Considerations can be specified as one of the most important parts of the research. Dissertations may even be doomed to failure if this part is missing.

According to Bryman and Bell (2007) [1] the following ten points represent the most important principles related to ethical considerations in dissertations:

  • Research participants should not be subjected to harm in any ways whatsoever.
  • Respect for the dignity of research participants should be prioritised.
  • Full consent should be obtained from the participants prior to the study.
  • The protection of the privacy of research participants has to be ensured.
  • Adequate level of confidentiality of the research data should be ensured.
  • Anonymity of individuals and organisations participating in the research has to be ensured.
  • Any deception or exaggeration about the aims and objectives of the research must be avoided.
  • Affiliations in any forms, sources of funding, as well as any possible conflicts of interests have to be declared.
  • Any type of communication in relation to the research should be done with honesty and transparency.
  • Any type of misleading information, as well as representation of primary data findings in a biased way must be avoided.

In order to address ethical considerations aspect of your dissertation in an effective manner, you will need to expand discussions of each of the following points to at least one paragraph:

1. Voluntary participation of respondents in the research is important. Moreover, participants have rights to withdraw from the study at any stage if they wish to do so.

2. Respondents should participate on the basis of informed consent. The principle of informed consent involves researchers providing sufficient information and assurances about taking part to allow individuals to understand the implications of participation and to reach a fully informed, considered and freely given decision about whether or not to do so, without the exercise of any pressure or coercion. [2]

3. The use of offensive, discriminatory, or other unacceptable language needs to be avoided in the formulation of Questionnaire/Interview/Focus group questions.

4. Privacy and anonymity or respondents is of a paramount importance.

5. Acknowledgement of works of other authors used in any part of the dissertation with the use of Harvard/APA/Vancouver referencing system according to the Dissertation Handbook

6. Maintenance of the highest level of objectivity in discussions and analyses throughout the research

7. Adherence to Data Protection Act (1998) if you are studying in the UK

In studies that do not involve primary data collection, on the other hand, ethical issues are going to be limited to the points d) and e) above.

Most universities have their own Code of Ethical Practice. It is critically important for you to thoroughly adhere to this code in every aspect of your research and declare your adherence in ethical considerations part of your dissertation.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  offers practical assistance to complete a dissertation with minimum or no stress. The e-book covers all stages of writing a dissertation starting from the selection to the research area to submitting the completed version of the work within the deadline. John Dudovskiy

Ethical Considerations in dissertation

[1] Bryman, A. &  Bell, E. (2007) “Business Research Methods”, 2nd edition. Oxford University Press.

[2] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6th edition, Pearson Education Limited.

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  • Indian J Anaesth
  • v.60(9); 2016 Sep

Legal and ethical issues in research

Camille yip.

1 Department of Women's Anaesthesia, KK Women's and Children's Hospital, Bukit Timah, Singapore

Nian-Lin Reena Han

2 Division of Clinical Support Services, KK Women's and Children's Hospital, Bukit Timah, Singapore

Ban Leong Sng

3 Anesthesiology and Perioperative Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore

Legal and ethical issues form an important component of modern research, related to the subject and researcher. This article seeks to briefly review the various international guidelines and regulations that exist on issues related to informed consent, confidentiality, providing incentives and various forms of research misconduct. Relevant original publications (The Declaration of Helsinki, Belmont Report, Council for International Organisations of Medical Sciences/World Health Organisation International Guidelines for Biomedical Research Involving Human Subjects, World Association of Medical Editors Recommendations on Publication Ethics Policies, International Committee of Medical Journal Editors, CoSE White Paper, International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use-Good Clinical Practice) form the literature that are relevant to the ethical and legal aspects of conducting research that researchers should abide by when conducting translational and clinical research. Researchers should note the major international guidelines and regional differences in legislation. Hence, specific ethical advice should be sought at local Ethics Review Committees.


The ethical and legal issues relating to the conduct of clinical research involving human participants had raised the concerns of policy makers, lawyers, scientists and clinicians for many years. The Declaration of Helsinki established ethical principles applied to clinical research involving human participants. The purpose of a clinical research is to systematically collect and analyse data from which conclusions are drawn, that may be generalisable, so as to improve the clinical practice and benefit patients in future. Therefore, it is important to be familiar with Good Clinical Practice (GCP), an international quality standard that is provided by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH),[ 1 ] or the local version, GCP of the Central Drugs Standard Control Organization (India's equivalent of US Food and Drug Administration)[ 2 ] and local regulatory policy to ensure that the research is conducted both ethically and legally. In this article, we will briefly review the legal and ethical issues pertaining to recruitment of human subjects, basic principles of informed consent and precautions to be taken during data and clinical research publications. Some of the core principles of GCP in research include defining responsibilities of sponsors, investigators, consent process monitoring and auditing procedures and protection of human subjects.[ 3 ]


The main role of human participants in research is to serve as sources of data. Researchers have a duty to ‘protect the life, health, dignity, integrity, right to self-determination, privacy and confidentiality of personal information of research subjects’.[ 4 ] The Belmont Report also provides an analytical framework for evaluating research using three ethical principles:[ 5 ]

  • Respect for persons – the requirement to acknowledge autonomy and protect those with diminished autonomy
  • Beneficence – first do no harm, maximise possible benefits and minimise possible harms
  • Justice – on individual and societal level.

Mistreatment of research subjects is considered research misconduct (no ethical review approval, failure to follow approved protocol, absent or inadequate informed consent, exposure of subjects to physical or psychological harm, exposure of subjects to harm due to unacceptable research practices or failure to maintain confidentiality).[ 6 ] There is also scientific misconduct involving fraud and deception.

Consent, possibility of causing harm

Based on ICH definition, ‘informed consent is a process by which a subject voluntarily confirms his or her willingness to participate in a particular trial, after having been informed of all aspects of the trial that are relevant to the subject's decision to participate’. As for a standard (therapeutic) intervention that carries certain risks, informed consent – that is voluntary, given freely and adequately informed – must be sought from participants. However, due to the research-centred, rather than patient-centred primary purpose, additional relevant information must be provided in clinical trials or research studies in informed consent form. The essential components of informed consent are listed in Table 1 [Adapted from ICH Harmonised Tripartite Guideline, Guideline for Good Clinical Practice E6(R1)].[ 1 ] This information should be delivered in the language and method that individual potential subjects can understand,[ 4 ] commonly in the form of a printed Participant Information Sheet. Informed consent is documented by means of written, signed and dated informed consent form.[ 1 ] The potential subjects must be informed of the right to refuse to participate or withdraw consent to participate at any time without reprisal and without affecting the patient–physician relationship. There are also general principles regarding risk assessment, scientific requirements, research protocols and registration, function of ethics committees, use of placebo, post-trial provisions and research publication.[ 4 ]

Essential components of an informed consent

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Special populations

Informed consent may be sought from a legally authorised representative if a potential research subject is incapable of giving informed consent[ 4 ] (children, intellectual impairment). The involvement of such populations must fulfil the requirement that they stand to benefit from the research outcome.[ 4 ] The ‘legally authorised representative’ may be a spouse, close relative, parent, power of attorney or legally appointed guardian. The hierarchy of priority of the representative may be different between different countries and different regions within the same country; hence, local guidelines should be consulted.

Special case: Emergency research

Emergency research studies occur where potential subjects are incapacitated and unable to give informed consent (acute head trauma, cardiac arrest). The Council for International Organisations of Medical Sciences/World Health Organisation guidelines and Declaration of Helsinki make exceptions to the requirement for informed consent in these situations.[ 4 , 7 ] There are minor variations in laws governing the extent to which the exceptions apply.[ 8 ]

Reasonable efforts should have been made to find a legal authority to consent. If there is not enough time, an ‘exception to informed consent’ may allow the subject to be enrolled with prior approval of an ethical committee.[ 7 ] Researchers must obtain deferred informed consent as soon as possible from the subject (when regains capacity), or their legally authorised representative, for continued participation.[ 4 , 7 ]

Collecting patient information and sensitive personal information, confidentiality maintenance

The Health Insurance Portability and Accountability Act has requirements for informed consent disclosure and standards for electronic exchange, privacy and information security. In the UK, generic legislation is found in the Data Protection Act.[ 9 ]

The International Committee of Medical Journal Editors (ICMJE) recommendations suggest that authors must ensure that non-essential identifying information (names, initials, hospital record numbers) are omitted during data collection and storage wherever possible. Where identifying information is essential for scientific purposes (clinical photographs), written informed consent must be obtained and the patient must be shown the manuscript before publication. Subjects should also be informed if any potential identifiable material might be available through media access.

Providing incentives

Cash or other benefits ‘in-kind’ (financial, medical, educational, community benefits) should be made known to subjects when obtaining informed consent without emphasising too much on it.[ 7 ] Benefits may serve as appreciation or compensation for time and effort but should not result in the inducement to participation.[ 10 ] The amount and nature of remuneration should be compared to norms, cultural traditions and are subjected to the Ethical Committee Review.[ 7 ]


Legal issues pertaining to regulatory bodies.

Various regulatory bodies have been constituted to uphold the safety of subjects involved in research. It is imperative to obtain approval from the appropriate regulatory authorities before proceeding to any research. The constitution and the types of these bodies vary nation-wise. The researchers are expected to be aware of these authorities and the list of various bodies pertinent to India are listed in the article “Research methodology II” of this issue.

Avoiding bias, inappropriate research methodology, incorrect reporting and inappropriate use of information

Good, well-designed studies advance medical science development. Poorly conducted studies violate the principle of justice, as there are time and resources wastage for research sponsors, researchers and subjects, and undermine the societal trust on scientific enquiry.[ 11 ] The Guidelines for GCP is an international ethical and scientific quality standard for designing, conducting, recording and reporting trials.[ 1 ]

Fraud in research and publication

De novo data invention (fabrication) and manipulation of data (falsification)[ 6 ] constitute serious scientific misconduct. The true prevalence of scientific fraud is difficult to measure (2%–14%).[ 12 ]

Plagiarism and its checking

Plagiarism is the use of others' published and unpublished ideas or intellectual property without attribution or permission and presenting them as new and original rather than derived from an existing source.[ 13 ] Tools such as similarity check[ 14 ] are available to aid researchers detect similarities between manuscripts, and such checks should be done before submission.[ 15 ]

Overlapping publications

Duplicate publications violate international copyright laws and waste valuable resources.[ 16 , 17 ] Such publications can distort evidence-based medicine by double-counting of data when inadvertently included in meta-analyses.[ 16 ] This practice could artificially enlarge one's scientific work, distorting apparent productivity and may give an undue advantage when competing for research funding or career advancement.[ 17 ] Examples of these practices include:

Duplicate publication, redundant publication

Publication of a paper that overlaps substantially with one already published, without reference to the previous publication.[ 11 ]

Salami publication

Slicing of data from a single research process into different pieces creating individual manuscripts from each piece to artificially increase the publication volume.[ 16 ]

Such misconduct may lead to retraction of articles. Transparent disclosure is important when submitting papers to journals to declare if the manuscript or related material has been published or submitted elsewhere, so that the editor can decide how to handle the submission or to seek further clarification. Further information on acceptable secondary publication can be found in the ICMJE ‘Recommendations for the Conduct, Reporting, Editing, and Publishing of Scholarly Work in Medical Journals’.

Usually, sponsors and authors are required to sign over certain publication rights to the journal through copyright transfer or a licensing agreement; thereafter, authors should obtain written permission from the journal/publisher if they wish to reuse the published material elsewhere.[ 6 ]

Authorship and its various associations

The ICMJE recommendation lists four criteria of authorship:

  • Substantial contributions to the conception of design of the work, or the acquisition, analysis or interpretation of data for the work
  • Drafting the work or revising it critically for important intellectual content
  • Final approval of the version to be published
  • Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Authors and researchers have an ethical obligation to ensure the accuracy, publication and dissemination of the result of research,[ 4 ] as well as disclosing to publishers relevant corrections, retractions and errata, to protect scientific integrity of published evidence. Every research study involving human subjects must be registered in a publicly accessible database (e.g., ANZCTR [Australia and NZ], ClinicalTrials.gov [US and non-US], CTRI [India]) and the results made publicly available.[ 4 ] Sponsors of clinical trials must allow all study investigators and manuscript authors access to the full study data set and the right to use all study data for publication.[ 5 ] Source documents (containing trial data) and clinical study report (results and interpretation of trial) form part of the essential documentation that must be retained for a length of time prescribed by the applicable local legislation.[ 1 ] The ICMJE is currently proposing a requirement of authors to share with others de-identified individual patient data underlying the results presented in articles published in member journals.[ 18 ]

Those who have contributed to the work but do not meet all four criteria should be acknowledged; some of these activities include provision of administrative support, writing assistance and proofreading. They should have their written permission sought for their names to be published and disclose any potential conflicts of interest.[ 6 ] The Council of Scientific Editors has identified several inappropriate types of authorship, such as guest authorship, honorary or gift authorship and ghost authorship.[ 6 ] Various interventions should be put in place to prevent such fraudulent practices in research.[ 19 ] The list of essential documents for the conduct of a clinical trial is included in other articles of the same issue.

The recent increase in research activities has led to concerns regarding ethical and legal issues. Various guidelines have been formulated by organisations and authorities, which serve as a guide to promote integrity, compliance and ethical standards in the conduct of research. Fraud in research undermines the quality of establishing evidence-based medicine, and interventions should be put in place to prevent such practices. A general overview of ethical and legal principles will enable research to be conducted in accordance with the best practices.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

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What is Ethical Consideration in Research? (The Complete Guide)

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by  Antony W

July 7, 2022

ethical considerations in research

What’s the first thing that comes to your mind when you read or hear someone mention the word ethics ? Some of us think of rules that help humanity to distinguish between right and wrong. Some link the term to professional conduct or religious creed such as the Ten Commandments.

When it comes to research, though, we need to think of ethical considerations as being more than just norms of conducts that differentiate between what’s acceptable and what’s not.

In research, ethical consideration is an important principle to which researchers must adhere so as to maintain scientific integrity, uphold research validity, and protect the rights of participants in research study. The principle not only ensures that participants take part in the study voluntarily, but also guarantees they are informed and safe for the research subject.

In this guide, we’ll dive deeper into ethical considerations in research to give you more insight into the topic.

Really our goal here is to help you understand the significance of pursuing information with ethical procedures that don’t pose any kind of threat to the target participants.

Related : How to Write a Research Paper

The Ethical Considerations You Must Make In Research

There are a number of ethical issues that you have to consider before you begin your research design. Check the table below for a summary of these issues:

It’s important that you observe the above ethical consideration because they help a great deal to ensure the authenticity of your research methods and the correctness and accuracy of the information you get from your participants in relation to your research study. 

Also Read: Can You Put Pictures in Research Paper?

Why Are Ethical Considerations in Research So Important?

Ethical considerations are important in research because they ensure participants take part in a research study voluntarily.

It means that researchers don’t have the right to identify participants forcefully and subject them to pressure to participate in the study. Ethical considerations also ensure that participants are not only educated about the research but also safe for the research subjects.

Here are at least 10 ethical considerations that you must uphold when conducting your research:

  • Researchers should not under any circumstance subject their participants to any kind of harm in any way whatsoever
  • One has to avoid misleading information and keep away from representing primary findings in a biased way
  • Researchers have the mandatory obligation to respect and uphold the dignity of the research participants
  • One must not involve participant in a research study without their full consent prior to the study
  • You need to ensure the full protection of the research participants in your study
  • There should be honesty and transparency in any type of communication in relation to the study in question
  • You have to declare affiliations in all forms. Also, you should be clear about any or all possible conflicts of interest
  • A researcher must avoid any form of deception or exaggeration about the aims and objectives of their research
  • You need to ensure a higher level of confidentiality of the research data
  • As a researcher, it’s your responsibility to ensure the  anonymity of the research participants

It’s important that you observe ethical consideration when conducting your research. Otherwise, it becomes difficult to uphold integrity in scientific research. More often than not, researchers who defy ethics end up with less credible research their methods of data collection are morally questionable.

Frequently Asked Questions

1. what is the meaning of research misconduct.

Research misconduct is a situation where a researcher makes up, manipulates, falsifies, or misrepresents data and results in their research report. In academic writing, research misconduct is a clear form of academic fraud.

Research misconduct isn’t accidental. Researches often commit them intentionally in violation of the ethical considerations. So rather than looking at it as a point of disagreement or a small mistake, institutions treat research misconduct as serious ethical failure that should attract severe consequences.

2. Why do ethical considerations in research matter?

Researchers need to take ethical considerations seriously so as to uphold human rights and dignity, and scientific integrity. Such considerations are also significant because they promote voluntary collaboration between the science community and the society. It’s a means by which those involved in the study can be sure of their safety as they volunteer in the research process.

3. Anonymity vs confidentiality: what’s the difference?

Anonymity and confidentially are important ethical considerations that you need to uphold when doing your research.

  • Anonymity : you don’t know who the participants in your study are. You guarantee the participants that their identity will remain unknown by not collecting personal information such as names, email addresses, photo, and phone numbers.
  • Confidentiality : You know who the participants in the study are, but you’ve removed their identity from your research report.

In the case where you must maintain anonymity or keep the identity of your participants confidential, it’s important to refer to them as groups rather than individual participants.

About the author 

Antony W is a professional writer and coach at Help for Assessment. He spends countless hours every day researching and writing great content filled with expert advice on how to write engaging essays, research papers, and assignments.

  • Open access
  • Published: 02 January 2024

Reflections on the process, challenges, and lessons learned conducting remote qualitative research on Violence against women during COVID-19 pandemic lockdown in South Africa

  • Pinky Mahlangu 1 , 2 , 3 ,
  • Mercilene Tanyaradzwa Machisa 1 , 2 ,
  • Rachel Jewkes 1 , 2 ,
  • Andrew Gibbs 4 , 5 , 6 ,
  • Nwabisa Shai 1 , 2 &
  • Yandisa Sikweyiya 1 , 2  

BMC Public Health volume  24 , Article number:  33 ( 2024 ) Cite this article

Metrics details

Violence against women (VAW) research is a sensitive topic, which has been conducted mainly using face-to-face methods. The COVID-19 pandemic lockdown and restrictions on movement presented an opportunity to conduct VAW research using remote methods. We discuss how we adapted methods, reflect on lessons learned, and make recommendations highlighting key considerations when conducting remote research on a sensitive topic of VAW.

We designed and conducted an exploratory qualitative study using remote methods with 18 men and 19 women, aged 18 years and older, who lived with their partner or spouse during lockdown in South Africa. The aim of the study was to explore experiences of COVID-19 lockdown, and its link to women and children’s experiences of violence in the homes. Data presented in this paper draws from researchers’ reflections drawn from debriefing sessions during the research process, and from participants’ interview transcripts.

Remote recruitment of participants took longer than anticipated, and we had to re-advertise the study. We could not ensure safety and privacy during interviews. Regardless of all the safety and privacy measures we put in place during the research process, some participants had an adult person present in the room during interviews, and the researchers had no control over interruptions. Rapport was difficult to establish without an in-person connection, which limited disclosure about violence experience (amongst women) and perpetration (amongst men).


Given the methodological and ethical challenges which limited disclosure of VAW remotely, we conclude that telephone interviews used in our study impacted on the quality of study data. Therefore, we do not recommend VAW research to be conducted remotely, unless it is essential and participants are already known to the interviewer and trust has been established.

Peer Review reports


Violence against Women (VAW) is a sensitive research topic requiring a skilled interviewer to establish rapport between researcher and participants, as well as ensuring confidentiality, privacy and safety [ 1 ]. Due to the importance of these conditions, the field has favoured conducting VAW research using in-person data collection methods to ensure that the research adheres to the required ethical and methodological guidance [ 1 ]. However, the COVID-19 pandemic posed challenges for in-person data collection due to the enforced lockdown. On the night of the 23rd of March 2020, the South African government announced a 21-day national lockdown to try and contain the corona virus outbreak as the number of confirmed positive cases jumped from 128 to 402. The 21-day national lockdown, described as alert level 5 started on 26 March to 16 April 2020, further extended until 30 April, thereafter followed by other subsequent alert levels characterized by a gradual easing of restrictions. During Alert level 5, physical distancing measures were implemented including restriction of movement of persons and goods, people could only go outside of their homes to seek or provide essential services and to get food. Most workplaces and schools were closed, leisure and social activities were restricted, and all interprovincial and international travel was banned [ 2 ]. The lockdown had negative socio-economic impacts on families and exacerbated some of the known drivers of domestic violence, including loss of livelihood, food insecurity and increased stress [ 3 ]. As families spent more time at home than usual, there were emerging reports based on police data and data from call centres in some countries suggesting increased violence against women and children during COVID-19 lockdown [ 4 , 5 ].

Against this background, primary research was needed to understand the impact of the COVID-19 pandemic on families during lockdown. Qualitative research was important to capture the lived experiences and meanings of COVID-19 pandemic and lockdown for families [ 6 , 7 ]. Conducting VAW research during COVID-19 was essential to inform violence prevention and response interventions at the time, and for future pandemic preparedness [ 8 , 9 ]. Asking women to share their experiences during lockdown was crucial in order to gain insights and inform design of responsive policies, services, and programmes [ 9 ]. The lockdown and physical distancing measures to control the spread of the virus meant that researchers could not access participants and conduct research in-person. The pandemic and lockdown presented researchers with an opportunity to adapt and use remote methods to conduct qualitative research, while adhering to rigorous ethical guidelines for conducting health research. Adaptation of methods from in-person to remote methods needed to be conducted carefully, especially amongst those working on sensitive topics such as violence against women (VAW), where trust between researchers and participant is crucial to enable disclosure. While we know much about use of conversational face- to-face methods in conducting research on VAW, the use of remote methods to conduct violence research is an emerging area [ 9 ]. At the time when research was conducted there were guidelines on how to conduct clinical trials during lockdown [ 10 , 11 ], but there was limited information on how to conduct qualitative research [ 12 , 13 ]. The lockdown thus required innovation and adaptation of the design and conduct of qualitative research using remote methods [ 14 ].

The literature examining whether, and how VAW research can be safely conducted remotely has started to emerge more recently [ 8 , 9 , 15 ], mainly from research in high income countries [ 15 , 16 ]. This paper aims to contribute to the evidence drawing from our experience of conducting remote qualitative research with men and women on intimate partner violence during lockdown in South Africa. We were interested to understand whether, and how the lockdown impacted or was linked to women and children’s experiences of violence in the homes in South Africa. The findings of the study are published elsewhere [ 3 ]. In this paper, we discuss how we adapted methods in order conduct VAW research remotely during COVID-19 lockdown, and reflect on ethical and methodological challenges we experienced while conducting VAW research using remote methods to recruit participants, collect data, and disburse reimbursements for time. We further make recommendations and highlight key considerations for conducting remote research on sensitive topics. The framework we use to structure the findings is the research process: from recruitment of participants, getting informed consent, and data collection. The paper contributes to the growing literature on use of remote methods on sensitive research topics in public health.

Study design and site

The study was conducted amongst 18 men and 19 women, aged 18 years and older, who lived with their partner or spouse during lockdown, in Gauteng province - one of the nine provinces in South Africa, which had the highest number of COVID-19 cases during the pandemic. Gauteng is the smallest of the South Africa’s nine provinces, but an urban and economic hub of the country which consists of cities including Johannesburg, Tshwane, Ekurhuleni and other surrounding metropolitan areas [ 17 ].


We developed and posted the study advert inviting anyone who was eligible to participate on the South African Medical Research Council’s (SAMRC’s) Facebook page, and shared it on personal Facebook accounts of the study team. The advert was also shared with social networks via WhatsApp by the research team. We encouraged social networks to widely share the advert with their networks. The study advert invited participants to share their experiences of the COVID-19 pandemic and lockdown. It had an email address and a cellphone number, which prospective participants used to contact the researchers to indicate interest to participate in the study. After receiving a message from participants indicating interest to participate, the study team would make initial contact with prospective participants using voice call. The initial call was to explain the objectives of the study, data collection procedures, potential risks, and benefits of participation, and to screen participants for eligibility. Furthermore, the importance of privacy and safety when conducting the interview was explained to participants, those who indicated that they had a private space and time to conduct the interview were included in the study.

To be eligible to participate in the study one had to be a man or woman, 18 years and older, living in Gauteng for an uninterrupted period between February and July 2020 during lockdown, living with a spouse and/or child(ren). In addition, we asked participants to indicate their income bracket, and used Statistics South Africa annual household income classification to categorize participants into low income, or middle and high income groups [ 18 ].

Ethical considerations

Ethics approval to conduct the study was granted by the SAMRC Human Research Ethics Committee (EC008-5/2020), and the research adhered to the WHO’s ethical standards for conducting VAW research [ 1 ]. Amongst others, there were four key ethical considerations we complied with when conducting the research remotely: we emphasized obtaining informed consent, the importance of privacy and safety during interviews, ensuring that the telephone interviews were conducted by experienced researchers with skills on conducting VAW research, and having measures to refer those who reported experiences of gender-based violence (GBV) to services. Whilst the WHO Guidelines on Ethical and Safety Recommendations for Research on Domestic Violence Against Women (2001) were useful to inform how we designed and conducted the research, they were limited in that they were developed to guide VAW research using face-to-face survey methods. Thus, we needed to adapt some of the methods to be suitable for conducting VAW research remotely. The Table  1 describes these adaptations.

Participants were given an opportunity to ask any questions and thereafter asked to provide verbal and written informed consent using WhatsApp, phone text or email. A consent form was sent to participants on the platform they selected for communication, most opted for WhatsApp, but a few preferred an email. The consent form was in English, had two brief questions, which had responses “yes and no”, asking participants “Do you agree to participate in the study?” and “Do you agree for the telephone interview to be audio recorded, and data to be anonymously used for the purpose of the study?”. Written consent received from participants was transferred to an email, then downloaded and safely stored on a password protected computer. The initial call would end with setting-up an appointment for the interview on the day and time suitable to participants, when they will have privacy to take the call.

Remote data collection process

Data was collected by some members of the research team, who are co-authors of the paper. The research team has extensive experience in conducting in-depth interviews (IDIs) on gender-based violence in South Africa and other settings. We conducted in-depth telephone interviews (IDTIs) of between 35 and 60 min, with 37 participants (18 men and19 women). The telephone interviews were conducted in order to comply with the COVID-19 social distancing measures to protect both the researchers and the participants. The interviews were conducted using a semi-structured interview guide with open-ended questions, and the interviewers were matched by gender and in the language preferred by the participants. Most of the interviews were conducted in English, and a few in IsiZulu, Sepedi, and IsiXhosa, the three predominant vernacular languages in Gauteng province. We used a digital PR200 cellphone recorder, which allowed for both calling and recording of the interview on one device. Reimbursement of R100 ($7.13) was given to all participants after the interview for their time, and R30 ($1.66) for data.

Debriefing sessions

The reflections presented in this paper are drawn from debriefing sessions that the research team had during data collection and at data analysis stages. The paper also draws data from the transcripts of interviews with participants to support or illustrate some of the reflections presented. The research team met three times during data collection process to reflect on the data collection process, discuss what was coming-up from the interviews, and to provide one another with emotional support during the lockdown period. Two meetings were also held by three members of the research team who coded the transcripts, developed the codebook and defined emerging themes, which were after shared with the whole research team for deliberation. The purpose of the two meetings was to share and discuss the codes and emerging themes from the data which were individually coded by the three co-authors. During the discussion, the coders further shared their reflections, and highlighting areas in the transcripts which were addressed in detail by participants, and those that were not. Reflections were also shared by the team during the writing of the study findings, where all co-authors provided written comments on the manuscript of the paper published, which were incorporated by the corresponding author [ 3 ]. The study PI took notes from the debriefing sessions and coding meetings held, which included reflections of all the co-authors except RJ who was only involved in the writing of the paper. Cross-team member discussion of the final set of reflections was done during conceptualization and writing of the paper.

The research process is used to structure the findings, starting with recruitment of participants and getting informed consent, and data collection using remote telephone interviews.

Recruitment of participants and getting informed consent

We remotely recruited participants from a wide age range, including older women and men. Participants were aged between 24 and 62. However, we observed and discussed that remote recruitment of eligible participants through online platforms took longer than we have experienced when conducting in-person recruitment. Moreover, we had to re-advertise the study before receiving sufficient expressions of interest from people who met the criteria for participation in the study. The long-time taken to recruit and the need to re-advertise the study suggest that either remote recruitment in our study was not a time-efficient method of recruitment or the criteria for the study and the platforms used may not have been readily accessible or as popular as we anticipated to the target population. We reflected that while social media allowed for a wider reach, our recruitment strategy might have excluded people who do not use social media platforms. It is also possible that some people who met the study criteria may have been hesitant, skeptical, or suspicious about participating in the study and this deterred their expression of interest. When participants are recruited in person, there is an opportunity for them to voice their concerns about the study and seek clarity by asking questions to recruiters.

Data collection using remote telephone interviews

Telephonic interviews were conducted at a second telephonic engagement with the participants, after receiving written informed consent. A few participants (about 8%) rescheduled their interview when we called them. Most of the interviews were conducted on the date and time selected by participants. This suggested that most participants found it easy to fit the interview into their schedule. We had a few instances where we had a bad line or network connectivity challenges, and the call kept cutting. Three key areas of learning were noted during the telephone interviews: establishing rapport, privacy during interviews, and disclosing violence experience and perpetration over the phone.

Rapport during telephone interviews

As researchers who conducted remote telephone interviews we learnt that rapport was difficult for us to establish without an in-person connection. While the first few questions in the interview guide were designed to build rapport (e.g. asking participant’s background information and about their families), it was difficult for us to establish rapport with participants over the phone. However, this experience varied. Some participants were open and willing to share broadly about their lives, while others were reserved and shared very little during the interview. To obtain information from those less open, we probed and asked the questions differently, however, this also did not yield much information. Another limitation with telephone interviews was not being able to see visual cues, which limited probing. We were sensitive to not probe to a point of causing distress, recognizing that we did not have visual cues to enable us to detect distress.

Privacy during telephone interviews

Before we commenced with the interview, participants were asked if they were in a private space and safe to conduct the interview. We proceeded with the interview only when participants confirmed that they were in a private space, and that it was safe to conduct the interview. Strategies used to ensure privacy varied, with some of the participants, for example, conducting the interview in their car. Further, participants were asked to indicate to the interviewer when their privacy was compromised during the interview, given that the researcher was not physically in the room with them to be able to monitor this. The interview guides were designed to ask open ended questions, for example, how participants were affected by COVID-19 pandemic, and how they experienced the COVID-19 lockdown in their families. We framed the questions in this manner to allow participants privacy to share what they wanted to share, although there was follow-up probing from the researchers. Throughout the interview, the interviewer ensured that they listened for signs of discomfort in participants’ responses, and tried to determine from the tone when there was distress and not probe further. For example, when a participant said “I would rather not talk about that in detail”. We assumed in those instances that the participant did not feel safe to discuss the matter further and did not push the line of inquiry. After such an instance, we would ask if the participant was still okay to continue or move to the next question.

During some interviews we realized that some participants did not have the privacy, that they had indicated prior to the start of the interview. For instance, we could hear voices in the background which suggested that a third adult person was present in the room during the interview. In some interviews with women, we heard a sound of a baby crying, with some women requesting to be excused to give the child to another adult person who was present at home. We could not ascertain whether that adult person was in the same room with the participant or a different room. One male participant could not openly respond to a question about whether there was any violence between him and his spouse in the home during lockdown. Limited by the presence of his spouse in the room, he responded:

It once happened to me, but my wife is here right now.

We learnt in our study that as researchers we have limited ability to ensure privacy during remote telephone interviews with participants. This is an area requiring further exploration to find ways to improve to ensure safety of participants.

Reimbursement of participants after telephone interviews

Shifting to remote methods also required that we adapt how we reimbursed participants for time. We needed to find an accessible platform to send money to participants without physical contact. We sent reimbursements using a digital e-wallet, which required participants to have a mobile phone to receive a pin number from the bank to use to withdraw money from an ATM, whenever is convenient to them. The pin number is easily renewable on one’s mobile phone at no cost to participants. With widespread ownership of mobile phones in South Africa, use of digital e-wallet to send and receive money is common across all socio-economic groups. E-wallet is considered a convenient method of receiving money as it does not require one to have a bank account, and the bank charges are charged to the person sending the money. The reimbursements were only disclosed to participants at the end of the interview to ensure that they do not influence decision about participation in the study. We did not know how easy or difficult it was for participants to access the money, but none reported having experienced challenges.

Disclosing violence experience and perpetration during telephone interviews

Our analysis of data revealed that talking about experiences and perpetration of intimate partner violence over the phone was challenging for most participants, both male and female, in varied ways. Both male and female participants spoke openly and elaborated in their responses about how COVID-19 and lockdown affected their livelihoods, difficulties of parenting during lockdown, violence they perpetrated against children, and about high levels of stress they experienced. However, both male and female participants were hesitant to respond to intimate partner violence (IPV) questions. Most women avoided talking about personal experiences, and more openly talked about IPV experiences of others in their family or community:

I wouldn’t say its violence; my husband is short-tempered and has anger. My next door neighbour… there was violence between him and the partner there. He is staying with a girlfriend. They are always fighting to an extent that those people break everything in the house. “My parents have had episodes of violence during the lockdown I would say. My dad has definitely uhm I think he’s starting to feel very cooped up and cranky, very impatient with my mom, aggressive and I wonder what else happens. We [husband and I] only had disagreements, sometimes very emotionally draining. My husband is a good husband.”

Amongst women who reported experiences of violence in the home during lockdown, only a few reported experiences of physical violence. Most women reported emotional violence perpetrated by their spouses.

Some men understated their perpetration of IPV during lockdown, avoiding labelling their experiences as violence, rather spoke about “small disagreements”, “misunderstanding”, or “tension”:

I am working in a food store, my wife doesn’t work, sometimes when i get home you find there is no food, sometimes she would blame me and pressurize me, you understand, we end up having a misunderstanding… she was saying you are the father, you should make a plan, you understand, she was giving me pressure. Sometimes we used to fight physically and breaking things in the house and sometimes verbally, but it was nothing much. Being confined in one space with someone that you are not used to spend much time together - because you were used to wake up in the morning and leave the house for work - that caused so much conflicts. We used to have a lot of small fights. There was tension, mainly caused by her moods, we would have heated exchanges, but I would not touch her.

A number of participants, both men and women, openly reported having beaten, shouted or threatened their children during lockdown. Participants in our study found it easier to talk about violence against children (VAC) than intimate partner violence. This could be explained by dominant beliefs about the acceptability of corporal punishment of children at home in South Africa.

This paper discusses adaptation we made, reflections, and lessons learned on using remote methods to conduct VAW research during COVID-19 lockdown in South Africa. Our study has confirmed some of the critiques of remote data collection documented in the literature suggesting underreporting, and difficulty of establishing rapport and ensuring participant safety and privacy without in-person interaction [ 8 , 15 ]. Our data also highlight some positive findings around the ease of scheduling telephone interview appointments, which participants found easy to fit into their schedule. Most of the scheduled interviews were conducted on the date and time agreed upon during the first call, and very few participants rescheduled their appointments. We could not secure privacy during the interviews, and this impacted on data quality. Even with the measures we implemented, before and at the start of the interview, we had no control over participants’ environments. As such, the lack of privacy limited participant’s ability to talk about experiences and perpetration of violence, which raised questions about validity and credibility of the data. There is acknowledgement in the literature that research methods that do not involve face to face engagement with participants and restrict the researcher’s ability to access their natural environment may limit the depth and extent to which researchers can explore the topic under investigation [ 12 ].

The safety of women participating in research on violence is extremely important and emphasized in the WHO Guidelines on Ethical and Safety Recommendations for Research on Domestic Violence Against Women [ 1 , 9 ]. While safety and privacy of participants was amongst the key ethical considerations in our research, it was a challenge to prevent disturbances during remote interviews with participants. Even after we had discussed the importance of privacy and stopping interviews if interrupted during interview, participants did not inform us as someone came into the room, and we had no other way of learning about this as we were not there. We had to rely on participants to manage their own safety risks around disclosure and the conversation and that was not satisfactory as we don’t know how well they did it. Our study further confirmed what has been observed in other studies which showed that talking about violence experience and perpetration is highly sensitive and difficult over the phone [ 8 , 9 ]. Without in-person contact, rapport between the interviewer and participant, which is critical for enabling disclosure of personal information, was difficult to establish. Participants in our study were reluctant to engage on personal topics and disclose violence experience (women) and perpetration (men). It was evident in some of the extracts that a few participants could not speak openly, and feared being overheard by their spouses, whom in some instances were present in the room during the telephone interview. As such, only a few women disclosed and reported experience of physical violence in our study. Many were reluctant to talk about personal experiences of violence. It could be that there was more violence experienced and perpetrated during lockdown than disclosed in our study. The two telephone calls or remote interaction with participants might have not been adequate to establish rapport and trust necessary to enable participants to openly and safely share about sensitive personal experiences. More research is needed to deepen understanding on how to remotely establish rapport and create participants’ emotional safety, and physical privacy to enable openness to share about sensitive topics during telephone interviews.

Notwithstanding, we also acknowledge that there could have been other factors such as social desirability and cultural beliefs that might have limited disclosure of violence experience and perpetration during COVID-19 lockdown amongst men and women in our study. At the time of the study, there was media coverage, and political calls and messaging on violence against women and children in South Africa. GBV was described by the President of the country as a second epidemic facing the country, with widely publicized messaging against it [ 19 ]. This meant that sensitization against GBV was high and men in our study may have not wanted to be counted amongst those who were perpetrating, and women as survivors of GBV. Furthermore, there are beliefs or socialization in some cultures in South Africa where disclosing what happens in a marriage or relationship with a spouse is discouraged. Everything about the marriage or relationship including IPV is considered a domestic matter, that needs to be kept private. Women who reported experiences of violence were referred by us to contact the National GBV Command Call Centre and the police. However, we do not know whether such referrals were taken up by the women.

Social media was possible to use to get participants, but it was not a very satisfactory way of recruiting people as we used multiple platforms and had to advertise twice. This suggests that the response rate was low and it was very hard to know what sort of biases would have been introduced. However, the value of using social media platforms for recruitment of participants in health research is increasingly being recognized for their wide reach, given their accessibility and use by most people [ 20 , 21 , 22 ]. Others have found social media to be an effective and cost effective platform which allowed for reach of a large number of participants during COVID-19 [ 23 ]. Despite the merits of social media platforms, others have cautioned that social media platforms can be biased towards a younger sample of participants from high socio-economic status, which was not the case in our study [ 20 , 24 ]. Our sample included both young and old men and women between age 24–62 years, from low, middle and high-income groups, with some unemployed. We had slightly more [ 19 ] females compared to [ 18 ] male participants in our study. We were very concerned about not overly inducing participation by saying that participants would be reimbursed for participation. As a result, unlike in other research, we did not tell participants this in advance. This may have contributed to the slow rate of recruitment and possibly some people who would have liked to earn something and share about their experiences didn’t do so as they didn’t know they would get reimbursement. Getting written informed consent on WhatsApp or SMS from participant’s in remote research was possible, though relatively new in health research, it is increasingly being accepted by Human Research Ethics Committees [ 25 ]. Others have argued that remote consent from participants who self-select to participate is truer and non-coercive given that participant’s express interest without researchers’ putting undue pressure on them to participate [ 26 ].

To respond to the challenges of establishing rapport, research on sensitive topics like violence can be conducted remotely only when participants are already engaged in the study and the partnership between participants and researcher is well established [ 8 , 25 , 27 ]. An established relationship of trust between participants and interviewer is important and can be used as leverage to facilitate rapport and connection in a remote interview. Starting with an informal conversation and asking questions that are not personal to the interviewee is also crucial to build the connection [ 25 ]. Bhatia et al. (2022) further suggest that shifting to remote data collection in violence research requires additional safeguarding processes, remote support for researchers, committing resources to additional steps required to protect participants adapting to moveable and unpredictable conditions specific to each context.

One needs to have a well-designed study, with clear safety and privacy protocols for participants. While the researcher has limited control of the space, he/she should before and at the start of the interview explain safety and privacy requirements to participants, and why that is important. There is a need to guide interviewers on how to respond or make safety decisions in the event where privacy is breached and women’s safety is compromised during a telephone interview. Use of safe words or code words by participants to indicate when safety is breached is encouraged for remote research on violence [ 27 ]. Emotional safety is important for women to share their experiences on sensitive topics. Given that there are no verbal cues to assist the interviewer to detect distress from participants telephone interviews, it is important that the interviewer carefully listens to detect changes in the tone and sudden pauses which can be interpreted to signal distress. Should the interviewer detect distress, they should always remind participants that they do not have to respond if not comfortable, and of their right to withdraw at any point during the interview. Remote interviews should be conducted either by experienced researchers, or well-trained interviewers who will know when and how to probe, implement privacy and safety protocols, and be able to detect distress over the phone. Debriefing sessions to support the research team during data collection, and to provide them space to brainstorm solutions to challenges encountered is even more critical when conducting remote research. Safeguarding and referral of participants to support services remains crucial in all research on sensitive topics, online or phone based services are most useful when movement of participants is restricted [ 25 ]. Our research had some limitations in that the study was conducted amongst a sample of men and women in Gauteng and thus the findings are not generalizable. However, the lessons learned in this study may be useful for others conducting remote research on sensitive topics in similar contexts. We acknowledge the limitations of the remote recruitment strategy we used, which might have excluded people who do not use social media platforms including Facebook and WhatsApp.

The COVID-19 lockdown and restriction of movement presented an opportunity to explore and use remote methods to conduct qualitative research on a sensitive topic of violence against women. In our study, we learnt that conducting VAW research using telephone interviews is challenging presents with methodological and ethical challenges around privacy and safety. It was difficult to establish rapport with participants without in-person contact, and negatively impacted on disclosure of violence experience and perpetration. Whilst these challenges are present in face to face research, they were heightened in remote research. Whilst the WHO guidelines on conducting domestic violence research with women, which we used in designing our study, were useful, they were limited at the time, as they were not designed for remote research. We conclude that conducting qualitative VAW research remotely requires a well thought through study design and planning; should be done by skilled researchers or well-trained interviewees, guided by privacy and safety protocols; among participants where a relationship of trust has been established, and have a clear understanding of the importance of safety and privacy during an interview. Lessons learned in designing and implementing remote methods during COVID-19 lockdown in our study could be useful for others planning to use similar methods to research sensitive topics, and is a contribution to knowledge on execution of remote research in public health.

Data availability

The datasets analysed in the study are available from the corresponding author on reasonable request.


Automated Teller Machine

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Gender Based Violence

In–depth Telephone Interviews

Intimate Partner Violence

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South African Medical Research Council

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We are grateful to all the women and men who participated in the study, shared their experiences and contributed valuable data which allowed us to write this publication.

The authors received funding from the South African Medical Research Council. The support of the DST – NRF Centre of Excellence (CoE) in Human Development towards this research is also hereby acknowledged. The opinions expressed and conclusions arrived at from the research are those of the authors and are not necessarily to be attributed to the CoE in Human Development or the SAMRC. The funders played no role in the research.

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Pinky Mahlangu, Mercilene Tanyaradzwa Machisa, Rachel Jewkes, Nwabisa Shai & Yandisa Sikweyiya

School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

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Pinky Mahlangu

Department of Psychology, Faculty of Health and Life Sciences, University of Exeter, Exeter, EX2 4QG, UK

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PM and YS conceptualized the study. PM received funding and coordinated data collection. PM, AG, NS, MM and YS developed data collection tools, conducted the interviews, analysed and interpreted the data, and contributed to debriefing sessions. PM drafted the manuscript. All authors read, reviewed and approved the final manuscript.

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Mahlangu, P., Machisa, M., Jewkes, R. et al. Reflections on the process, challenges, and lessons learned conducting remote qualitative research on Violence against women during COVID-19 pandemic lockdown in South Africa. BMC Public Health 24 , 33 (2024). https://doi.org/10.1186/s12889-023-17480-z

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Ethical Considerations in Research | Types & Examples

Published on 7 May 2022 by Pritha Bhandari .

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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