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Ethical Considerations – Types, Examples and Writing Guide

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Ethical Considerations

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

Some of the key ethical considerations in research include:

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

Types of Ethical Considerations

Types of Ethical Considerations are as follows:

Research Ethics:

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

Business Ethics :

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

Medical Ethics :

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

Environmental Ethics :

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

Legal Ethics

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

Social Ethics

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

Information Ethics

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

Cultural Ethics

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

Technological Ethics

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

Journalism Ethics

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

Educational Ethics

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

Political Ethics

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

Professional Ethics

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

Personal Ethics

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

Global Ethics

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

Applications of Ethical Considerations

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

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

Examples of Ethical Considerations

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

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

How to Write Ethical Considerations

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

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

When to Write Ethical Considerations

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

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

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

Purpose of Ethical Considerations

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

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

Advantages of Ethical Considerations

Here are some of the advantages of ethical considerations:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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A Guide to Logistical/Ethical Considerations in Thesis/Dissertation Writing

4-minute read

• 14th May 2023

Why include a section on logistical/ethical considerations in your thesis/dissertation?

Ethical and logistical considerations are the guidelines that marshal your research practices and activities. With so many necessary steps to planning your dissertation , it may be tempting to dash off your logistical and ethical considerations section. However, don’t make that mistake! Including a thorough section on logistical and ethical considerations in your thesis shows that you have carefully considered your research plan, from the ethical implications of your research findings to the impact of performing the study itself.

And above all else, not providing well-thought-out ethical and logistical considerations in your research plan could derail your entire dissertation and have other grave consequences . But not to worry! Here, we offer a step-by-step guide to writing your logistical and ethical considerations section so that you can tick another essential item off your thesis checklist .

Steps for creating a logistical/ethical considerations section

• Clarify your ethical and logistical principles.

Your ethical and logistical principles will depend on many factors, such as research topic, fieldwork, and the possibility of direct interaction with vulnerable populations.

However, several overarching research principles are always helpful to remember. For example, the Belmont Report lists three often invoked principles: respect for persons, beneficence (i.e., maximize potential benefits to research subjects and minimize potential harm), and justice (i.e., people should be treated fairly). However, many other principles exist (and we offer a few other frequently cited principles below that might apply to your research).

If you haven’t done so already, discuss the ramifications of your dissertation work from an ethical standpoint with your adviser, who may bring up concerns that you’ve overlooked. You should also check with your organization’s Institutional Review Board (IRB) to confirm that there are no policies you need to be aware of.

• Evaluate each step of your research plan, as well as its potential risks and implications, and plan how you will ensure the ethical treatment of all persons involved.

Now that you have clarified your ethical and logistical principles, go through each stage of your research plan and consider the ethical impact of each step. Come up with a systematic plan to make sure that you’re protecting the ethical standards you’ve laid out for each one of the people affected by your research.

• Record your practices thoroughly and carefully during your research.

During the course of your study, keep detailed records of how you made sure the practices that address the ethical and logistical considerations were completed.

For example, if you should be obtaining verbal consent before conducting an interview, maintain a system to record that the consent was received.

Or, if it’s necessary to keep your digital data secure, be sure to make a note of the hardware and software you use. Plenty of online templates can help you keep these details organized.

• Write the ethical and logistical considerations section.

If you’ve kept detailed records, writing up your ethical and logistical considerations should be a straightforward process. It’s more common these days to see a section devoted to research ethics in dissertation structures .

Once again, check with your adviser to make sure you follow the proper protocol when you add your section on ethical and logistical considerations to your dissertation.

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Potential ethical and logistical considerations

This is not a comprehensive list, but here are a few more common ethical and logistical considerations that may apply to your research work:

●  Informed consent : Participants should be able to voluntarily join the study and know what the study is about and what the implications of the work are.

●  Anonymity, confidentiality, and data protection : Participants should have a reasonable expectation that their confidential data will remain private.

●  Nondiscrimination : You should avoid discrimination on the basis of sex, race, ethnicity, or any other factor.

●  Social responsibility : Research should contribute to the common good.

Following the four steps outlined in this post will help you write an ethical and logistical considerations section in your dissertation:

1. Define your principles

2. Evaluate the risks and implications of each stage of your research

3. Record your practices carefully

4. Write up your considerations in the appropriate format for the dissertation.

Although ethical considerations vary from study to study, our guide should get you through another step in writing your thesis! Remember to include enough time for editing and proofreading your dissertation , and if you’re interested in some help from us, you can try a sample of our services for free . Good luck writing your dissertation!

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Ethical considerations in research: Best practices and examples

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

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

Examples of ethical considerations in research

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

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

Voluntary participation

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

Informed consent

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

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

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

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

• Email address
• Photographs
• Video footage

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

Confidentiality

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

Some ways to ensure confidentiality include:

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

Potential for harm

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

• Psychological harm
• Social harm
• Physical harm

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

Fair payment

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

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

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

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

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

Ethical research made easy with Prolific

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

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

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Ethical Considerations In Psychology Research

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

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

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

What are Ethical Guidelines?

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

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

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

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

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

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

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

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

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

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

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

Informed Consent

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

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

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

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

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

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

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

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

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

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

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

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

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

Participants must be given information relating to the following:

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

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

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

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

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

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

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

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

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

Protection of Participants

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Confidentiality

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

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

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

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

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

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

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

Withdrawal from an Investigation

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

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

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

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

Ethical Issues in Psychology & Socially Sensitive Research

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

But consider the following examples:

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

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

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

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

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

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

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

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

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

Ethical Guidelines For Carrying Out SSR

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Arguments for SSR

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

Arguments against SSR

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

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

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

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

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

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

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

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

Further Information

• MIT Psychology Ethics Lecture Slides

BPS Documents

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

APA Documents

APA Ethical Principles of Psychologists and Code of Conduct

Frequently asked questions

What are ethical considerations in research.

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

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

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

Frequently asked questions: Methodology

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Snowball sampling is best used in the following cases:

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

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

Reproducibility and replicability are related terms.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There are two subtypes of construct validity.

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

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

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

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

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

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

In statistics, dependent variables are also called:

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

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

Independent variables are also called:

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

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

Overall, your focus group questions should be:

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

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

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

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

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

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

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

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

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

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

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

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

Unstructured interviews are best used when:

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

The four most common types of interviews are:

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

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

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

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

Deductive reasoning is also called deductive logic.

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

Here are a few common types:

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

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

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

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

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

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

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

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

Triangulation can help:

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

But triangulation can also pose problems:

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

There are four main types of triangulation :

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

These are four of the most common mixed methods designs :

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

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

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

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

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

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

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

Correlation coefficients always range between -1 and 1.

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

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

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

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

Quantitative research designs can be divided into two main categories:

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

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

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

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

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

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

Questionnaires can be self-administered or researcher-administered.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Systematic error is generally a bigger problem in research.

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

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

Random and systematic error are two types of measurement error.

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

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

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

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

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

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

The difference between explanatory and response variables is simple:

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

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

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

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

There are 4 main types of extraneous variables :

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

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

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

In a factorial design, multiple independent variables are tested.

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

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

Advantages:

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

Disadvantages:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

If something is a mediating variable :

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

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

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

There are three key steps in systematic sampling :

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There are five common approaches to qualitative research :

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

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

Operationalization means turning abstract conceptual ideas into measurable observations.

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

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

When conducting research, collecting original data has significant advantages:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Discrete and continuous variables are two types of quantitative variables :

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

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

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

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

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

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

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

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

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

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

When designing the experiment, you decide:

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

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

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

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

The validity of your experiment depends on your experimental design .

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

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

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

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

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

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

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

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

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

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

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

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Ethical Considerations – Types & Examples

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Ethical considerations are integral to academic writing, particularly in shaping the methodology and conduct of research. They ensure that the research is reliable, credible, and conducted with respect for all involved parties. In designing the methodology for a study, it is paramount to account for these ethical considerations, as they underpin the trustworthiness of the academic discourse.

Inhaltsverzeichnis

• 1 Ethical Considerations – In a Nutshell
• 2 Definition: Ethical considerations
• 3 Why are ethical considerations necessary?
• 4 Ethical considerations: Types of ethical issues
• 5 Ethical Considerations: The danger of unethical practices

Ethical Considerations – In a Nutshell

• Ethical considerations are a crucial element of viable research .
• Disregarding ethical concerns can cause severe repercussions .
• Researchers must always uphold ethical considerations in the field as a basic condition for scientific research.

Definition: Ethical considerations

Ethical considerations in research refer to guidelines and principles which researchers must adhere to as they conduct their research. Research often involves face-to-face interaction with people as researchers study behaviors and test the effects of certain phenomena on a target population . Ethical considerations dictate the nature of such interactions to ensure research is done per the set rules and principles.

Why are ethical considerations necessary?

Ethical considerations are important because they promote research objectives , including avoidance of error, truth, and knowledge. Ethical considerations prohibit false interpretations and misrepresentation of facts in deriving conclusions from any research undertaking.

Furthermore, ethical considerations are necessary to promote trust , collaboration , and mutual respect since research usually involves cooperation between researchers and people from different dispositions. A cohesive environment fostered by ethical considerations ensures all the parties involved throughout the research can exchange responses and ideas for successful research undertaking in the following ways:

• Safeguarding the rights of the participants: It is vital to ensure that the rights of the participants are not violated in any way. Failure to respect the rights of research participants often leads to misleading information or hostility in some instances.
• Promote research validity: Going against ethical considerations through coercion or deliberately misleading research participants invalidates the research findings. Any evidence of misconduct during research may render your findings unusable and attract penalties.
• Protecting scientific integrity: Science aims to solve some of humanity’s most complex problems. Researchers should be guided by ethical considerations to collect data and propose useful findings used in policy making.

Ethical considerations also promote public participation in adoption of policies informed by research. Lack of adherence to ethical considerations may cause backlash from the public and inhibit efforts to create policies around known research undertakings. Additionally, ethical considerations help to hold researchers accountable for their methods during the research.

Ethical considerations: Types of ethical issues

Researchers should observe the following ethical considerations throughout their research:

Voluntary participation

Researchers should ensure no participants are coerced into participating in a study. Voluntary participation is a vital principle of ethics in research as it ensures every research participant does so as a personal decision. This is particularly relevant in “captive” populations such as prisons and institutions where the participants may be wrongfully mandated to participate in research studies.

Anonymity in research means that the identity of research participants should be kept secret by ensuring responses cannot be linked back to specific respondents. It can also imply that no personal identification details such as names and residential addresses are collected during the initial stages of the research.

Potential for harm

Potential for harm implies potential physical or emotional injury and other inconveniences that may arise from a subject’s participation in research. Researchers must fully disclose the potential risks associated with a study before any engagement with the research participants. The element of risk is usually captured in the consent form, which outlines the potential risks and the procedures in place for each.

Informed consent

Informed consent is one of the pillars of ethics in research. It is closely associated with voluntary participation, which implies participants should join a research case of their own volition with full disclosure from the research team. Consent must be obtained prospectively, and no undue influence should be exerted on the respondents. Informed consent may be given in writing or given orally.

Confidentiality

Most research projects involve the collection of personal data. Researchers must ensure the research participants’ identities and responses are protected. Confidentiality is important in studies such as health research, where a breach of confidence could stigmatize participants known to suffer from an ailment. Researchers should ensure that no one outside the research team can access respondents’ confidential information unless otherwise required by legal bodies.

Results communication

Communication of research results may raise ethical issues. Researchers are responsible for ensuring that they communicate their results honestly and credibly. Plagiarism is one of the most widespread ethical concerns in scientific research where researchers unlawfully present other people’s work as their own.

Ethical Considerations: The danger of unethical practices

Unethical research practices invalidate the research findings and cause grave physical, social, and psychological harm to the research participants. One of the most infamous cases of blatant ethical misconduct was the syphilis experiment of the 1940s carried out in Tuskegee, US.

The disease affected at least 1 in 10 Americans, and the government soon flagged syphilis as a national pandemic. Medical experts identified unprotected sex as the major avenue for transmission, although studies also showed that it could be transmitted during childbirth. Researchers propose two main research questions:

• Did late-stage syphilis excuse the risks of prevailing treatments?
• Was race a factor in the progression of the disease?

Initially, the research examined the progression of syphilis with minimal treatment in black men with late-stage non-contagious syphilis. However, the medications were replaced with placebos administered through invasive spinal taps to test the neurological effects of the disease. When the participants died, the PHS would use their bodies to “further their research.”

In today’s circumstances, the complete disregard for ethical principles, in this case, is appalling, but fortunately, it has set the foundation for ethical considerations.

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Why are ethical considerations important?

Ethical considerations are important to protect research participants . They also ensure research findings are credible , honest , and valid .

What is the difference between anonymity and confidentiality in research?

Anonymity refers to the actions undertaken by the researcher to ensure the participants’ identity cannot be linked to their responses . Confidentiality refers to the measures taken to ensure no one outside the research team knows the participants’ identities .

What is informed consent in research?

Informed consent is one of the most important ethical considerations. It means that research participants must agree to participate with full information and without undue influence.

What is research misconduct?

It refers to the manipulation and falsification of data in research. It is an adverse ethical matter as it may damage scientific credibility and an institution’s integrity.

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How to Write an Ethics Paper: Guide & Ethical Essay Examples

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An ethics essay is a type of academic writing that explores ethical issues and dilemmas. Students should evaluates them in terms of moral principles and values. The purpose of an ethics essay is to examine the moral implications of a particular issue, and provide a reasoned argument in support of an ethical perspective.

Writing an essay about ethics is a tough task for most students. The process involves creating an outline to guide your arguments about a topic and planning your ideas to convince the reader of your feelings about a difficult issue. If you still need assistance putting together your thoughts in composing a good paper, you have come to the right place. We have provided a series of steps and tips to show how you can achieve success in writing. This guide will tell you how to write an ethics paper using ethical essay examples to understand every step it takes to be proficient. In case you don’t have time for writing, get in touch with our professional essay writers for hire . Our experts work hard to supply students with excellent essays.

What Is an Ethics Essay?

An ethics essay uses moral theories to build arguments on an issue. You describe a controversial problem and examine it to determine how it affects individuals or society. Ethics papers analyze arguments on both sides of a possible dilemma, focusing on right and wrong. The analysis gained can be used to solve real-life cases. Before embarking on writing an ethical essay, keep in mind that most individuals follow moral principles. From a social context perspective, these rules define how a human behaves or acts towards another. Therefore, your theme essay on ethics needs to demonstrate how a person feels about these moral principles. More specifically, your task is to show how significant that issue is and discuss if you value or discredit it.

Purpose of an Essay on Ethics

The primary purpose of an ethics essay is to initiate an argument on a moral issue using reasoning and critical evidence. Instead of providing general information about a problem, you present solid arguments about how you view the moral concern and how it affects you or society. When writing an ethical paper, you demonstrate philosophical competence, using appropriate moral perspectives and principles.

Things to Write an Essay About Ethics On

Before you start to write ethics essays, consider a topic you can easily address. In most cases, an ethical issues essay analyzes right and wrong. This includes discussing ethics and morals and how they contribute to the right behaviors. You can also talk about work ethic, code of conduct, and how employees promote or disregard the need for change. However, you can explore other areas by asking yourself what ethics mean to you. Think about how a recent game you watched with friends started a controversial argument. Or maybe a newspaper that highlighted a story you felt was misunderstood or blown out of proportion. This way, you can come up with an excellent topic that resonates with your personal ethics and beliefs.

Ethics Paper Outline

Sometimes, you will be asked to submit an outline before writing an ethics paper. Creating an outline for an ethics paper is an essential step in creating a good essay. You can use it to arrange your points and supporting evidence before writing. It also helps organize your thoughts, enabling you to fill any gaps in your ideas. The outline for an essay should contain short and numbered sentences to cover the format and outline. Each section is structured to enable you to plan your work and include all sources in writing an ethics paper. An ethics essay outline is as follows:

• Background information
• Thesis statement
• Restate thesis statement
• Summarize key points
• Final thoughts on the topic

Using this outline will improve clarity and focus throughout your writing process.

Ethical Essay Structure

Ethics essays are similar to other essays based on their format, outline, and structure. An ethical essay should have a well-defined introduction, body, and conclusion section as its structure. When planning your ideas, make sure that the introduction and conclusion are around 20 percent of the paper, leaving the rest to the body. We will take a detailed look at what each part entails and give examples that are going to help you understand them better.  Refer to our essay structure examples to find a fitting way of organizing your writing.

Ethics Paper Introduction

An ethics essay introduction gives a synopsis of your main argument. One step on how to write an introduction for an ethics paper is telling about the topic and describing its background information. This paragraph should be brief and straight to the point. It informs readers what your position is on that issue. Start with an essay hook to generate interest from your audience. It can be a question you will address or a misunderstanding that leads up to your main argument. You can also add more perspectives to be discussed; this will inform readers on what to expect in the paper.

Ethics Essay Introduction Example

You can find many ethics essay introduction examples on the internet. In this guide, we have written an excellent extract to demonstrate how it should be structured. As you read, examine how it begins with a hook and then provides background information on an issue. 

Imagine living in a world where people only lie, and honesty is becoming a scarce commodity. Indeed, modern society is facing this reality as truth and deception can no longer be separated. Technology has facilitated a quick transmission of voluminous information, whereas it's hard separating facts from opinions.

In this example, the first sentence of the introduction makes a claim or uses a question to hook the reader.

Ethics Essay Thesis Statement

An ethics paper must contain a thesis statement in the first paragraph. Learning how to write a thesis statement for an ethics paper is necessary as readers often look at it to gauge whether the essay is worth their time.

When you deviate away from the thesis, your whole paper loses meaning. In ethics essays, your thesis statement is a roadmap in writing, stressing your position on the problem and giving reasons for taking that stance. It should focus on a specific element of the issue being discussed. When writing a thesis statement, ensure that you can easily make arguments for or against its stance.

Ethical Paper Thesis Example

Look at this example of an ethics paper thesis statement and examine how well it has been written to state a position and provide reasons for doing so:

The moral implications of dishonesty are far-reaching as they undermine trust, integrity, and other foundations of society, damaging personal and professional relationships. 

The above thesis statement example is clear and concise, indicating that this paper will highlight the effects of dishonesty in society. Moreover, it focuses on aspects of personal and professional relationships.

Ethics Essay Body

The body section is the heart of an ethics paper as it presents the author's main points. In an ethical essay, each body paragraph has several elements that should explain your main idea. These include:

• A topic sentence that is precise and reiterates your stance on the issue.
• Evidence supporting it.
• Examples that illustrate your argument.
• A thorough analysis showing how the evidence and examples relate to that issue.
• A transition sentence that connects one paragraph to another with the help of essay transitions .

When you write an ethics essay, adding relevant examples strengthens your main point and makes it easy for others to understand and comprehend your argument. 

Body Paragraph for Ethics Paper Example

A good body paragraph must have a well-defined topic sentence that makes a claim and includes evidence and examples to support it. Look at part of an example of ethics essay body paragraph below and see how its idea has been developed:

Honesty is an essential component of professional integrity. In many fields, trust and credibility are crucial for professionals to build relationships and success. For example, a doctor who is dishonest about a potential side effect of a medication is not only acting unethically but also putting the health and well-being of their patients at risk. Similarly, a dishonest businessman could achieve short-term benefits but will lose their client’s trust.

Ethics Essay Conclusion

A concluding paragraph shares the summary and overview of the author's main arguments. Many students need clarification on what should be included in the essay conclusion and how best to get a reader's attention. When writing an ethics paper conclusion, consider the following:

• Restate the thesis statement to emphasize your position.
• Summarize its main points and evidence.
• Final thoughts on the issue and any other considerations.

You can also reflect on the topic or acknowledge any possible challenges or questions that have not been answered. A closing statement should present a call to action on the problem based on your position.

Sample Ethics Paper Conclusion

The conclusion paragraph restates the thesis statement and summarizes the arguments presented in that paper. The sample conclusion for an ethical essay example below demonstrates how you should write a concluding statement.  

In conclusion, the implications of dishonesty and the importance of honesty in our lives cannot be overstated. Honesty builds solid relationships, effective communication, and better decision-making. This essay has explored how dishonesty impacts people and that we should value honesty. We hope this essay will help readers assess their behavior and work towards being more honest in their lives.

In the above extract, the writer gives final thoughts on the topic, urging readers to adopt honest behavior.

How to Write an Ethics Paper?

As you learn how to write an ethics essay, it is not advised to immediately choose a topic and begin writing. When you follow this method, you will get stuck or fail to present concrete ideas. A good writer understands the importance of planning. As a fact, you should organize your work and ensure it captures key elements that shed more light on your arguments. Hence, following the essay structure and creating an outline to guide your writing process is the best approach. In the following segment, we have highlighted step-by-step techniques on how to write a good ethics paper.

1. Pick a Topic

Before writing ethical papers, brainstorm to find ideal topics that can be easily debated. For starters, make a list, then select a title that presents a moral issue that may be explained and addressed from opposing sides. Make sure you choose one that interests you. Here are a few ideas to help you search for topics:

• Review current trends affecting people.
• Think about your personal experiences.
• Study different moral theories and principles.
• Examine classical moral dilemmas.

Once you find a suitable topic and are ready, start to write your ethics essay, conduct preliminary research, and ascertain that there are enough sources to support it.

2. Conduct In-Depth Research

Once you choose a topic for your essay, the next step is gathering sufficient information about it. Conducting in-depth research entails looking through scholarly journals to find credible material. Ensure you note down all sources you found helpful to assist you on how to write your ethics paper. Use the following steps to help you conduct your research:

• Clearly state and define a problem you want to discuss.
• This will guide your research process.
• Develop keywords that match the topic.
• Begin searching from a wide perspective. This will allow you to collect more information, then narrow it down by using the identified words above.

3. Develop an Ethics Essay Outline

An outline will ease up your writing process when developing an ethic essay. As you develop a paper on ethics, jot down factual ideas that will build your paragraphs for each section. Include the following steps in your process:

• Review the topic and information gathered to write a thesis statement.
• Identify the main arguments you want to discuss and include their evidence.
• Group them into sections, each presenting a new idea that supports the thesis.
• Write an outline.
• Review and refine it.

Examples can also be included to support your main arguments. The structure should be sequential, coherent, and with a good flow from beginning to end. When you follow all steps, you can create an engaging and organized outline that will help you write a good essay.

4. Write an Ethics Essay

Once you have selected a topic, conducted research, and outlined your main points, you can begin writing an essay . Ensure you adhere to the ethics paper format you have chosen. Start an ethics paper with an overview of your topic to capture the readers' attention. Build upon your paper by avoiding ambiguous arguments and using the outline to help you write your essay on ethics. Finish the introduction paragraph with a thesis statement that explains your main position.  Expand on your thesis statement in all essay paragraphs. Each paragraph should start with a topic sentence and provide evidence plus an example to solidify your argument, strengthen the main point, and let readers see the reasoning behind your stance. Finally, conclude the essay by restating your thesis statement and summarizing all key ideas. Your conclusion should engage the reader, posing questions or urging them to reflect on the issue and how it will impact them.

5. Proofread Your Ethics Essay

Proofreading your essay is the last step as you countercheck any grammatical or structural errors in your essay. When writing your ethic paper, typical mistakes you could encounter include the following:

• Spelling errors: e.g., there, they’re, their.
• Homophone words: such as new vs. knew.
• Inconsistencies: like mixing British and American words, e.g., color vs. color.
• Formatting issues: e.g., double spacing, different font types.

While proofreading your ethical issue essay, read it aloud to detect lexical errors or ambiguous phrases that distort its meaning. Verify your information and ensure it is relevant and up-to-date. You can ask your fellow student to read the essay and give feedback on its structure and quality.

Ethics Essay Examples

Writing an essay is challenging without the right steps. There are so many ethics paper examples on the internet, however, we have provided a list of free ethics essay examples below that are well-structured and have a solid argument to help you write your paper. Click on them and see how each writing step has been integrated. Ethics essay example 1

Ethics essay example 2

Ethics essay example 3

Ethics essay example 4

College ethics essay example 5

Ethics Essay Writing Tips

When writing papers on ethics, here are several tips to help you complete an excellent essay:

• Choose a narrow topic and avoid broad subjects, as it is easy to cover the topic in detail.
• Ensure you have background information. A good understanding of a topic can make it easy to apply all necessary moral theories and principles in writing your paper.
• State your position clearly. It is important to be sure about your stance as it will allow you to draft your arguments accordingly.
• When writing ethics essays, be mindful of your audience. Provide arguments that they can understand.
• Integrate solid examples into your essay. Morality can be hard to understand; therefore, using them will help a reader grasp these concepts.

Bottom Line on Writing an Ethics Paper

Creating this essay is a common exercise in academics that allows students to build critical skills. When you begin writing, state your stance on an issue and provide arguments to support your position. This guide gives information on how to write an ethics essay as well as examples of ethics papers. Remember to follow these points in your writing:

• Create an outline highlighting your main points.
• Write an effective introduction and provide background information on an issue.
• Include a thesis statement.
• Develop concrete arguments and their counterarguments, and use examples.
• Sum up all your key points in your conclusion and restate your thesis statement.

Contact our academic writing platform and have your challenge solved. Here, you can order essays and papers on any topic and enjoy top quality. 

Daniel Howard is an Essay Writing guru. He helps students create essays that will strike a chord with the readers.

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Top 5 Ethical Considerations in Research

While research is based on the pillars of innovation, trust, and transparency, it also requires scientists and academics to abide by certain ethical considerations in research. The world is increasingly dependent on the scientific community to come up with solutions to global problems. When inaccurate or plagiarised results are published, only to be retracted later, it leads not only to wasted time and resources, but also threatens the precious trust that people have in the scientific process and scholarly publishing. Therefore, it is important for researchers to understand and abide by these ethical considerations in research not only when conducting experiments but also when publishing the results.

The National Research Council of the National Academies defines ethics and integrity in research as a series of good practices, which include among other aspects, intellectual honesty in performing and reporting research, fairness in peer reviews, transparency in communication, collegiality in scientific interactions, and protection and care of human and animal subjects during research. 1 To put it simply, ethical considerations in research refers to a code of conduct that must be followed when planning, conducting, and reporting research.

Despite these ethical considerations in research, many researchers are left grappling with ethical dilemmas and many face journal rejection, retractions, loss of employment, and other penalties because they lack or did not completely adhere to the mandated guidelines. To make it simpler for you, we’ve put together key ethical considerations in research every author should know about.

Table of Contents

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Fabrication and falsification of data or results

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Ethical approvals, informed consent, privacy, and confidentiality

Duplicate submissions and salami slicing.

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Frequently Asked Questions (FAQs)

Plagiarism and duplication of others’ work.

Avoiding plagiarism is one of the basic ethical considerations in research. Plagiarism is presenting someone else’s work as your own without acknowledging them, which is unacceptable in scientific research. This unauthorised use is akin to stealing ideas, thoughts, or words and using them for your benefit.

However, all research is built on previously published work and many researchers end up relying too much on the work of others. Violations of this ethical consideration in research may happen due to a lack of experience or skill, forgetting to correctly cite a source or not understanding what constitutes plagiarism. Regardless of the reason, plagiarism is considered a serious ethical violation making it imperative for researchers to understand this key ethical consideration in research and take care to avoid unintentional or self-plagiarism in their work. You can do this by acknowledging people who have contributed to your research, properly citing all sources used in the research paper, and avoiding a direct copy-paste of text from other sources.

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Conducting and reporting research methods, data, and results honestly is at the very top of the list of ethical considerations in research. Fabrication is making up data or results, while falsification is manipulating or altering data or results, both of which are seen as major ethical violations. As a researcher, you need to steer clear of the temptation to make up data, exaggerate findings, and mislead readers with vague or contradictory explanations.

It is always better to be honest and state all aspects of your research and its results accurately instead of over-exaggerating findings and being found out. If found guilty of violating this ethical consideration in research, you risk being heavily penalized, being suspended or expelled, face rejection, or be forced to retract your paper, all of which will impact your credibility as a researcher. Take time to review your work carefully so that you can identify and eliminate even inadvertent errors in data presentation. It may be a good idea to keep a full record of your research, so that you can go back to check on certain sections if so required.

Conflicts of interest and potential for bias

Conflicts of interest occur when competing financial obligations, personal values and stands, or professional interests compromise a researcher’s ability to be objective. While conflicts of interest are not a major ethical consideration in research and scholarly publishing, not recognizing or declaring them is seen as unethical. It is critical for researchers to identify and disclose any and all potential conflicts of interest when submitting their manuscript for publication.

Ethical considerations in research require researchers to keep aside personal biases and conduct research in an objective manner without letting your own views or cultural perspectives seep into the research study. Stay vigilant and avoid any kind of discrimination and focus instead on the scientific competence and integrity of people involved in research. It may help to discuss your study with peers or have your supervisor review your research plan and data to see if they can identify any possible bias.

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Before you start any study involving people or animals, make sure you meet the ethical considerations in research methodology along with the requisite approvals from respective review boards. It is important to respect the rights of the subjects with regards to informed consent, privacy, and confidentiality. Create detailed and well-designed research plans, taking help from your mentor or supervisor if needed, that reduce harm to the subjects and maximize benefits both for the participants and those conducting the research. Similarly, researchers working with animals must get the necessary permissions and make sure they are properly cared for.

One of the key ethical considerations in research is ensuring the manuscripts you submit to journals are original and have not been published before or submitted elsewhere. Researchers who intentionally submit a paper to multiple journals are seen as breaching the basic standards and ethical considerations in research. In fact, authors are required to disclose details of related or similar papers at the time manuscript submission. This holds true even of the paper is in another language or has been published only in a particular region.

Similarly, researchers must avoid “slicing” their manuscript into segments for publication in different journals to boost their publication output as it is considered unethical. As a rule, if the “slices” of study share the same aim, methodology, and study group it must be submitted as a single manuscript and should never be broken down or published separately.

Understanding and following these ethical considerations in research goes a long way in ensuring that your work earns the trust and support of your peers, supervisors, and the wider community. However, this is far easier said than done. Fortunately, today there are trusted AI writing tools like Paperpal that can make your journey a smoother one.  

Make your manuscript submission ready with Paperpal

Manuscript submission is one of the most important steps in the publication journey, and you need to make sure you’ve covered all the set ethical guidelines. Here, it’s not unrealistic to be tired or even frustrated with the many small but essential checks required when preparing your research manuscript for journal submission. This is where Paperpal comes in, with a full suite of language and technical checks to help move your manuscript closer to journal acceptance.  

Paperpal is a comprehensive AI academic writing tool that is tailored to support students and researchers worldwide achieve high-quality content in half the time. Based on over 21 years of STM expertise and trained on millions of language corrections by leading academic editors across subject areas, Paperpal can quickly grasp academic context and provide accurate suggestions to improve your writing quality.  

The Paperpal Prime subscription is the most effective AI solution for academics, offering unlimited language checks, paraphrasing support, consistency checks, as well as a trusted online plagiarism checker and a suite of 30+ checks to ensure your manuscript is submission ready. Supercharge your writing and effortlessly deliver high-quality writing that has the best change of publication success. 

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Ethical considerations in research are important to ensure the protection of participants’ rights, well-being, and dignity. Ethical guidelines help researchers maintain integrity, promote fairness, and minimize harm. By following ethical principles, such as obtaining informed consent, ensuring participant confidentiality, and conducting research with integrity, researchers uphold the ethical standards necessary for trustworthy and responsible research. Ethical considerations also contribute to the credibility and reliability of research outcomes and help build public trust in the scientific community.

Researchers can protect participant confidentiality by implementing various measures. These include obtaining informed consent regarding data confidentiality, using anonymization techniques to remove personal identifiers, securely storing and transmitting data, and restricting access to sensitive information. Researchers must adhere to legal and ethical obligations to safeguard participants’ privacy and confidentiality. Additionally, when reporting research findings, researchers should use aggregated data or pseudonyms to further protect participant identities. By prioritizing participant confidentiality, researchers demonstrate respect for individuals’ privacy rights and foster trust in the research process.

Researchers obtain informed consent by providing participants with clear and comprehensive information about the research study. This includes explaining the purpose, procedures, potential risks, benefits, and any alternatives available. Participants must have the opportunity to ask questions and fully understand the implications of their participation before providing voluntary and informed consent. Researchers should document the consent process through written consent forms or other appropriate means, ensuring that participants have freely given their consent and have the option to withdraw at any time without repercussions.

• Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct , Institute of Medicine National Research Council of the National Academics, 2002. https://nap.nationalacademies.org/catalog/10430/integrity-in-scientific-research-creating-an-environment-that-promotes-responsible

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• Ethical Considerations in Research | Types & Examples

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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Ethical Considerations in Decision-Making Essay

Ethics plays an important role in our decision-making process, be it individually or collectively in an organizational context. Ethics deals with knowing what is wrong and what is right. Thus, it involves analyzing ethical decisions, beliefs, and actors inline with different activities. Recognizing the risks of poor decision-making can prevent ethical issues that arise in our daily life or career.

In this light, this paper focuses on the attributes of poor decision making, how to resist unethical acts, and the essential components of ethical leadership.

Decision-making entails reducing uncertainty about many alternatives, which allows the decision maker to make the best choice. However, several people are not good in decision-making as they believe, and the few who set goals do not achieve them.

According to Mallor et al (2010), the three common characteristics of poor decision-making are failing to remember objectives, overconfidence, and complexity of issues. It is easy for people to set goals and not achieve anything.

The reason is that they set them, but do not do anything to make sure that their activities do not deviate from the set goals. After setting the goals, managers fail to remember them on daily basis and thus, they make no progress.

Similarly, overconfidence causes people to overvalue their knowledge and underestimate the risks in decision-making. Many decision makers think that if they are able to accomplish their goals before without much effort, then they are too confident that they will achieve them without working hard or considering other alternatives.

Complexity of issues is another cause of poor decision-making. As the issues become more complex, it is not easy to come up with meaningful and best solutions. There is a possibility of ignoring some important issues and considering the simple and less important ones.

Resisting suggestions to act unethically is helpful in avoiding the causes of poor decision-making. First, finding mentors and peer support group is essential in resisting unethical acts. Individuals in these groups will be able to share information that relates to their work, and discuss on many matters such as the code of ethics.

Second, the team members can forward their concern to the authority about any unethical matters. Individuals should work with the firm to stop unethical behavior where they report such matters to the top management.

Lastly, recognition of unethical requests and people is important in this sense. When team members are taught on how to deal with unethical issues in their daily activities, they will be able to tell between both ethical and unethical issues (Mallor et al., 2010).

In this regard, there are many ways to act ethically as a leader in an organization. First, the leader should put the organizations interest first. This means that the leader should listen to the other team members and more so give them more power in decision making. In other words, he should leave his ego and his self-interest behind and do what is best for the firm. A good leader should implement ways in which those who are under him can question his authority just in case he acts unethically.

Additionally, participative decision-making is the best rather than autocratic leadership because the other group members will be able to give more information and thus, it is easy to make decisions. The group members will have a feel of ownership in making decisions and more so in areas that affect them and thus, become more productive.

Gaylord et al (2009) suggests that a leader must also strive to become interpersonally competent. He should learn to understand more on body language and facial expressions, which could have many meanings. Communication and good listening skills are also important because the leader can understand the team members better. However, before trying to understand others, he should first have self-understanding.

In conclusion, ethical consideration takes an important part in decision-making. Understanding and avoiding the major characteristics of poor decision-making, including failing to remember goals, overconfidence, and complexity of issues provides an avenue for solving ethical problems.

As a leader, it is therefore important to find help from support groups, work with organization, and recognize suspicious activities in order to resist unethical acts. Finally, a good leader must first consider organization’s interest, apply participative decision-making, and practice interpersonal competency to lead ethically.

Gaylord, A., Jentsz, Miller, R. L., Rank B. C. (2009). Business Law: Text and Summarized Cases: Legal, Ethical, Global and E-Commerce Environment . Cengage Learning. New York.

Mallor, J.P., Barnes, A.J., Bowers, T., & Langvardt, A.W. (2010). Business Law: The Ethical, Global, And Ecommerce Environment (14th ed.). New York: Irwin/McGraw Hill.

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Teachers are using AI to grade essays. But some experts are raising ethical concerns

W hen Diane Gayeski, a professor of strategic communications at Ithaca College, receives an essay from one of her students, she runs part of it through ChatGPT, asking the AI tool to critique and suggest how to improve the work.

“The best way to look at AI for grading is as a teaching assistant or research assistant who might do a first pass … and it does a pretty good job at that,” she told CNN.

She shows her students the feedback from ChatGPT and how the tool rewrote their essay. “I’ll share what I think about their intro, too, and we’ll talk about it,” she said.

Gayeski requires her class of 15 students to do the same: run their draft through ChatGPT to see where they can make improvements.

The emergence of AI is reshaping education, presenting real benefits, such as automating some tasks to free up time for more personalized instruction, but also some big hazards, from issues around accuracy and plagiarism to maintaining integrity.

Both teachers and students are using the new technology. A report by strategy consultant firm Tyton Partners, sponsored by plagiarism detection platform Turnitin, found half of college students used AI tools in Fall 2023. Meanwhile, while fewer faculty members used AI, the percentage grew to 22% of faculty members in the fall of 2023, up from 9% in spring 2023.

Teachers are turning to AI tools and platforms — such as ChatGPT, Writable, Grammarly and EssayGrader — to assist with grading papers, writing feedback, developing lesson plans and creating assignments. They’re also using the burgeoning tools to create quizzes, polls, videos and interactives to up the ante” for what’s expected in the classroom.

Students, on the other hand, are leaning on tools such as ChatGPT and Microsoft CoPilot — which is built into Word, PowerPoint and other products.

But while some schools have formed policies on how students can or can’t use AI for schoolwork, many do not have guidelines for teachers. The practice of using AI for writing feedback or grading assignments also raises ethical considerations. And parents and students who are already spending hundreds of thousands of dollars on tuition may wonder if an endless feedback loop of AI-generated and AI-graded content in college is worth the time and money.

“If teachers use it solely to grade, and the students are using it solely to produce a final product, it’s not going to work,” said Gayeski.

The time and place for AI

How teachers use AI depends on many factors, particularly when it comes to grading, according to Dorothy Leidner, a professor of business ethics at the University of Virginia. If the material being tested in a large class is largely declarative knowledge — so there is a clear right and wrong — then a teacher grading using the AI “might be even superior to human grading,” she told CNN.

AI would allow teachers to grade papers faster and more consistently and avoid fatigue or boredoms, she said.

But Leidner noted when it comes to smaller classes or assignments with less definitive answers, grading should remain personalized so teachers can provide more specific feedback and get to know a student’s work, and, therefore, progress over time.

“A teacher should be responsible for grading but can give some responsibility to the AI,” she said.

She suggested teachers use AI to look at certain metrics — such as structure, language use and grammar — and give a numerical score on those figures. But teachers should then grade students’ work themselves when looking for novelty, creativity and depth of insight.

Leslie Layne, who has been teaching ChatGPT best practices in her writing workshop at the University of Lynchburg in Virginia, said she sees the advantages for teachers but also sees drawbacks.

“Using feedback that is not truly from me seems like it is shortchanging that relationship a little,” she said.

She also sees uploading a student’s work to ChatGPT as a “huge ethical consideration” and potentially a breach of their intellectual property. AI tools like ChatGPT use such entries to train their algorithms on everything from patterns of speech to how to make sentences to facts and figures.

Ethics professor Leidner agreed, saying this should particularly be avoided for doctoral dissertations and master’s theses because the student might hope to publish the work.

“It would not be right to upload the material into the AI without making the students aware of this in advance,” she said. “And maybe students should need to provide consent.”

Some teachers are leaning on software called Writable that uses ChatGPT to help grade papers but is “tokenized,” so essays do not include any personal information, and it’s not shared directly with the system.

Teachers upload essays to the platform, which was recently acquired by education company Houghton Mifflin Harcourt, which then provides suggested feedback for students.

Other educators are using platforms such as  Turnitin  that boast plagiarism detection tools to help teachers identify when assignments are written by ChatGPT and other AI. But these types of detection tools are far from foolproof; OpenAI shut down its own AI-detection tool last year due to what the company called a “low rate of accuracy.”

Setting standards

Some schools are actively working on policies for both teachers and students. Alan Reid, a research associate in the Center for Research and Reform in Education (CRRE) at Johns Hopkins University, said he recently spent time working with K-12 educators who use GPT tools to create end-of-quarter personalized comments on report cards.

But like Layne, he acknowledged the technology’s ability to write insightful feedback remains “limited.”

He currently sits on a committee at his college that’s authoring an AI policy for faculty and staff; discussions are ongoing, not just for how teachers use AI in the classroom but how it’s used by educators in general.

He acknowledges schools are having conversations about using generative AI tools to create things like promotion and tenure files, performance reviews, and job postings.”

Nicolas Frank, an associate professor of philosophy at University of Lynchburg, said universities and professors need to be on the same page when it comes to policies but need to stay cautious .

“There is a lot of danger in making policies about AI at this stage,” he said.

He worries it’s still too early to understand how AI will be integrated into everyday life. He is also concerned that some administrators who don’t teach in classrooms may craft policy that misses nuances of instruction.

“That may create a danger of oversimplifying the problems with AI use in grading and instruction,” he said. “Oversimplification is how bad policy is made.”

To start, he said educators can identify clear abuses of AI and begin policy-making around those.

Leidner, meanwhile, said universities can be very high level with their guidance, such as making transparency a priority — so students have a right to know when AI is being used to grade their work — and identifying what types of information should never be uploaded into an AI or asked of an AI.

But she said universities must also be open to “regularly reevaluating as the technology and uses evolve.”

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Developmental, Cultural, and Ethical Considerations for Corporal Punishment.

Introduction.

Child discipline using corporal punishment raises developmental, cultural, ethical, and legal difficulties based on personal and social norms. This essay uses developmental psychology, cultural studies, ethics, and law to study child corporal punishment. Understand discipline impacts in light of child development. Culture shapes parenting and corporal punishment. Ethics and law define the appropriate discipline based on child rights and wellbeing. To study child discipline’s corporal punishment challenges, this essay investigates these interwoven aspects, including personal beliefs and professional ethics.

Developmental Considerations

Developmental stages affect how children view and respond to discipline, especially corporal punishment. Younger children may not grasp physical discipline due to cognitive maturity. They may find it arbitrary or confusing, generating fear, uncertainty, and distress rather than understanding their wrongdoing. Research shows that physical punishment damages children’s mental and emotional development (Durrant, 2008). The child may model aggressive conflict resolution, increasing antagonism. Corporal punishment can also lower self-esteem and social confidence. Adolescents face parents and authoritative adults throughout identity exploration and assertion.

Punishment during this stage may cause parent-child conflict and rebellion. Conflicts can damage relationships and communication. Continuous physical discipline may make teenagers resentful and unfair, affecting their emotional well-being and coping skills (Henderson & Thompson, 2016). Caregivers and social workers must emphasize communication, positive reinforcement, and non-violent conflict resolution to support cognitive and emotional development in children and adolescents.

Cultural Considerations

Different societies see and practice corporal punishment differently due to culture. Spanking is rooted in many cultures and religions. Because of the biblical phrase “Spare the rod, spoil the child,” various civilizations adopt physical punishment for discipline. Some generations and communities use this term to justify corporal punishment, while others consider it a relic of the past that no longer applies to modern child-rearing. Culture influences parenting with varied disciplining styles (Lansford & Dodge, 2008). Authoritarian cultures may believe that physical punishment teaches children discipline and respect. Collectivism and harmony-focused cultures may favor non-violent discipline emphasizing communication, negotiation, and positive reinforcement.

Social workers helping diverse families must grasp these cultural disparities. They must know these differences and understand that discipline varies by circumstance. Social professionals need cultural competence to match their interventions and advice to families’ values (Lansford & Dodge, 2008). Social workers can help families build culturally sensitive discipline techniques that benefit the child’s well-being by understanding and accepting these cultural distinctions.

Ethical & Legal Considerations

The ethics of physical punishment include protecting children’s rights and welfare. UNCRC promotes children’s right to protection from bodily or mental damage, including corporal punishment. It stresses the significance of a safe, supportive environment for child development. Social workers’ ethics demand that they put kids first. It means supporting non-violent discipline that develops children (Miller-Perrin & Rush, 2018). Positive and constructive discipline promotes the ethical need to protect children’s physical and mental health. Cultural norms and values influence corporal punishment laws worldwide. Some countries ban home and school physical punishment, while others allow it within limitations. Based on ethics, social workers should promote children’s rights and well-being. Advocate for UNCRC-aligned legislation and policies that ban physical punishment and encourage healthy child development through non-violent discipline.

In conclusion, corporal punishment discourse is complicated and needs analysis. Culture, personal experiences, and social norms shape discipline perspectives. However, social workers and caretakers must research these connections and grasp corporal punishment’s effects on children. Open communication, empathy, and understanding are essential for positive discipline. According to research, love, respect, and being heard and understood promote discipline, emotional intelligence, and problem-solving in children.

Miller-Perrin, C., & Rush, R. (2018). Attitudes, knowledge, practices, and ethical beliefs of psychologists related to spanking: A survey of American Psychological Association division members. Psychology, Public Policy, and Law, 24(4), 405–417.

Lansford, J. E., & Dodge, K. A. (2008). Cultural Norms for Adult Corporal Punishment of Children and Societal Rates of Endorsement and Use of Violence. Parenting, 8(3), 257–270.

Durrant, J. E. (2008). Physical Punishment, Culture, and Rights: Current Issues for Professionals. Journal of Developmental & Behavioral Pediatrics 29(1):55-66.

Henderson, D. A., & Thompson, C. L. (2016). Counseling Children [PDF]. Vdoc.pub.

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Essay On Ethical Considerations

Type of paper: Essay

Topic: Health , Nursing , Health Care , Ethics , Allocation , Patient , Insurance , Policy

Published: 09/19/2022

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There are many ethical considerations that have to be made before deciding whether or not a patient is warranted long term or short term care. Short term health care is usually offered by private insurance companies for duration of time up to six months. Long term health care on the other hand is also called nursing home care. This is usually for the elderly seeing as costs in homes have gone up most people prefer to take out long term insurance (Ruth Ludwick, 2003). The age of the patient is taken into consideration with the very elderly not recommended for the short term insurance. The health status of the patient is also taken into consideration as an ethical issue. Most short term health care is not for the critically ill (Asher, 2010). Optional benefits you expect from the insurance cover. Micro allocation of health care refers to making decisions on how to utilize limited resources when the demand surpasses the supply. It is faced by many ethical conflicts; one being the political approach of allocation. The health care facility would prefer to spend its resources to save more patients at the expense of one patient. Another ethical consideration is whether one should receive resources on the first come first served basis or those in greater need should be treated before. The urgency of the treatment and the probability that it will work are other ethical considerations to be made. The micro allocation policy by the health care facility on micro allocation affects a facilities long term policy (Michael nd). It would mean that the long term policy will be raised for those with scarce resources and the cover may not meet all the required needs.

Asher, J. P. (2010). The Right to Health: A Resource Manual for NGOs. Martinus Nijhoff Publishers. Michael A. Gillette, P. (n.d.). Introduction to Micro Allocation. Bioethical services . Ruth Ludwick, P. R. (2003). Ethics. Online Journal of Nursing .

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StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

StatPearls [Internet].

Nursing ethical considerations.

Lisa M. Haddad ; Robin A. Geiger .

Affiliations

Last Update: August 14, 2023 .

• Definition/Introduction

Ethical values are essential for any healthcare provider. Ethics comes from the Greek word “ethos,” meaning character. Ethical values are universal rules of conduct that provide a practical basis for identifying what kinds of actions, intentions, and motives are valued. [1]  Ethics are moral principles that govern how the person or a group will behave or conduct themselves. The focus pertains to the right and wrong of actions and encompasses the decision-making process of determining the ultimate consequences of those actions. [2]  Each person has their own set of personal ethics and morals. Ethics within healthcare are important because workers must recognize healthcare dilemmas, make good judgments and decisions based on their values while keeping within the laws that govern them. To practice competently with integrity, nurses, like all healthcare professionals, must have regulation and guidance within the profession. [3]  The American Nurses Association (ANA) has developed the Code of Ethics for this purpose.

• Issues of Concern

The onset of nursing ethics can be traced back to the late 19 century. At that time, it was thought that ethics involved virtues such as physician loyalty, high moral character, and obedience. [3]  Since that early time, the nursing profession has evolved, and nurses are now part of the healthcare team and are patient advocates. The first formal Code of Ethics to guide the nursing profession was developed in the 1950’s. Developed and published by the ANA, it guides nurses in their daily practice and sets primary goals and values for the profession. Its function is to provide a succinct statement of the ethical obligations and duties of every individual who enters the nursing profession. It provides a nonnegotiable ethical standard and is an expression of nursing’s own understanding of its commitment to society. The Code of Ethics has been revised over time. The current version represents advances in technology, societal changes, expansion of nursing practice into advanced practice roles, research, education, health policy, and administration, and builds and maintains healthy work environments. [3]

The Code of Ethics for Nurses is divided into nine provisions to guide the nurse. The following is a summary of the American Nurses Association Code of Ethics for Nurses: 

Provision 1. The nurse practices with compassion and respect for the inherent dignity, worth, and unique attributes of every person. 

The nurse must have a high level of respect for all individuals, and allow dignity in regards to dealings in care and communication. It's important that patient's families are also treated with respect for their relationship to the patient. Nurses must understand the professional guidelines in communications and work with colleagues and patient families. It's important to understand the proper professional relationship that should be maintained with families and patients. All individuals, whether patients or co-workers have the right to decide on their participation in care and work.

Provision 2. The nurse’s primary commitment is to the patient, whether an individual, family, group, community, or population.

The patient should always be a first and primary concern. The nurse must recognize the need for the patient to include their individual thought into care practices. Any conflict of interest, whether belonging to external organizations, or the nurse's habits or ideals that conflict with the act of being a nurse, should be shared and addressed to not impact patient care. Collaboration with internal and external teams to foster best patient care is a necessity. Understanding professional boundaries and how they relate to patient care outcomes is important.

Provision 3. The nurse promotes, advocates for, and protects the rights, health, and safety of the patient.

It is important for the nurse to understand all privacy guidelines with regards to patient care and patient identifiers. Nurses involved in research must understand all aspects of participation including informed consent and full disclosure to the patient of all aspects required to participate in the study. The nurse must understand any institutional standards set in place to review his/her performance; this includes measurements of progress and the need for further review or study to meet performance standards. To become a nurse, competence must be demonstrated in clinical and documentation prowess. Standards of competence will continue at institutions and academic organizations that employ the nurse. If there is witness or recognition of questionable healthcare practice, it is important that the patient is protected by reporting any misconduct or potential safety concern. And finally, the nurse will not provide patient care while under the influence of any substance that may impair thought or action, this includes prescription medication.

Provision 4 . The nurse has authority, accountability, and responsibility for nursing practice; makes decisions; and takes action consistent with the obligation to provide optimal patient care.

As a nurse, it's inherent that accountability for all aspects of care aligns with responsible decision making. Use of authority must be professional and about all aspects of individualism and patient, ethical concerns. Nursing decisions must be well thought, planned, and purposefully implemented responsibly. Any delegation of nursing activities or functions must be done with respect for the action and the ultimate results to occur. 

Provision 5 . The nurse owes the same duties to self as to others, including the responsibility to promote health and safety, preserve wholeness of character and integrity, maintain competence, and continue personal and professional growth.

A nurse must also demonstrate care for self as well as others. An ideal nurse, will have self-regard towards healthcare practices and uphold safe practice within the care setting and at home. It's important for a nurse to have a high regard for care as an overall inert ability once the profession is entered. A character becoming a nurse would include integrity. Nurses should be concerned for personal growth in regards to continued learning of the profession. The ability to grow as a nurse with improvements to care, changes or trends in care should be adapted to maintain competence and allow growth of the profession.

Provision 6. The nurse, through individual and collective effort, establishes, maintains, and improves the ethical environment of the work setting and conditions of employment that are conducive to safe, quality health care.

As a nursing profession, standards should be outlined within and external to institutions of work that dictate ethical obligations of care and need to report any deviations from appropriateness. It's important to understand safety, quality and environmental considerations that are conducive to best patient care outcomes.

Provision 7 . The nurse, in all roles and settings, advances the profession through research and scholarly inquiry, professional standards development, and the generation of both nursing and health policy.

Nurse education should include principles of research, and each nurse should understand how to apply scholarly work and inquiry into practice standards. Nurse committees and board memberships are encouraged to contribute to health policy and professional standards. The ability to maintain professional practice standards should continue, changing and enhancing as developments in practice may over time.

Provision 8. The nurse collaborates with other health professionals and the public to protect human rights, promote health diplomacy, and reduce health disparities. 

Through collaboration within the discipline, maintaining the concept that health is a right for all individuals will open the channels of best practice possibilities. The nurse understands the obligation to continue to advance care possibilities by committing to constant learning and preparation. The ability of the nurse to practice in various healthcare settings may include unusual situations that require continued acts of diplomacy and advocacy.

Provision 9. The profession of nursing, collectively through its professional organization, must articulate nursing values, maintain the integrity of the profession, and integrate principles of social justice into nursing and health policy.

Nurses must continue to gather for committees and organize groups where they may share and evaluate values for accuracy and continuation of the profession. It is within these organizations that nurses may join in strength to voice for social justice. There is a need for continued political awareness to maintain the integrity of the nursing profession. The ability of the nurse to contribute to health policy should be shared among the profession, joining nurses throughout the world for a unified voice.

American Nurses Association. (2015). Code of ethics with interpretative statements. Silver Spring, MD

• Clinical Significance

Ethical values are essential for all healthcare workers. Ethical practice is a foundation for nurses, who deal with ethical issues daily. Ethical dilemmas arise as nurses care for patients. These dilemmas may, at times, conflict with the Code of Ethics or with the nurse's ethical values. Nurses are advocates for patients and must find a balance while delivering patient care. There are four main principles of ethics: autonomy, beneficence, justice, and non-maleficence.

Each patient has the right to make their own decisions based on their own beliefs and values. [4] . This is known as autonomy. A patient's need for autonomy may conflict with care guidelines or suggestions that nurses or other healthcare workers believe is best. A person has a right to refuse medications, treatment, surgery, or other medical interventions regardless of what benefit may come from it. If a patient chooses not to receive a treatment that could potentially provide a benefit, the nurse must respect that choice.

Healthcare workers have a duty to refrain from maltreatment, minimize harm, and promote good towards patients. [4]  This duty of particular treatment describing beneficence. Healthcare workers demonstrate this by providing a balance of benefits against risks to the patient. Assisting patients with tasks that they are unable to perform on their own, keeping side rails up for fall precautions, or providing medications in a quick and timely manner are all examples of beneficence.

All patients have a right to be treated fair and equally by others. Justice involves how people are treated when their interest competes with others. [5] . A current hot topic that addresses this is the lack of healthcare insurance for some. Another example is with patients in rural settings who may not have access to the same healthcare services that are offered in metropolitan areas.

Patients have a right to no harm. Non-maleficence requires that nurses avoid causing harm to patients. [6]  This principle is likely the most difficult to uphold. Where life support is stopped or patients have chosen to stop taking medication that can save their lives, the nurse is put in a morally challenging position.

Nurses should know the Code of Ethics within their profession and be aware and recognize their own integrity and moral character. Nurses should have a basic and clear understanding of key ethical principles. The nursing profession must remain true to patient care while advocating for patient rights to self-identify needs and cultural norms. Ethical considerations in nursing, though challenging, represent a true integration of the art of patient care.

Nurses have a responsibility to themselves, their profession, and their patients to maintain the highest ethical principals. Many organizations have ethics boards in place to review ethical concerns. Nurses at all levels of practice should be involved in ethics review in their targeted specialty area. It is important to advocate for patient care, patient rights, and ethical consideration of practice. Ethics inclusion should begin in nursing school and continue as long as the nurse is practicing.

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Disclosure: Lisa Haddad declares no relevant financial relationships with ineligible companies.

Disclosure: Robin Geiger declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Haddad LM, Geiger RA. Nursing Ethical Considerations. [Updated 2023 Aug 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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The Pros and Cons of Abortion

This essay about the complexities of abortion examines ethical, psychological, and societal aspects of the issue. It addresses the clash between personal autonomy and societal responsibility, ethical concerns surrounding the status of the fetus, and the psychological toll abortion can take on individuals. Additionally, it explores the broader societal implications, including the unequal distribution of abortion services and the demographic consequences. Through fostering dialogue and understanding, it advocates for navigating this complex issue with empathy and compassion.

How it works

Abortion stands at the crossroads of deeply-held convictions, where the clash between personal autonomy and societal responsibility gives rise to a myriad of ethical, psychological, and societal considerations. While proponents advocate for women’s rights and reproductive freedom, the landscape of abortion cons presents a tapestry of moral quandaries and societal implications that cannot be overlooked. This essay embarks on a journey through the intricate terrain of abortion cons, delving into the ethical complexities, potential psychological reverberations, and broader societal concerns that shape this polarizing issue.

The Ethical Quandary: Central to the abortion debate lies the ethical quandary surrounding the status of the fetus and the rights it may possess. Critics argue vehemently that abortion undermines the sanctity of life, representing a profound violation of human dignity and the intrinsic value of every individual. They contend that the deliberate termination of a developing life raises fundamental questions about the moral obligations we owe to the most vulnerable members of society.

Moreover, the practice of selective abortion, driven by factors such as gender, disability, or socioeconomic status, exacerbates ethical concerns, challenging notions of equality and justice. The notion of selectively choosing which lives are deemed worthy of continuation raises troubling ethical dilemmas, calling into question the very essence of human rights and the principles upon which they are founded.

Navigating the Psychological Terrain: Beyond the realm of ethics, the psychological ramifications of abortion cast a long shadow, with individuals often grappling with a complex array of emotions in the aftermath of the procedure. While advocates emphasize the importance of reproductive autonomy and freedom from unwanted pregnancies, it is crucial to acknowledge the psychological toll that abortion can exact on individuals.

Research underscores the diverse emotional responses to abortion, with some individuals experiencing feelings of guilt, grief, and regret in the wake of their decision. The existential reckoning precipitated by the termination of a pregnancy forces individuals to confront profound moral questions, often leading to a period of introspection and soul-searching. Furthermore, societal stigma surrounding abortion amplifies these psychological burdens, perpetuating a culture of shame and silence that isolates those who have undergone the procedure.

Societal Implications: The reverberations of the abortion debate extend far beyond individual choices, resonating throughout society and giving rise to broader societal implications. Critics argue that widespread access to abortion threatens the fabric of society, desensitizing individuals to the value of human life and eroding the moral foundations upon which society rests. Moreover, concerns have been raised about the demographic consequences of abortion, particularly in regions where it is utilized as a form of population control.

Furthermore, the unequal distribution of abortion services exacerbates existing socioeconomic disparities, disproportionately affecting marginalized communities with limited access to healthcare resources. This perpetuates cycles of inequality and injustice, deepening the fault lines of social division and exacerbating structural inequities.

Conclusion: In conclusion, the debate over abortion is a complex and multifaceted discourse, characterized by divergent perspectives and deeply-held convictions. While proponents advocate for women’s rights and reproductive autonomy, it is imperative to engage with the legitimate concerns raised by abortion cons. By fostering open dialogue, empathy, and understanding, we can navigate this complex terrain with nuance and compassion, striving towards solutions that uphold the dignity and well-being of all individuals involved.

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