Ethical Considerations in Research: The Complete 2026 Guide for Scholars
You have spent months, maybe even years, planning your research for your PhD. You are confident about your research topic, methodology, and contribution to the field. But are you sure about the ethical validity of your research?
Ethical research is a distant thought for many PhD research scholars in India, a formality that needs to be filled in, a box that needs to be ticked. This, however, can prove to be a costly oversight for you as a research scholar in India, as you can be forced to withdraw your thesis, get your research paper retracted from a journal, or even risk your academic career as a whole.
This guide will discuss all ethical considerations in research for your PhD, not theoretically, but practically, which you can apply from your next research session itself, as well as how the ICMR, the Belmont report, and the Helsinki declaration apply to you as a research scholar in India.
What Are Ethical Considerations in Research?
According to Bryman and Bell (2007), “A set of ethical considerations is a group of principles which guarantee research is carried out honestly, respectfully, and responsibly toward individuals, institutions, and the scientific community.” These ethical considerations are not optional. They are part of the submission guidelines of every respectable research journal, every PhD viva examination, and every ethics review committee in India and across the world.
Ethical research, as per the National Research Council of the National Academies, is “A series of good practices including intellectual honesty in performing and reporting research, fairness in peer review, candor in communication, collegiality in scientific interaction, and protection and care of human and animal subjects.” In other words, “It is as important how research is carried out as what is discovered.”
The most important codes of governance in research ethics in India are the ICMR National Ethical Guidelines for Biomedical and Health Research Involving Human Participants (2017), and the UGC research ethics guidelines for social sciences research. For international publications, the Declaration of Helsinki (1964, revised in 2013) and the Belmont Report (1979) are the universally accepted codes of ethics.
8 Core Ethical Considerations in Research
The following are the eight areas, which encompass the whole ethical domain of doctoral research, based on the three ethical principles of respect for persons, beneficence, and justice, as outlined in the Belmont Report, and applicable both in India and internationally.
Informed consent is not a form; it is a process. Informed consent starts from the moment you first contact a prospective participant and continues until the participant leaves the study. According to the ICMR National Ethical Guidelines, informed consent upholds the value of individual autonomy, which is the participant’s right to make a free and unhindered decision about whether or not to participate in the research.
1. Informed Consent — The Non-Negotiable Foundation
For consent in a PhD research to be valid, it must be voluntary, informed, free from coercion, and capacitated in the following ways:
- Voluntary: There must be no pressure, inducement, or coercion in the process. Participants must be made aware that they can withdraw from the study at any given time without negative consequences on the relationship with you.
- Informed: The process, risks, potential benefits, and data use, including any confidentiality arrangements, are clearly explained in a way that the person being asked to participate will understand.
- Competent: The consenting individual must be competent to consent. This means if they are a child under 18 years of age, cognitively impaired, or in a dependency situation with the researcher, consent must be obtained from a legally competent person and assent from the participant if they are competent to consent to the research.
- Ongoing: Ongoing consent is required if there is a significant change to the research.
Where PhD candidates most commonly go wrong: Consent forms written at a postgraduate reading level for participants who are members of the public; lack of provision for participants to withdraw from the research; assumption of tick box consent for an online survey; and lack of consideration of the power dynamics if the lecturer and/or employer is also the researcher.
2. Ethics Committee / IRB Approval — Before You Collect a Single Data Point
In India, all universities require formal ethical clearances from an Institutional Ethics Committee (IEC) or Institutional Review Board (IRB) before any research involving human participants, animals, or personal data can begin. This is not a formal requirement, but it is a prerequisite. Ethics clearances applied for when data collection is already in progress are almost universally denied.
There are three levels of review, and you must understand which of these levels applies to your research.
- Exempt Review: This is for minimal risk anonymous surveys of adults. The critical point is that even for exempt review, self-determination of exemption is not allowed.
- Expedited Review: This is for research of modest risk, reviewed by a single reviewer. This is usually for research using existing data, small biological samples, or non-sensitive interviews.
- Full Board Review: This is for research of more than minimal risk, vulnerable participants, deception, or investigational treatments. The full board of reviewers will review this.
Your ethics application must address: the scientific rationale for the study; recruitment methods and criteria; specific risks and how you will mitigate them; copies of all participant-facing documents; data management and storage protocols; and your plan for data retention and deletion after the research concludes.
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3. Privacy, Confidentiality, and Anonymity — Understanding the Differences
These three concepts are often confused with one another in the context of a PhD thesis. This has serious ethical and legal ramifications. This is the key difference between them:
| Concept | Description |
|---|---|
| Privacy | A participant's right to control their personal information and who they are willing to share it with. |
| Confidentiality | You know who participants are, but protect their identity in all reporting. The data is de-identified before it is analyzed or reported. |
| Anonymity | You never know who the participants are. You do not collect identifying information at any time. |
Practical steps to protect participants: use a coding system for participants at the point of collection; safely house the key; password-encrypt digital files so only approved researchers can access them; house physical documents safely; develop a timeline for the retention and eventual destruction of the documents (usually 5-10 years after publication). In a small-scale study, one hospital ward, one university department, be aware that even without name identifiers, individuals may still be identifiable through their role, gender, and level of experience. Scribbr (2024) states: “You can only be certain that your participants remain anonymous if you do not collect any personal identifying information from the start.”
4. Plagiarism and Academic Integrity — More Than Copy-Paste
One of the most important aspects of PhD research ethics is avoiding plagiarism; however, it’s also a complex issue that extends beyond the common understanding that it’s simply a case of ‘cut-and-paste’ for many PhD scholars. Paperpal (2023) states that one of the primary reasons for plagiarism is that many scholars often plagiarize due to a lack of understanding rather than any intention to plagiarize. The five types of plagiarism that every PhD scholar should understand are:
Direct Plagiarism: When a scholar copies someone’s work word for word without using quotes.
Paraphrasing Plagiarism: When a scholar fails to cite a piece of work that they have paraphrased.
Mosaic Plagiarism: When a scholar combines quotes from multiple sources without citing the sources.
Self-Plagiarism: When a scholar re-uses a large part of their previously published work.
Idea Plagiarism: When a scholar uses another scholar’s research design or theoretical framework without citing the scholar’s work.
Best practice: be consistent with citations throughout all chapters, not just the literature review. Keep a research journal from day one, so you can track the origin of every idea. If you are using sections from your existing conference papers or preprints, you should admit this in the introduction of your thesis.
5. Research Integrity — Fabrication, Falsification, and Honest Reportin
The two most serious research violations in academic research are fabrication, which entails making up results or information that was never observed or measured, and falsification, which entails manipulating or changing research information to arrive at a predetermined conclusion. These are considered research misconduct, which can lead to criminal prosecution, not just academic punishment.
However, research integrity can also take on other, less obvious forms that PhD students should be on guard against, which include: selective presentation of results, where only statistically significant results are presented, with null results omitted; ‘p-hacking,’ or running multiple analyses on a dataset to arrive at a statistically significant result; and the use of ‘visualizations,’ or graphs, which are used to mislead about the relationship between variables.
Protection Strategy: Keeping a research diary in which you detail all of your research methodology, even when you deviate from your original plan, and considering registering your research on the Open Science Framework (OSF) to protect yourself against claims of research misconduct, as this will provide a ‘timestamped record’ of your research plan that can be publicly accessed in perpetuity.
6. Conflicts of Interest and Researcher Bias
Conflicts of interest occur when the researcher’s capacity to be objective may be, or may appear to be, compromised by their personal, financial, or professional interests. Conflicts of interest are more prevalent in research than most researchers are willing to admit, particularly in the case of PhD research.
Some of the common conflicts of interest that may occur in research include: the funding of the research by companies that have a vested interest in the outcome of the research; the recruitment of participants through the researcher’s social network; the researcher’s ideological commitment to the predetermined outcome of the research; and the researcher’s need to produce publishable research to attain academic promotions.
It is not the researcher’s ethical responsibility to eliminate conflicts of interest, as this may be impossible, but to disclose the conflicts of interest openly and transparently in the research thesis, research articles, and in any presentation of the research to the public. It is the responsibility of the ethics committee, the reviewers, and the examiners of the research to have the information to make their own judgment on whether the potential conflict of interest has compromised the researcher.
7. Duplicate Submission and Salami Slicing
As PhD students strive to get published, which is a requirement for thesis completion in Indian universities, two related hazards arise:
Duplicate Submission: Submitting a paper to more than one journal at a time is a breach of the intellectual property rights of the journal that you have initially sent your paper to. It is also a waste of time for the peer reviewers of both journals.
Salami Slicing: Breaking up a research paper into smaller publications to boost publication credentials is a breach of academic integrity. If you have multiple publications that have used the same participants, same primary data set, or same research hypothesis, you should submit all these publications as one paper. Before splitting a paper, you should always consult your supervisor; also, you should always disclose any prior dissemination of related work in your journal cover letter and thesis introduction.
8. Research Involving Vulnerable Populations
When it comes to research involving groups where the ability to give “full and voluntary informed consent” may be compromised, the guidelines and frameworks demand a higher ethical standard. The groups identified as “vulnerable groups” by the ICMR guidelines and other international guidelines include children and minors, where parental or guardian consent along with the assent of the minor, if old enough to understand, is required; individuals suffering from cognitive or mental health conditions; prisoners or individuals living within a closed environment; patients living in a relationship of dependence on the researcher; and economically disadvantaged groups, where monetary incentives may act as undue influence.
It is a requirement of researchers working within a vulnerable group to clearly justify the involvement of such groups within the research and to include additional safeguards within the research design. These include a lower threshold of risk, continuous monitoring of the participant for signs of distress, and referral pathways should a participant become distressed. Ethics committees will reject research proposals failing to address this requirement.
Emerging Ethical Challenges in 2026: AI Tools and Digital Data
The fast pace of development of AI writing tools, language models, and data analysis software is giving rise to a new class of ethical issues, which many of the existing institutional frameworks have not fully addressed. This is something PhD students need to proactively deal with.
Using AI Tools in Your PhD Research
Three areas of concern need to be addressed. First, authorship and attribution: if an AI tool is used to produce substantive text or other material that is incorporated into your thesis or research paper, what does it mean to assert sole individual authorship of a work—nowadays, most major journals demand explicit declarations of the use of AI tools and what they were used for and how their results were validated. Second, data integrity: it is possible for an AI tool to “hallucinate”—that is, produce citations, statistics, or other claims that are utterly fabricated. The inclusion of such material without explicit verification of its accuracy against primary sources constitutes a form of unintentional falsification. Third, originality risk: it is possible for an AI tool to include copyrighted material or paraphrase it and thus constitute plagiarism.
Current guidelines: Disclose all AI tools used and state how they were used. Also, verify every factual claim generated by AI against sources before presenting them. It is worth noting that different institutions have different guidelines on how to use AI. Check with your institution for its policy on AI.
Social Media and Digital Trace Data
Social media and digital trace data research present unique ethical concerns. The guiding ethical principle in this area of research is: Just because digital data is accessible does not mean it is ethical to use. Social media posters do so with a particular audience in mind (friends, expressing themselves to their community). Using their data for research is not what they signed up for. Moreover, there is a high risk of re-identification of digital trace data. Digital trace data may be anonymized, but with available data out there, it is possible to re-identify anonymized digital trace data. This has been shown in various publications. It would be wise to ensure that if you used secondary data, the original collection was done ethically and with consent for secondary use.
How to Write the Ethics Section of Your PhD Thesis
In most PhD theses, there is a section dedicated to ethics in Chapter 3: Research Methodology. This section should prove that you have adhered to the ethics requirements rather than simply making a statement that you have done so. You should use key words in your statement.
A good section on ethics should have seven parts:
- Ethical framework: List the frameworks that you have adopted for your research, with a brief explanation of each framework.
- Ethics approval: Specify the name of the body that approved your research study, the reference number for the approval, and the date on which the study was approved. The approval letter should also be attached as an appendix.
- Information provided to participants: You should specify exactly how you obtained participants’ information, with a brief explanation of the information sheet you used, the time participants were given to consider the information, and the methods you used for obtaining participants’ information.
- Participant protection: Elaborate on how privacy, confidentiality, and anonymity were ensured—not only that you had the intention to do so, but also how this was achieved.
- Risk assessment: Show evidence of a risk assessment and discuss how the design minimized the risks compared to the benefits.
- Positionality: Elaborate on the positionality of the researcher and whether there were any conflicts of interest, power relations between the participants and the researcher, and so on.
- Data management: Elaborate on how the data was managed, including storage and security, and the plans for the eventual destruction of the data.
Quick Reference: 8 Ethical Considerations at a Glance
| Consideration | Core Requirement | Where Candidates Go Wrong |
|---|---|---|
| Informed Consent | Voluntary, informed, competent, ongoing — documented in writing | Forms too complex; no withdrawal mechanism; power dynamics ignored |
| Ethics Approval | Obtain committee approval before any data collection begins | Collecting data first, then applying — almost always rejected |
| Privacy & Confidentiality | Remove identifiers; secure storage; defined retention timeline | Re-identification risk in small communities overlooked |
| Plagiarism Avoidance | Attribute every idea, phrase, and dataset that is not originally yours | Paraphrasing without citation; reusing own prior work undisclosed |
| Research Integrity | Report all findings honestly — including null results | Selective reporting; p-hacking; misleading graphs |
| Conflict of Interest | Disclose all funding, relationships, and personal stakes upfront | Assuming no financial payment means no conflict exists |
| Duplicate Submission | Submit to one journal at a time; disclose all prior dissemination | Submitting to multiple journals simultaneously |
| Vulnerable Populations | Enhanced consent, lower risk threshold, clear referral pathways | Applying standard adult consent to children or impaired individuals |
Frequently Asked Questions About Research Ethics in PhD
The eight core ethical considerations are: (1) informed consent, (2) ethics committee/IRB approval, (3) privacy and confidentiality, (4) plagiarism avoidance, (5) research integrity (no fabrication or falsification), (6) conflict of interest disclosure, (7) avoidance of duplicate submission or salami slicing, and (8) protection of vulnerable populations. Each is explained in depth in this guide.
Not necessarily — but you cannot self-declare exemption. If the dataset contains identifiable personal information, or if the original data collection consent does not explicitly cover your intended secondary use, you must seek formal exemption confirmation from your institution's ethics committee. For survey research, most Indian universities require at minimum an expedited review even for low-risk studies.
With anonymity, you never know the identity of participants — no identifying information is collected at any point. With confidentiality, you know who the participants are but take steps to remove or protect their identity in all reporting and publications. Anonymity offers stronger privacy protection but is harder to achieve. Confidentiality is more common in qualitative research where the researcher and participant interact directly.
Yes — but with full transparency. You must disclose which AI tools you used, the specific tasks they assisted with, and how their outputs were verified against primary sources. AI tools may not be listed as authors. Check your university's current AI use policy, as standards differ. Any AI-generated factual claim must be independently verified before inclusion, since AI models can and do fabricate plausible-sounding references.
Your ethics section should cover: the ethical framework you followed (e.g., ICMR guidelines, Belmont Report); your ethics committee approval details including the reference number and date; how informed consent was obtained and documented; specific measures taken to protect privacy and confidentiality; a risk assessment and mitigation plan; disclosure of any conflicts of interest; and your data management, storage, and destruction protocol.
A full board IEC review at an Indian university typically takes 4–12 weeks. Expedited reviews may be completed in 1–3 weeks. You should submit your ethics application well before your planned data collection start date — ideally at least 8 weeks ahead — and build this waiting period explicitly into your research timeline.
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