| Course | EDP 820 Ethics and Professional Standards in Psychology |
|---|---|
| Module | Module 7 |
| Paper type | Doctoral participant protection paper |
| Length | About 1,019 words, 6 pages |
| Format | APA 7 student paper |
| School | Aspen University |
| Program | Doctor of Education |
| Updated | October 2026 |
Free sample paper for EDP 820 Module 7
Cover Stories, Vulnerable Labels and Open Data: Protecting Participants in One Study
Student Name
Doctor of Education Program, Aspen University
EDP 820: Ethics and Professional Standards in Psychology
Instructor Name
Month Day, Year
Cover Stories, Vulnerable Labels and Open Data: Protecting Participants in One Study
Dr. Ellis, a faculty member in the composite Columbus university's psychology department, submitted a proposal to the review board on which Ruth serves. The study would recruit first-generation college students, tell them it concerns study habits, give them a difficult timed test while measuring heart rate and self-reported stress and then debrief them. Dr. Ellis plans to post the de-identified data, including age, gender, major, hometown, parents' education and employment and grades, in a public repository, following open science practice. Dr. Ellis and the proposal are imagined for this course. This paper presents the board's analysis.
Deception
Hertwig and Ortmann (2008) reviewed the arguments researchers use to defend deception in experiments. The main arguments are that deception is necessary to study some behaviors, that participants do not mind and that debriefing repairs any harm. The authors found evidence for each to be weaker than often claimed. Alternatives to deception exist for many questions. Participants who experience deception may become suspicious in later studies, which can compromise the validity of research using the same participant pool. And debriefing does not always undo false beliefs. They argued that deception should be used only when truly necessary.
Vulnerability
Levine et al. (2004) examined the concept of vulnerability in research ethics. Regulations and guidelines designate certain groups, such as children, prisoners and pregnant women, as vulnerable. The authors argued that the concept had become so broad that nearly everyone could be labeled vulnerable, and that labeling whole groups risks stereotyping them and excluding them from research that could benefit them. They suggested instead identifying the specific characteristics of a situation that create vulnerability, such as dependence on the researcher, limited capacity to consent or social disadvantage, and designing protections for those.
Re-identification
Rocher et al. (2019) developed a statistical model to estimate how likely it is that a person can be correctly re-identified from a dataset that has been stripped of names but retains demographic attributes. Applying it to population data, they estimated that fifteen demographic attributes would be enough to single out almost every American, more than 99.9 percent of them. Even datasets that are incomplete samples of a population offered limited protection. Their findings challenge the assumption that removing names makes data anonymous.
| Risk | In the proposal | Research | Safeguard |
|---|---|---|---|
| Deception | Cover story about study habits | Hertwig and Ortmann (2008) | Milder cover story: "how students respond to timed tests"; full debriefing |
| Stress | Difficult test induces stress | Levine et al. (2004): situational vulnerability | Right to stop; brief calming activity; resources |
| Situational vulnerability | Students worried about academic standing | Levine et al. (2004) | Guarantee results never shared with instructors |
| Re-identification | Hometown, major and parents' jobs in public data | Rocher et al. (2019) | Restricted repository access; coarsen variables |
| Exclusion | Labeling first-generation students vulnerable | Levine et al. (2004) | Include them, with targeted protections |
Applying the Analysis
Deception: the board asked whether a full cover story was necessary. Dr. Ellis argued that telling students the study measured stress would change their stress. The board agreed some concealment was justified but required a milder cover story that was true as far as it went, that the study concerns how students respond to timed tests, and immediate, thorough debriefing.
Vulnerability: first-generation students are not vulnerable as a group, and excluding or overprotecting them would deny them representation in research about their own experience. But specific circumstances create risk: some may worry that poor performance will be reported to instructors or affect their standing. The board required a written guarantee that results would never be shared with instructors and that participation had no bearing on grades.
Privacy: the planned public dataset combined hometown, major, parents' occupations and grades, attributes that together could identify individuals in a small population of first-generation students. Following Rocher and colleagues, the board required that data be deposited in a repository with controlled access, available to qualified researchers under a data use agreement, and that variables such as hometown be coarsened to region.
Balancing Protection and Open Science
Open data serves research integrity and lets others check findings. The board's safeguards preserve that value through controlled access rather than refusing to share data.
The Debriefing
Because the study withholds its full purpose, debriefing carries much of the ethical weight. Immediately after the test, a research assistant will explain the real purpose, why it was not disclosed in advance and how the stress measures will be used. Participants will be told that the test was designed to be difficult and that their scores say nothing about their ability. Hertwig and Ortmann (2008) noted that debriefing does not always correct false beliefs, so the assistant will ask participants to describe the study's purpose in their own words before they leave, correcting any misunderstanding. Participants may withdraw their data after debriefing, with no penalty.
Including First-Generation Students
One board member suggested excluding first-generation students as a vulnerable group. Ruth argued against it, drawing on Levine et al. (2004): the label would treat students as fragile because of their background, and excluding them would mean research about their experience would proceed without them. Justice, one of the Belmont principles, concerns fair access to the benefits of research as well as fair distribution of its burdens. The board agreed that targeted protections, not exclusion, were the right response.
If Participants Become Distressed
Some participants may find the test upsetting. The research assistant will watch for distress, offer to stop and provide a brief calming activity before debriefing. Participants will receive information about the counseling center. Any participant who remains distressed will be offered a same-day appointment through an arrangement with the center.
The Board's Vote
The board approved the study with these conditions by a unanimous vote, and Dr. Ellis accepted them.
Conclusion
Hertwig and Ortmann showed that deception should be minimized and justified, Levine and colleagues showed that protections should target specific circumstances rather than labels and Rocher and colleagues showed that removing names does not guarantee anonymity. For Dr. Ellis's study, a milder cover story, targeted protections and controlled data access protect participants while keeping the research possible.
References
Hertwig, R., & Ortmann, A. (2008). Deception in experiments: Revisiting the arguments in its defense. Ethics & Behavior, 18(1), 59-92. https://doi.org/10.1080/10508420701712990
Levine, C., Faden, R., Grady, C., Hammerschmidt, D., Eckenwiler, L., & Sugarman, J. (2004). The limitations of "vulnerability" as a protection for human research participants. The American Journal of Bioethics, 4(3), 44-49. https://doi.org/10.1080/15265160490497083
Rocher, L., Hendrickx, J. M., & de Montjoye, Y.-A. (2019). Estimating the success of re-identifications in incomplete datasets using generative models. Nature Communications, 10, Article 3069. https://doi.org/10.1038/s41467-019-10933-3
EDP 820 Module 7 instructions, in plain terms
Module 7 of EDP 820 usually asks for a paper on protecting research participants. Follow the Module 7 instructions in your Aspen course; the study is a composite. Address deception and its justification, with evidence. Address vulnerability and how protections should be targeted. Address privacy and confidentiality, including risks in shared data. Apply these to a proposed study and recommend safeguards. Use APA 7, and weigh protection against participants' interests in being included in research and in benefiting from open science. Explain how debriefing will work when deception is used, including how you will check that false beliefs have been corrected. Say how data will be shared, if at all.
Inside the EDP 820 Module 7 example
Dr. Ellis, a composite faculty member, proposes telling first-generation students that a study concerns study habits when it actually measures stress responses to a difficult test, and posting de-identified data online. Hertwig and Ortmann review defenses of deception and evidence that it can make participants suspicious. Levine and colleagues argue for identifying specific sources of vulnerability rather than labeling groups. Rocher, Hendrickx and de Montjoye model re-identification and show most Americans could be identified from fifteen demographic attributes. A table lists each risk beside its remedy, and the board approves the study with a milder cover story, full debriefing and restricted data access. Sections describe the debriefing, the board's discussion of whether first-generation students should be included and what happens to participants who become distressed.
EDP 820 Module 7 rubric: what earns full marks
A strong participant protection paper weighs risks and benefits with evidence rather than applying rules mechanically. This example evaluates the deception's necessity, identifies specific circumstances that create vulnerability for first-generation students rather than labeling them and uses re-identification evidence to show why de-identification alone is insufficient. Safeguards are proportionate and preserve the study's value, including access to data for other researchers under controlled conditions. It also describes the debriefing in detail, including a check that participants understood the real purpose, and explains why including first-generation students serves justice as well as science. The board's reasoning is shown, not just its decision, which reflects good practice for review boards and makes the analysis teachable.
EDP 820 Module 7 help from the desk
Participant protection papers often prohibit deception or label groups vulnerable without analysis. Evaluate whether deception is necessary and what it costs. Identify specific circumstances that create vulnerability. Show why de-identification may not protect privacy. Propose safeguards that protect participants while keeping research possible. Debrief fully when deception is used. Describe debriefing concretely, including how you will confirm that participants understand the real purpose. Explain why including a group can serve justice. Show the reasoning behind each safeguard. Consider whether safeguards undermine the study's value, and adjust them so both protection and research are served. State who conducts the debriefing.
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EDP 820 Module 7 questions, answered
What does EDP 820 Module 7 usually ask for?
Aspen's EDP 820 covers protecting research participants in this module, so a paper on deception, vulnerability and privacy in a proposed study is typical. Read your Module 7 prompt for details.
Is deception in research ethical?
Hertwig and Ortmann found several common defenses weaker than assumed and noted that deception can make participants suspicious; it should be minimized and justified.
Who counts as a vulnerable research participant?
Levine and colleagues argued that labeling whole groups vulnerable can stereotype them; protections should target specific circumstances that create risk.
Where can I find a free EDP 820 Module 7 sample paper?
This page holds the whole paper: deception, vulnerability and re-identification risk applied to one proposed study, with safeguards.
Can anonymous data be re-identified?
Rocher, Hendrickx and de Montjoye estimated that most Americans could be correctly re-identified from fifteen demographic attributes in supposedly anonymous datasets.