How to Choose a Dissertation Topic That’s Actually Doable

 

Three years. That’s how long one of my students spent trying to get IRB approval for a study on childhood trauma experiences among homeless veterans. Three years of revisions, appeals, and ultimately rejection after rejection.

The topic was original. It was definitely problem-driven. The literature review was solid. But it was completely unfeasible from day one, and nobody told her that.

See, she wanted to interview homeless veterans about their childhood experiences of abuse and neglect. Sounds reasonable, right? Wrong. Homeless individuals are considered a vulnerable population. Veterans with trauma histories are a vulnerable population. And asking people to relive childhood abuse experiences puts them at risk of psychological harm.

The IRB was never going to approve that study. Never. But she spent three years and thousands of dollars in tuition trying to make it work because her professors didn’t have the guts to tell her the truth: some topics, no matter how important they seem, are simply not doable in a doctoral program.

This is one of the biggest mistakes I see doctoral students make. They fall in love with a topic that sounds important and exciting, but they never stop to ask the most basic question: Can I actually do this study and graduate in a reasonable amount of time?

Here’s what your professors won’t tell you: feasibility isn’t just important – it’s everything. You can have the most original, problem-driven topic in the world, but if you can’t collect data, get IRB approval, or access your target population, you’re not graduating anytime soon.

After chairing dozens of dissertation committees, I can spot an unfeasible topic immediately. And I’m gonna teach you how to do the same thing. Because the difference between students who finish in two years and those who take five or six years often comes down to one thing: they picked feasible dissertation topic ideas from the beginning.

Today I’ll show you exactly what makes a topic unfeasible, the three non-negotiable rules for feasibility, and how to reality-check your topic before you waste months or years pursuing something that was doomed from the start.

Examples of Unfeasible but Interesting Topics

Let me start by showing you some real examples of topics that students have proposed to me over the years. These all sound fascinating, and they’d make important contributions to the literature. But they’re completely unfeasible for doctoral students.

Example 1: “A phenomenological study of altar boys and girls in Boston in the 1980s who were sexually abused by priests.”

Why it’s unfeasible: This involves a vulnerable population (abuse survivors), traumatic experiences that could cause psychological harm if revisited, and potential legal issues for both the researcher and the institution. No IRB will approve this study, ever.

Example 2: “A quasi-experimental study of the effects of a new gun safety law on gun-related injuries in Colorado.”

Why it’s unfeasible: The law is too new to have generated enough post-implementation data. Quasi-experimental designs need substantial “before” and “after” periods to account for threats to internal validity. You’d be waiting years for enough data to make the study meaningful.

Example 3: “Qualitative descriptive study of the racist attitudes and perceptions of homeowners in a predominantly white and affluent suburb of Atlanta.”

Why it’s unfeasible: Good luck recruiting participants who are willing to admit racist attitudes to a researcher. Even if you found willing participants, social desirability bias would make their responses worthless. You’d have no way to ensure measurement validity.

Example 4: “A longitudinal study of career outcomes for PhD graduates from online programs versus traditional programs.”

Why it’s unfeasible: This would require tracking graduates for decades and accessing employment data that most institutions don’t collect or share. You’d need resources and timeframes that no doctoral student has access to.

I’ve seen students spend months developing proposals for topics like these, only to have their committees or IRB shut them down. And the worst part? Their professors often knew these topics were unfeasible from the beginning but didn’t have the courage to say so directly.

The National Institutes of Health has published guidelines on research feasibility that many doctoral programs ignore when advising students. The basic principle is simple: if you can’t reasonably expect to complete data collection within your program’s timeframe and with your available resources, the topic isn’t feasible.

But here’s what really frustrates me: most of these unfeasible topics could be modified to become doable. That student who wanted to study childhood trauma among homeless veterans? We could have designed a study examining resilience factors among veterans who successfully transitioned out of homelessness. Same general area of interest, but focused on strengths rather than trauma, and studying people who were no longer in crisis.

The key is learning to recognize feasibility issues before you get emotionally invested in a topic. Because once you’ve spent months researching and writing about a topic, it’s hard to let go – even when all the evidence points to it being undoable.

Rule 1 — Vulnerable Populations

This is the big one that trips up more students than anything else. If your study involves vulnerable populations, you’re looking at months or years of additional IRB review, and possibly outright rejection.

Here’s who counts as vulnerable populations according to most IRBs:

• Children (anyone under 18)
• Pregnant women
• People with mental health conditions
• People with cognitive impairments
• Economically disadvantaged individuals
• Racial and ethnic minorities (in certain contexts)
• Prisoners or people involved in the criminal justice system
• People who are terminally or chronically ill
• Elderly individuals in institutional settings
• Homeless individuals
• People with substance abuse issues
• Victims of trauma or abuse

Now, this doesn’t mean you can’t study these populations at all. But it does mean you need to be extremely careful about how you approach your research questions and methodology.

I worked with a social work student who wanted to study coping strategies among single mothers receiving government assistance. Single mothers aren’t automatically a vulnerable population, but economically disadvantaged individuals are. So we had to redesign the study to focus on strengths and positive coping mechanisms rather than deficits or problems.

Instead of asking “How do you cope with the stress of poverty?” we asked “What strategies have helped you successfully manage work and family responsibilities?” Same general topic, but framed in a way that didn’t put participants at risk or make them feel judged.

The Department of Health and Human Services provides detailed guidance on research involving vulnerable populations. The basic principle is that the research must provide direct benefit to the population being studied, and the risks must be minimized as much as possible.

Here are some strategies for working with potentially vulnerable populations:

Focus on strengths rather than deficits. Instead of studying trauma, study resilience. Instead of studying failure, study success factors.

Use anonymous surveys rather than interviews. This reduces the risk of psychological harm and makes IRB approval more likely.

Partner with established service organizations. They can help you access participants safely and ethically.

Study professionals who work with vulnerable populations rather than the populations themselves. Teachers, social workers, nurses, and counselors can provide valuable insights without putting vulnerable individuals at risk.

But honestly? If you’re a doctoral student working within tight timeframes and limited resources, I usually recommend avoiding vulnerable populations altogether. There are plenty of important research questions you can address without navigating the additional complexities these populations require.

I know that sounds callous, but I’ve seen too many students get stuck in IRB review for months or years because they insisted on studying populations that required special protections. Your dissertation is supposed to demonstrate your research skills, not solve all the world’s problems.

Rule 2 — Available Data

This might seem obvious, but you’d be shocked how many students propose topics that require data that doesn’t exist yet or isn’t accessible to them.

I had a student who wanted to evaluate the effectiveness of a new employee wellness program at her company. Sounds feasible, right? The problem was that the program had only been running for three months. You can’t evaluate the effectiveness of a wellness program with three months of data – you need at least a year, preferably two or three years, to see meaningful outcomes.

Here’s what you need to consider about data availability:

Timing Issues:

• New policies, programs, or interventions need time to show effects
• Longitudinal studies require data collection over extended periods
• Some outcome variables (like graduation rates or health outcomes) take years to manifest

Access Issues:

• Organizational data often requires permissions you can’t guarantee
• Government data may have restrictions or lengthy approval processes
• Medical records and educational records have strict privacy protections
• Some organizations won’t share data with external researchers

Quality Issues:

• Existing datasets may not include the variables you need
• Data collection methods may not meet your research standards
• Missing data or small sample sizes may limit what analyses you can perform

The Inter-university Consortium for Political and Social Research maintains thousands of datasets that are available for secondary analysis. If your research questions can be answered using existing, high-quality data, you’ll save yourself months of data collection time and thousands of dollars in research costs.

But here’s a pro tip: always have a backup plan for data collection. I’ve seen students plan entire dissertations around accessing specific organizational data, only to have the organization change their mind about participation at the last minute.

I worked with a nursing student who planned to study patient satisfaction data from a particular hospital system. Six months into her literature review, the hospital informed her that their new privacy policies prohibited sharing patient data with external researchers. Fortunately, we had identified several alternative data sources during the planning phase, so she was able to pivot without starting over.

Questions to ask about data availability:

• Does the data you need already exist, or will you need to collect it yourself?
• If you need to collect data, how long will that realistically take?
• Do you have guaranteed access to your target population or organization?
• Are there legal, ethical, or institutional barriers to accessing the data you need?
• What’s your backup plan if your primary data source falls through?

And here’s something most students don’t think about: the cost of data collection. Surveys, interviews, focus groups, and observational studies all require time and money. Make sure you have realistic estimates of what your data collection will cost and how long it will take.

Rule 3 — Measurement Validity

This is the most subtle feasibility issue, but it can kill your dissertation just as surely as IRB problems or data access issues. If you can’t measure what you claim to be studying, your research is worthless.

The classic example is any study that asks people about socially sensitive topics. Want to study racist attitudes? Good luck getting honest answers. Want to study illegal behaviors? People aren’t going to admit to breaking the law. Want to study sensitive workplace issues like sexual harassment or discrimination? Social desirability bias will make your data meaningless.

I remember a student who wanted to study “authentic leadership behaviors” among executives. Sounds reasonable until you think about it. What executive is going to admit to being an inauthentic leader? Even if they answered honestly, people have blind spots about their own leadership behaviors that make self-report data questionable.

Here are the measurement validity issues that make topics unfeasible:

Social Desirability Bias:

• People give answers they think are socially acceptable rather than truthful answers
• Particularly problematic with sensitive topics like prejudice, illegal behavior, or personal failures
• Can’t be completely eliminated, only minimized

Self-Report Limitations:

• People don’t always have accurate insight into their own behaviors, attitudes, or motivations
• Memory is unreliable, especially for past events or emotional experiences
• People may genuinely believe things about themselves that aren’t accurate

Access to Observable Behaviors:

• Some behaviors happen in private settings you can’t observe
• Organizations may not allow researchers to observe sensitive processes
• Ethical issues may prevent observation of certain activities

Construct Validity Issues:

• Some concepts are too abstract or complex to measure reliably
• Multiple competing definitions of the same concept in the literature
• Existing measurement instruments may not capture what you’re really interested in

But here’s the thing – measurement validity issues don’t always make a topic completely unfeasible. Sometimes you can address them through better research design.

That student studying authentic leadership? We redesigned the study to focus on how followers perceive and respond to different leadership behaviors, rather than asking leaders to self-report their own authenticity. We used 360-degree feedback instruments that compared leader self-perceptions with follower perceptions. Much more valid measurement of the underlying constructs.

For sensitive topics, consider these alternatives:

• Study people who work with the population you’re interested in rather than the population directly
• Use indirect measurement techniques or behavioral indicators rather than direct questions
• Focus on positive behaviors rather than negative ones
• Use anonymous surveys rather than identifiable interviews

The key is being realistic about what you can actually measure given your constraints. If you can’t get valid, reliable data on your key variables, you need to either change your approach or change your topic.

Conclusion

Look, I get it. When you find a topic that excites you, the last thing you want to hear is that it’s not doable. But here’s the reality: feasibility determines how quickly you graduate and how much you’ll spend on tuition.

I’ve seen students add two or three years to their programs because they chose unfeasible topics. I’ve seen others spend thousands of extra dollars because they had to start over when their original topics proved impossible to execute.

The students who finish fastest and with the least stress are the ones who choose feasible dissertation topic ideas from the beginning. They pick topics they can actually complete within their program’s timeframes and with their available resources.

That doesn’t mean settling for boring topics or lowering your standards. It means being strategic about how you pursue your research interests. Almost any topic can be made feasible with the right modifications.

Worried about whether your topic is actually doable? Need help identifying the feasibility issues before you waste months pursuing something that won’t work? Contact us today and let’s have an honest conversation about what it will really take to complete your study.

We’ve helped hundreds of students avoid the feasibility traps that derail doctoral programs. We can help you reality-check your topic, identify potential problems before they become disasters, and design research that you can actually complete.

And if you want to make sure your topic meets all the criteria for dissertation success – not just feasibility, but also originality and being problem-driven – check out our comprehensive guide on how to pick the right topic for your online doctoral dissertation.

Remember: the goal isn’t to pick the most ambitious topic possible. The goal is to pick a topic that demonstrates your research competence while actually allowing you to graduate. Choose feasibility over excitement, and you’ll thank yourself later when you’re walking across that stage instead of still struggling with data collection issues