Here are some of the best questions for a college doctoral student survey about mental health and well-being, plus practical tips on crafting them. If you want to build your own survey in seconds, you can generate one with Specific.
The best open-ended questions for a college doctoral student survey about mental health and well-being
Open-ended questions are powerful for surfacing the real stories and nuanced experiences behind the numbers. These questions work best when you want unfiltered, qualitative insights or when exploring areas you don’t fully understand yet. Here are ten open-ended questions we recommend asking college doctoral students:
What are the biggest stressors you’ve experienced during your doctoral studies?
Can you describe a time when you felt overwhelmed, anxious, or depressed as a doctoral student?
How do you typically cope with academic and research pressures?
What resources or support systems (if any) have helped you manage your mental health?
How has your supervisor or academic department influenced your mental well-being?
What barriers have kept you from seeking support for mental health concerns?
How has your perception of mental health changed since starting your Ph.D. program?
Can you share any strategies or habits that have improved your sense of well-being?
What changes would you like to see in your institution’s approach to doctoral students’ mental health?
If you’ve ever considered pausing or leaving your program, what factors contributed to that decision?
This type of questioning taps into the reality that Ph.D. students are six times more likely to experience anxiety and depression than the general population, making space for honest and sometimes unexpected answers that single-choice options may never capture. [3]
The best single-select multiple-choice questions for a college doctoral student survey about mental health and well-being
Single-select multiple-choice questions are your go-to when you want to quantify trends, make comparisons, or ease someone into the conversation—especially when respondents might feel overwhelmed by open-ends. In high-stress environments like doctoral programs, this can lower the barrier to sharing. Here are three strong examples:
Question: During your doctoral studies, how often have you experienced significant anxiety or stress?
Daily
Several times a week
Once a week
Rarely
Never
Question: Which of the following best describes your primary source of support for mental health challenges?
Friends or peers
Family
Counseling or mental health services
Faculty or supervisors
I do not have a support system
Other
Question: Have you considered taking a break or withdrawing from your Ph.D. due to mental health concerns?
Yes, seriously considered
Yes, briefly considered
No, never considered
When to follow up with “why?” Don’t stop at the initial choice—asking “why?” after a selection brings out underlying motivations and context. For example: If a doctoral student selects “Faculty or supervisors” as their support, a follow-up like “Can you share what your supervisor did to support your well-being?” opens a new layer of insights. This is especially important, given that nearly 36% of doctoral researchers have considered ending or taking a break from studies due to poor mental health [4].
When and why to add the “Other” choice? Include “Other” when your option list might not fit everyone’s reality. A follow-up then invites them to describe their unique experience, often uncovering root causes or influences you hadn’t predicted—essential for honest mental health data.
Using NPS questions for doctoral student well-being: why it works
Net Promoter Score (NPS) is common in business, but it’s also valuable in mental health surveys for doctoral students. Asking, “On a scale from 0 to 10, how likely are you to recommend this institution as a supportive environment for doctoral student mental health and well-being?” is quick, universally understood, and highly relatable. The follow-up—“Why did you choose that rating?”—is what brings out actionable feedback.
NPS provides a clear, comparable signal of overall sentiment and, when tracked over time, can reveal the impact of changes to support structures, counseling, or institutional policies. You can generate an NPS survey for college doctoral students’ mental health and well-being in moments. Given data showing that 56% of doctoral students have considered dropping out due to stress and anxiety, using a standardized measure like NPS helps contextualize your findings and supports benchmarking [8].
The power of follow-up questions
Rich data often comes from smart follow-ups. That’s where features like automated follow-up questions shine, as explained in our article on AI follow-up questions. With our approach at Specific, AI-driven follow-ups happen in real time, responding contextually to each answer. It feels like a natural conversation with a skilled interviewer. This not only saves your team time—no more manual back-and-forth emails—but also improves outcome clarity.
College doctoral student: “I’ve been struggling with motivation.”
AI follow-up: “Can you share what factors contributed to this lack of motivation? For example, was it related to workload, supervision, or another reason?”
When follow-ups are skipped, responses like “I’m stressed” or “Support is lacking” sit unexplained, forcing you to guess at the true causes.
How many follow-ups to ask? Generally, two or three targeted follow-up questions per main prompt are enough to gain deep insights without overwhelming respondents. With Specific, you can set how persistent the follow-ups are and always enable skipping to the next question when you get the information you need.
This makes it a conversational survey: When every response can naturally lead to a deeper exploration, respondents remain engaged and the data quality improves significantly.
AI-powered analysis is easier than ever. Even with a mountain of open-text answers, AI survey response analysis tools make qualitative data manageable. See our guide on AI-driven survey response analysis if you want to explore actionable insights at scale.
Automated follow-up questions are new for many research teams—try generating a survey and see how the experience changes your approach.
Prompting ChatGPT (or GPT-4) for great survey questions
Using generative AI like ChatGPT for survey question generation can give you fresh, unbiased ideas—especially if you’re hitting creative walls or want inspiration tailored to doctoral students’ mental health. Try these prompts:
Start simple:
Suggest 10 open-ended questions for college doctoral student survey about mental health and well-being.
But if you want the AI to be sharper, add context about your goals, audience, and concerns. For example:
You are a university researcher creating a survey for current Ph.D. students in biomedical fields to understand how research pressure and supervisor support influence rates of depression and anxiety. Suggest 10 open-ended questions that can reveal students’ coping mechanisms and highlight gaps in institutional support.
Next step: categorize questions, so you can focus on areas that matter most.
Look at the questions and categorize them. Output categories with the questions under them.
Then, drill down even more by prompting:
Generate 10 questions for categories “coping strategies” and “supervision challenges.”
What is a conversational survey—and why does it matter?
A conversational survey is a feedback method powered by AI that engages respondents in a chat-like, dynamic flow—very different from old-school forms. Here’s how it stacks up against manual surveys:
Manual Survey Creation | AI-Generated Conversational Survey |
---|---|
Requires research, copy-pasting, manual logic settings | Just describe your goal in a prompt—AI creates and refines the survey instantly |
Respondents see static forms, often feel impersonal | Feels like a real conversation, often increases response quality and rates |
Follow-ups must be planned ahead, are limited | Follow-up questions are generated in real time based on each answer |
Qualitative analysis is manual and slow | AI summarizes and analyzes responses for you |
Why use AI for college doctoral student surveys?
AI survey generators remove friction—for both researchers and participants. If you want to see an AI survey example in action, you can use our AI survey builder or check a detailed guide on how to create a college doctoral student survey about mental health and well-being. These tools ensure that feedback is engaging, personal, and actionable. At Specific, we’re relentless about making this the best possible user and respondent experience in the conversational survey space.
See this mental health and well-being survey example now
If you need actionable, honest feedback from college doctoral students, see a mental health and well-being survey example powered by conversational AI. Experience deeper insights, faster survey build, and richer analysis—start now and elevate your research.