$200/hr · Mercor · Hourly, 40 hours a week
You evaluate and improve pharmaceutical and clinical questionnaires, ensuring methodological rigor, design consistency, and therapeutic-area accuracy across physician and patient studies.
What you would do
- Analyze survey instruments to identify problematic phrasing, logical inconsistencies, and measurement concerns that threaten data validity
- Review screeners, branching patterns, and response scales for alignment with research objectives and logical consistency
- Assess questionnaire construction for cumulative respondent burden, recall demands, and systematic bias sources
- Deliver written documentation explaining methodological issues and recommending targeted improvements
- Collaborate with clinical specialists to verify disease terminology, treatment pathways, and clinical accuracy
Who they want
- 3+ years developing, fielding, or reviewing healthcare surveys with physician or patient respondents
- Command of questionnaire design principles, survey methodology, and measurement-error sources
- Background in at least one therapeutic area such as oncology, inflammatory bowel disease, neurology, or pulmonology
- Experience with survey platforms like Qualtrics, Alchemer, or comparable tools
- Excellent written reasoning and ability to communicate detailed methodological feedback
Main skills
What the interview asks about
1.Question wording and construction
Ambiguous phrasing, double-barreled items, and leading language introduce measurement error; evaluating question quality is core to preventing data corruption.
For example: “I'm showing you three draft prostate-cancer screener questions: one uses specialist terminology, another asks two things at once, the third assumes prior knowledge. How would you prioritize which to address, and how would you reframe each one?”
2.Survey logic and branching patterns
Skip logic errors force unsuitable respondents through irrelevant sections, creating missing data, fatigue, and noise; correct flow is essential for clean datasets.
For example: “Your ulcerative-colitis instrument asks all respondents detailed treatment-history questions regardless of diagnosis confirmation. What specific data quality problems would this create, and how would you fix the flow?”
3.Measurement bias and systematic error
Recall demands, question sequencing, and scale construction each introduce predictable distortion; identifying these requires both statistical thinking and field intuition.
For example: “A migraine-severity instrument places symptom-frequency questions after an extended section on daily functional impact. What ordering effect could occur, and what changes would you recommend to the sequence?”
4.Therapeutic accuracy and clinical fit
Survey assumptions must align with disease progression, symptom presentations, and clinical terminology; misalignment produces responses that don't reflect clinical reality.
For example: “Draft language asks about 'typical' prostate-cancer treatment length without stratifying by disease stage or risk category. What clinical assumptions are flawed, and how would you revise this question?”
5.Documentation and written explanation
Clear written feedback ensures researchers understand exactly what problems exist and why specific changes matter; vague comments waste revision cycles and delay projects.
For example: “You identify five concerns in a 40-item ulcerative-colitis instrument covering screener logic, scale design, and phrasing. Summarize the two most important issues for the research lead in one paragraph with specific reasoning.”
A task you may get
You receive a draft questionnaire for a new indication and produce a documented review spanning screener design, question clarity, scale construction, and clinical terminology, with specific revisions ranked by severity and methodological impact.
How to prepare
- Review published survey-design literature in pharmaceutical research and healthcare, documenting common methodological pitfalls and solutions
- Select one therapeutic area and study it deeply: learn diagnostic criteria, treatment algorithms, symptom timelines, and both physician and patient perspectives
- Become familiar with at least one survey platform and explore its capabilities for screener logic, branching, and data validation
- Prepare examples from your own work where you improved questionnaires, explaining exactly what changed and the methodological reason for each revision
The facts
- Pay
- $200/hr
- Hours
- Hourly, 40 hours a week
- Where
- Remote
- Posted
- 9/4/2026
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