Study Planner
Plan digital health studies and research protocols without assuming a particular app stack.
When to Use
Use this skill when you need to:
- shape a research question into a study plan
- define enrollment, consent, and participation requirements
- design data collection and assessment schedules
- align outcomes, operations, and participant burden
Working Style
Start by understanding the study, not the interface. Ask questions before proposing structure.
Clarify:
- objective or hypothesis
- participant population
- study type and duration
- primary and secondary outcomes
- expected study procedures and burden
- operational constraints such as staffing, review, and follow-up
Planning Framework
1. Study Overview
Define:
- study name
- objective or hypothesis
- population
- study type such as observational, interventional, feasibility, or survey-based
- duration and major milestones
2. Enrollment and Consent
Work through:
- inclusion criteria
- exclusion criteria
- recruitment channels
- screening steps
- consent requirements
- participant withdrawal process
Do not assume device ownership, app literacy, or language access without checking.
3. Data Collection Plan
Create a table like this:
| Data Type | Source | Frequency | Purpose | Notes |
|---|---|---|---|---|
| Baseline demographics | Intake questionnaire | Once | Eligibility and cohort description | Keep minimal |
| Symptoms | Participant self-report | Daily or weekly | Outcome tracking | Define burden clearly |
| Clinical measurements | Device, sensor, chart, or manual entry | As needed | Primary or secondary outcomes | Clarify validation path |
| Engagement data | Product telemetry | Ongoing | Feasibility and adherence | Avoid collecting unnecessary detail |
4. Assessment Schedule
Map the study rhythm:
- baseline
- recurring assessments
- triggered events
- follow-up visits
- closeout or exit steps
For each step, note:
- what happens
- expected completion time
- whether it is required or optional
- what constitutes missingness or protocol deviation
5. Outcome Measures
Define:
- primary outcomes
- secondary outcomes
- feasibility or engagement measures
- timing of analysis
- what success or signal detection means
Push for measurable outcomes, not vague aspirations.
Operational Questions
Ask about:
- who monitors study progress
- who responds to missed assessments
- what happens if participants stop engaging
- whether reminders, escalations, or coordinator outreach are planned
- what data quality review is needed during the study
Deliverable Format
Produce a concise study planning brief with:
- study summary
- enrollment and consent plan
- data collection matrix
- assessment schedule
- outcome measures
- operational risks and open questions
Save the brief as docs/planning/study-brief.md in the project repository.
Guardrails
- Keep the plan platform-agnostic unless the user explicitly wants implementation advice.
- Do not assume a particular interoperability standard, sensor integration, or client architecture by default.
- Flag where clinical, statistical, or IRB review is still needed.
- Highlight participant burden whenever the plan becomes too heavy.
Checklist
- Objective and population clearly defined
- Study type and duration captured
- Enrollment and consent plan outlined
- Data collection matrix created
- Assessment schedule defined
- Primary and secondary outcomes specified
- Operational responsibilities identified
- Key risks and open questions documented