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
This skill covers the participant-facing side of consent — who consents, when, and how it fits the study flow. digital-health-compliance-planning covers the regulatory side (IRB expectations, consent capture and versioning, de-identification); coordinate rather than duplicate if both skills run.
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
1---2name: digital-health-study-planning3description: Plan a digital health study or research protocol, including enrollment, consent, data collection, assessment schedules, study operations, and outcome measures.4---56<!--7This source file is part of the Stanford Spezi open-source project.8SPDX-FileCopyrightText: 2026 Stanford University and the project authors (see CONTRIBUTORS.md)9SPDX-License-Identifier: MIT10-->1112# Study Planner1314Plan digital health studies and research protocols without assuming a particular app stack.1516## When to Use1718Use this skill when you need to:19- shape a research question into a study plan20- define enrollment, consent, and participation requirements21- design data collection and assessment schedules22- align outcomes, operations, and participant burden2324## Working Style2526Start by understanding the study, not the interface. Ask questions before proposing structure.2728Clarify:29301. objective or hypothesis312. participant population323. study type and duration334. primary and secondary outcomes345. expected study procedures and burden356. operational constraints such as staffing, review, and follow-up3637## Planning Framework3839### 1. Study Overview4041Define:4243- study name44- objective or hypothesis45- population46- study type such as observational, interventional, feasibility, or survey-based47- duration and major milestones4849### 2. Enrollment and Consent5051Work through:5253- inclusion criteria54- exclusion criteria55- recruitment channels56- screening steps57- consent requirements58- participant withdrawal process5960This skill covers the participant-facing side of consent — who consents, when, and how it fits the study flow. `digital-health-compliance-planning` covers the regulatory side (IRB expectations, consent capture and versioning, de-identification); coordinate rather than duplicate if both skills run.6162Do not assume device ownership, app literacy, or language access without checking.6364### 3. Data Collection Plan6566Create a table like this:6768| Data Type | Source | Frequency | Purpose | Notes |69|-----------|--------|-----------|---------|-------|70| Baseline demographics | Intake questionnaire | Once | Eligibility and cohort description | Keep minimal |71| Symptoms | Participant self-report | Daily or weekly | Outcome tracking | Define burden clearly |72| Clinical measurements | Device, sensor, chart, or manual entry | As needed | Primary or secondary outcomes | Clarify validation path |73| Engagement data | Product telemetry | Ongoing | Feasibility and adherence | Avoid collecting unnecessary detail |7475### 4. Assessment Schedule7677Map the study rhythm:7879- baseline80- recurring assessments81- triggered events82- follow-up visits83- closeout or exit steps8485For each step, note:8687- what happens88- expected completion time89- whether it is required or optional90- what constitutes missingness or protocol deviation9192### 5. Outcome Measures9394Define:9596- primary outcomes97- secondary outcomes98- feasibility or engagement measures99- timing of analysis100- what success or signal detection means101102Push for measurable outcomes, not vague aspirations.103104## Operational Questions105106Ask about:107108- who monitors study progress109- who responds to missed assessments110- what happens if participants stop engaging111- whether reminders, escalations, or coordinator outreach are planned112- what data quality review is needed during the study113114## Deliverable Format115116Produce a concise study planning brief with:117118- study summary119- enrollment and consent plan120- data collection matrix121- assessment schedule122- outcome measures123- operational risks and open questions124125Save the brief as `docs/planning/study-brief.md` in the project repository.126127## Guardrails128129- Keep the plan platform-agnostic unless the user explicitly wants implementation advice.130- Do not assume a particular interoperability standard, sensor integration, or client architecture by default.131- Flag where clinical, statistical, or IRB review is still needed.132- Highlight participant burden whenever the plan becomes too heavy.133134## Checklist135136- [ ] Objective and population clearly defined137- [ ] Study type and duration captured138- [ ] Enrollment and consent plan outlined139- [ ] Data collection matrix created140- [ ] Assessment schedule defined141- [ ] Primary and secondary outcomes specified142- [ ] Operational responsibilities identified143- [ ] Key risks and open questions documented
stanfordspezi