| name | jama-study-design |
| description | Use when locking the study design and internal-validity safeguards for a JAMA clinical manuscript (RCT, cohort, diagnostic, or systematic review). Strengthens design choices; it does NOT pick the reporting checklist or run the statistics. |
Study Design & Internal Validity (jama-study-design)
When to trigger
- Choosing or defending the design: RCT vs cohort vs case-control vs diagnostic
- A reviewer will ask whether the analysis is intention-to-treat or per-protocol
- Bias, confounding, or missing data threaten the primary inference
- The design and the reporting checklist need to be aligned before writing
Design-specific safeguards JAMA reviewers expect
Randomized clinical trials
- A single, pre-specified primary outcome; secondary outcomes clearly labeled
- Adequate randomization (sequence generation) and allocation concealment
- Blinding of participants, clinicians, outcome assessors where feasible — state what was blinded
- Intention-to-treat as the primary analysis; per-protocol only as secondary/sensitivity
- A priori sample-size / power calculation tied to the primary outcome
- Pre-defined stopping rules and handling of interim analyses
Cohort / case-control (observational)
- Explicit confounding control: prespecified covariates, adjustment strategy, DAG reasoning
- Clear definitions of exposure, outcome, and follow-up windows; avoid immortal-time bias
- Selection-bias and information-bias appraisal; how participants entered the sample
- Association, not causation — design and language must respect this
Diagnostic-accuracy studies
- Pre-specified reference standard, applied to all participants, blinded to index test
- Consecutive or random enrollment; report spectrum of disease
- Pre-defined thresholds; report sensitivity/specificity/predictive values with CIs
Systematic reviews / meta-analyses
- Pre-registered protocol (e.g., PROSPERO), pre-specified eligibility and outcomes
- Comprehensive, reproducible search; duplicate screening and extraction
- Risk-of-bias assessment; pre-planned heterogeneity and sensitivity analyses
Decision table
| Question | Design / action |
|---|
| Does an intervention cause an outcome? | RCT; if infeasible, strong quasi-design |
| What is the prognosis / risk of an exposure? | Prospective cohort with confounder plan |
| How accurate is a test? | Diagnostic-accuracy study (vs reference) |
| What does the totality of evidence show? | Systematic review ± meta-analysis |
| Rare outcome, exposure already occurred | Case-control (watch selection bias) |
Checklist
Anti-patterns
- Promoting a secondary or post hoc outcome to "primary" after seeing results
- Per-protocol analysis presented as primary for an RCT
- "Adjusted for everything" with no pre-specified covariate rationale
- Causal claims from an observational design
- Reference standard chosen or applied after knowing the index-test result
- No power calculation, then attributing a null result to "trends"
Worked example: locking the design (illustrative)
Vignette (illustrative): a multicenter randomized clinical trial, N = 3,400 adults with acute kidney injury across 18 sites, early vs standard renal-replacement timing; pre-specified primary outcome 28-day all-cause mortality, 28.5% vs 31.2%, absolute risk difference -2.7 percentage points (95% CI, -6.1 to 0.7). For a Journal of the American Medical Association Original Investigation, the design safeguards a JAMA reviewer checks: a single pre-specified primary outcome, documented allocation concealment, intention-to-treat as primary (per-protocol only as sensitivity), and an a priori power calculation tied to mortality. The 95% CI crossing zero means the trial does not establish benefit — the Conclusions must say "no significant difference," not "a trend toward benefit."
Reviewer pushback and the JAMA fix
- "Is this intention-to-treat or per-protocol?" Fix: make ITT the primary analysis and relegate per-protocol to clearly labeled sensitivity.
- "Primary outcome looks chosen after seeing the data." Fix: cite the registry/protocol; demote any post hoc outcome to exploratory.
- "Causal language from an observational design." Fix: switch to associational verbs and frame confounding as a residual threat.
Calibration anchors (hedge where uncertain): a single pre-specified primary outcome, allocation concealment, ITT-as-primary, and an a priori power calculation are durable JAMA expectations; the matching EQUATOR checklist (CONSORT/STROBE/STARD/PRISMA) follows from the design — confirm specifics against current author guidelines.
Operating pass for JAMA
Run this as a concrete capability pass. First lock the clinical question, patient population, estimand or endpoint, safety/ethics issue, and reporting checklist; then test whether the manuscript addresses clinical reviewers who ask whether the evidence changes patient care, policy, or medical decision-making while satisfying reporting standards.
- Primary move: Return a claim-evidence-risk ledger; every recommendation must point to a manuscript location or missing artifact.
- Decision ledger: return
claim / evidence / blocker / next edit rows so the next pass can patch the manuscript directly.
- Sibling comparison: compare against NEJM for field-changing clinical medicine, Lancet for global-health breadth, specialty journals for narrower clinical domains; if the neighboring outlet has the stronger audience claim, recommend re-routing before polishing.
- Verification floor: before submission-ready advice, re-open
resources/official-source-map.md for volatile rules and name the one unresolved fact that could change the recommendation.
Output format
【Design】RCT / cohort / case-control / diagnostic / systematic review
【Primary outcome】... (pre-specified: yes/no)
【Key validity safeguards in place】...
【Validity gaps to fix】...
【Causal vs associational claim】...
【Matching EQUATOR checklist】CONSORT / STROBE / STARD / PRISMA
【Next skill】jama-reporting-standards
