¶ How to Run N‑of‑1 Experiments (Without Fooling Yourself)
Good experiments reduce guesswork. Great experiments change decisions.
¶ The Minimum Viable Experiment
- Question: what outcome are you trying to change?
- Primary metric: the one number you will judge success on.
- Intervention: one variable with explicit parameters.
- Design: ABAB or crossover, plus a washout if needed.
- Duration: long enough to be meaningful for that metric.
- Decision rule: written before you start.
¶ Choose a Design
¶ A) Before/After (fast, weakest)
Best for obvious acute effects (e.g., caffeine timing → sleep latency), but highly confounded.
¶ B) ABAB (best default)
- A: baseline
- B: intervention
- A: remove intervention
- B: reintroduce
If the effect appears and disappears with the intervention, confidence rises quickly.
¶ C) Randomized Crossover (strong, more work)
Alternate conditions in random order (e.g., supplement vs placebo, or two doses) with washouts as needed.
Reporting note
Formal N-of-1 trials have established reporting guidance (CONSORT extension / CENT). We adapt the same mindset: define outcomes, design, and analysis up front to avoid “storytelling with data.”[1]
¶ Confounders Checklist (Most Common Failure Modes)
Keep these as stable as possible:
- Sleep schedule (wake time is the anchor)
- Travel / time zone shifts
- Illness
- Training volume and intensity
- Alcohol
- Major diet shifts (especially carb intake)
- New supplements or medication changes
¶ Washout Guidance (Rule of Thumb)
- If an intervention has an acute effect, you may not need a washout.
- If it has a half-life or delayed physiological adaptation, plan a washout.
- If you don’t know: start conservative, and track symptoms to estimate decay.
Safety rule
If you develop concerning symptoms, stop the experiment and see Red Flags.
¶ Templates (Copy/Paste)
¶ Experiment Brief
| Field | Fill in |
|---|---|
| Goal | (e.g., improve sleep latency) |
| Primary metric | (e.g., sleep latency minutes, averaged weekly) |
| Secondary metrics | (e.g., total sleep time, next-day energy) |
| Intervention | (exact dose/parameters, timing, brand/device) |
| Design | ABAB / crossover |
| Total duration | (e.g., 6 weeks) |
| Washout | (yes/no; length) |
| Decision rule | (e.g., continue if latency ↓ ≥15 min with no next-day grogginess) |
| Stop rule | (symptoms, BP threshold, abnormal labs, etc.) |
¶ Daily Log (Minimal)
| Date | Sleep | Energy | Mood | Training | Intervention | Notes |
|---|---|---|---|---|---|---|
| YYYY‑MM‑DD |
¶ Simple Analysis (Enough for Most People)
- Compare weekly averages rather than single days.
- Look for repeatability: does the signal show up across multiple B phases?
- Decide in advance what counts as “worth it” (effect size and effort).
¶ References
Shamseer L, Sampson M, Bukutu C, et al. CONSORT extension for reporting N-of-1 trials (CENT) 2015: Explanation and elaboration. BMJ. 2015;350:h1793. https://pubmed.ncbi.nlm.nih.gov/25962917/ ↩︎
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