A Series of Personalized Melatonin Supplement Interventions for Poor Sleep: Feasibility Randomized Crossover Trial for Personalized N-of-1 Treatment
Bibliographic record
Abstract
Background: Poor sleep (defined by short sleep duration or poor quality) is a common condition with potential serious health consequences. Exogenous melatonin supplements have been found to effectively improve poor sleep but have also been shown to have heterogeneity of treatment effects (HTEs) between individuals. Personalized N-of-1 trials, in which each participant is the unit of analysis, are ideal for identifying whether a treatment with high HTE is beneficial for each individual patient. Objective: This study aimed to identify the feasibility, acceptability, and effectiveness of a series of personalized N-of-1 trials of melatonin for poor sleep. Methods: This study consisted of 60 digital, personalized N-of-1 crossover trials comparing the effects of 3.0 mg and 0.5 mg of melatonin versus placebo for poor sleep with randomization to 1 of 2 orders. The trial comprised a 2-week baseline period and a 12-week intervention period. The primary outcomes were usability of the personalized trial system (measured using the System Usability Scale [SUS]) and participant satisfaction with the trial. Effectiveness outcomes included sleep duration (measured using a Fitbit activity tracker [Google]) and sleep quality (measured using the consensus sleep diary). Results: Participants rated the usability of the personalized trial as acceptable (average SUS score 76.3, SD 17.1), and 96% (55/57) of those who completed satisfaction surveys stated that they would recommend the trial to others. Importantly, indices of HTE were low for 3.0 mg and 0.5 mg doses of melatonin, indicating that the effect of these treatments on sleep duration and sleep quality did not substantially vary between participants and that averaged treatment responses are appropriate. Averaged participant sleep duration did not significantly differ between the 3.0 mg (P=.70) and 0.5 mg (P=.90) melatonin intervention periods and the baseline period. In addition, regression models did not show differences between different levels of melatonin and placebo periods for sleep duration or quality. Conclusions: Participant ratings of the usability of and satisfaction with this series of personalized N-of-1 trials of melatonin for sleep suggest these trials are both feasible and acceptable. However, our results show that melatonin supplements did not significantly improve sleep duration or sleep quality. Furthermore, the treatment effects' lack of heterogeneity among participants suggests that future use of N-of-1 trials of melatonin for poor sleep is not needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".