Adequate sleep is crucial for mood regulation and injury prevention, especially among high school female athletes. However, many in this demographic experience insufficient sleep. This study investigates the feasibility and preliminary effects of an AI-supported mobile health (mHealth) intervention that provides personalized sleep feedback based on continuous sleep data.
Study Overview
The pilot randomized controlled trial involved 25 high school female soccer players from a single team. The study aimed to evaluate the technical and operational feasibility of delivering personalized sleep feedback using AI technology. The primary outcome measured was sleep efficiency, while secondary and exploratory outcomes included total sleep time (TST), wake after sleep onset (WASO), subjective sleep quality, mood state, and sports injury severity.
The trial commenced with a baseline period from weeks 1 to 4, followed by random allocation of participants into intervention (n=12) and control (n=13) groups. The intervention group received AI-generated personalized feedback via LINE, while the control group received nonpersonalized sleep information.
Results
All participants completed the trial, demonstrating 100% message delivery success and questionnaire completion in both groups. The intervention group had a median of 26 valid Fitbit wear nights, compared to 22 in the control group. Notably, the change in sleep efficiency favored the intervention group, with a Hodges-Lehmann between-group difference of 2% (95% CI 0.50%-4%; P=.046; r=0.35).
Other nominal between-group differences were observed in the Pittsburgh Sleep Quality Index (PSQI-J) total score and sleep difficulty score. Exploratory outcomes also indicated differences in REM sleep duration.
What this study does not show
This study does not establish long-term effects of the AI-generated feedback on sleep quality or athletic performance, nor does it confirm the generalizability of the findings beyond the specific population studied.
Evidence scorecard
- Analytic validity: Established
- Clinical validity: Established
- Clinical utility: Partial
The evidence class is human_rct, indicating that the study was conducted with human participants in a randomized controlled trial format.