Journal Articles

Sleep quality is a crucial concern, particularly among youth. The integration of health coaching with question-answering (QA) systems presents the potential to foster behavioural changes and enhance health outcomes. This study proposes a novel human-AI sleep coaching model, combining health coaching by peers and a QA system, and assesses its feasibility and efficacy in improving university students’ sleep quality. Methods In a four-week unblinded pilot randomised controlled trial, 59 university students (mean age: 21.9; 64% males) were randomly assigned to the intervention (health coaching and QA system; n = 30) or the control conditions (QA system; n = 29). Outcomes included efficacy of the intervention on sleep quality (Pittsburgh Sleep Quality Index; PSQI), objective and self-reported sleep measures (obtained from Fitbit and sleep diaries) and feasibility of the study procedures and the intervention. Results Analysis revealed no significant differences in sleep quality (PSQI) between intervention and control groups (adjusted mean difference = −0.51, 95% CI: [−1.55–0.77], p = 0.40). The intervention group demonstrated significant improvements in Fitbit measures of total sleep time (adjusted mean difference = 32.5, 95% CI: [5.9–59.1], p = 0.02) and time in bed (adjusted mean difference = 32.3, 95% CI: [2.7–61.9], p = 0.03) compared to the control group, although other sleep measures were insignificant. Adherence was high, with the majority of the intervention group attending all health coaching sessions. Most participants completed baseline and post-intervention self-report measures, all diary entries, and consistently wore Fitbits during sleep. Conclusions The proposed model showed improvements in specific sleep measures for university students and the feasibility of the study procedures and intervention. Future research may extend the intervention period to see substantive sleep quality improvements.