USleep: Efficacy of App-Based Audio Interventions to Improve Sleep Disturbance in Working Adults, a Multi-Arm Randomised Controlled Trial
STUDY OBJECTIVES: To evaluate the efficacy of three categories of standalone, audio-based sleep interventions (Bedtime Stories, Sleep Sounds, Sleep Skills) delivered via mental health application (MHapp) in improving sleep among working adults with sleep disturbance. METHODS: A multi-arm, parallel randomised controlled trial was conducted. Adults with self-reported sleep disturbances were recruited online and randomly allocated to Bedtime Stories, Sleep Sounds, Sleep Skills, or digital control. Participants completed self-report questionnaires on sleep disturbance and other related outcomes at baseline (t0) and after the 4-week intervention (t1). The primary analysis followed an intention-to-treat approach using mixed-effects models. RESULTS: A total of 495 working adults (mean age = 32.7 years; 55.8% female) were randomised. For sleep disturbance (primary outcome), the between-group Hedges' g effect sizes were very small and not statistically significant (Bedtimes stories vs control: g = 0.12, 95% CI -0.13 to 0.37, Sleep Sounds vs control: g = 0.14, 95%CI -0.11 to 0.39, Sleep Skills 0.07, 95% CI -0.07 to 0.29), with slightly greater reductions in sleep disturbance for the intervention groups than control. The same pattern was observed for sleep-related impairment, mental health, wellbeing and pre-sleep arousal. CONCLUSIONS: Audio-based sleep interventions delivered via a MHapp did not demonstrate superior efficacy over a digital control condition in reducing self-reported sleep disturbance among working adults. Although safe and well-tolerated, their use as standalone treatments for sleep disturbance is not supported by these findings. Future research should explore effectiveness in real-world settings, including user content choice across categories, and use objective sleep measures. CLINICAL TRIAL REGISTRATION: Registered at https://www.isrctn.com/ under 'Evaluating the efficacy of audio-based digital tools to improve sleep on the Unmind workplace wellbeing platform'; https://www.isrctn.com/ISRCTN13426045; registration number: 13426045.
Authors
- Marcos Economides (ORCID: https://orcid.org/0000-0003-0511-5432)
- Kate Cavanagh (ORCID: https://orcid.org/0000-0002-9863-1462)
- Jessica Vazzaz (ORCID: https://orcid.org/0009-0004-5300-2576)
- Heather Bolton
- Faith Matcham
Institutions
- East Sussex County Council (GB)
- University of Sussex (GB)
- Sussex County Community College (US)
- Google DeepMind (United Kingdom) (GB)
Publication Details
- Journal
- SLEEP
- Published
- 2026-05-31
- DOI
- https://doi.org/10.1093/sleep/zsag154
- Primary Topic
- Sleep and related disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00