An interactive tool to personalise 24-hour activity, sitting and sleep prescription for optimal health outcomes
Personalised interventions which optimise the balance of physical activity (PA), sleep and sedentary behaviour (i.e., time use) in the 24-h day may be more effective than one-size-fits-all approaches. We present an interactive app to personalise 24-h time use based on individuals' health and sociodemographic characteristics. Analyses used cross-sectional data from 53,057 UK Biobank participants. Average daily time use was measured using 7-day accelerometry data and expressed as a 24-h composition using isometric log-ratio transformation. Five cognitive composites were derived from web-based tests. Regularized linear regression examined the relationship between 24-h time-use composition and cognition, with sociodemographic and health characteristics as additional predictors. Model estimates were used to estimate optimized cognition based on the interaction of 24-h time-use composition and personal characteristics. Our 'ideal day' app delivers personalised 24-h time-use recommendations tailored to individual characteristics. We demonstrate that personalisation of time-use interventions can be achieved in real time using open-source software.
Authors
- Ty Stanford (ORCID: https://orcid.org/0000-0002-8570-5493)
- Tim Olds (ORCID: https://orcid.org/0000-0001-6894-5519)
- Maddison L. Mellow (ORCID: https://orcid.org/0000-0002-0514-8261)
- Dorothea Dumuid (ORCID: https://orcid.org/0000-0003-3057-0963)
- Aaron Miatke (ORCID: https://orcid.org/0000-0002-4329-9730)
- Ashleigh E. Smith (ORCID: https://orcid.org/0000-0001-6316-2259)
Institutions
- The University of Adelaide (AU)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-03-17
- DOI
- https://doi.org/10.1038/s41746-026-02542-4
- Primary Topic
- Physical Activity and Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00