Background: Monitoring is integral to adequately recognise and track mental health indicators of symptoms and functioning. Early identification of warning signs from digital footprints could facilitate adaptive and dynamic just in-time monitoring and care for individuals with common mental disorders.
Methods: Self-report data on mental health and lifestyle behaviour from 120 male and female Australian young adults experiencing psychological distress were collected online. API software was used to download participant's daily activity duration measurements over eight months from linked commercial activity tracker apps and wearables in real time. An independent samples t-test was conducted to compare the differences in daily durations of recorded physical activity between wearable devises and smartphone apps. Entropy techniques using R interpol package were used to analyse volatility in daily activity duration.
Results: DASS-21 depression, stress and anxiety sub-scale scores indicated the study sample on average, had a moderate level of psychological distress. Daily activity duration was significantly greater from wearable devices when compared with smartphone apps (t-test = 25.4, p < 0.001). Entropy indices were not related with any of the DASS-21 measures. However, significant correlation between DASS-21 anxiety subscale scores and entropy of those with over 45 days measurements (r = 0.58, p = 0.02) was observed.
Limitations: The observational nature of this study prohibits causal inference. As a convenience sample was used, the results may lack generalisability to the wider population.
Conclusions: Continuous monitoring using commercial apps and wearables as a resource to help clinicians augment clinical care for common mental disorders appears viable.
Keywords: Common mental disorders; Daily activity duration; Digital foot prints; Smartphone apps; Wearables.
Copyright © 2018. Published by Elsevier B.V.