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Acceptance of smartwatches for automated self-report in mental health interventions

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

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Publication date5/06/2020
<mark>Original language</mark>English
Event25th annual international CyberPsychology, CyberTherapy & Social Networking Conference - Milan, Italy
Duration: 5/06/2020 → …

Conference

Conference25th annual international CyberPsychology, CyberTherapy & Social Networking Conference
Abbreviated titleCYPSY25
Country/TerritoryItaly
CityMilan
Period5/06/20 → …

Abstract

Tracking of mood is an activity commonly employed within a range of
mental health interventions. Physical activity and sleep are also important for
contextualising mood data but can be difficult to track manually and rely on
retrospective recall. Smartwatches show potential to help reduce the burden on users in terms of remembering to track, and the effort of tracking, as well as difficulties in accurate recall of sleep and activity. This ongoing study explores the acceptance of the use of a smartwatch app for automated self-report in a mental health intervention context. The watch app studied allows the manual self-report of mood and automated self-report of sleep and physical activity. Acceptance is measured through usage metrics and a questionnaire based on the Health Information Technology Acceptance Model. Acceptance issues more specific to the context of mental health interventions (e.g. perceived stigma) are also explored. The questionnaire is delivered before first use of the app, after initial use, and following sustained use, in order to assess the evolution of patients’ acceptance over time.