Accepted author manuscript, 158 KB, PDF document
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
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TY - CONF
T1 - Acceptance of smartwatches for automated self-report in mental health interventions
AU - Nadal, Camille
AU - Sas, Corina
AU - Doherty, Gavin
PY - 2020/6/5
Y1 - 2020/6/5
N2 - Tracking of mood is an activity commonly employed within a range ofmental health interventions. Physical activity and sleep are also important forcontextualising mood data but can be difficult to track manually and rely onretrospective 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.
AB - Tracking of mood is an activity commonly employed within a range ofmental health interventions. Physical activity and sleep are also important forcontextualising mood data but can be difficult to track manually and rely onretrospective 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.
KW - Technology acceptance
KW - self-report
KW - smartwatch
KW - mental health
M3 - Conference paper
T2 - 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference
Y2 - 5 June 2020
ER -