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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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Acceptance of smartwatches for automated self-report in mental health interventions. / Nadal, Camille; Sas, Corina; Doherty, Gavin.
2020. Paper presented at 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, Milan, Italy.

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

Harvard

Nadal, C, Sas, C & Doherty, G 2020, 'Acceptance of smartwatches for automated self-report in mental health interventions', Paper presented at 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, Milan, Italy, 5/06/20.

APA

Nadal, C., Sas, C., & Doherty, G. (2020). Acceptance of smartwatches for automated self-report in mental health interventions. Paper presented at 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, Milan, Italy.

Vancouver

Nadal C, Sas C, Doherty G. Acceptance of smartwatches for automated self-report in mental health interventions. 2020. Paper presented at 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, Milan, Italy.

Author

Nadal, Camille ; Sas, Corina ; Doherty, Gavin. / Acceptance of smartwatches for automated self-report in mental health interventions. Paper presented at 25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, Milan, Italy.

Bibtex

@conference{f414235c0d894fee857aaf34b32fa621,
title = "Acceptance of smartwatches for automated self-report in mental health interventions",
abstract = "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{\textquoteright} acceptance over time.",
keywords = "Technology acceptance, self-report, smartwatch, mental health",
author = "Camille Nadal and Corina Sas and Gavin Doherty",
year = "2020",
month = jun,
day = "5",
language = "English",
note = "25th annual international CyberPsychology, CyberTherapy & Social Networking Conference, CYPSY25 ; Conference date: 05-06-2020",

}

RIS

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 -