TY - GEN
T1 - The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health
AU - Kruzan, Kaylee Payne
AU - Ng, Ada
AU - Stiles-Shields, Colleen
AU - Lattie, Emily G.
AU - Mohr, David C.
AU - Reddy, Madhu
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/4/19
Y1 - 2023/4/19
N2 - Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients' symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients' desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.
AB - Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients' symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients' desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.
KW - anxiety
KW - depression
KW - digital mental health
KW - mobile phone app
KW - primary care
KW - self-management
KW - sensing
KW - tracking
UR - http://www.scopus.com/inward/record.url?scp=85160021960&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85160021960&partnerID=8YFLogxK
U2 - 10.1145/3544548.3581209
DO - 10.1145/3544548.3581209
M3 - Conference contribution
C2 - 38873656
AN - SCOPUS:85160021960
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
Y2 - 23 April 2023 through 28 April 2023
ER -