The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health.
Kaylee Payne KruzanAda NgColleen Stiles-ShieldsEmily G LattieDavid C MohrMadhu ReddyPublished in: Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference (2023)
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.
Keyphrases
- mental health
- healthcare
- primary care
- electronic health record
- end stage renal disease
- big data
- physical activity
- ejection fraction
- newly diagnosed
- chronic kidney disease
- mental illness
- peritoneal dialysis
- sleep quality
- blood pressure
- social media
- health information
- chronic pain
- palliative care
- case report
- combination therapy
- deep learning