Date of Award
January 2024
Document Type
Open Access Thesis
Degree Name
Medical Doctor (MD)
Department
Medicine
First Advisor
Teresa Chahine
Second Advisor
Erica Herzog
Abstract
Objective: The mental health crisis is accelerating, with 55.8M American adults in treatment in 2022. Digital mental health is a growing field with implications for mental health care. The objective of this study was to understand patients’ mental health treatment experience and the relationship with their perspectives of a novel digital health product geared toward improving care quality.
Methods: In December 2023, an IRB-exempt questionnaire was sent to undergraduate and graduate students at campuses across the North-East United States, as well as healthcare-focused Slack® groups.
Results: Of the 1,127 respondents, 28% were actively in treatment for their mental health, 25% were treated in the past, and 1% was on a waiting list. Of those with treatment exposure currently or in the past, 85% experienced challenges with communication during their clinical encounter. Among those, 69% experienced a negative emotional impact, began avoiding care, or even terminated care. Over half (57%) currently use or have used a digital health product. With an overview of the novel digital health product, 71% were Very Likely to share data related to sleep and 62% were Very Likely to share activity data. There was a statistically significant association between treatment exposure and likelihood of data sharing (for Sleep: chi squared c2 (df = 2, n = 1,124) = 14.03, p = 0.001; for Activity: c2 (df = 2, n = 1,121) = 22.13, p < 0.001). Fewer respondents were Very Likely to share sleep and activity compared to expected frequencies if they had exposure to treatment with challenges. For mobile application retention, 351 respondents would fill out a 2–3-minute survey daily and 541 would consider it.
Conclusion: There exists a Data Gap between patients and clinicians, driven by communication challenges that impact the care experience for patients. There exists a clear role for a digital health product that addresses the Data Gap to improve care quality, assuming privacy concerns and patient retention incentives are addressed and implemented.
Recommended Citation
Guo, Clara Zhang, "Patient Perceptions Of Machine Learning-Enabled Digital Mental Health" (2024). Yale Medicine Thesis Digital Library. 4231.
https://elischolar.library.yale.edu/ymtdl/4231
Comments
This is an Open Access Thesis.