ThoughtLine Web Server for Mental Health Wellness and Psychotherapy
Name
cantow-mcantow-meng-eecs-2023-thesis.pdf
Description
Thesis PDF
Size
3.55 MB
Format
Adobe PDF
Checksum (MD5)
4b9e4abf34a03be7e95d52bd723fe98a
Author(s)
Cantow, Michael R.
Advisor(s)
Fletcher, Rich
Date Issued
June 2023
Publisher
Massachusetts Institute of Technology
Abstract
Mental health is a significant and growing public health concern, with depression representing the leading cause of disability world-wide. While ongoing research actively explores the potential of mobile technology and artificial intelligence to support mental health, limited attention has been given to the field of mental health wellness and prevention. Drawing inspiration from the preventive benefits of exercise in physical health, this project aims to develop a platform for mental health wellness and prevention in the form of an online web server for audiotherapy. The server architecture allows for the utilization of various audio files, including mindfulness meditation, storytelling, nature sounds, and neuromodulation. In this thesis, I describe the design and architecture of the server platform, emphasizing academic digital mental health research and future project reusability. In addition to providing access to audio files, the web application incorporates standard psychological clinical assessments for health screening and a chat bubble feature that employs a pre-existing NLP algorithm to identify signs of depression. By collecting data on audio file access history, and tracking psychological assesssments and NLP model outcomes over time, clinicians can use this platform to engage in formal quantitative research within this emerging research domain. Our research platform, ThoughtLine.org, includes a user-friendly smartphone and web interface powered by our containerized server infrastructure, DockMed. The initial prototype described here has been prepared for a future clinical study with MIT students; however, the platform can be used for a variety of clinical studies with support for individual account registration and user groups.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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