This is an open enrollment study to collect data for the optimization of smartphone-based algorithms for the early detection of mental health and suicidal risk in a student population. Approximately 2000 students, ages 8-23, will be recruited by therapists across 30 schools and mental health centers.
Study Type
OBSERVATIONAL
Enrollment
22
App to detect presence of mental state
Clarigent Health
Mason, Ohio, United States
Algorithm development
Participants will be asked about their mental health using standardized questionnaires and a specific set of additional questions developed to encourage an open conversation with the therapist. The app will record the therapy session and a proprietary algorithm will be tested to determine if it can accurately detect the presence of a mental state (for example, suicidal intention) as compared with the standardized questionnaires (e.g. Columbia scale) and the therapists' clinical impression.
Time frame: 3 years
App optimization
Convenient and accessible use of the app in a variety of settings where adolescents and young adults may require intervention for mental health and suicide-related concerns. Upon completion of the therapy sessions, the therapists will be asked to complete a questionnaire to provide feedback on the usability of the device in a real-world setting. This information will drive modifications to the app and to the device that it is used with (e.g. smartphone, tablet) to create second generation models that are user-friendly and provide valuable information in clinical settings.
Time frame: 3 years
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