Psychiatric Profiles of eHealth Users Evaluated Using Data Mining Techniques: Cohort Study.

ABSTRACT:

Background

New technologies are changing access to medical records and the relationship between physicians and patients. Professionals can now use e-mental health tools to provide prompt and personalized responses to patients with mental illness. However, there is a lack of knowledge about the digital phenotypes of patients who use e-mental health apps.

Objective

This study aimed to reveal the profiles of users of a mental health app through machine learning techniques.

Methods

We applied a nonparametric model, the Sparse Poisson Factorization Model, to discover latent features in the response patterns of 2254 psychiatric outpatients to a short self-assessment on general health. The assessment was completed through a mental health app after the first login.

Results

SUBMITTER: Lopez-Castroman J 

PROVIDER: S-EPMC7857940 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature