Adolescent, parent, and provider attitudes toward a machine learning based clinical decision support system for selecting treatment for youth depression.

ABSTRACT:

Background

Machine learning based clinical decision support systems (CDSSs) have been proposed as a means of advancing personalized treatment planning for disorders, such as depression, that have a multifaceted etiology, course, and symptom profile. However, machine learning based models for treatment selection are rare in the field of psychiatry. They have also not yet been translated for use in clinical practice. Understanding key stakeholder attitudes toward machine learning based CDSSs is critical for developing plans for their implementation that promote uptake by both providers and families.

Methods

In Study 1, a prototype machine learning based Clinical Decision Support System for Youth Depression (CDSS-YD) was demonstrated to focus groups of adolescents with a diagno

SUBMITTER: Gunlicks-Stoessel M 

PROVIDER: S-EPMC10759496 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature