Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.

ABSTRACT:

Background

The introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered interventions for treating anxiety and depression by improving human-computer interactions. Although these advances, particularly in complex models such as generative artificial intelligence (AI), are highly promising, robust evidence validating the effectiveness of the interventions remains sparse.

Objective

The aim of this study was to determine whether self-administered interventions based on NLP models can reduce depressive and anxiety symptoms.

Methods

We conducted a systematic review and meta-analysis. We searched Web of Science, Scopus, MEDLINE, PsycINFO, IEEE Xplore, Embase, and Cochrane Library from inception to November

SUBMITTER: Villarreal-Zegarra D 

PROVIDER: S-EPMC11375382 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature