Machine Learning in Health Promotion and Behavioral Change: Scoping Review.

ABSTRACT:

Background

Despite health behavioral change interventions targeting modifiable lifestyle factors underlying chronic diseases, dropouts and nonadherence of individuals have remained high. The rapid development of machine learning (ML) in recent years, alongside its ability to provide readily available personalized experience for users, holds much potential for success in health promotion and behavioral change interventions.

Objective

The aim of this paper is to provide an overview of the existing research on ML applications and harness their potential in health promotion and behavioral change interventions.

Methods

A scoping review was conducted based on the 5-stage framework by Arksey and O'Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews an

SUBMITTER: Goh YS 

PROVIDER: S-EPMC9204568 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature