Interpretable Machine Learning Models for Analyzing Determinants Affecting the Use of mHealth Apps Among Family Caregivers of Patients With Stroke in Chinese Communities: Cross-Sectional Survey Study.

ABSTRACT:

Background

Mobile health (mHealth) apps are believed to be an effective method to support family caregivers to better care for patients with stroke. This study's purpose was to explore the status and the influencing factors of mHealth app use among family caregivers of patients with stroke via machine learning (ML) models.

Objective

This study aimed to understand the status quo of mHealth app use among community family caregivers of patients with stroke and the factors influencing their use behavior. Six ML models were used to construct the classifier, and the Shapley Additive Explanations (SHAP) algorithm was introduced to interpret the best ML model.

Methods

In this cross-sectional study, family carers of patients with stroke were recruited. Data on their basic prof

SUBMITTER: Du Y 

PROVIDER: S-EPMC12643396 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature