Service quality evaluation of integrated health and social care for older Chinese adults in residential settings based on factor analysis and machine learning.

ABSTRACT:

Objective

To evaluate the service quality of integrated health and social care institutions for older adults in residential settings in China, addressing a critical gap in the theoretical and empirical understanding of service quality assurance in this rapidly expanding sector.

Methods

This study employs three machine learning algorithms-Backpropagation Neural Networks (BPNN), Feedforward Neural Networks (FNN), and Support Vector Machines (SVM)-to train and validate an evaluative item system. Comparative indices such as Mean Squared Error, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and predictive performance metrics were employed to assess the models.

Results

The service quality evaluation model, enhanced by factor analysis and fuzzy BPNN, demon

SUBMITTER: Liu Z 

PROVIDER: S-EPMC11660055 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature