Quality factors affecting the continued use of mobile health apps in ethnic minority regions of Southwest China using PLS-SEM and ANN.

Mobile technology has significantly accelerated the rapid development of healthcare services. Despite the convenience brought by the proliferation of mobile health (mHealth) apps, the challenge of promoting their continued use among patients has garnered attention from many scholars and administrators. Based on the Expectation Confirmation Model (ECM), this study explores the impact of quality elements on the continuance intention of mHealth apps in Southwest China's ethnic minority regions. Researchers conducted a structured questionnaire survey on 337 users of mHealth apps in these regions to measure their self-reported responses to seven constructs: information quality, system quality, service quality, perceived usefulness, confirmation, satisfaction, and continuance intention. The study uses the structural equation model-artificial neural network (SEM-ANN) approach to interpret the compensatory and non-linear relationships between predictors and continuance intention. The findings reveal that user satisfaction and perceived usefulness significantly predict the continuance intention to use mHealth apps. All other relationships were confirmed except for the non-significant relationships between service quality and confirmation, service quality and perceived usefulness, and system quality and perceived usefulness. Furthermore, based on the normalized importance obtained from the multilayer perceptron, the most critical predictors identified were satisfaction (100%), followed by information quality (70.2%), perceived usefulness (43.2%), system quality (25.1%), and confirmation (17.6%). Finally, this study presents theoretical and practical implications for the continuance intention towards mHealth apps in Southwest China's ethnic minority regions.