A health planning expert system for promoting quality of life among older adults in Buriram province

Vollständiger Abstract

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This study aimed to (1) develop a knowledge base for health planning among older adults and (2) develop and transfer an expert system to support personalized health planning and promote the quality of life of older adults in Buriram Province, Thailand. This applied research adopted the System Development Life Cycle (SDLC), comprising five main phases: Knowledge Acquisition and Contextual Requirements Analysis; Ontology Design and Knowledge Base Construction; System Analysis, Design, and Development based on object-oriented principles; System Testing and Performance Evaluation; and Technology Transfer. The knowledge base was developed using an ontology-based approach and was grounded in three core health planning principles: diet, exercise, and emotional well-being. It comprised 18 main classes and 12 rule sets containing a total of 144 inference rules. The developed expert system was implemented as a mobile application for managing personal profiles, health histories, dietary behaviors, and exercise habits. Based on these data, the system generates personalized recommendations for food, exercise, and recreational activities according to the individual health conditions of older adults. The performance of the inference mechanism was evaluated using six case studies by comparing system-generated recommendations with expert judgments. The results showed an average Recommendation Matching Rate (RMR) of 0.567, with average precision, recall, and F1-score values of 0.893, 0.788, and 0.836, respectively. These findings indicate that the system achieved high precision in generating recommendations and demonstrated a good overall level of agreement with expert judgments. The usability evaluation yielded a high overall mean score (X̄ = 3.92), indicating favorable user acceptance of the developed system. The developed technology was subsequently transferred to the target users to support its practical application in health planning for older adults. GRAPHICAL ABSTRACT HIGHLIGHTS An expert system was developed to transform elderly health information into personalized lifestyle recommendations. The system integrates 144 clinical knowledge-based rules for adaptive health planning in older adults. Validation with expert judgments demonstrated high recommendation reliability and strong user acceptance.