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Falls are a major health concern for older adults, often leading to injuries and reduced independence. This study develops and evaluates a mobile application integrating two validated fall-risk assessment tools—the Stay Independent Brochure (SIB) and the 44-question Thai Home Falls Hazards Assessment Tool (Thai-HFHAT). The app utilizes a cloud-based architecture with a relational database for real-time analytics and user tracking. In Phase 1, 30 healthcare professionals assessed the app’s technical performance and user experience using a modified System Usability Scale (SUS), achieving a high usability score of 85.2. In Phase 2, 67 older adults used the app for self-assessment, with test–retest reliability evaluated over one week. The app showed strong reliability, with intraclass correlation coefficients (ICCs) of 0.80 for the SIB (Thai-version) and 0.77 for the Thai-HFHAT. Cloud-hosted analytics revealed significant correlations between fall occurrences and both SIB (r = 0.657, p < 0.001) and Thai-HFHAT scores (r = 0.709, p < 0.001), demonstrating the app’s predictive validity. The findings confirm the app’s effectiveness as a self-assessment tool for fall-risk screening among older adults, combining clinical validity with high usability. The integration of culturally adapted tools into a cloud-supported platform demonstrates the value of informatics in geriatric care. Future studies should focus on expanding the app’s reach, incorporating AI-driven risk prediction, enhancing interoperability with electronic health records (EHRs), and improving long-term user engagement to maximize its impact in community settings.
Details
Applications programs;
Telemedicine;
Environmental risk;
User satisfaction;
Mobile communications networks;
Medical personnel;
Risk factors;
Mobile computing;
User experience;
Hazard assessment;
Brochures;
Older people;
Access control;
Correlation coefficients;
Electronic health records;
Validation studies;
Risk assessment;
Data integrity;
Validity;
Internet access;
Aging;
Prevention;
Reliability;
Cloud computing;
Self assessment;
Adults;
Public health;
Access to information;
Professionals;
Real time;
Relational data bases
; Jiraphat, Nawarat 1
; Chadapa, Rungruangbaiyok 1
; Mackenzie, Lynette 4
; Voravuth, Somsak 5 ; Wannaprom Nipaporn 6 1 Department of Physical Therapy, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat 80160, Thailand; [email protected] (C.L.); [email protected] (J.N.); [email protected] (C.R.), Movement Sciences and Exercise Research Center, Walailak University, Nakhon Si Thammarat 80160, Thailand
2 Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand; [email protected]
3 Informatics Innovation Center of Excellence (IICE), School of Informatics, Walailak University, Nakhon Si Thammarat 80160, Thailand; [email protected]
4 Discipline of Occupational Therapy, School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW 2141, Australia; [email protected]
5 Department of Medical Technology, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat 80160, Thailand; [email protected]
6 Department of Physical Therapy, School of Allied Health Sciences, University of Phayao, Phayao 56000, Thailand