Towards an AI-driven selfmanagement app for patients with hip and knee osteoarthritis: development of a theory-driven model as a first step
C. J. J. Kloek, E. Boonstra, C. Veenhof, F. Groen, B. Cijs, M. Klein
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AbstractOsteoarthritis (OA) of the hip and knee is among the most common and rapidly increasing chronic diseases. Guidelines recommend a stepped-care strategy: starting with nonsurgical treatments including self-care, education and behavioral and rehabilitative components prior to more expensive joint-replacement. However, there is an underuse of self-care, exercises and weight management and an overuse of surgical treatments1. The SMART app aims to empower people throughout their entire OA journey by using self-administered data and AI-algorithms to provide just-in-time guidance in optimal selfmanagement. Guidance that can be provided by the app consist of selfcare modules on physical activity, weight management or sleep, general information on OA, information on relevant (healthcare) professionals or positive reinforcement. To determine at what time people could benefit from which type of guidance, the (potential) determinants of a worsening in pain, physical functioning and participation were determined with a systematic review2 and a focus group with experts and interviews with patients. As a first step in the development of the AI-algorithm in the SMART app, this study aimed to develop a theory-driven model to predict at what time people might benefit from what guidance.Keywords: digital health, artificial intelligence, osteoarthritis, self-management
C. J. J. Kloek, E. Boonstra, C. Veenhof, F. Groen, B. Cijs, M. Klein (2024). Towards an AI-driven selfmanagement app for patients with hip and knee osteoarthritis: development of a theory-driven model as a first step. Gerontechnology, 23(2), 1-1
https://doi.org/10.4017/gt.2024.23.s.1123.opp