Clinical Trial: Development and Evaluation of the Real-World Implementation Feasibility of a Stratified Self-Care Support Model Integrating Artificial Intelligence and Nursing Expertise Based on Risk Perception Mismatch for Fall Prevention in Older Adults (Japan)

Tokyo, Aug. 24 -- UMIN Clinical Trials Registry (UMIN-CTR) received information related to the study (UMIN000062660) titled 'A Study of AI- and Nurse-Supported Self-Care for Fall Prevention in Older Adults' on Aug. 23.

Study Type: Interventional

Study Design: Basic Design - Single arm Randomization - Non-randomized Blinding - Open -no one is blinded Control - Uncontrolled

Primary Sponsor: Institute - The University of Osaka

Condition: Condition - Risk of falls and fractures in older adults Classification by malignancy - Others Genomic information - NO

Objective: Narrative objectives1 - The aim of this study is to develop a stratified self-care support model for community-dwelling older adults that integrates AI-based daily self-care support with support from nursing experts, focusing on risk perception mismatch, RPM, between objective fall and fracture risk and individuals' subjective risk perceptions. Through a three-month intervention, the study will evaluate changes in fear of falling, self-efficacy, physical activity, self-perception, and health behaviors, as well as the acceptability, feasibility, sustainability, and efficiency of the model, to assess its potential for real-world implementation. Basic objectives2 - Safety,Efficacy

Intervention: Interventions/Control_1 - All participants will receive self-care support using a research AI system for three months. The AI system will support assessment of lifestyle, physical activity, sleep, and health conditions; explanation of assessment results; daily reflection; verbalization of reasons for successful or unsuccessful health behaviors; review of behavioral goals; and provision of general information on fall prevention and lifestyle improvement. Participants at high risk, defined as those with a history of falls or fragility fractures, will additionally receive consultations with nursing experts to establish feasible behavioral goals based on their lifestyle, values, and risk perceptions. An interim assessment will be conducted one month after the start of the intervention, with an additional nursing consultation provided to high-risk participants as needed. The final assessment will be conducted three months after the start of the intervention.

Eligibility: Age-lower limit - 65 years-old = Gender - Male and Female Key inclusion criteria - Individuals aged 65 to 84 years Community-dwelling individuals Individuals with a history of falls or fear of falling, or an interest in fall and fracture prevention Individuals who are able to use a smartphone Individuals who are able to use the research AI application or research AI system Individuals who are able to provide informed consent to participate in the study Key exclusion criteria - Individuals who have been advised by a physician to restrict physical activity Individuals with an implanted pacemaker Individuals certified as requiring support or long-term care under the Japanese long-term care insurance system Individuals who are unable to provide informed consent or participate in the study due to severe cognitive impairment or other reasons Individuals considered unsuitable for participation by the principal investigator Target Size - 160

Recruitment Status: Recruitment status - Preinitiation Date of protocol fixation - 2026 Year 08 Month 19 Day Anticipated trial start date - 2026 Year 09 Month 28 Day Last follow-up date - 2027 Year 01 Month 27 Day

To know more, visit https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000071729

Disclaimer: Curated by HT Syndication.