Primary osteoporosis presents a significant global public health burden. Resistance training effectively improves bone mineral density (BMD) and physical function in older adults. Traditional supervised training programs face practical barriers regarding spatial accessibility, temporal constraints, and long-term adherence. Mobile health (mHealth) and smart community facilities offer scalable solutions for home-based interventions. The clinical efficacy of high-intensity digital exercise prescriptions and the specific mechanistic role of technology acceptance require rigorous validation through randomized controlled trials.
This study is a single-center, single-blind, parallel-group randomized controlled trial. 98 older adults diagnosed with primary osteoporosis will be recruited from a smart elderly care community. Participants will be randomly assigned to either an intervention group or a control group. The study consists of a 32-week core intervention period followed by a 12-month observational follow-up phase to evaluate long-term effectiveness.
The intervention group will undergo a smart community-based resistance training program. Participants will complete 40 to 60 minutes of structured elastic band training 3 times a week. The protocol applies progressive overload, starting at 50-60% of 1-repetition maximum (1RM) and advancing to 70-80% 1RM. Smart health bracelets and mobile applications will deliver standardized video demonstrations, monitor real-time physiological metrics, and track attendance. Community staff holding fitness certifications will provide periodic offline coaching, error correction, and safety supervision.
The control group will receive routine care. Participants will maintain their usual daily activities and attend a monthly offline group seminar covering osteoporosis prevention, nutrition, and fall prevention strategies.
The primary objective is to evaluate longitudinal changes in lumbar spine BMD and physical performance, measured by the Short Physical Performance Battery (SPPB), at 16 and 32 weeks. Secondary objectives include assessing upper limb handgrip strength, health-related quality of life (SF-36), and dimensions of technology acceptance during the intervention and the subsequent 12-month follow-up period. The study will utilize mediation models and machine learning frameworks to explore whether baseline technology acceptance directly influences clinical outcomes or serves as an antecedent driving initial adherence.
