Monika Siegrist

Introduction High exercise adherence is a key factor for effective exercise programmes. However, little is known about predictors of exercise adherence to a multimodal machine‐based training in older retirement home residents. Aims To assess exercise adherence and potential predictors of adherence. Furthermore, to evaluate user acceptance of the multimodal training and the change in exercise self‐efficacy. Methods In this sub‐analysis of the bestform‐F study, a total of 77 retirement home residents ≥65 years (mean age: 85.6 ± 6.6 years, 77.9% female) participated in a 6‐month machine‐based resistance, coordination and endurance training. Attendance to the training was documented for each training session. To identify potential predictors a multiple linear regression model was fitted to the data. Analyzed predictors included age, sex, body mass index (BMI), physical function, exercise self‐efficacy, and physical activity history. Different domains of user acceptance (e.g. safety aspects, infrastructure) and exercise self‐efficacy were assessed by a questionnaire and the exercise self‐efficacy scale (ESES), respectively. Results Mean exercise adherence was 67.2% (median: 74.4%). The regression model ( R 2 = 0.225, p = 0.033) revealed that the 6‐minute walk test (6‐MWT) at baseline significantly predicted exercise adherence (β: 0.074, 95% confidence interval (CI): 0.006–0.142, p = 0.033). Different user domains were rated at least as good by 83.9%–96.9% of participants, reflecting high acceptance. No statistically significant change was found for exercise self‐efficacy over 6 months (mean change: 0.47 ± 3.08 points, p = 0.156). Conclusion Retirement home residents attended more than two thirds of offered training sessions and physical function at baseline was the key factor for predicting adherence. User acceptance of the training devices was highly rated. These findings indicate good potential for implementation of the exercise programme.