Usability Evaluation for the Amulet Wearable Device in Rural Older Adults with Obesity.

Mobile health (mHealth) interventions hold the promise of augmenting existing health promotion interventions. Older adults present unique challenges in advancing new models of health promotion using technology including sensory limitations and less experience with mHealth, underscoring the need for specialized usability testing. We use an open-source mHealth device as a case example for its integration in a newly designed health services intervention. We performed a convergent, parallel mixed-methods study including semi-structured interviews, focus groups, and questionnaires, using purposive sampling of 29 older adults, 4 community leaders and 7 clinicians in a rural setting We transcribed the data, developed codes informed by thematic analysis using inductive and deductive methods, and assessed the quantitative data using descriptive statistics. Our results suggest the importance of end-users in user-centered design of mHealth devices and that aesthetics are critically important. The prototype could potentially be feasibly integrated within health behavior interventions. Centralized dashboards were desired by all participants and ecological momentary assessment could be an important part of monitoring. Concerns of mHealth, including the prototype device, include the device's accuracy, its intrusiveness in daily life and privacy. Formative evaluations are critically important prior to deploying large-scale interventions.

Detection and Monitoring of Repetitions Using an mHealth-Enabled Resistance Band.

Sarcopenia is defined as an age-related loss of muscle mass and strength which impairs physical function leading to disability and frailty. Resistance exercises are effective treatments for sarcopenia and are critical in mitigating weight-loss induced sarcopenia in older adults attempting to lose weight. Yet, adherence to home-based regimens, which is a cornerstone to lifestyle therapies, is poor and cannot be ascertained by clinicians as no objective methods exist to determine patient compliance outside of a supervised setting. Our group developed a Bluetooth connected resistance band that tests the ability to detect exercise repetitions. We recruited 6 patients aged 65 years and older and recorded 4 specific, physical therapist-led exercises. Three blinded reviewers examined the findings and we also applied a peak Ending algorithm to the data. There were 16.6 repetitions per exercise across reviewers, with an intraclass correlation of 0.912 (95%CI: 0.853-0.953, p<0.001) between reviewers and the algorithm. Using this novel resistance band, we feasibly detected repetition of exercises in older adults.