Designing for healthy ageing: Lessons learned from engaging pre-frail older adults in the development of digital self-monitoring health technologies

Older adults may accept mHealth technologies, but skepticism about data accuracy can limit their engagement and willingness to change behaviors.

Summary and findings

This study explored the engagement of pre-frail older adults with a prototype mobile health (mHealth) intervention aimed at improving frailty outcomes through self-monitoring. Thirty older adults trialed the intervention, which included a smartwatch, sleep analyser, and passive environmental sensors. While acceptance of the technology was high, engagement with the sensor data was limited, and skepticism about data accuracy hindered behavioral changes.

Abstract

<title>Abstract</title> <p>Mobile health (mHealth) technology, including wearable monitoring devices and mobile applications displaying personal health and fitness data, is increasingly ubiquitous. Its use is limited outside of consumer, non-clinical applications among younger adults. However, there is potential for this technology to support preventative healthcare programs for older adults to maintain their independence and extend their healthy lifespan. There is evidence to show the efficacy of self-monitoring interventions using mobile health technology in this group in a study setting, but adherence, engagement and real-world uptake remain a challenge. This demonstrates the need to consider how we might tailor these consumer mHealth offerings to be more accessible for this group among whom digital literacy is often a barrier, in turn increasing uptake and engagement. Here, we discuss qualitative insights from a group of 30 older adults trialling a prototype mHealth intervention designed to improve frailty outcomes through self-monitoring. While acceptance of the hardware (smartwatch, sleep analyser, and passive environmental sensors) and accompanying application was high and reports of usability and utility were generally positive, the depth of engagement with the sensor data was limited. In addition, scepticism surrounding data accuracy contributed to a reluctance to make behavioural changes. Furthermore, the participant’s expectations of the system’s technical capabilities and degree of personalisation were not entirely met. Based on these findings, we present recommendations for further investigation, including alternative design approaches that may improve accessibility of mHealth applications for older adults and increase their engagement with self-monitoring healthy ageing interventions.</p>

Limitations

• Not reported in abstract.

Elsewhere in the ARA 290 corpus