Older Adults’ Experiences With Using Wearable Devices: Qualitative Systematic Review and Meta-synthesis

Abstract

Background Older adults may use wearable devices for various reasons, ranging from monitoring clinically relevant health metrics or detecting falls to monitoring physical activity. Little is known about how this population engages with wearable devices, and no qualitative synthesis exists to describe their shared experiences with long-term use. Objective This study aims to synthesize qualitative studies of user experience after a multi-day trial with a wearable device to understand user experience and the factors that contribute to the acceptance and use of wearable devices. Methods We conducted a systematic search in CINAHL, APA PsycINFO, PubMed, and Embase (2015-2020; English) with fixed search terms relating to older adults and wearable devices. A meta-synthesis methodology was used. We extracted themes from primary studies, identified key concepts, and applied reciprocal and refutational translation techniques; findings were synthesized into third-order interpretations, and finally, a “line-of-argument” was developed. Our overall goal was theory development, higher-level abstraction, and generalizability for making this group of qualitative findings more accessible. Results In total, we reviewed 20 papers; 2 evaluated fall detection devices, 1 tested an ankle-worn step counter, and the remaining 17 tested activity trackers. The duration of wearing ranged from 3 days to 24 months. The views of 349 participants (age: range 51-94 years) were synthesized. Four key concepts were identified and outlined: motivation for device use, user characteristics (openness to engage and functional ability), integration into daily life, and device features. Motivation for device use is intrinsic and extrinsic, encompassing many aspects of the user experience, and appears to be as, if not more, important than the actual device features. To overcome usability barriers, an older adult must be motivated by the useful purpose of the device. A device that serves its intended purpose adds value to the user’s life. The user’s needs and the support structure around the device—aspects that are often overlooked—seem to play a crucial role in long-term adoption. Our “line-of-argument” model describes how motivation, ease of use, and device purpose determine whether a device is perceived to add value to the user’s life, which subsequently predicts whether the device will be integrated into the user’s life. Conclusions The added value of a wearable device is the resulting balance of motivators (or lack thereof), device features (and their accuracy), ease of use, device purpose, and user experience. The added value contributes to the successful integration of the device into the daily life of the user. Useful device features alone do not lead to continued use. A support structure should be placed around the user to foster motivation, encourage peer engagement, and adapt to the user’s preferences.

The Views and Needs of People With Parkinson Disease Regarding Wearable Devices for Disease Monitoring: Mixed Methods Exploration

“…The lack of motivation to use a wearable device should not be underestimated, as previous evidence suggests that user preference influences utility and sustained use [ 35 ]. Although people with Parkinson disease may have more medical needs than other older adults, both populations are more inclined to use a wearable device when they are motivated by the medical benefits of the device [ 42 ]. When a wearable device offers tangible improvements to their lives, older adults and people with Parkinson disease may be willing to sacrifice esthetic features in favor of useful device functions.…”

Health-Related Telemonitoring Parameters/Signals of Older Adults: An Umbrella Review

“…Accordingly, 18 systematic reviews were included in this umbrella review ( Figure 1 ). Nine of the reviews were developed in European countries [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ], four in North American countries [ 26 , 27 , 28 , 29 ], three in Australia [ 30 , 31 , 32 ], one in Pakistan [ 33 ], and one in India [ 34 ]. The number of studies included in each review varied between 7 and 73, with an average of 32 studies, and a median of 25 studies.…”

“…The databases most commonly searched by the studies included MEDLINE (ten studies [ 17 , 19 , 21 , 22 , 23 , 26 , 28 , 30 , 31 , 33 ]), PubMed by nine [ 18 , 20 , 24 , 25 , 27 , 29 , 31 , 32 , 33 ]), EMBASE by eight [ 17 , 20 , 21 , 22 , 26 , 28 , 29 , 32 ], CINAHL by six [ 17 , 20 , 23 , 29 , 30 , 31 ], SCOPUS by five [ 19 , 23 , 24 , 25 , 34 ], COCHRANE by four [ 18 , 26 , 30 , 33 ], Web of Science by three [ 19 , 22 , 25 ], Science Direct [ 19 , 23 ], Google Scholar [ 29 , 33 ], ACM digital [ 19 , 24 ], IEE Xplorer [ 19 ,…”

“…The methodological quality of each systematic review is shown in Table 2 . Only four reviews were considered high quality [ 21 , 22 , 29 , 32 ], five presented moderate quality [ 17 , 23 , 25 , 26 , 30 ], eight presented low quality [ 18 , 19 , 20 , 24 , 27 , 28 , 31 , 33 ], and one showed critically low quality [ 34 ].…”

“…The reviews included samples ranging from 290 to 17131 participants [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 ].…”