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.

Background Older adults with diabetes take fewer steps per day than those without diabetes. The purpose of the present study was to investigate the association of daily step count with incident diabetes in community-dwelling 70-year-olds. Methods This prospective cohort study included N = 3055 community-dwelling 70-year-olds (52% women) who participated in a health examination in Umeå, Sweden during 2012–2017, and who were free from diabetes at baseline. Daily step count was measured for 1 week using Actigraph GT3X+ accelerometers. Cases of diabetes were collected from the Swedish National Patient Register. The dose-response association was evaluated graphically using a flexible parametric model, and hazard ratios (HR) with 95% confidence intervals (CI) were calculated using Cox regressions. Results During a mean follow-up of 2.6 years, diabetes was diagnosed in 81 participants. There was an inverse nonlinear dose-response association between daily step count and incident diabetes, with a steep decline in risk of diabetes from a higher daily step count until around 6000 steps/day. From there, the risk decreased at a slower rate until it leveled off at around 8000 steps/day. A threshold of 4500 steps/day was found to best distinguish participants with the lowest risk of diabetes, where those taking ≥ 4500 steps/day, had 59% lower risk of diabetes, compared to those taking fewer steps (HR, 0.41, 95% CI, 0.25–0.66). Adjusting for visceral adipose tissue (VAT) attenuated the association (HR, 0.64, 95% CI, 0.38–1.06), which was marginally altered after further adjusting for sedentary time, education and other cardiometabolic risk factors and diseases (HR, 0.58, 95% CI, 0.32–1.05). Conclusions A higher daily step count is associated with lower risk of incident diabetes in community-dwelling 70-year-olds. The greatest benefits occur at the lower end of the activity range, and much earlier than 10,000 steps/day. With the limitation of being an observational study, these findings suggest that promoting even a modest increase in daily step count may help to reduce the risk of diabetes in older adults. Because VAT appears to partly mediate the association, lifestyle interventions targeting diabetes should apart from promoting physical activity also aim to prevent and reduce central obesity.

The aim was to evaluate the tone and electric activity of the quadriceps muscle at rest and different torque levels. The second aim was to study whether thickness of soft tissues and change in the joint position would affect muscle tone. Eighteen healthy subjects participated. Computerized muscle tonometer (CMT) and surface electromyography (sEMG) measurements were performed: seated, first at rest with leg straight and then with the knee at 60 degrees . Thereafter measurements were obtained at levels of 80, 60, 40 and 20% of the maximum isometric torque at the same knee angle. Thickness of skin, subcutis and muscle was measured by ultrasound. The CMT values taken were the depth the indenter travelled and the work it did while compressing the right rectus femoris and vastus intermedius muscles. Expressed as mean (SD) depth the change in muscle tone changed from 29.2 (3.6) mm in the relaxed position to 16.9 (5.2) mm at 80% of maximal torque, and expressed as work the values were from 1589 (150) mJ to 739 (149) mJ respectively. The correlation between CMT, sEMG and torque measurements varied from r = -0.52 to -0.71 (p < 0.01). CMT was able to detect a change of 20% in torque production and 4% in tone. Tone values, at each torque level, were significantly separate from the values at the other force levels (p < 0.001-0.04). Soft tissue thickness explained most of the tone results at rest (57%). The repeatability of the CMT measures was good (ICCs 0.75-0.99). Both depth and work correlated with electric activity and muscle torque, but the correlation with work was higher. In conclusion, muscle activity, length and thickness have to be taken into account when evaluating muscle tone.

Background Wearable devices can diagnose, monitor, and manage neurological disorders such as Parkinson disease. With a growing number of wearable devices, it is no longer a case of whether a wearable device can measure Parkinson disease motor symptoms, but rather which features suit the user. Concurrent with continued device development, it is important to generate insights on the nuanced needs of the user in the modern era of wearable device capabilities. Objective This study aims to understand the views and needs of people with Parkinson disease regarding wearable devices for disease monitoring and management. Methods This study used a mixed method parallel design, wherein survey and focus groups were concurrently conducted with people living with Parkinson disease in Munster, Ireland. Surveys and focus group schedules were developed with input from people with Parkinson disease. The survey included questions about technology use, wearable device knowledge, and Likert items about potential device features and capabilities. The focus group participants were purposively sampled for variation in age (all were aged >50 years) and sex. The discussions concerned user priorities, perceived benefits of wearable devices, and preferred features. Simple descriptive statistics represented the survey data. The focus groups analyzed common themes using a qualitative thematic approach. The survey and focus group analyses occurred separately, and results were evaluated using a narrative approach. Results Overall, 32 surveys were completed by individuals with Parkinson disease. Four semistructured focus groups were held with 24 people with Parkinson disease. Overall, the participants were positive about wearable devices and their perceived benefits in the management of symptoms, especially those of motor dexterity. Wearable devices should demonstrate clinical usefulness and be user-friendly and comfortable. Participants tended to see wearable devices mainly in providing data for health care professionals rather than providing feedback for themselves, although this was also important. Barriers to use included poor hand function, average technology confidence, and potential costs. It was felt that wearable device design that considered the user would ensure better compliance and adoption. Conclusions Wearable devices that allow remote monitoring and assessment could improve health care access for patients living remotely or are unable to travel. COVID-19 has increased the use of remotely delivered health care; therefore, future integration of technology with health care will be crucial. Wearable device designers should be aware of the variability in Parkinson disease symptoms and the unique needs of users. Special consideration should be given to Parkinson disease–related health barriers and the users’ confidence with technology. In this context, a user-centered design approach that includes people with Parkinson disease in the design of technology will likely be rewarded with improved user engagement and the adoption of and compliance with wearable devices, potentially leading to more accurate disease management, including self-management.

BACKGROUND Older adults (OA) can use wearable devices (WD) to monitor clinically relevant health metrics, improve physical activity, and monitor for falls. Little is known about how this population engages with WDs and no qualitative synthesis exists to describe their shared experiences with long term use of WD. OBJECTIVE This study attempts to understand the shared experience of OAs who took part in WD trials and the factors that contribute to the acceptance and sustained use of WDs. We aimed to synthesize qualitative studies that analysed the user experience after a multi-day trial with a WD. METHODS A systematic search was conducted of CINAHL, APA Psych Info, PubMed, and EMBASE (2015-2020, English) with fixed search terms relating to ‘older adults’ and ‘wearable devices,’ following PRISMA guidelines. An inductive meta-synthesis methodology was employed. Themes were extracted from primary studies, key concepts were identified, and reciprocal and refutational translation techniques were applied; findings were synthesised into third order interpretations and finally, a ‘line-of-argument’ was developed. RESULTS In total, 20 papers were reviewed; two evaluated fall detection devices, one tested an ankle worn step counter, and the remaining 17 tested activity trackers. Duration of wearing ranged from 3 days to 24 months. The views of 349 OAs (age range 51-94), were synthesised. Four key concepts were identified and outlined, namely: 1) motivation for device use, 2) user characteristics (openness to engage and functional ability), 3) integration into daily life, and 4) device features. Our ‘line-of-argument’ model describes how motivation, ease of use, and device purpose determine if a device is perceived to add value to the user’s life, which subsequently predicts if the device will be integrated into the user’s life. CONCLUSIONS In order to overcome usability barriers (e.g. limited technical ability), a support structure should be placed around the user that fosters motivation, encourages engagement with peers, and adapts to the user’s preferences. Future research should evaluate our model by conducting long term WD trials that use qualitative methods to comprehensively address the multiple stages of device use and the many factors that contribute to adherence.