A review of activity trackers for senior citizens: research perspectives, commercial landscape and the role of the insurance industry

The objective assessment of physical activity levels through wearable inertial-based motion detectors for the automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in the literature. However, their application to older adults can present particular constraints. This paper reviews the adoption of wearable devices in senior citizens by describing various researches for monitoring physical activity indicators, such as energy expenditure, posture transitions, activity classification, fall detection and prediction, gait and balance analysis, also by adopting consumer-grade fitness trackers with the associated limitations regarding acceptability. This review also describes and compares existing commercial products encompassing activity trackers tailored for older adults, thus providing a comprehensive outlook of the status of commercially available motion tracking systems. Finally, the impact of wearable devices on life and health insurance companies, with a description of the potential benefits for the industry and the wearables market, was analyzed as an example of the potential emerging market drivers for such technology in the future

The use of mobile devices for physical activity tracking in older adults’ everyday life

Objective: The tracking of one’s own physical activity with mobile devices is a way of monitoring and motivating oneself to remain healthy. Older adults’ general use of mobile devices for physical activity tracking has not yet been examined systematically. The study aimed to describe the use of physical activity trackers, smartwatches and smartphones, or tablets for tracking physical activity and to examine the reasons for the use of these technologies. Methods: Participants aged ≥50 years (N = 1013) living in Switzerland were interviewed in a telephone survey. To address the research questions, we calculated descriptive frequency distributions, tested for differences between groups, and performed logistic regression analyses. Results: Descriptive and multivariate analyses showed that (a) 20.5% of participants used mobile devices for physical activity tracking; (b) men, younger individuals, those with a strong interest in new technology, and those who frequently exercised had a higher likelihood of using mobile devices for physical activity tracking; and (c) participants more often agreed with reasons for use relating to tracking physical activity and motivating oneself to remain healthy than they did with reasons relating to social factors. Conclusions: The study presented representative data about the actual use of mobile tracking technology in persons over 50 years of age. Today, mainly active and younger elderly (mostly men) with a high interest in technology are using tracking technologies. Results indicate a need for further studies on motivational and usability aspects regarding the use of mobile health tracking devices by older adults

Applying Ajzen's Theory of Planned Behaviour: Changing Physical Activity Health Behaviour with Activity-Tracking Technology

Pairing modern day technology with Azjen’s popular Theory of Planned Behaviour, the objectives were to i) determine whether a mobile connected activity-tracking device could change physical activity (PA) health behaviour, ii) test whether the theory of planned behaviour (TPB) could predict participation in physical activity, measured by mobile technology, iii) determine if PA engagement is correlated with mobile communication usage and vehicle journey time. Participants consisted of 41 males and 28 females (N=69), each completing standard TPB measures at baseline. Intervention included a health warning/advice sheet and the physical attachment of an activity-tracking device paired with a mobile application for the duration of two weeks. The data retrieved included the participant’s daily steps count, the participant’s daily time spent travelling by motor vehicle or not, and the participant’s daily amount of mobile communication usage time. A statistically significant increase in activity was observed in the device-wearing group, with a medium effect size. Findings did not support the TPB as a predictor of PA engagement in a technology intervention context. There was no statistical relationship between PA participation and mobile communication usage or vehicle journey time. Findings suggest a basis for developing interventions to include mobile connected devices for improved behavioural health

Physical Activity and Psychological Well-Being in Older Adults

A growing body of research suggests that physical activity (PA) is positively associated with psychological well-being in various populations. However, previous studies have predominantly focused on the preventive or curative effect of PA on negative psychological disorders, such as depression and anxiety, while largely ignored the positive psychological well-being, which is commonly conceptualized by two distinct dimensions, i.e., hedonic well-being and eudaimonic well-being. Both hedonic well-being and eudaimonic well-being are predictive of various health outcomes in older adults. Therefore, there is a need for more research to explore the relationship between PA and psychological well-being, especially the positive aspects of psychological well-being, in the older population. This dissertation includes three distinct but related papers to extend our current knowledge on the relationship between PA and psychological well-being in older adults. In the first study, I used the longitudinal data collected at three time points from the Health and Retirement Study (HRS) to examine the potential bidirectional relationship between PA and purpose in life, the latter of which is a key component of eudaimonic well-being, in a sample of 4591 older individuals. The cross-lagged panel analysis, adjusting for a range of sociodemographic and health covariates, did not support a bidirectional relationship between PA and purpose in life in older adults. While purpose in life was positively associated with future vigorous-intensity PA, moderate-intensity PA, and light-intensity PA, none of the PA variables predicted purpose in life in later time points. The second study and the third study were based on a 12-week multicomponent intervention conducted in older adults living in retirement communities. A total of 58 participants were voluntarily assigned to the experimental group (n =40) or the comparison group (n=18). The intervention group attended three 45-min group exercise lessons per week and wore a Fitbit activity tracker during the weekdays for 12 weeks combined with weekly feedback and personalized activity goals. The second study only involved participants in the experimental group and examined the effectiveness and acceptability of the Fitbit activity tracker for promoting PA. Daily step counts measured by the Fitbit activity tracker indicated that participants had an average increase of 900 steps/day from baseline to the end of the intervention. Individual interviews and the Acceptance questionnaire suggested that the Fitbit activity tracker was an acceptable and useful tool for older adults to self-track their PA. The third study examined the intervention effects on life satisfaction, happiness, eudaimonic well-being, depressive symptoms. Linear mixed models revealed that participants in the experimental group significantly improved happiness compared to the comparison group after controlling for baseline age and self-rated health. However, there was no difference regarding the changes in life satisfaction, eudaimonic well-being, and depressive symptoms between the two groups. Overall, this dissertation expands the current knowledge about the relationship between PA and psychological well-being in older adults. Combining the results from these studies suggests that the effect of PA on psychological well-being may differ by different components of psychological well-being. Future research should seek to explore the mechanisms linking the possible relationship between PA and psychological well-being, and develop more effective PA interventions to improve psychological well-being for the older population.PHDKinesiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163031/1/zzj_1.pd

Patters of use and key predictors for the use of wearable health care devices by US adults: insights from a national survey

Background: Despite the growing popularity of wearable health care devices (from fitness trackes such as Fitbit to smartwatches such as Apple Watch and more sophisticated devices that can collect information on metrics such as blood pressure, glucose levels, and oxygen levels), we have a limited understanding about the actual use and key factors affecting the use of these devices by US adults. Objective: The main objective of this study was to examine the use of wearable health care devices and the key predictors of wearable use by US adults. Methods: Using a national survey of 4551 respondents, we examined the usage patterns of wearable health care devices (use of wearables, frequency of their use, and willingness to share health data from a wearable with a provider) and a set of predictors that pertain to personal demographics (age, gender, race, education, marital status, and household income), individual health (general health, presence of chronic conditions, weight perceptions, frequency of provider visits, and attitude towards exercise), and technology self-efficacy using logistic regression analysis. Results: About 30% (1266/4551) of US adults use wearable health care devices. Among the users, nearly half (47.33%) use the devices every day, with a majority (82.38% weighted) willing to share the health data from wearables with their care providers. Women (16.25%), White individuals (19.74%), adults aged 18-50 years (19.52%), those with some level of college education or college graduates (25.60%), and those with annual household incomes greater than US $75,000 (17.66report using wearable health care devices. We found that the use of wearables declines with age: Adults aged >50 years were less likely to use wearables compared to those aged 18-34 years (odds ratios [OR] 0.46-0.57). Women (OR 1.26, 95White individuals (OR 1.65, 95incomes greater than US$75,000 (OR 2.6, 95% CI 1.39-4.86) were more likely to use wearables. US adults who reported feeling healthier (OR 1.17, 95% CI 0.98-1.39), were overweight (OR 1.16, 95% CI 1.06-1.27), enjoyed exercise (OR 1.23, 95% CI 1.06-1.43), and reported higher levels of technology self-efficacy (OR 1.33, 95% CI 1.21-1.46) were more likely to adopt and use wearables for tracking or monitoring their health. Conclusions: The potential of wearable health care devices is under-realized, with less than one-third of US adults actively using these devices. With only younger, healthier, wealthier, more educated, technoliterate adults using wearables, other groups have been left behind. More concentrated efforts by clinicians, device makers, and health care policy makers are needed to bridge this divide and improve the use of wearable devices among larger sections of American society [Abstract copyright: ©Ranganathan Chandrasekaran, Vipanchi Katthula, Evangelos Moustakas. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.10.2020.

Wearable devices to improve physical activity and reduce sedentary behaviour: an umbrella review

Background: Several systematic reviews (SRs), with and without meta-analyses, have investigated the use of wearable devices to improve physical activity, and there is a need for frequent and updated syntheses on the topic. Objective: We aimed to evaluate whether using wearable devices increased physical activity and reduced sedentary behaviour in adults. Methods: We conducted an umbrella review searching PubMed, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library, MedRxiv, Rxiv and bioRxiv databases up to February 5th, 2023. We included all SRs that evaluated the efficacy of interventions when wearable devices were used to measure physical activity in adults aged over 18 years. The primary outcomes were physical activity and sedentary behaviour measured as the number of steps per day, minutes of moderate to vigorous physical activity (MVPA) per week, and minutes of sedentary behaviour (SB) per day. We assessed the methodological quality of each SR using the Assessment of Multiple Systematic Reviews, version 2 (AMSTAR 2) and the certainty of evidence of each outcome measure using the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations). We interpreted the results using a decision-making framework examining the clinical relevance and the concordances or discordances of the SR effect size. Results: Fifty-one SRs were included, of which 38 included meta-analyses (302 unique primary studies). Of the included SRs, 72.5% were rated as 'critically low methodological quality'. Overall, with a slight overlap of primary studies (corrected cover area: 3.87% for steps per day, 3.12% for MVPA, 4.06% for SB) and low-to-moderate certainty of the evidence, the use of WDs may increase PA by a median of 1,312.23 (IQR 627-1854) steps per day and 57.8 (IQR 37.7 to 107.3) minutes per week of MVPA. Uncertainty is present for PA in pathologies and older adults subgroups and for SB in mixed and older adults subgroups (large confidence intervals). Conclusions: Our findings suggest that the use of WDs may increase physical activity in middle-aged adults. Further studies are needed to investigate the effects of using WDs on specific subgroups (such as pathologies and older adults) in different follow-up lengths, and the role of other intervention components

Rethinking Wearable Activity Trackers as Assistive Technologies: A Qualitative Study on Long-Term Use

This study proposes that wearable activity trackers (WATs), such as Fitbit, Apple Watch, can be viewed as assistive technologies to promote older adults’ health and independent living. Qualitative interview data with 20 older adults (65 and older) who had used WATs for six months or longer were analyzed within the framework of the Match Person and Technology (MPT) model. We found that personal and psychosocial factors, environmental factors, and technology-related factors contributed to the participants’ long-term engagement with WATs. Determination and self-discipline, support from one’s family members and friends, and goal setting and feedback of goal accomplishment were among the most mentioned facilitators of using WATs for more than six months. We discussed the design implications of these findings

Health Wearable Tools and Health Promotion

The application of wearable technology for health purposes is a multidisciplinary research topic. To summarize key contributions and simultaneously identify outstanding gaps in research, the input-mechanism-output (I-M-O) framework was applied to synthesize findings from 275 relevant papers in the period 2010–2021. Eighteen distinct cross-disciplinary themes were identified and organized under the I-M-O framework. Studies that covered input factors have largely been technocentric, exploring the design of various health wearables, with less emphasis on usability. While studies on user acceptance and engagement are increasing, there remains room for growth in user- centric aspects such as engagement. While measurement of physiological health indictors has grown more sophisticated due to sensitivity of sensors and the advancements in predictive algorithms, a rapidly growing area of research is that of measuring and tracking mental states and emotional health.Relatively few studies explore theoretically backed explanations of the role of health wearables, with technocentric theories predicting adoption favored. These mainly focused on mechanisms of adoption, while postadoption use and health behavior change were less explored. As a consequence, compared to adoption mechanisms, there is an opportunity to increase our understanding of the continued use of wearables and their effects on sustained health behavior change. While a range of incentives such as social, feedback, financial, and gamification are being tested, it is worth noting that negative attitudes, such as privacy concerns, are being paid much more attention as well. Output factors were studied in both individual and organizational settings, with the former receiving considerably more attention than the latter. The progress of research on health wearables was discussed from an interdisciplinary angle, and the role of social scientists was highlighted for the advancement of research on wearable health

Older adults’ experiences with using wearable devices:Qualitative systematic review and meta-synthesis

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