Wearable device adoption among older adults: A mixed-methods study

Farivar, Samira; Abouzahra, Mohamed; Ghasemaghaei, Maryam

doi:10.1016/j.ijinfomgt.2020.102209

Cited by 87 publications

(63 citation statements)

References 130 publications

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“…The most frequently recognized barrier (65%) was perceived lack of skills and knowledge to use wearable monitoring technology in patients. Obviously, cognitive problems and generally older age might complicate the use of technological devices in daily life in stroke patients [36]. Especially for this group of patients, a user-friendly design of technology is desirable [14,28].…”

Section: Discussionmentioning

confidence: 99%

Wearable Activity Monitoring in Day-to-Day Stroke Care: A Promising Tool but Not Widely Used

Braakhuis

Bussmann

Ribbers

et al. 2021

Sensors

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Physical activity monitoring with wearable technology has the potential to support stroke rehabilitation. Little is known about how physical therapists use and value the use of wearable activity monitors. This cross-sectional study explores the use, perspectives, and barriers to wearable activity monitoring in day-to-day stroke care routines amongst physical therapists. Over 300 physical therapists in primary and geriatric care and rehabilitation centers in the Netherlands were invited to fill in an online survey that was developed based on previous studies and interviews with experts. In total, 103 complete surveys were analyzed. Out of the 103 surveys, 27% of the respondents were already using activity monitoring. Of the suggested treatment purposes of activity monitoring, 86% were perceived as useful by more than 55% of the therapists. The most recognized barriers to clinical implementation were lack of skills and knowledge of patients (65%) and not knowing what brand and type of monitor to choose (54%). Of the non-users, 79% were willing to use it in the future. In conclusion, although the concept of remote activity monitoring was perceived as useful, it was not widely adopted by physical therapists involved in stroke care. To date, skills, beliefs, and attitudes of individual therapists determine the current use of wearable technology.

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Section: Discussionmentioning

confidence: 99%

Wearable Activity Monitoring in Day-to-Day Stroke Care: A Promising Tool but Not Widely Used

Braakhuis

Bussmann

Ribbers

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…Meanwhile, the perception of usefulness and ease of use will have a significant impact on the adoption behavior of individual users in various fields (Li et al, 2012;Wang, 2015;Elhajjar & Ouaida, 2019). The influencing factors of the adoption behavior of individual users can be divided into the following three categories: (1) Psychological factors mainly include user perception, behavior and attitude (Wang et al, 2015;Li & Zhong, 2016), user expectations (Liu, 2015;Geng et al, 2017;Yuen et al, 2021), cognition (Farivar et al, 2020), self-efficacy (Alam et al, 2020;Irfan et al, 2020) and user trust level (Liu, 2015;Li & Zhong, 2016). ( 2) Technical characteristics mainly include compatibility (Yang et al, 2012), matching degree of task and technology (Liu, 2015), task characteristics (Wang, 2015) and technical characteristics and convenience (Alam et al, 2020).…”

Section: Adoption Behavior Of Individual Usersmentioning

confidence: 99%

Adoption behavior of water efficiency labeling: origin, research progress and theoretical framework – evidence from China

et al. 2021

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Research on the adoption behavior of water efficiency labeling is of great significance for improving citizens' water-saving consciousness and promoting water-saving techniques and standards. This study sorted out 559 papers about adoption behavior and then systematically analyzed the origin and research progress of water efficiency labeling in different fields. Finally, related theories and empirical analysis are integrated, and a research framework of ‘gold ingot’ that focuses on adoption behavior is constructed. The study found that the research mainly involves three contents in the current: adoption behavior of corporate users, adoption behavior of rural households and adoption behavior of individual users. Based on the above literature analysis, this study proposes a theoretical framework for research on the adoption behavior of water efficiency labeling.

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“…The development of technologies to support healthy aging efforts are on the rise. These technologies include wearable and remote pervasive sensors, voice activated systems, and predictive analytics, including digital phenotyping (11)(12)(13)(14)(15)(16). Digital tools and strategies are increasingly applied to health promotion, disease prevention, and treatment efforts yet, are not always tested with diverse populations.…”

Section: Introductionmentioning

confidence: 99%

Learning From Older Adults to Promote Independent Physical Activity Using Mobile Health (mHealth)

Nebeker

Zlatar

2021

Front. Public Health

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Background: Healthy aging is critically important for several reasons, including economic impact and quality of life. As the population of older adults rapidly increases, identifying acceptable ways to promote healthy aging is a priority. Technologies that can facilitate health promotion and risk reduction behaviors may be a solution, but only if these mobile health (mHealth) tools can be used by the older adult population. Within the context of a physical activity intervention, this study gathered participant's opinions about the use of an mHealth device to learn about acceptance and to identify areas for improvement.Methods: The Independent Walking for Brain Health study (NCT03058146) was designed to evaluate the effectiveness of a wearable mHealth technology in facilitating adherence to a physical activity prescription among participants in free-living environments. An Exit Survey was conducted following intervention completion to gauge participant's perceptions and solicit feedback regarding the overall study design, including exercise promotion strategies and concerns specific to the technology (e.g., privacy), that could inform more acceptable mHealth interventions in the future. The Digital Health Checklist and Framework was used to guide the analysis focusing on the domains of Privacy, Access and Usability, and Data Management.Results: Participants (n = 41) were in their early 70's (mean = 71.6) and were predominantly female (75.6%) and White (92.7%). Most were college educated (16.9 years) and enjoyed using technology in their everyday life (85.4%). Key challenges included privacy concerns, device accuracy, usability, and data access. Specifically, participants want to know what is being learned about them and want control over how their identifiable data may be used. Overall, participants were able to use the device despite the design challenges.Conclusions: Understanding participant's perceptions of the challenges and concerns introduced by mHealth is important, as acceptance will influence adoption and adherence to the study protocol. While this study learned from participants at studycompletion, we recommend that researchers consider what might influence participant acceptance of the technology (access, data management, privacy, risks) and build these into the mHealth study design process. We provide recommendations for future mHealth studies with older adults.

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Wearable device adoption among older adults: A mixed-methods study

Cited by 87 publications

References 130 publications

Wearable Activity Monitoring in Day-to-Day Stroke Care: A Promising Tool but Not Widely Used

Wearable Activity Monitoring in Day-to-Day Stroke Care: A Promising Tool but Not Widely Used

Adoption behavior of water efficiency labeling: origin, research progress and theoretical framework – evidence from China

Learning From Older Adults to Promote Independent Physical Activity Using Mobile Health (mHealth)

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