Older Adults’ Use of and Attitudes toward Activity Monitoring Technologies

Fausset, Cara Bailey; Mitzner, Tracy L.; Price, Chandler; Jones, Brian; Fain, Brad; Rogers, Wendy A.

doi:10.1177/1541931213571374

Cited by 66 publications

(57 citation statements)

References 10 publications

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“…Furthermore, we found that non-users expected WATs to track diverse activities and were disappointed that the technology did not do it. This is echoed by the findings of another study advocating for a more tailored approach to tracking activities salient to older adults [39]. Additionally, our findings regarding social support strengthened the evidence from previous studies where social support has been found to be one of the most important and consistent predictors of physical activity adherence [40][41][42][43].…”

Section: Comparison With Prior Worksupporting

confidence: 76%

The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change (Preprint)

Kononova¹,

Li²,

Kamp³

et al. 2018

Preprint

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Background: Physical activity benefits older adults by protecting against morbidity and mortality. Wearable activity trackers (WATs) offer the opportunity to increase physical activity through continuous monitoring. We explore the nuances of WAT use and adoption among older adults using the transtheoretical model (TTM) of behavior change. Objective: We investigate older adults' perceptions and uses of WATs in different stages of WAT adoption. Method: Data for the research come from 10 focus groups. The first set of focus groups was with participants who had never used WATs. These focus groups included a WAT trial. Other focus groups (without the trial) were conducted with short-term, long-term, and former WAT users. Results: Older adults in different WAT use stages liked and wished for different WAT features, with long-term users being the most diverse and sophisticated users of WATs. Long-term users had developed a habit of WAT use while other participants needed to employ various encouragement strategies. Social support, with the focus on collaboration, was the primary motivator for long-term users, while short-term and former users focused on competition, and non-users engaged in vicarious WAT use experiences. Finally, longterm users were more likely to see benefits of WATs while other participants focused on obstacles related to WAT use. Conclusion: WATs may be an effective technology to encourage physical activity among older adults. Yet, WATs alone are not likely to be successful in changing behavior. Tailored approaches based on the TTM stage of change as well as motivations, facilitators, and specific WAT characteristics that are important for older adults will ensure successful longterm use.Keywords: older adults, wearable activity trackers, Transtheoretical Model, physical activity, focus groups IntroductionThe focus of the present study is on exploring the nuances of adopting wearable activity trackers (WATs) in the population of adults who are 65 years of age or older using the transtheoretical model of behavior change (TTM) [1]. Academic and industry research has shown that the use of WATs can increase physical activity through continuous monitoring of activity progress [2][3]. Physical activity is beneficial for older adults due to its protective power against chronic diseases, many of which increase with older age [4].Despite the evident benefits of WATs for older generations, digital care today is more available to younger populations, leaving older adults on the periphery of the industry [5]. 1As little as 7% of older adults owned an activity tracker in 2014 [6]. Only a few studies have been done to understand how and why older adults use WATs and why they choose not to use or stop using this wearable technology [7][8][9].Even if individuals decide to use WATs, it does not guarantee that they will continue using them on a long-term basis. One in three WAT users of all adult ages stop using the device within six months after purchase [10][11]. Length of use is correlated with age, with th...

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Section: Comparison With Prior Worksupporting

confidence: 76%

The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change (Preprint)

Kononova¹,

Li²,

Kamp³

et al. 2018

Preprint

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“…Coding schemes were developed based on the findings from the heuristic evaluation, and the pilot study (Fausset et al, 2013). The initial interview and diaries also influenced the coding scheme for the final interview.…”

Section: Resultsmentioning

confidence: 99%

Older Adults’ Acceptance of Activity Trackers

et al. 2016

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Objective To assess the usability and acceptance of activity tracking technologies by older adults. Method First in our multi-method approach, we conducted heuristic evaluations of two activity trackers that revealed potential usability barriers to acceptance. Next, questionnaires and interviews were administered to 16 older adults (Mage=70, SDage=3.09, rangeage= 65-75) before and after a 28-day field study to understand facilitators and additional barriers to acceptance. These measurements were supplemented with diary and usage data and assessed if and why users overcame usability issues. Results The heuristic evaluation revealed usability barriers in System Status Visibility; Error Prevention; and Consistency and Standards. The field study revealed additional barriers (e.g., accuracy, format), and acceptance-facilitators (e.g., goal-tracking, usefulness, encouragement). Discussion The acceptance of wellness management technologies, such as activity trackers, may be increased by addressing acceptance-barriers during deployment (e.g., providing tutorials on features that were challenging, communicating usefulness).

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“…More recent studies (e.g., [4]- [6], [8]) explored reasons for abandoning activity trackers in more naturalistic settings. [5] observed that older adults stopped using their activity monitors when the device was uncomfortable or the data it collected was inaccurate. [8] argued that for long-term use motivational affordances are required, otherwise informational affordances of such activity trackers diminish over time.…”

Section: Background and Related Workmentioning

confidence: 99%

An Exploratory Study for Understanding Reasons of (Not-)Using Internet of Things

Garg

Kim

2018

Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems

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The potential of things or objects generating and processing data about day-to-day activities of its users has given a new level of popularity to Internet of Things (IoT) among its consumers. Even though the popularity has seen a steady increase, the use of IoT devices has been slow and abandonment rapid. To build on the existing literature and advance our understanding of the sociological processes of use and non-use of these devices, this paper presents results from the survey of 489 IoT users. Our qualitative analysis of open ended questions revealed that the motives for use include multi-functionality of devices that provide control over daily activities, social competitive edge, economic advantage, and habit. The justifications for limiting or stopping the use include privacy concerns, information overload and inaccuracy, demotivation because of the reminders about pending or failed goals, no excitement after satisfying initial curiosity, and maintenance becoming unmanageable in terms of effort, time, and money.

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Older Adults’ Use of and Attitudes toward Activity Monitoring Technologies

Cited by 66 publications

References 10 publications

The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change (Preprint)

The Use of Wearable Activity Trackers Among Older Adults: Focus Group Study of Tracker Perceptions, Motivators, and Barriers in the Maintenance Stage of Behavior Change (Preprint)

Older Adults’ Acceptance of Activity Trackers

An Exploratory Study for Understanding Reasons of (Not-)Using Internet of Things

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