Remote health coaching for interactive exercise with older adults in a home environment

Jimison, Holly; Hagler, Stuart; Kurillo, Gregorij; Bajcsy, Růžena; Pavel, Misha

doi:10.1109/embc.2015.7319633

Cited by 15 publications

(46 citation statements)

References 16 publications

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“…Randomized trial [2,3,11,48,55,56] Pilot study [12,13,14,21,26,31,35,39,40,43,44,45,46,47,53,54] Observational study [28,30] Preliminary studies for assessing usability or codesign choices [1,5,9,15,18,20,23,24,27,34,49] System proposal (no user study) [6,16,17,19,22,25,29,36,52] Study protocol [4,7,8,32,33,41] Field study [10,…”

Section: Type Of Study Papersmentioning

confidence: 99%

“…Hence, because of a limited understanding of how to design and implement e-coaching interventions for older adults, as well as limited evidence regarding their effectiveness in promoting healthrelated outcomes, we refrained from excluding further papers and kept all 56 for our analysis. In fact, among the 56 papers selected as eligible for the analysis, five reported results of randomized controlled trials [2,3,11,55,56] and one study was a clinical trial [48], six reported protocols for future randomized trials [4, 7, 8, 32, 33, 41], 16 presented results of pilot studies [12,13,14,21,26,31,35,39,40,43,44,45,46,47,53,54] and two were observational studies [28,30], while [38] presented a pre-post intervention study. Eleven presented the results of a preliminary assessment of a system in terms of usability or co-design choice [1,5,9,15,18,20,23,24,27,34,49], four [10,42,50,51] presented a field study for deriving the requirements of a coaching system, and nine presented only a proposal of a coaching system or an architectural implementation, without any user study [6,…”

Section: Type Of Study Papersmentioning

confidence: 99%

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Virtual Coaches for Older Adults’ Wellbeing: A Systematic Review

et al. 2020

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Virtual Coaches, also known as e-coaches, are a disruptive technology in healthcare. Indeed, among other usages, they might provide cost-effective solutions for increasing human wellbeing in different domains, such as physical, nutritional, cognitive, social, and emotional. This paper presents a systematic review of virtual coaches specifically aimed at improving or maintaining older adults' health in the aforementioned domains. Such digital systems assume various forms, from classic apps, to more advanced conversational agents or robots. Fifty-six articles describing a virtual coach for older adults and aimed at improving their wellbeing were identified and further analyzed. In particular, we presented how previous studies defined their virtual coaches, which behavioral change models and techniques they adopted and the overall system architecture, in terms of monitoring solutions, processing methods and modalities for intervention delivery. Our results show that few thorough evaluations of e-coaching systems have been conducted, especially regarding multi-domain coaching approaches. Through our analysis, we identified the wellbeing domains that should be addressed in future studies as well as the most promising behavior change models and techniques and coaching interfaces. Previous work illustrates that older adults often appreciate conversational agents and robots. However, the lack of a multidomain intervention approach in the current literature motivates us to seek to define future solutions.

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Section: Type Of Study Papersmentioning

confidence: 99%

Section: Type Of Study Papersmentioning

confidence: 99%

Virtual Coaches for Older Adults’ Wellbeing: A Systematic Review

et al. 2020

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Section: Behavior Modelingmentioning

confidence: 99%

“…Research [22] shows that most behavior changes require new knowledge, though knowledge alone may not be sufficient to bring about the desired behavior change. According to Jimison et al [22], human cognition (what people know and think) and behavior (people's action) go hand in hand. Behavior modeling, in the context of SCT, is a behavior change technique through which a domain expert or coach teaches an observer (by way of demonstration) how to perform a given behavior correctly, in either physical setting (e.g., gym) or virtual setting (e.g., video).…”

Section: Behavior Modelingmentioning

confidence: 99%

“…In this section, we present a review of the literature related to behavior modeling in the health domain. Jimison et al [22] investigated the effectiveness of using interactive exercise videos for remote coaching of older adults in their homes. They developed an online-based interactive video exercise system (composed of a human behavior model and Kinect camera's skeleton representation), which was used to demonstrate the performance of certain types of chair exercises to older adults residing in their homes.…”

Section: Related Workmentioning

confidence: 99%

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Investigation of the moderating effect of race-based personalization of behavior model design in fitness application

Oyibo

Vassileva

2019

SN Appl. Sci.

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Persuasive technologies are more likely to be successful if personalized to the target audience. However, in the context of exercise behavior modeling in fitness applications, there is limited research on the moderating effect of personalization based on the race characteristic of the user. To bridge this gap, we carried out an empirical study (n = 669) to examine how race-based personalization moderates the relationships between the perceived persuasiveness of behavior model design and three key social-cognitive determinants of behavior: outcome expectations, self-efficacy beliefs, and self-regulation beliefs. We based our investigation on user evaluation of bodyweight-exercise behavior models (videos) featured in a fitness app prototype based on all four constructs. Our results showed that, in both tailored and untailored contexts, behavior models (i.e., their perceived persuasiveness) have a significant influence on both black/brown and white users' outcome expectations and self-regulation beliefs. However, they are more likely to be effective in influencing black/brown observers than white observers in the respective contexts. Moreover, black/brown models are more likely to have a significant influence on users' self-efficacy beliefs than white models. Specifically, it is only when the black/brown models are tailored to black/brown observers and contra-tailored to white observers that the perceived persuasiveness of behavior model design has a significant effect on self-efficacy beliefs. Finally, among black/brown observers, our results indicate that behavior model designs are more likely to be effective when tailored than when contra-tailored or untailored, but this is hardly the case among white users. Our study contributes to the body of knowledge by being one of the first to demonstrate the potential effectiveness of race-based personalization of exercise behavior models in the domain of persuasive technologies aimed at motivating behavior change.

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