Mobile and Connected Health Technology Needs for Older Adults Aging in Place: Cross-Sectional Survey Study (Preprint)

Abstract

BACKGROUND An increasing number of mobile and wearable devices are available in the market. However, the extent to which these devices can be used to assist older adults to age in place remains unclear. OBJECTIVE This study aimed to assess older adults’ perceptions of using mobile and connected health technologies. METHODS Using a cross-sectional design, a total of 51 participants were recruited from a senior community center. Demographics and usage of mobile or wearable devices and online health communities were collected using a survey questionnaire. Descriptive statistics assessed usage of devices and online health communities. The Fisher exact test was used to examine the relationship between technology usage and having access to a smartphone. RESULTS The sample was primarily comprised non-Hispanic white (35/51, 69%), educated (39/51, 76% any college), and female (36/51, 71%) participants, with an average age of 70 (SD 8) years. All participants were insured and nearly all lived at home (49/51, 94%). A total of 86% (44/51) of the participants had heard of wearable health devices, but only 18 out of 51 (35%) had ever used them. Over 80% (42/51) expressed interest in using such devices and were interested in tracking exercise and physical activity (46/51, 90%), sleep (38/51, 75%), blood pressure (34/51, 67%), diet (31/51, 61%), blood sugar (28/51, 55%), weight (26/51, 51%), and fall risk (23/51, 45%). The greatest concerns about using wearable devices were cost (31/51, 61%), safety (14/51, 28%), and privacy (13/51, 26%); one-fourth (12/51) reported having no concerns. They were mostly interested in sharing data from mobile and connected devices with their health care providers followed by family, online communities, friends, and no one. About 41% (21/51) of the older adults surveyed reported having ever heard of an online health community, and roughly 40% (20/51) of the participants reported being interested in joining such a community. Most participants reported having access to a smartphone (38/51, 74%), and those with such access were significantly more likely to show interest in using a wearable health device (P<.001) and joining an online health community (P=.05). CONCLUSIONS Our findings suggest that, although few older adults are currently using mobile and wearable devices and connected health technologies for managing health, they are open to this idea and are mostly interested in sharing such data with their health care providers. Further studies are warranted to explore strategies to balance the data sharing preference of older adults and how to best integrate mobile and wearable device data with clinical workflow for health care providers to promote healthy aging in place.

Dual focus of Technology Acceptance and TechnologyResistant Model: Deep Learning Approach

“…Interestedly, eventhough aging specific factors and elders' propensity related to technology has a negative relationship; there was a positive influence of aging specific factors on technology usage. This result further confirmed that positive attitudes of elders towards their own aging [45], self-image congruence, believing that using technology will facilitate to organizing in the life (Choudrie et al (2017) and more sensitive to ergonomic design of technology (regarding material, weight, comfort, quality and features) rather than price sensitivity [16] are leading elders to seriously consider using the specific technology. This result is further confirmed by negatively influence of aging specific factors on elders' technology resistance.…”

“…On the basis of considering attitudes of older adults towards their own aging could foster increased access to and usability of technologies to support their independent living [45]. We, therefore, propose to include five aging-specific factors namely; Self-image congruence (SIC); Aging Satisfaction (AS); Performance Expectancy (PE); Effort Expectancy (EE) and Functional Congruence (FC) to offer a more accurate indulgent of consumer acceptance or resistance of technology in the aspect of elderly community.…”

Toward a Framework for Embodiment in Communication Technologies: Facilitating Social Connectivity for Older Adults

“…User-centered design is an iterative process which focuses on understanding the user and their context, across each stage of the design process, including the user in the actual design process (Gardan, 2017). The reviewed literature identifies education as another effective tool in addressing some of the challenges and concerns pertaining to technology (Wang et al, 2016). Practitioners and researchers should work together to develop educational tools (i.e., technology classes, tech training), which can help enhance older adults' ability to utilize technologies across the continuum of embodiment.…”

Coadaptation Between Smart Technologies and Older Adults Over Time: Protocol for a Scoping Review

“…Smart technologies can also be customized to a degree to the unique needs and preferences of older adults [15,16] and are increasingly used to support occupational and leisure activities in various aspects of daily life [14,17]. To date, research has demonstrated that smart technologies can promote independent living, enhance health and well-being, and help to improve the quality of life in older adults and their caregivers [14,[18][19][20][21]. For example, smart wearable devices can serve as fall detection and prevention tools, providing alerts or notifications in case of a fall or sudden changes in movement patterns that can help older adults with their self-management and active engagement [22,23].…”