Healthy Aging

会議の名前
CHI 2024
Redefining Activity Tracking Through Older Adults' Reflections on Meaningful Activities
要旨

Activity tracking has the potential to promote active lifestyles among older adults. However, current activity tracking technologies may inadvertently perpetuate ageism by focusing on age-related health risks. Advocating for a personalized approach in activity tracking technology, we sought to understand what activities older adults find meaningful to track and the underlying values of those activities. We conducted a reflective interview study following a 7-day activity journaling with 13 participants. We identified various underlying values motivating participants to track activities they deemed meaningful. These values, whether competing or aligned, shape the desirability of activities. Older adults appreciate low-exertion activities, but they are difficult to track. We discuss how these activities can become central in designing activity tracking systems. Our research offers insights for creating value-driven, personalized activity trackers that resonate more fully with the meaningful activities of older adults.

著者
Yiwen Wang
University of Maryland, College Park, Maryland, United States
Mengying Li
University of Maryland-Park, College Park, Maryland, United States
Young-Ho Kim
NAVER AI Lab, Seongnam, Gyeonggi, Korea, Republic of
Bongshin Lee
Microsoft Research, Redmond, Washington, United States
Margaret Danilovich
CJE SeniorLife, Chicago, Illinois, United States
Amanda Lazar
University of Maryland, College Park, Maryland, United States
David E Conroy
The Pennsylvania State University, University Park, Pennsylvania, United States
Hernisa Kacorri
University of Maryland, College Park, Maryland, United States
Eun Kyoung Choe
University of Maryland, College Park, Maryland, United States
論文URL

doi.org/10.1145/3613904.3642170

動画
“X-Ray Vision” as a Compensatory Augmentation for Slowing Cognitive Map Decay in Older Adults
要旨

Safe and efficient navigation often relies on the development and retention of accurate cognitive maps that include inter-landmark relations. For many older adults, cognitive maps are difficult to form and remember over time, which introduces serious challenges for independence and mobility. To address this problem, we explore an innovative compensatory augmentation solution enabling enhanced inter-landmark learning via an “X-Ray Vision” simulation. Results with (n=45) user study participants suggest superior older adult cognitive map retention over time from a single learning session with the augmentation versus a control condition without the augmentation. Furthermore, results characterize differences in decay of cognitive maps between older adults and a control of younger adults. These findings suggest important implications for future augmented reality devices and the ways in which they can be used to promote memory and independence among older adults.

著者
Christopher Bennett
The University of Maine, Orono, Maine, United States
Paul D. S.. Fink
The University of Maine, Orono, Maine, United States
Nicholas A. Giudice
The University of Maine, Orono, Maine, United States
論文URL

doi.org/10.1145/3613904.3642644

動画
Mentorable Interfaces for Automated Vehicles: A New Paradigm for Designing Learnable Technology for Older Adults
要旨

We introduce a conceptual framework exploring the learning methods for older adults in navigating automated vehicle interfaces. Through semi-structured interviews, we observed distinct approaches to learning, and based on these, offer a novel conceptualization of a ‘mentorable’ interface to enhance technology education. The introduction of automated vehicles (AVs) to transportation has required novel lenses to technology adoption. Although AVs require less demand in cognitive, motor, and sensory acuity, there is an increasing dependence on digital literacy. While technology education has been broadly explored through the lens of learnability, this paradigm does not work well for older adults due to its inherent trial-and-error approach to independent learning. Because older adults rely heavily on additional external support in learning technologies, we present a conceptual framework for ‘mentorability’, where a network of support is emphasized, and mentorship is integrated into the design process for in-vehicle interfaces.

著者
Togtokhtur Batbold
Queensland University of Technology, Brisbane, Australia
Alessandro Soro
Queensland University of Technology, Brisbane, Australia
Ronald Schroeter
Queensland University of Technology (QUT), Brisbane, Australia
論文URL

doi.org/10.1145/3613904.3642390

動画
LightSword: A Customized Virtual Reality Exergame for Long-Term Cognitive Inhibition Training in Older Adults
要旨

The decline of cognitive inhibition significantly impacts older adults' quality of life and well-being, making it a vital public health problem in today's aging society. Previous research has demonstrated that Virtual reality (VR) exergames have great potential to enhance cognitive inhibition among older adults. However, existing commercial VR exergames were unsuitable for older adults' long-term cognitive training due to the inappropriate cognitive activation paradigm, unnecessary complexity, and unbefitting difficulty levels. To bridge these gaps, we developed a customized VR cognitive training exergame (LightSword) based on Dual-task and Stroop paradigms for long-term cognitive inhibition training among healthy older adults. Subsequently, we conducted an eight-month longitudinal user study with 12 older adults aged 60 years and above to demonstrate the effectiveness of LightSword in improving cognitive inhibition. After the training, the cognitive inhibition abilities of older adults were significantly enhanced, with benefits persisting for 6 months. This result indicated that LightSword has both short-term and long-term effects in enhancing cognitive inhibition. Furthermore, qualitative feedback revealed that older adults exhibited a positive attitude toward long-term training with LightSword, which enhanced their motivation and compliance.

著者
Qiuxin Du
Beijing Institute of Technology, Beijing, Haidian District, China
Zhen Song
The Central Academy of Drama, Beijing, China
Haiyan Jiang
Beijing Institute of Technology, Beijing, China
Xiaoying Wei
IIP(Computational Media and Arts), Hong Kong, China
Dongdong Weng
Beijing Institute of Technology, Beijing, China
Mingming Fan
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
論文URL

doi.org/10.1145/3613904.3642187

動画