1
|
Xu Y, Huang Q, Teng S, Wang Y, Sun H, Li M, Li J, Zhu M, Tang X. Aged smart-care application program for promoting quality of life among older adults in the community: Study protocol of a three-arm randomized controlled trial. Digit Health 2025; 11:20552076251326218. [PMID: 40109406 PMCID: PMC11920978 DOI: 10.1177/20552076251326218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2024] [Accepted: 02/18/2025] [Indexed: 03/22/2025] Open
Abstract
Objectives To describe a study protocol for a three-arm randomized controlled trial that will evaluate the effectiveness of an Aged Smart-Care (ASC) application program intervention for community-dwelling older adults in China. Methods This randomized controlled trial with three arms will be conducted at eight community health service centers. Participants will be randomly assigned to one of three groups: the interactive ASC (ASC + I) group, the regular ASC group, or the control group. The ASC + I group will receive management from a multidisciplinary medical team, while the regular ASC group will only utilize the ASC. The primary outcome will be assessed using the Medical Outcomes Study Short Form 36 (SF-36) Health Survey. The secondary outcomes include general self-efficacy, medication adherence, effectiveness of health behavior interventions, BMI, number of outpatient visits, and number of hospitalizations. Data will be collected at baseline, immediately post-intervention, 3 months, 6 months, and 1 year after the intervention. Generalized estimating equations model will be employed for data analysis. Conclusions This study clarifies the development process of the ASC and designs a three-arm randomized controlled trial to examine the efficacy of the ASC for older adults in the community. The results of the study will compare differences in the quality of life of participants in different groups. This will help community healthcare workers to choose appropriate interventions regarding the ASC. Furthermore, this provides scientific guidance for the Integrated Theory of Health Behavior Change theory in the field of mobile health tool development.
Collapse
Affiliation(s)
- Yue Xu
- School of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Qiyuan Huang
- School of Nursing, Fujian Medical University, Fuzhou, Fujian, China
| | - Shuang Teng
- School of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Yulong Wang
- School of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Huabei Sun
- The People's Hospital of Pizhou, Xuzhou, Jiangsu, China
| | - Mei Li
- The People's Hospital of Pizhou, Xuzhou, Jiangsu, China
| | - Junxin Li
- Johns Hopkins School of Nursing, Baltimore, MD, USA
| | - Muwei Zhu
- School of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Xianping Tang
- School of Nursing, Xuzhou Medical University, Xuzhou, Jiangsu, China
| |
Collapse
|
2
|
Qu NZ, Li J, Kongmanee J, Chignell M. Public opinion on types of voice systems for older adults. J Rehabil Assist Technol Eng 2024; 11:20556683241287414. [PMID: 39421012 PMCID: PMC11483701 DOI: 10.1177/20556683241287414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2024] [Accepted: 09/12/2024] [Indexed: 10/19/2024] Open
Abstract
Public opinion may influence the adoption of technologies for older adults, yet studies on different contexts of technology for older adults is limited. In an online YouGov survey (N = 500) with text-and-image vignettes, participants gave more positive ratings of social acceptability, trust, and perceived impact on eldercare when the voice assistant ("VA" system) shown in the vignette performed a functional task (medication adherence) versus when it performed a social task (companionship). The VA received more positive sentiment comments when it appeared to use a machine learning (ML)-based dialogue system compared to when it appeared to be using a rule-based dialogue system. These results may assist designers and stakeholders select what type of voice system to develop or use with older adults.
Collapse
Affiliation(s)
- Noah Zijie Qu
- Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Jamy Li
- School of Computing Engineering and the Built Environment, Edinburgh Napier University, Edinburgh, Scotland, UK
| | - Jaturong Kongmanee
- Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| | - Mark Chignell
- Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
3
|
Shah RR, Dixon CC, Fowler MJ, Driesse TM, Liang X, Summerour CE, Gross DC, Spangler HB, Lynch DH, Batsis JA. Using Voice Assistant Systems to Improve Dietary Recall among Older Adults: Perspectives of Registered Dietitians. J Nutr Gerontol Geriatr 2024; 43:1-13. [PMID: 38287658 PMCID: PMC10922685 DOI: 10.1080/21551197.2024.2302619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Dietary assessments are important clinical tools used by Registered Dietitians (RDs). Current methods pose barriers to accurately assess the nutritional intake of older adults due to age-related increases in risk for cognitive decline and more complex health histories. Our qualitative study explored whether implementing Voice assistant systems (VAS) could improve current dietary recall from the perspective of 20 RDs. RDs believed the implementing VAS in dietary assessments of older adults could potentially improve patient accuracy in reporting food intake, recalling portion sizes, and increasing patient-provider efficiency during clinic visits. RDs reported that low technology literacy in older adults could be a barrier to implementation. Our study provides a better understanding of how VAS can better meet the needs of both older adults and RDs in managing and assessing dietary intake.
Collapse
Affiliation(s)
- Rahi R. Shah
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| | - Claudia C. Dixon
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| | - Michael J. Fowler
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| | - Tiffany M. Driesse
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| | - Xiaohui Liang
- Department of Computer Science, University of Massachusetts Boston, Boston, MA
| | - Caroline E. Summerour
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
| | - Danae C. Gross
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| | - Hillary B. Spangler
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
| | - David H. Lynch
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
| | - John A. Batsis
- Division of Geriatric Medicine, University of North Carolina School of Medicine, Chapel Hill NC
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill NC
| |
Collapse
|
4
|
Chen C, Lifset ET, Han Y, Roy A, Hogarth M, Moore AA, Farcas E, Weibel N. Screen or No Screen? Lessons Learnt from a Real-World Deployment Study of Using Voice Assistants With and Without Touchscreen for Older Adults. ASSETS. ANNUAL ACM CONFERENCE ON ASSISTIVE TECHNOLOGIES 2023; 2023:52. [PMID: 39086515 PMCID: PMC11290471 DOI: 10.1145/3597638.3608378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing structured requests and perceiving how such devices operate. Voice-first user interfaces have the potential to address these challenges by enabling multimodal interactions. Standalone voice + touchscreen Voice Assistants (VAs), such as Echo Show, are specific types of devices that adopt such interfaces and are gaining popularity. However, the affordances of the additional touchscreen for older adults are unknown. Through a 40-day real-world deployment with older adults living independently, we present a within-subjects study (N = 16; age M = 82.5, SD = 7.77, min. = 70, max. = 97) to understand how a built-in touchscreen might benefit older adults during device setup, conducting self-report diary survey, and general uses. We found that while participants appreciated the visual outputs, they still preferred to respond via speech instead of touch. We identified six design implications that can inform future innovations of senior-friendly VAs for managing healthcare and improving quality of life.
Collapse
Affiliation(s)
- Chen Chen
- Computer Science and Engineering, University of California San Diego, La Jolla, CA, United States
| | - Ella T Lifset
- Biological Sciences, University of California San Diego, La Jolla, CA, United States
| | - Yichen Han
- Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Arkajyoti Roy
- Department of Mathematics, University of California San Diego, La Jolla, CA, United States
| | - Michael Hogarth
- School of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Alison A Moore
- School of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Emilia Farcas
- Qualcomm Institute, University of California San Diego, La Jolla, CA, United States
| | - Nadir Weibel
- Computer Science and Engineering, University of California San Diego, La Jolla, CA, United States
| |
Collapse
|
5
|
Chen C, Lifset ET, Han Y, Roy A, Hogarth M, Moore AA, Farcas E, Weibel N. How do Older Adults Set Up Voice Assistants? Lessons Learned from a Deployment Experience for Older Adults to Set Up Standalone Voice Assistants. DIS. DESIGNING INTERACTIVE SYSTEMS (CONFERENCE) 2023; 2023:164-168. [PMID: 39081517 PMCID: PMC11288472 DOI: 10.1145/3563703.3596640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
While standalone Voice Assistants (VAs) are promising to support older adults' daily routine and wellbeing management, onboarding and setting up these devices can be challenging. Although some older adults choose to seek assistance from technicians and adult children, easy set up processes that facilitate independent use are still critical, especially for those who do not have access to external resources. We aim to understand the older adults' experience while setting up commercially available voice-only and voice-first screen-based VAs. Rooted in participants observations and semi-structured interviews, we designed a within-subject study with 10 older adults using Amazon Echo Dot and Echo Show. We identified the values of the built-in touchscreen and the instruction documents, as well as the impact of form factors, and outline important directions to support older adult independence with VAs.
Collapse
Affiliation(s)
- Chen Chen
- Computer Science and Engineering, University of California San Diego, La Jolla, CA, United States
| | - Ella T Lifset
- Biological Sciences, University of California San Diego, La Jolla, CA, United States
| | - Yichen Han
- Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Arkajyoti Roy
- Department of Mathematics, University of California San Diego, La Jolla, CA, United States
| | - Michael Hogarth
- School of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Alison A Moore
- School of Medicine, University of California San Diego, La Jolla, CA, United States
| | - Emilia Farcas
- Qualcomm Institute, University of California San Diego, La Jolla, CA, United States
| | - Nadir Weibel
- Computer Science and Engineering, University of California San Diego, La Jolla, CA, United States
| |
Collapse
|