Skip to main content
Top
Published in: BMC Geriatrics 1/2022

Open Access 01-12-2022 | Care | Research

The willingness and influencing factors to choose smart senior care among old adults in China

Authors: Qiyuan Huang, Ying Li, Xiang Wu, Song Ge, Zhe Qu, Aming Wang, Xianping Tang

Published in: BMC Geriatrics | Issue 1/2022

Login to get access

Abstract

Background

Population aging has become an escalating issue in China resulting in increasing healthcare demand. Smart senior care has the potential to help older adults live independently and relieve the pressure of healthcare including home-based care. This study aimed to explore Chinese older adults’ preferred access models and service content of smart senior care and factors affecting their willingness to choose smart senior care.

Methods

This was a cross-sectional study. A total of 760 community-dwelling older adults from Xuzhou, China were included in this study. Their demographics, family support, health status, smart senior care use, and willingness to choose smart senior care were collected. The Chi-square test was used for single factor analysis of each variable. The statistically significant variables were included in the logistics regression model to analyze factors influencing older adults’ willingness to choose smart senior care. The chi-square goodness of fit test was used to analyze the preferred content and access models of smart senior care; the Bonferroni method was used to correct the results.

Results

The finding indicated that participants’ age, number of children, frequency of children visiting parents, adequate senior care, self-reported health, chronic diseases, smartphone use, and attitude toward smart senior care were significantly associated with their willingness to choose the smart senior care (p < 0.05). For smart senior care access models, participants preferred the remote monitoring model, telephone call model, and the community site model over the health smart home model and the smart application platform model. There was no statistical difference among these three preferred access models (p’ > 0.005). Regarding service content, participants desired medical care service the most (p’ < 0.005).

Conclusions

Chinese older adults’ willingness to choose smart senior care is affected by personal, family, health, and other factors. To develop China’s senior care, we should consider their demand and preference for smart senior care. It is important to enrich the content of smart senior care, especially on medical care services, and maintain the dynamic balance between supply and demand using a diverse supply approach.
Appendix
Available only for authorised users
Literature
1.
go back to reference Yu J, de Antonio A, Villalba-Mora E. Older adult segmentation according to residentially-based lifestyles and analysis of their needs for smart home functions. Int J Environ Res Public Health. 2020;17(22):8492. Yu J, de Antonio A, Villalba-Mora E. Older adult segmentation according to residentially-based lifestyles and analysis of their needs for smart home functions. Int J Environ Res Public Health. 2020;17(22):8492.
2.
go back to reference Hu Y, Wang J, Nicholas S, et al. The sharing economy in China's aging industry: applications, challenges, and recommendations. J Med Internet Res. 2021;23(7):e27758.CrossRef Hu Y, Wang J, Nicholas S, et al. The sharing economy in China's aging industry: applications, challenges, and recommendations. J Med Internet Res. 2021;23(7):e27758.CrossRef
4.
go back to reference World Health Organization. World report on ageing and health. Geneva: WHO Press; 2015. World Health Organization. World report on ageing and health. Geneva: WHO Press; 2015.
5.
go back to reference Zhang X, Dupre ME, Qiu L, et al. Urban-rural differences in the association between access to healthcare and health outcomes among older adults in China. BMC Geriatr. 2017;17(1):151.CrossRef Zhang X, Dupre ME, Qiu L, et al. Urban-rural differences in the association between access to healthcare and health outcomes among older adults in China. BMC Geriatr. 2017;17(1):151.CrossRef
7.
go back to reference Wang B, Xu L. Construction of the "internet plus" community smart elderly care service platform. J Healthc Eng. 2021;2021:4310648.CrossRef Wang B, Xu L. Construction of the "internet plus" community smart elderly care service platform. J Healthc Eng. 2021;2021:4310648.CrossRef
8.
go back to reference Meng Q, Hong Z, Li Z, et al. Opportunities and challenges for Chinese elderly care industry in smart environment based on Occupants' needs and preferences. Front Psychol. 2020;11:1029.CrossRef Meng Q, Hong Z, Li Z, et al. Opportunities and challenges for Chinese elderly care industry in smart environment based on Occupants' needs and preferences. Front Psychol. 2020;11:1029.CrossRef
9.
go back to reference Kang HJ, Han J, Kwon GH. Determining the intellectual structure and academic trends of smart home health care research: Coword and topic analyses. J Med Internet Res. 2021;23(1):e19625.CrossRef Kang HJ, Han J, Kwon GH. Determining the intellectual structure and academic trends of smart home health care research: Coword and topic analyses. J Med Internet Res. 2021;23(1):e19625.CrossRef
10.
go back to reference Sánchez VG, Taylor I, Bing-Jonsson PC. Ethics of SMART house welfare technology for older adults: a systematic literature review. Int J Technol Assess Health Care. 2017;33(6):691–9.CrossRef Sánchez VG, Taylor I, Bing-Jonsson PC. Ethics of SMART house welfare technology for older adults: a systematic literature review. Int J Technol Assess Health Care. 2017;33(6):691–9.CrossRef
11.
go back to reference Reeder B, Chung J, Lyden K, et al. Older women's perceptions of wearable and smart home activity sensors. Inform Health Soc Care. 2020;45(1):96–109.CrossRef Reeder B, Chung J, Lyden K, et al. Older women's perceptions of wearable and smart home activity sensors. Inform Health Soc Care. 2020;45(1):96–109.CrossRef
12.
go back to reference Kawamura K, Kamiya M, Suzumura S, et al. Impact of the coronavirus disease 2019 outbreak on activity and exercise levels among older patients. J Nutr Health Aging. 2021;25(7):921–5.CrossRef Kawamura K, Kamiya M, Suzumura S, et al. Impact of the coronavirus disease 2019 outbreak on activity and exercise levels among older patients. J Nutr Health Aging. 2021;25(7):921–5.CrossRef
13.
go back to reference Shen J, Naeim A. Telehealth in older adults with cancer in the United States:the emerging use of wearable sensors. J Geriatr Oncol. 2017;8(6):437–42.CrossRef Shen J, Naeim A. Telehealth in older adults with cancer in the United States:the emerging use of wearable sensors. J Geriatr Oncol. 2017;8(6):437–42.CrossRef
14.
go back to reference Costa A, Rincon JA, Carrascosa C, et al. Activities suggestion based on emotions in AAL environments. Artif Intell Med. 2018;86:9–19.CrossRef Costa A, Rincon JA, Carrascosa C, et al. Activities suggestion based on emotions in AAL environments. Artif Intell Med. 2018;86:9–19.CrossRef
15.
go back to reference Lee LN, Kim MJ. A critical review of smart residential environments for older adults with a focus on pleasurable experience. Front Psychol. 2019;10:3080.CrossRef Lee LN, Kim MJ. A critical review of smart residential environments for older adults with a focus on pleasurable experience. Front Psychol. 2019;10:3080.CrossRef
16.
go back to reference Banbury A, Nancarrow S, Dart J, et al. Adding value to remote monitoring: co-design of a health literacy intervention for older people with chronic disease delivered by telehealth - the telehealth literacy project. Patient Educ Couns. 2020;103(3):597–606.CrossRef Banbury A, Nancarrow S, Dart J, et al. Adding value to remote monitoring: co-design of a health literacy intervention for older people with chronic disease delivered by telehealth - the telehealth literacy project. Patient Educ Couns. 2020;103(3):597–606.CrossRef
17.
go back to reference Evans J, Papadopoulos A, Silvers CT, et al. Remote health monitoring for older adults and those with heart failure: adherence and system usability. Telemed J E Health. 2016;22(6):480–8.CrossRef Evans J, Papadopoulos A, Silvers CT, et al. Remote health monitoring for older adults and those with heart failure: adherence and system usability. Telemed J E Health. 2016;22(6):480–8.CrossRef
18.
go back to reference Nagapuri S, Maeder AJ, Williams PAH. Health smart homes: user perspectives. Stud Health Technol Inform. 2019;266:127–35. Nagapuri S, Maeder AJ, Williams PAH. Health smart homes: user perspectives. Stud Health Technol Inform. 2019;266:127–35.
19.
go back to reference Maeder AJ, Williams PAH. Health smart homes: new challenges. Stud Health Technol Inform. 2017;245:166–9. Maeder AJ, Williams PAH. Health smart homes: new challenges. Stud Health Technol Inform. 2017;245:166–9.
20.
go back to reference Liu N, Yin J, Tan SS, et al. Mobile health applications for older adults: a systematic review of interface and persuasive feature design. J Am Med Inform Assoc. 2021;28(11):2483–501.CrossRef Liu N, Yin J, Tan SS, et al. Mobile health applications for older adults: a systematic review of interface and persuasive feature design. J Am Med Inform Assoc. 2021;28(11):2483–501.CrossRef
21.
go back to reference Paiva JOV, Andrade RMC, de Oliveira PAM, et al. Mobile applications for elderly healthcare: a systematic mapping. PLoS One. 2020;15(7):e0236091.CrossRef Paiva JOV, Andrade RMC, de Oliveira PAM, et al. Mobile applications for elderly healthcare: a systematic mapping. PLoS One. 2020;15(7):e0236091.CrossRef
22.
go back to reference Gaines JM, Poey JL, Marx KA, et al. Health and medical services use: a matched case comparison between CCRC residents and national health and retirement study samples. J Gerontol Soc Work. 2011;54(8):788–802.CrossRef Gaines JM, Poey JL, Marx KA, et al. Health and medical services use: a matched case comparison between CCRC residents and national health and retirement study samples. J Gerontol Soc Work. 2011;54(8):788–802.CrossRef
23.
go back to reference Klamroth-Marganska V. Stroke rehabilitation: therapy robots and assistive devices. Adv Exp Med Biol. 2018;1065:579–87.CrossRef Klamroth-Marganska V. Stroke rehabilitation: therapy robots and assistive devices. Adv Exp Med Biol. 2018;1065:579–87.CrossRef
24.
go back to reference Koutentakis D, Pilozzi A, Huang X. Designing socially assistive robots for Alzheimer's disease and related dementia patients and their caregivers: where we are and where we are headed. Healthcare (Basel). 2020;8(2):E73.CrossRef Koutentakis D, Pilozzi A, Huang X. Designing socially assistive robots for Alzheimer's disease and related dementia patients and their caregivers: where we are and where we are headed. Healthcare (Basel). 2020;8(2):E73.CrossRef
25.
go back to reference Zhang Q, Li M, Wu Y. Smart home for elderly care: development and challenges in China. BMC Geriatr. 2020;20(1):318.CrossRef Zhang Q, Li M, Wu Y. Smart home for elderly care: development and challenges in China. BMC Geriatr. 2020;20(1):318.CrossRef
26.
go back to reference Report of the World Health Organization. Active ageing: a policy framework. Aging Male. 2002;5(1):1–37. Report of the World Health Organization. Active ageing: a policy framework. Aging Male. 2002;5(1):1–37.
27.
go back to reference Gordana D, Roschelle F, Courtney G, et al. Factors influencing community dwelling older adults' readiness to adopt smart home technology: a qualitative exploratory study. J Adv Nurs. 2021;77(12):4847–61.CrossRef Gordana D, Roschelle F, Courtney G, et al. Factors influencing community dwelling older adults' readiness to adopt smart home technology: a qualitative exploratory study. J Adv Nurs. 2021;77(12):4847–61.CrossRef
28.
go back to reference Yuanyuan C, Mojisola E, Caroline R, et al. Decision-making factors toward the adoption of smart home sensors by older adults in Singapore: mixed methods study. JMIR Aging. 2022;5(2):e34239.CrossRef Yuanyuan C, Mojisola E, Caroline R, et al. Decision-making factors toward the adoption of smart home sensors by older adults in Singapore: mixed methods study. JMIR Aging. 2022;5(2):e34239.CrossRef
29.
go back to reference Sumit M, Emad A, Moein N, et al. Smart homes for elderly healthcare-recent advances and research challenges. Sensors (Basel, Switzerland). 2017;17(11):2496. Sumit M, Emad A, Moein N, et al. Smart homes for elderly healthcare-recent advances and research challenges. Sensors (Basel, Switzerland). 2017;17(11):2496.
30.
go back to reference Nthubu B. An overview of sensors, design and healthcare challenges in smart homes: future design questions. Healthcare (Basel, Switzerland). 2021;9(10):1329. Nthubu B. An overview of sensors, design and healthcare challenges in smart homes: future design questions. Healthcare (Basel, Switzerland). 2021;9(10):1329.
31.
go back to reference Jung LS, Joo CM, Hye YS, et al. Development and evaluation of smartphone usage management system for preventing problematic smartphone use. Digital health. 2022;8:20552076221089095. Jung LS, Joo CM, Hye YS, et al. Development and evaluation of smartphone usage management system for preventing problematic smartphone use. Digital health. 2022;8:20552076221089095.
32.
go back to reference Nattino G, Pennell ML, Lemeshow S. Assessing the goodness of fit of logistic regression models in large samples: a modification of the Hosmer-Lemeshow test. Biometrics. 2020;76(2):549–60.CrossRef Nattino G, Pennell ML, Lemeshow S. Assessing the goodness of fit of logistic regression models in large samples: a modification of the Hosmer-Lemeshow test. Biometrics. 2020;76(2):549–60.CrossRef
33.
go back to reference Ranstam J. Multiple P-values and Bonferroni correction. Osteoarthritis Cartilage. 2016;24(5):763–4. Ranstam J. Multiple P-values and Bonferroni correction. Osteoarthritis Cartilage. 2016;24(5):763–4.
34.
go back to reference Armstrong RA. When to use the Bonferroni correction. Ophthalmic Physiol Opt. 2014;34(5):502–8.CrossRef Armstrong RA. When to use the Bonferroni correction. Ophthalmic Physiol Opt. 2014;34(5):502–8.CrossRef
35.
go back to reference Kramer AA, Zimmerman JE. Assessing the calibration of mortality benchmarks in critical care: the Hosmer-Lemeshow test revisited. Crit Care Med. 2007;35(9):2052–6.CrossRef Kramer AA, Zimmerman JE. Assessing the calibration of mortality benchmarks in critical care: the Hosmer-Lemeshow test revisited. Crit Care Med. 2007;35(9):2052–6.CrossRef
37.
go back to reference Xu H, Dupre ME, Danan G, et al. The impact of residential status on cognitive decline among older adults in China: results from a longitudinal study. BMC Geriatr. 2017;17(1):107.CrossRef Xu H, Dupre ME, Danan G, et al. The impact of residential status on cognitive decline among older adults in China: results from a longitudinal study. BMC Geriatr. 2017;17(1):107.CrossRef
40.
go back to reference Han WJ, Whetung T, Mao X, Roof O. Three generations: grandparental co-residence and child outcomes in China. Fam Process. 2020;59(3):1144–60.CrossRef Han WJ, Whetung T, Mao X, Roof O. Three generations: grandparental co-residence and child outcomes in China. Fam Process. 2020;59(3):1144–60.CrossRef
41.
go back to reference Song Y. Losing an only child: the one-child policy and elderly care in China. Reprod Health Matters. 2014;22(43):113–24.CrossRef Song Y. Losing an only child: the one-child policy and elderly care in China. Reprod Health Matters. 2014;22(43):113–24.CrossRef
Metadata
Title
The willingness and influencing factors to choose smart senior care among old adults in China
Authors
Qiyuan Huang
Ying Li
Xiang Wu
Song Ge
Zhe Qu
Aming Wang
Xianping Tang
Publication date
01-12-2022
Publisher
BioMed Central
Keyword
Care
Published in
BMC Geriatrics / Issue 1/2022
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/s12877-022-03691-3

Other articles of this Issue 1/2022

BMC Geriatrics 1/2022 Go to the issue
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine