Analysis of Factors Influencing the Willingness of Chinese Older Adults to Use mHealth Devices: Nationwide Cross-Sectional Survey Study
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| Publicado en: | Journal of Medical Internet Research vol. 27 (2025), p. e66804 |
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| Autor principal: | |
| Otros Autores: | , , , |
| Publicado: |
Gunther Eysenbach MD MPH, Associate Professor
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 1438-8871 | ||
| 024 | 7 | |a 10.2196/66804 |2 doi | |
| 035 | |a 3222368489 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Yan, Mengyao | |
| 245 | 1 | |a Analysis of Factors Influencing the Willingness of Chinese Older Adults to Use mHealth Devices: Nationwide Cross-Sectional Survey Study | |
| 260 | |b Gunther Eysenbach MD MPH, Associate Professor |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Background:In addition to standard older adult care services, mobile medical devices have proved to be an effective tool for controlling the health of older adults. However, little is known about the variables driving the acceptance of these gadgets and the willingness of older adults in China to use them.Objective:This study aims to explore the factors that affect the use of mobile health (mHealth) devices by older adults in China, focusing on individual, social, and family influences.Methods:The Psychology and Behavior Investigation of Chinese Residents survey database provided the data for this study. The survey was conducted in 148 Chinese cities between June 20 and August 31, 2022. The parameters linked to older persons’ desire to use mobile medical devices were determined by this study using a combination model of multiple stepwise linear regression and a classification and regression tree decision tree.Results:In total, 4085 older adults took part in the poll. On a scale of 0 to 100, the average score for willingness to adopt mHealth devices was 63.70 (SD 25.11). The results of the multiple stepwise linear regression showed that having a postgraduate degree and higher (β=.040; P=.007), being unemployed (β=.037; P=.02), having a high social status (β=.085; P<.001), possessing high health literacy (β=.089; P<.001), demonstrating high self-efficacy (β=.043; P=.02), not living with children (β=.0340; P=.02), having a household per capita monthly income of >Y4000 (US $550) (β=.048; P=.002), experiencing high perceived social support (β=.096; P<.001), reporting a high quality of life (β=.149; P<.001), having higher levels of family communication (β=–.071; P<.001), having an identity bubble (β=.085; P<.001), not having chronic diseases (β=.049; P=.001), and experiencing mild depression (β=–.035; P=.02) were associated with older adults’ willingness to use mHealth devices. The classification and regression tree decision tree model’s findings demonstrated that the primary determinants of older adults’ desire to use mHealth devices are quality of life, identity bubble, social status, health literacy, family health, and perceived social support.Conclusions:This study uses the Andersen Healthcare Utilization Model to investigate the effects of demand variables, enabling resources, and predisposing traits on older persons’ propensity to use mHealth devices. These results offer reference data for the marketing and use of mHealth devices for older individuals in the future. The ultimate goal of this strategy is to create a balanced and harmonious integration of technology and humanistic care. | |
| 651 | 4 | |a China | |
| 653 | |a Behavior | ||
| 653 | |a Databases | ||
| 653 | |a Unemployed people | ||
| 653 | |a Social status | ||
| 653 | |a Telemedicine | ||
| 653 | |a Regression analysis | ||
| 653 | |a Questionnaires | ||
| 653 | |a Health status | ||
| 653 | |a Older people | ||
| 653 | |a Adult care services | ||
| 653 | |a Global health | ||
| 653 | |a Variables | ||
| 653 | |a Medical supplies | ||
| 653 | |a Classification | ||
| 653 | |a Hypotheses | ||
| 653 | |a Blood pressure | ||
| 653 | |a Aging | ||
| 653 | |a Public health | ||
| 653 | |a Marketing | ||
| 653 | |a Polls & surveys | ||
| 653 | |a Caregivers | ||
| 653 | |a Desire | ||
| 653 | |a Families & family life | ||
| 653 | |a Population | ||
| 653 | |a Health literacy | ||
| 653 | |a Health services | ||
| 653 | |a Chronic illnesses | ||
| 653 | |a Integrated care | ||
| 653 | |a Quality of life | ||
| 653 | |a Decision making | ||
| 653 | |a Identity | ||
| 653 | |a Social support | ||
| 653 | |a Hypertension | ||
| 653 | |a Wearable computers | ||
| 653 | |a Medical equipment | ||
| 653 | |a Willingness | ||
| 653 | |a Perceived social support | ||
| 653 | |a Family psychology | ||
| 653 | |a Physicians | ||
| 653 | |a Health services utilization | ||
| 653 | |a Adults | ||
| 653 | |a Self-efficacy | ||
| 653 | |a Psychology | ||
| 653 | |a Literacy | ||
| 653 | |a Mental health services | ||
| 653 | |a Social classes | ||
| 700 | 1 | |a Sun, Wendi | |
| 700 | 1 | |a Tan, Cheng | |
| 700 | 1 | |a Wu, Yibo | |
| 700 | 1 | |a Liu, Yuanli | |
| 773 | 0 | |t Journal of Medical Internet Research |g vol. 27 (2025), p. e66804 | |
| 786 | 0 | |d ProQuest |t Library Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3222368489/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3222368489/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3222368489/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |