Evidence map›Paper›PMID 40053781›Full record

ArticleJournal of medical Internet research2025

Analysis of Factors Influencing the Willingness of Chinese Older Adults to Use mHealth Devices: Nationwide Cross-Sectional Survey Study.

Mengyao Yan, Wendi Sun, Cheng Tan, Yibo Wu, Yuanli Liu

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mengyao Yan *Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0000-0002-6614-7959
Wendi Sun *School of Humanities and Management, Zhejiang Chinese Medical University, Zhejiang, China.ORCID 0009-0001-3269-9915
Cheng TanSchool of Government, Peking University, Beijing, China.ORCID 0009-0002-5385-9794
Yibo WuSchool of Public Health, Peking University, Beijing, China.ORCID 0000-0001-9607-313X
Yuanli LiuChinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.ORCID 0009-0004-8461-2668

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

objectiveThis 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.

methodsThe 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.

resultsIn 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.

conclusionsThis 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.

Indexed as

TelemedicineAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and Questionnaireshealth managementmedical servicesmobile health devicesmobile phoneolder adults

Identifiers

PMID40053781
PMCPMC11920664

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.