Evidence map›Paper›PMID 38939563›Full record

ArticleFrontiers in public health2024

Analysis of demand and influencing factors for smart senior care among older adults in underdeveloped regions of western China: a case study of Lanzhou.

Yunhua Wang, Hongyu Zeng, Fengli Lv, Jiancheng Wang

Abstract read
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Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

The trial behind it

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3 · Its place in the literature

Who cites it

7 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

4 authors.

Yunhua WangSchool of Management, Lanzhou University, Lanzhou, China.
Hongyu ZengSchool of Public Health, Lanzhou University, Lanzhou, China.
Fengli LvSchool of Public Health, Lanzhou University, Lanzhou, China.
Jiancheng WangGansu Health Vocational College, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: With the rapid development of artificial intelligence and Internet-of-Things technology, internal support systems among families are gradually weakening, which can no longer satisfy the current demands of older adults. In this context, smart senior care has become a new development direction. However, existing studies on the demand for smart senior care are primarily concentrated in economically developed provinces and mega-cities in eastern China; their research results or conclusions may not apply to underdeveloped areas in the Western region. Therefore, our study selects Lanzhou as a representative city in an underdeveloped western region to investigate the demand of older adults for smart senior care and analyze the influencing factors. Methods: This cross-sectional study included 4,815 older adults from Lanzhou, China. A structured questionnaire was designed to investigate the demands of the older adults for smart senior care and analyze thie influencing factors. The Chi-square test was used for single factor analysis of each variable. The logistic regression model included the statistically significant variables to analyze factors influencing older adults' demand for smart senior care. A significance level of Results: Among the surveyed older adults, 1,625 (33.75%) expressed a demand for smart senior care. The finding indicated that participants' age, level of education, marital status, monthly income, number of children, type of endowment insurance, and knowledge of smart senior care were significantly associated with their demands for smart senior care ( Conclusion: In Lanzhou, older adults show a low level of knowledge but a high demand for smart senior care. Their demand is influenced by personal, family, health conditions, senior care security, and other factors. To advance smart senior care, government departments should accelerate the improvement of the laws and regulations on smart senior care while vigorously enhancing the service's publicity to raise knowledge about it. Additionally, the service contents for smart senior care should be expanded to meet the diversified demands of older adults.

Indexed as

Health Services Needs and DemandAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHealth Services for the AgedHumansMaleMiddle AgedSurveys and Questionnairesdemandinfluencing factorsLanzhouolder adultssmart senior care

Identifiers

PMID38939563
PMCPMC11210194

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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.