Evidence map›Paper›PMID 35764930›Full record

ArticleBMC geriatrics2022

Association between internet use and successful aging of older Chinese women: a cross-sectional study.

Yao Jiang, Fan Yang

Abstract read
In one paragraph

Article in BMC geriatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
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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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

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

2 authors.

Yao JiangZhou Enlai School of Government, Nankai University, Tianjin, 300350, China.
Fan YangDepartment of Labor and Social Security, School of Public Administration, Sichuan University, Chengdu, 610065, China. yangfan1987@scu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe internet has become ubiquitous in contemporary human life. However, little is known about the association between internet use and older people's aging process, especially that of older women.

methodsUsing the nationally representative dataset of the China Longitudinal Aging Social Survey 2016, we examined the relationship between internet usage and the successful aging of older Chinese women. The sample in this study consisted of 2713 respondents with an average age of 69.963 years. Successful aging was defined as no major diseases, no disability, high cognitive functioning, high physical functioning, and active engagement with life. Older women's internet use behavior was represented by internet use frequency. Probit and instrumental variable models were employed to test the association between internet use frequency and successful aging of older women. The Karlson/Holm/Breen (KHB) mediation analysis was used to estimate the mediating effect of social capital on the relationship between internet use frequency and older women's successful aging.

resultsUsing a probit model (coefficient = 0.030, p < 0.001) and an instrumental variable probit model (coefficient = 0.287, p < 0.001), it was found that a successful aging status was significantly correlated with an increase in internet use frequency. The functional mechanism analysis suggested that social capital partially mediated the overall association between internet use frequency and successful aging.

conclusionsThis study suggests that the more frequently older Chinese women use the internet, the greater the possibility of successful aging. Our findings provide new evidence from China about the determinants of older women's aging process and aid in formulating targeted aging policies for older women in developing countries and regions.

Indexed as

AgingInternet UseAgedAsian PeopleChinaCross-Sectional StudiesFemaleHumansGender roleInternet useOlder womenSocial exclusionSuccessful aging

Identifiers

PMID35764930
PMCPMC9241215

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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.