Evidence map›Paper›PMID 38632588›Full record

ArticleBMC public health2024

The impact of internet use on health among older adults in China: a nationally representative study.

Yanyan Zhou, Yang Bai, Jun Wang

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

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

36 citing papers in PubMed.

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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

3 authors.

Yanyan Zhou *School of Agricultural Economics and Rural Development, Renmin University of China, Beijing, 100872, China.
Yang Bai *School of Public Administration and Policy, Renmin University of China, Beijing, 100872, China.
Jun WangCenter for Health Policy Research and Evaluation, Renmin University of China, Beijing, 100872, China. hpreruc2022@126.com.

Funding

Joint Funds of the National Natural Science Foundation of China 72042002
6 · The paper itself

Abstract

BACKGROUND AND

objectivesAging poses a significant challenge worldwide, with China's aging status becoming particularly severe. What is the impact of Internet use on the health of the elderly? Existing studies have drawn conflicting conclusions that Internet use improves or harms health. The purpose of this study was to explore how Internet use affects the health of older adults, and the mechanisms and heterogeneity of these effects. RESEARCH DESIGN AND

methodsBased on Grossman's theory, this paper constructs a health production function model. Using the data of China Family Panel Studies (CFPS) from 2014 to 2020, we investigated the impact of Internet use on the health of older adults using fixed effect model and instrumental variable method. We also examined the mediating role of health information acquisition, lifestyle, and social interaction in these associations.

resultsInternet use is positively associated with self-rated health and negatively associated with psychological sub-health level. Internet use promotes the health of older adults by facilitating access to health information, healthy lifestyles, and enhancing social interaction. And the impacts are heterogeneous at the individual and regional levels. DISCUSSION AND IMPLICATIONS: We should progressively enhance the level of internet accessibility for older adults, while concurrently addressing and narrowing the 'digital divide'. By generating an abundance of superior health-related information, we can significantly improve health education tailored for the elderly. Additionally, it is crucial to offer extensive training opportunities designed to equip older adults with the necessary skills to proficiently navigate the internet.

Indexed as

AgingInternet UseAgedChinaHealthy LifestyleHumansInternetMental HealthHealth accessInternet useLifestyleOlder adultsSocial interaction

Identifiers

PMID38632588
PMCPMC11022463

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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.