Evidence map›Paper›PMID 34950065›Full record

ArticleFrontiers in psychiatry2021

Internet Use and Depressive Symptoms Among Older Adults in China.

Hua-Lei Yang, Shuo Zhang, Si-Qing Zhang, Lin Xie, Yuan-Yang Wu, Yi-Dan Yao, Li-Li Tang, Zhi-Yun Li

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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

31 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

8 authors.

Hua-Lei YangSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan, China.
Shuo ZhangSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan, China.
Si-Qing ZhangSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan, China.
Lin XieDepartment of Population and Labor Economics, University of Chinese Academy of Social Science, Beijing, China.
Yuan-Yang WuSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan, China.
Yi-Dan YaoSchool of Public Administration, Zhongnan University of Economics and Law, Wuhan, China.
Li-Li TangCollege of Chemistry and Chemical Engineering, Yantai University, Yantai, China.
Zhi-Yun LiCollege of Politics and Public Administration, Qingdao University, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the effect of using the Internet on depression symptoms of older Chinese, based on 7,801 adults aged over 60 years from the 2018 China Family Panel Studies. Results showed that the elderly who used the Internet reported lower depression scores, and the more frequent they use Internet, the lower their depression scores. Moreover, using the Internet for social contact and entertainment decreased the depression scores of the older adults, but when using Internet for learn, work, and commercial activity, the relief of depressive symptoms disappeared. Therelief of depression symptoms through Internet use were heterogeneous among different groups: the elderly aged 60-70, women, rural residents, and those with lower education attainment. Moreover, Internet use decreased the depression scores by increasing the frequency of contact with their children and increasing the importance of their enjoyment of life. According to the relief of depression by using Internet reasonably, policies should be designed to ensure that all ages could have easy access to the Internet.

Indexed as

Chinadepressive symptomsdigital ageInternet useolder adults

Identifiers

PMID34950065
PMCPMC8688754

What OpenQuestion holds

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Registered trials

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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.