Evidence map›Paper›PMID 36159277›Full record

ArticleFrontiers in public health2022

Amelioration and deterioration: Social network typologies and mental health among female domestic workers in China.

Binbin Tang, Mahefuzha Mamubieke, Maitixirepu Jilili, Linping Liu, Bowen Yang

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 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

5 authors.

Binbin TangSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, China.
Mahefuzha MamubiekeSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, China.
Maitixirepu JililiSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, China.
Linping LiuSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, China.
Bowen YangSchool of Social and Behavioral Sciences, Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous quantitative studies on the effects of social network types on mental health have obtained inconsistent or conflicting results, due to problems such as sample selection bias or crude measurement of variables. In this study, we avoided these problems by using appropriate statistical methodology to examine the effect of various forms of social network on the mental health of a sample of 987 Chinese female domestic workers. Thus, we measured social network types in terms of both network attributes (friend networks and family networks) and interaction channels (face-to-face, telephone, and WeChat/QQ channels, where the latter are two popular online messaging platforms in China), and used the coarsened exact matching method to obtain a balanced sample. The results showed that social network typologies had positive and negative effects on the mental health of this sample of domestic workers, as evidenced by (1) In terms of network attributes, family networks were associated with improved mental health and friend networks were associated with worsened mental health; (2) In terms of interaction channels, the significant amelioration in mental health from family networks came from face-to-face interactions, the significant deterioration in mental health from friends networks came from telephone interactions, and in terms of other interaction channels, family networks and friends networks had no significant effect on mental health. Robustness tests indicated that these conclusions are reliable. We discuss the possible mechanisms of which different types of social networks influence mental health.

Indexed as

Mental HealthSocial SupportChinaFemaleFriendsHumansSocial Networkingcoarsened exact matchingdomestic workersface-to-facefamily networkfriend networkmental healthnetwork types

Identifiers

PMID36159277
PMCPMC9492937

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