Evidence map›Paper›PMID 36767131›Full record

ArticleInternational journal of environmental research and public health2023

Supervision Effects on Negative Affect and Psychological Distress: Evidence from Social Workers in China.

Bin Tu, Chienchung Huang, Sophie Sitar, Yulu Wang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Bin TuGuangdong Research Center for NPO, Guangdong University of Foreign Studies, Guangzhou 510420, China.
Chienchung HuangSchool of Social Work, Rutgers University, New Brunswick, NJ 08901, USA.ORCID 0000-0003-2297-1468
Sophie SitarLaw School, Rutgers University, Newark, NJ 07102, USA.
Yulu WangSchool of Public Administration, Guangdong University of Foreign Studies, Guangzhou 510420, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supervision is an imperative practice within the social work field. It provides social workers with support systems, ensures that social workers are adhering to professional standards, and protects clients. Research has also shown that quality supervision can improve social workers' professional capacity and reduce work stress. However, most of this research has been confined to social workers' experiences within Western countries and has been largely qualitative in nature. Thus, this study aims to examine the experience of 489 social workers based in Guangzhou, China to understand how supervision affects their negative affect and psychological distress. The findings indicate that supervision not only reduces negative affect and psychological distress amongst Chinese social workers, but also is especially effective for social workers with high job demands. When job demands are high, social workers who receive both individual and group supervision also appear to have lower negative affect and psychological distress as compared to social workers who only receive individual supervision. These findings emphasize the significance of supervision as a buffer factor to reduce negative affect and psychological distress amongst Chinese social workers who face high job demands.

Indexed as

Occupational StressPsychological DistressAffectHumansOccupationsSocial SupportSocial WorkersStress, PsychologicalSurveys and QuestionnairesChinajob demandsnegative affectpsychological distresssocial workerssupervision

Identifiers

PMID36767131
PMCPMC9913909

What OpenQuestion holds

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LicenceCC BY
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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.