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Article: Prevalence, risk, and protective factors of self-stigma for people living with depression: A systematic review and meta-analysis

TitlePrevalence, risk, and protective factors of self-stigma for people living with depression: A systematic review and meta-analysis
Authors
KeywordsDepression
meta-analysis
Prevalence
Protective factor
Risk factor
Self-stigma
Issue Date1-Jul-2023
PublisherElsevier
Citation
Journal of Affective Disorders, 2023, v. 332, p. 327-340 How to Cite?
Abstract

Background

People living with depression are subjected to widespread stigmatization worldwide. Self-stigma may negatively affect patients' treatment, recovery, and psychological well-being. This review aims to summarize and synthesize the evidence on the prevalence, risk, and protective factors of depression self-stigma.

Methods

Four online databases, PubMed, PsycINFO, Web of Science, and Embase, were searched to identify eligible studies. Fifty-six studies involving a total of 11,549 samples were included in the final analysis. Four reviewers independently screened the literature, extracted data, and assessed the risk of bias in eligible studies. Pearson's r was chosen as the effect size metric of risk and protective factors.

Results

The results showed that the global prevalence of depression self-stigma was 29 %. Levels of self-stigma varied across regions, but this difference was not significant. Two demographic factors were identified: ethnicity (r = 0.10, p < 0.05) and having a partner/married (r = −0.22, p < 0.001). Five risk factors were identified: depression severity (r = 0.33, p < 0.01), public stigma (r = 0.44, p < 0.001), treatment stigma (r = 0.46, p < 0.001), perceived stigma (r = 0.37, p < 0.001), and enacted stigma (r = 0.71, p < 0.001). Five protective factors were identified: quality of life (r = −0.38, p < 0.001), social relationship (r = −0.26, p < 0.05), self-esteem (r = −0.46, p < 0.001), extroversion (r = −0.32, p < 0.001), and social functioning (r = −0.49, p < 0.001).

Limitations

Heterogeneity was observed in some of the results. Causality cannot be inferred due to the predominance of cross-sectional designs among the included literature.

Conclusions

Risk and protective factors of depression self-stigma exist across many dimensions. Future research should examine the inner mechanisms and effectiveness of interventions to reduce stigma.


Persistent Identifierhttp://hdl.handle.net/10722/337605
ISSN
2023 Impact Factor: 4.9
2023 SCImago Journal Rankings: 2.082
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDu, N-
dc.contributor.authorChong, E-
dc.contributor.authorWei, D-
dc.contributor.authorLiu, Z-
dc.contributor.authorMu, Z-
dc.contributor.authorDeng, S-
dc.contributor.authorHuang, Y-
dc.date.accessioned2024-03-11T10:22:28Z-
dc.date.available2024-03-11T10:22:28Z-
dc.date.issued2023-07-01-
dc.identifier.citationJournal of Affective Disorders, 2023, v. 332, p. 327-340-
dc.identifier.issn0165-0327-
dc.identifier.urihttp://hdl.handle.net/10722/337605-
dc.description.abstract<h3>Background</h3><p>People living with depression are subjected to widespread stigmatization worldwide. Self-stigma may negatively affect patients' <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/therapeutic-procedure" title="Learn more about treatment from ScienceDirect's AI-generated Topic Pages">treatment</a>, recovery, and psychological well-being. This review aims to summarize and synthesize the evidence on the prevalence, risk, and protective factors of depression self-stigma.</p><h3>Methods</h3><p>Four online databases, PubMed, PsycINFO, Web of Science, and Embase, were searched to identify eligible studies. Fifty-six studies involving a total of 11,549 samples were included in the final analysis. Four reviewers independently screened the literature, extracted data, and assessed the risk of bias in eligible studies. Pearson's <em>r</em> was chosen as the effect size metric of risk and protective factors.</p><h3>Results</h3><p>The results showed that the global prevalence of depression self-stigma was 29 %. Levels of self-stigma varied across regions, but this difference was not significant. Two demographic factors were identified: ethnicity (<em>r</em> = 0.10, p < 0.05) and having a partner/married (<em>r</em> = −0.22, p < 0.001). Five risk factors were identified: depression severity (<em>r</em> = 0.33, p < 0.01), public stigma (<em>r</em> = 0.44, p < 0.001), <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/therapeutic-procedure" title="Learn more about treatment from ScienceDirect's AI-generated Topic Pages">treatment</a> stigma (<em>r</em> = 0.46, p < 0.001), perceived stigma (<em>r</em> = 0.37, p < 0.001), and enacted stigma (<em>r</em> = 0.71, p < 0.001). Five protective factors were identified: <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/quality-of-life" title="Learn more about quality of life from ScienceDirect's AI-generated Topic Pages">quality of life</a> (<em>r</em> = −0.38, p < 0.001), social relationship (<em>r</em> = −0.26, p < 0.05), self-esteem (<em>r</em> = −0.46, p < 0.001), extroversion (<em>r</em> = −0.32, p < 0.001), and social functioning (<em>r</em> = −0.49, p < 0.001).</p><h3>Limitations</h3><p>Heterogeneity was observed in some of the results. Causality cannot be inferred due to the predominance of cross-sectional designs among the included literature.</p><h3>Conclusions</h3><p>Risk and protective factors of depression self-stigma exist across many dimensions. Future research should examine the inner mechanisms and effectiveness of interventions to reduce stigma.</p>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofJournal of Affective Disorders-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectDepression-
dc.subjectmeta-analysis-
dc.subjectPrevalence-
dc.subjectProtective factor-
dc.subjectRisk factor-
dc.subjectSelf-stigma-
dc.titlePrevalence, risk, and protective factors of self-stigma for people living with depression: A systematic review and meta-analysis-
dc.typeArticle-
dc.identifier.doi10.1016/j.jad.2023.04.013-
dc.identifier.scopuseid_2-s2.0-85152705414-
dc.identifier.volume332-
dc.identifier.spage327-
dc.identifier.epage340-
dc.identifier.eissn1573-2517-
dc.identifier.isiWOS:001054938400001-
dc.identifier.issnl0165-0327-

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