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Published on: February 19, 2021
The association between self-concept, self-concept clarity, and self-injurious thoughts and behaviors (SI, SA, and
CongYuan Liao1, Yi Hou1, DongKui Li1
1Faculty of Psychology, Southwest University, Chongqing, 400715, China.
Background:
Self-injurious thoughts and behaviors (SITBs), including suicidal ideation (SI), suicide attempts (SA), and non-suicidal self-injury (NSSI), pose a significant global public health challenge. This meta-analysis examines the relationship between self-concept, self-concept clarity, and SITBs. Although prior research suggests associations between self-concept, self-concept clarity, and SITBs, the strength and direction of these relationships remain inconsistent.
Methods:
This meta-analysis synthesized effect sizes from studies in PubMed, PsycInfo, and Web of Science, using a three-level meta-analytic model to examine associations between self-concept, self-concept clarity, and SITBs.
Results:
A total of 33 studies with 113 effect sizes (N = 23,772) were analyzed. Significant negative correlations were found between self-concept and suicidal ideation (r = -0.234), and suicide attempts (r = -0.194). The correlation with NSSI (r = -0.258) was not stable. Significant heterogeneity was present, but no significant moderators were found. No publication bias was identified. Self-concept clarity was negatively associated with suicidal ideation (r = -0.295) and NSSI (r = -0.257). The association with suicide attempts (r = -0.244) was inconclusive. The results for self-concept clarity should be considered exploratory, and no publication bias, sensitivity, or moderator tests were conducted due to the limited number of effect sizes.
Conclusion:
This meta-analysis highlights some significant, albeit small, negative associations between self-concept, self-concept clarity, and SITBs. However, due to the limited number of studies and effect sizes, some results should be considered exploratory. Future research should explore potential mediating and moderating factors and examine longitudinal relationships to better understand the causal pathways.
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