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A meta-analysis of the relationship between anxiety and non-suicidal self-injury based on knowledge graphs
Jieyao Shi1, Pan Gao1, Bingqian Zhou2
1Suzhou Vocational University, Jiangsu, China.
Objective:
The existing research on the relationship between anxiety and non-suicidal self-injury (NSSI) is inconsistent, and there is no systematic review on this area. This study aims to explore the relationship between anxiety and NSSI, in order to provide evidence-based medicine evidence for the early identification of preventable occurrence factors of NSSI.
Methods:
The semantic query (i.e. SPARQL) method was used to retrieve the anxiety- related literature on the Knowledge graph of NSSI, which consist of the metadata and semantic annotation data of English literature related to non-suicidal self-injury in PubMed by June 2023. Two researchers strictly followed the inclusion and exclusion criteria for independent literature screening. After evaluating the quality of the included studies, the selected data was subjected to meta-analysis using RevMan5.3 software.
Results:
A total of 14 studies met the inclusion criteria of the meta-analysis, including 44064 subjects. The results showed that the proportion of anxiety in the NSSI group was significantly higher than that in the non-NSSI group, and the difference between the groups was statistically significant (OR=3.60, 95% Cl=2.08-6.22, p<0.01).
Conclusion:
There is a significant correlation between anxiety and NSSI, which is a possible risk factor for NSSI. However, due to limitations of the design type, quantity, and quality of the included study, further research is needed on the causal relationship between anxiety and NSSI. Furthermore, we show that using knowledge graphs is an effective approach to retrieve literature for meta-analysis.
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