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Suicidal Ideation in South Korean: A Systematic Review

BACKGROUND: We systematically reviewed (evaluated methodological quality) meta-analysis studies on the suicidal ideation of South Koreans using a measurement tool to assess systematic reviews version 2 (AMSTAR-2) to present the ways for improving the quality of follow-up meta-analysis studies and su...

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Detalles Bibliográficos
Autores principales: Been, Seonjae, Byeon, Haewon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Tehran University of Medical Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362824/
https://www.ncbi.nlm.nih.gov/pubmed/37484152
http://dx.doi.org/10.18502/ijph.v52i6.12951
Descripción
Sumario:BACKGROUND: We systematically reviewed (evaluated methodological quality) meta-analysis studies on the suicidal ideation of South Koreans using a measurement tool to assess systematic reviews version 2 (AMSTAR-2) to present the ways for improving the quality of follow-up meta-analysis studies and suggest the direction of future studies. METHODS: We analyzed 11 meta-analysis studies based on AMSTAR-2 criteria by collecting documents related to suicidal thoughts using seven electronic databases (DBPia, Scholar, KISS, KCI, RISS, KoreaEmbase, and National Assembly Electronic Library) from Jan 1, 2000 to Dec 3, 2022. RESULTS: Among the 142 papers searched, we analyzed the final 11 selected studies. Not all analyzed meta-analysis studies conducted quality assessment and these studies omitted the list of excluded references and the adequacy of the literature search. Moreover, 54.5% of the analyzed studies (six out of eleven studies) did not present the effect of publication bias. Consequently, SOMETHING was critically low due to omissions in critical domains. CONCLUSION: In all 11 studies analyzed, 2 or more of 7 critical domains were omitted, and the quality level was confirmed to be critically low. Therefore, future meta-analysis studies on suicidal ideation will have to include quality assessment and improve the quality of meta-analysis, such as testing bias effects.