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对中国社会科学中采用元分析的系统评价的方法学质量和报告完整性的批判性评估:一项系统评价。

Critical appraisal of methodological quality and completeness of reporting in Chinese social science systematic reviews with meta-analysis: A systematic review.

作者信息

Guo Liping, Miller Sarah, Zhou Wenjie, Wei Zhipeng, Ren Junjie, Huang Xinyu, Xing Xin, White Howard, Yang Kehu

机构信息

School of Basic Medical Sciences, Evidence-Based Medicine Centre Lanzhou University Lanzhou China.

School of Public Health, Center for Evidence-Based Social Science Lanzhou University Lanzhou China.

出版信息

Campbell Syst Rev. 2025 Jan 19;21(1):e70014. doi: 10.1002/cl2.70014. eCollection 2025 Mar.

DOI:10.1002/cl2.70014
PMID:39834796
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11743190/
Abstract

BACKGROUND

A systematic review is a type of literature review that uses rigorous methods to synthesize evidence from multiple studies on a specific topic. It is widely used in academia, including medical and social science research. Social science is an academic discipline that focuses on human behaviour and society. However, consensus regarding the standards and criteria for conducting and reporting systematic reviews in social science is lacking. Previous studies have found that the quality of systematic reviews in social science varies depending on the topic, database, and country.

OBJECTIVES

This study evaluates the completeness of reporting and methodological quality of intervention and non-intervention systematic reviews in social science in China. Additionally, we explore factors that may influence quality.

SEARCH METHODS

We searched three major Chinese electronic databases-CNKI, VIP, and Wangfang-for intervention and non-intervention reviews in social science published in Chinese journals from 1 January 2009 to 2 December 2022.

SELECTION CRITERIA

We included intervention and non-intervention reviews; however, we excluded overviews, qualitative syntheses, integrative reviews, rapid reviews, and evidence syntheses/summaries. We also excluded meta-analyses that used advanced methods (e.g., cross-sectional, cumulative, Bayesian, structural equation, or network meta-analyses) or that focused on instrument validation.

DATA COLLECTION AND ANALYSIS

We extracted data using a coding form with publication information and study content characteristics. This study conducted pilot extraction and quality assessment with four authors and formal extraction and assessment with two groups of four authors each. PRISMA2020 and MOOSE were used to evaluate the reporting completeness of intervention and non-intervention reviews. AMSTAR-2 and DART tools were adopted to assess their methodological quality. We described the characteristics of the included reviews with frequencies and percentages. We used SPSS (version 26.0) to conduct a linear regression analysis and ANOVA to explore the factors that may influence both completeness of reporting and methodological quality.

MAIN RESULTS

We included 1176 systematic reviews with meta-analyses published in Chinese journals between 2009 and 2022. The top three fields of publication were psychology (417, 35.5%), education (388, 33.0%), and management science (264, 22.4%). Four hundred and thirty-two intervention reviews were included. The overall completeness of reporting in PRISMA and compliance rate of the methodological process in AMSTAT-2 were 49.9% and 45.5%, respectively. Intervention reviews published in Chinese Social Science Citation Index (CSSCI) journals had lower reporting completeness than those published in non-CSSCI journals (46.7% vs. 51.1%), similar to methodological quality (39.6% vs. 47.9%). A few reviews reported the details on registration (0.2%), rationality of study selection criteria (1.6%), sources of funding for primary studies (0.2%), reporting bias assessment (2.8%), certainty of evidence assessment (1.2%), and sensitivity analysis (107, 24.8%). Seven hundred and forty-four non-intervention reviews were included. The overall completeness of reporting in MOOSE and compliance rate of the methodological process in DART were 51.8% and 50.5%, respectively. Non-intervention reviews published in CSSCI journals had higher reporting completeness than those published in non-CSSCI journals (53.3% vs. 50.3%); however, there was no difference in methodological quality (51.0% vs. 50.0%). Most reviews did not report the process and results of selection (80.8%), and 58.9% of reviews did not describe the process of data extraction; only 9.5% assessed the quality of included studies; while none of the reviews examined bias by confounding, outcome reporting bias, and loss to follow-up. An improving trend over time was observed for both intervention and non-intervention reviews in completeness of reporting and methodological quality (PRISMA:  = 0.24,  < 0.01; AMSTAR-2:  = 0.17,  < 0.01; MOOSE:  = 0.34,  < 0.01; DART:  = 0.30,  < 0.01). The number of authors and financial support also have a positive effect on quality.

AUTHORS' CONCLUSIONS: Completeness of reporting and methodological quality were low in both intervention and non-intervention reviews in Chinese social sciences, especially regarding registration, protocol, risk of bias assessment, and data and code sharing. The sources of literature, number of authors, publication year, and funding source declarations were identified as factors that may influence the quality of reviews. More rigorous standards and guidelines for conducting and reporting reviews are required in social science research as well as more support and incentives for reviewers to adhere to them.

摘要

背景

系统评价是一种文献综述类型,它采用严格的方法来综合来自多项关于特定主题研究的证据。它在学术界被广泛使用,包括医学和社会科学研究。社会科学是一门专注于人类行为和社会的学科。然而,在社会科学领域,对于进行和报告系统评价的标准和准则缺乏共识。先前的研究发现,社会科学中系统评价的质量因主题、数据库和国家而异。

目的

本研究评估中国社会科学领域干预性和非干预性系统评价的报告完整性和方法学质量。此外,我们还探讨可能影响质量的因素。

检索方法

我们检索了三个主要的中文电子数据库——中国知网、维普和万方——以获取2009年1月1日至2022年12月2日发表在中国期刊上的社会科学干预性和非干预性综述。

纳入标准

我们纳入了干预性和非干预性综述;然而,我们排除了概述、定性综合、整合性综述、快速综述以及证据综合/总结。我们还排除了使用先进方法(如横断面、累积、贝叶斯、结构方程或网络荟萃分析)或专注于工具验证的荟萃分析。

数据收集与分析

我们使用包含出版信息和研究内容特征的编码表格提取数据。本研究由四位作者进行了预提取和质量评估,并由两组每组四位作者进行了正式提取和评估。采用PRISMA2020和MOOSE评估干预性和非干预性综述的报告完整性。采用AMSTAR - 2和DART工具评估其方法学质量。我们用频率和百分比描述了纳入综述的特征。我们使用SPSS(版本26.0)进行线性回归分析和方差分析,以探讨可能影响报告完整性和方法学质量的因素。

主要结果

我们纳入了20

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/20167a2ceb78/CL2-21-e70014-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/90001e9468fb/CL2-21-e70014-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/276325ddf142/CL2-21-e70014-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/bfe70fff59f2/CL2-21-e70014-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/a1d63ba987f2/CL2-21-e70014-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/7cb91030b432/CL2-21-e70014-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/fddd59921962/CL2-21-e70014-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/bb2b59528407/CL2-21-e70014-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/5e439dcea248/CL2-21-e70014-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/b892db540f5c/CL2-21-e70014-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/20167a2ceb78/CL2-21-e70014-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/90001e9468fb/CL2-21-e70014-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/276325ddf142/CL2-21-e70014-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/bfe70fff59f2/CL2-21-e70014-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/a1d63ba987f2/CL2-21-e70014-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/7cb91030b432/CL2-21-e70014-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/fddd59921962/CL2-21-e70014-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/bb2b59528407/CL2-21-e70014-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/5e439dcea248/CL2-21-e70014-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/b892db540f5c/CL2-21-e70014-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3331/11743190/20167a2ceb78/CL2-21-e70014-g010.jpg

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