A Primer on Meta-Analytic Structural Equation Modeling: the Case of Depression

被引:10
作者
Valentine, Jeffrey C. [1 ]
Cheung, Mike W-L [2 ]
Smith, Eric J. [1 ]
Alexander, Olivia [1 ]
Hatton, Jessica M. [1 ]
Hong, Ryan Y. [2 ]
Huckaby, Lucas T. [1 ]
Patton, Samantha C. [3 ]
Possel, Patrick [1 ]
Seely, Hayley D. [1 ]
机构
[1] Univ Louisville, Coll Educ & Human Dev, Louisville, KY 40292 USA
[2] Natl Univ Singapore, Dept Psychol, Singapore, Singapore
[3] Emory Univ, Sch Med, Atlanta, GA USA
关键词
Systematic review; Meta-analysis; Meta-analytic structural equation modeling; MASEM;
D O I
10.1007/s11121-021-01298-5
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
In this paper, we show how the methods of systematic reviewing and meta-analysis can be used in conjunction with structural equation modeling to summarize the results of studies in a way that will facilitate the theory development and testing needed to advance prevention science. We begin with a high-level overview of the considerations that researchers need to address when using meta-analytic structural equation modeling (MASEM) and then discuss a research project that brings together theoretically important cognitive constructs related to depression to (a) show how these constructs are related, (b) test the direct and indirect effects of dysfunctional attitudes on depression, and (c) test the effects of study-level moderating variables. Our results suggest that the indirect effect of dysfunctional attitudes (via negative automatic thinking) on depression is two and a half times larger than the direct effect of dysfunctional attitudes on depression. Of the three study-level moderators tested, only sample recruitment method (clinical vs general vs mixed) yielded different patterns of results. The primary difference observed was that the dysfunctional attitudes -> automatic thoughts path was less strong for clinical samples than it was for general and mixed samples. These results illustrate how MASEM can be used to compare theoretically derived models and predictions resulting in a richer understanding of both the empirical results and the theories underlying them.
引用
收藏
页码:346 / 365
页数:20
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