潜在增长模型
纵向研究
调解
心理学
结构方程建模
调解
临床心理学
干预(咨询)
发展心理学
计算机科学
社会心理学
统计
数学
机器学习
精神科
法学
政治学
作者
Shijun Zhu,Knar Sagherian,Yan Wang,Eun‐Shim Nahm,Erika Friedmann
出处
期刊:Nursing Research
[Lippincott Williams & Wilkins]
日期:2021-02-03
卷期号:70 (3): 184-192
被引量:10
标识
DOI:10.1097/nnr.0000000000000503
摘要
Background Intervention studies are used widely in nursing research to explore the efficacy of intervention programs for changing targeted health outcomes. However, the analyses of such studies have focused predominantly on their main intervention effects; most studies ignore the mechanisms underlying how the intervention programs work partly because of lack of application details of the longitudinal mediation analysis techniques. Objectives The aim of this study was to illustrate an application of parallel process latent growth curve modeling (PP-LGCM) to examine longitudinal moderated mediation effects. Methods Longitudinal data from an online bone health intervention study were used to demonstrate the step-by-step application of PP-LGCM with Mplus statistical software. Results With modification indices, we were able to achieve adequate model fit for PP-LGCM in our data. The mediation effects of self-efficacy on the intervention effects on exercise were nonsignificant for the entire sample. However, the conditional indirect effect showed the mediation effects were moderated by age group. Discussion PP-LGCM provides an efficient way to analyze and explain the underlying mechanisms for the intervention effects in a trial, especially when the intervention program is guided by a theory.
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