Koenig Harold G, Carey Lindsay B
Department of Psychiatry and Behavioral Sciences, and Department of Medicine, Box 3400 Duke University Medical Center, Durham, NC, 27710, USA.
Division of Psychiatry, Department of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
J Relig Health. 2025 Apr;64(2):1276-1286. doi: 10.1007/s10943-025-02249-y. Epub 2025 Jan 14.
There has been concern raised in religion/spirituality (R/S) research about the use of measures of spirituality that are contaminated by indicators of mental and/or social health. Many of these scales are used widely in published studies examining associations with health, and yet many researchers and reviewers are not aware of contamination issues. We have previously cautioned researchers to be careful in their choice of religious/spirituality (R/S) measures (Koenig and Carey in J Relig Health, 63(5):3729-3743. https://doi.org/10.1007/s10943-024-02112-6 , 2024), and to avoid using measures contaminated with the health outcome being assessed, which will result in tautological findings (particularly between spirituality and mental health). However, not all is lost. There are approaches for analyzing collected data using contaminated measures that can still result in meaningful and interpretable results, which may contribute to our knowledge of the impact of R/S on health. In this brief article, we describe several approaches for analyzing such data including deleting contaminated items from the scale, analyzing subscales separately, and modeling psychosocial scales, subscales, or collections of variables as mediators in the causal pathway that leads from R/S to health. The use of path analysis or structural equation modeling to identify direct effects and indirect effects through mediating constructs may also be helpful in this regard.
宗教/灵性(R/S)研究中,人们对使用受心理和/或社会健康指标污染的灵性测量方法表示担忧。许多此类量表在已发表的研究中被广泛用于检验与健康的关联,但许多研究人员和审稿人并未意识到污染问题。我们之前曾告诫研究人员在选择宗教/灵性(R/S)测量方法时要谨慎(Koenig和Carey,《宗教健康杂志》,63(5):3729 - 3743。https://doi.org/10.1007/s10943-024-02112-6,2024),并避免使用受所评估健康结果污染的测量方法,因为这会导致同义反复的结果(尤其是在灵性与心理健康之间)。然而,并非毫无办法。对于使用受污染测量方法收集的数据,仍有一些分析方法能够得出有意义且可解释的结果,这可能有助于我们了解R/S对健康的影响。在这篇简短的文章中,我们描述了几种分析此类数据的方法,包括从量表中删除受污染的项目、分别分析子量表,以及将心理社会量表、子量表或变量集合建模为从R/S到健康的因果路径中的中介变量。在这方面,使用路径分析或结构方程模型来识别通过中介结构的直接效应和间接效应可能也会有所帮助。