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 andreviewers 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 mayalso be helpful in this regard.
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