Intervention research is often time- and resource-intensive, with numerous participants involved over extended periods of time. In order to maximize the value of intervention studies, multiple outcome measures are often included, either to ensure a diverse set of outcomes is being assessed or to refine assessments of specific outcomes. In the paper, we advocate for combining assessments, rather than relying on individual measures assessed separately, to better evaluate the effectiveness of interventions. Specifically, we argue that by pooling information from individual measures into a single outcome, composite scores can provide finer estimates of the underlying theoretical construct of interest, while retaining important properties more sophisticated methods often forego, such as transparency and interpretability.
Shiny app: https://kwiebels.shinyapps.io/Multiple_outcomes_in_interventions/
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