The benefit of measuring both wellbeing pathways and outcomes is that university programming staff will have more information with which to create targeted, evidence-based interventions to support wellbeing. To quantitatively evaluate the performance of the outcome items, we used confirmatory latent factor models. To quantitatively evaluate the performance of the pathway items, we used MIMIC models.
Through the spring 2019 administration, we administered the Assessment using a planned missing data design to reduce participant burden.
In dimensions with outcome items, the three or four outcome items in that dimension are designed to measure a narrowly defined latent construct. The spring 2019 version of the Wellbeing Assessment represents the final set of outcome items: 18 dimensions and 57 items. Items were modeled with simple structure, and the 18 dimensions were allowed to correlate.
Complete details of the spring 2019 psychometric analyses are available in our report on the spring 2019 methods and psychometrics. In addition to details about the items’ factor structure, the report includes analyses of reliability, measurement invariance, and convergent and discriminant validity.
In dimensions with pathway items, we quantitatively evaluated the effectiveness of the pathway items using structural equation and factor modeling using Mplus© software (2017). Details about our use of structural equation modeling as a method of establishing structural validity (using Messick, 1995) can be found in the attached paper, presented at the annual meeting of The National Council on Measurement in Education (NCME).
An example of our approach to these structural equation models is shown below in Figure 1. In that figure, the left-most blue box are pathway items; the central red box is outcome items. The right-most green box includes other important outcomes that are associated with wellbeing in the dimension. Examples include: overall life satisfaction, mood, academic engagement, and intent to transfer.