Method: Researchers worked with ~35 steering committee members who represented birth parents and staff of child welfare and court/legal systems to review/identify items for measuring specific and behavioral agency practices and court/legal practices that were viewed as important to quality services. Collaborative measurement construction yielded two instruments – one instrument included 17-items that measured court/legal system practices and the second instrument included 27-items that measured child welfare casework/agency practice. Data were collected via survey that was administered by a birth parent organization, resulting in a statewide sample of 386 parents. Participants responded to each instrument using a Likert-type scale; higher scores indicated higher positive experiences with casework and court/legal systems. We conducted exploratory and confirmatory factor analyses (EFA and CFA) to establish internal consistency validity and construct validity of each newly developed measure.
Results: Results revealed preliminary evidence of reliability and construct validity for both measures assessing parent experiences of child welfare. These measures were developed without hypothesized a priori factors, thus, we conducted separate EFAs to establish if each measure was comprised of multiple factors. Results from the EFA established the number of factors for each measure and explained over 70% of the variance for each model. CFA was then conducted on each model which further showed that each measure demonstrated acceptable fit with statistically significant factor loadings for each item and sufficient reliability (CFI’s >.90, TLI’s >.89, RMSEAs = .100 - .110, Cronbach’s alpha’s > .95).
Conclusions: Collaboration with community partners to co-create measurement tools for program assessment was meaningful in two important ways. First, it helped to deemphasize researchers as the main holders of knowledge. Including the diverse voices and expertise of community partners is essential to ensuring that research incorporates measures the collective identifies as important to understanding participant experiences in child welfare. Second, researchers can apply advanced quantitative statistical methods to test whether these co-created tools capture what the team hopes to learn. Overall, this process provides balance to research by distributing knowledge of all those involved to construct impactful studies for understanding the experiences of those impacted by the child welfare system.