AUTHOR=Pullmann Michael D. , Lucid Leah , Harrison Julie P. , Martin Prerna , Deblinger Esther , Benjamin Katherine S. , Dorsey Shannon TITLE=Implementation Climate and Time Predict Intensity of Supervision Content Related to Evidence Based Treatment JOURNAL=Frontiers in Public Health VOLUME=6 YEAR=2018 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2018.00280 DOI=10.3389/fpubh.2018.00280 ISSN=2296-2565 ABSTRACT=

Objective: Children infrequently receive evidence-based treatments (EBTs) for mental health problems due to a science-to-practice implementation gap. Workplace-based clinical supervision, in which supervisors provide oversight, feedback, and training on clinical practice, may be a method to support EBT implementation. Our prior research suggests that the intensity of supervisory focus on EBT (i.e., thoroughness of coverage) during workplace-based supervision varies. This study explores predictors of supervisory EBT intensity.

Methods: Participants were twenty-eight supervisors and 70 clinician supervisees. They completed a baseline survey, and audio recorded supervision sessions over 1 year. Four hundred and thirty eight recordings were coded for supervision content. We chose to explore predictors of two EBT content elements due to their strong evidence for effectiveness and sufficient variance to permit testing. These included a treatment technique (“exposure”) and a method to structure treatment (“assessment”). We also explored predictors of non-EBT content (“other topics”). Mixed-effects models explored predictors at organizational/supervisor, clinician, and session levels.

Results: Positive implementation climate predicted greater intensity of EBT content coverage for assessment (coefficient = 0.82, p = 0.004) and exposure (coefficient = 0.87, p = 0.001). Intensity of exposure coverage was also predicted by more time spent discussing each case (coefficient = 0.04, p < 0.001). Predictors of greater non-EBT content coverage included longer duration of supervision sessions (coefficient = 0.05, p < 0.001) and lower levels of supervisor EBT knowledge (coefficient = −0.17, p = 0.013). No other supervisor- or clinician-level variables were significant predictors in the mixed effects models.

Conclusion: This was the first study to explore multi-level predictors of objectively coded workplace-based supervision content. Results suggest that organizations that expect, support and reward EBT are more likely to have greater intensity of EBT supervision coverage, which in turn may positively impact clinician EBT fidelity and client outcomes. There was evidence that supervisor knowledge of the EBT contributes to greater coverage, although robust supervisor and clinician factors that drive supervision are yet to be identified. Findings highlight the potential effectiveness of implementation strategies that simultaneously address organizational implementation climate and supervisor practices. More research is needed to identify mechanisms that support integration of EBT into supervision.