Symposia
Improved Use of Research Evidence
Meredith R. Boyd, M.A. (she/her/hers)
Graduate Student
University of California Los Angeles
Ann Arbor, Michigan
Kendra S. Knudsen, M.A.
Doctoral Student
UCLA
Los Angeles, California
Jon Ahuna, MA (he/him/his)
Graduate Student
University of South Carolina
Columbia, South Carolina
Given that much of the challenge of intervening on low treatment engagement is figuring out what practice to do for what problem, supervision has the potential to drive clinical practice, rather than simply debrief it.
To this end, study 1 examined which supervision activities increase the likelihood that a therapist will use a practice at the next treatment session. Across 192 supervision sessions, three behaviors were associated with increase follow through in treatment: (1) explicit selection of the therapeutic practice the therapist will use in their next treatment session, (2) preparation through activities such as reviewing manuals, role plays, and modeling, and (3) review of how use of the practice went in the past. Moreover, for each activity (select, prepare, review) done in supervision, the clinician was 3 times more likely to use the selected practice in treatment.
Acknowledging the varied functions of and limited time for supervision, study 2 examined supervision efficiency as rated by independent coders on a Likert-type scale (1=low to 5=high). We found that the amount of time spent in supervision was similar across conditions. Importantly, efficiency was significantly higher in the CKS condition (M = 3.94) than in the PG condition (M = 2.04). In addition, supervisors accounted for significantly greater variance (52%) in efficiency than did providers (4%), with the remaining variance (44%) unexplained. Thus, structured decision-making resources do not take more time and can result in higher efficiency in supervision.
In study 3, data from 95 therapists collected at the end of the study were examined in multilevel models to yield the relative variance explained by individual, organizational, and innovation characteristics on behavioral intentions to continue to their study-trained engagement resources. Individual and organizational characteristics were not significant predictors of intentions after controlling for innovation characteristics, which accounted for 75% of variability. Furthermore, mediational path analyses revealed a statistically significant indirect effect of study condition on intentions through perceptions of innovation characteristics (B = .410, 95% Bootstrapped CI = [.071, .780]). That innovation characteristics were related to therapist intentions might explain why some innovations are received more favorably than others.
Together, these studies suggest that clinical supervision might be an untapped, but important, driver of clinical practice.