Racial/ethnic disparities in therapist effectiveness: a conceptualization and initial study of cultural competence.

As a result of mental health disparities between White and racial/ethnic minority clients, researchers have argued that some therapists may be generally competent to provide effective services but lack cultural competence. This distinction assumes that client racial/ethnic background is a source of variability in therapist effectiveness. However, there have been no direct tests of the therapist as a source of health disparities. We provided an initial test of the distinction between general and cultural competence by examining client racial/ethnic background as a source of variability in therapist effectiveness. We analyzed cannabis use outcomes from a psychotherapy trial (N = 582) for adolescent cannabis abuse and dependence using Bayesian multilevel models for count outcomes. We first tested whether therapists differed in their effectiveness and then tested whether disparities in treatment outcomes varied across therapist caseloads. Results suggested that therapists differed in their effectiveness in general and that effectiveness varied according to client racial/ethnic background. Therapist effectiveness may depend partially on client racial/ethnic minority background, providing evidence that it is valid to distinguish between general and cultural competence.

Benchmarking the effectiveness of psychotherapy treatment for adult depression in a managed care environment: a preliminary study.

This preliminary study evaluated the effectiveness of psychotherapy treatment for adult clinical depression provided in a natural setting by benchmarking the clinical outcomes in a managed care environment against effect size estimates observed in published clinical trials. Overall results suggest that effect size estimates of effectiveness in a managed care context were comparable to effect size estimates of efficacy observed in clinical trials. Relative to the 1-tailed 95th-percentile critical effect size estimates, effectiveness of treatment provided in this setting was observed to be between 80% (patients with comorbidity and without antidepressants) and 112% (patients without comorbidity concurrently on antidepressants) as compared to the benchmarks. Because the nature of the treatments delivered in the managed care environment were unknown, it was not possible to make conclusions about treatments. However, while replications are warranted, concerns that psychotherapy delivered in a naturalistic setting is inferior to treatments delivered in clinical trials appear unjustified.

Estimating variability in outcomes attributable to therapists: a naturalistic study of outcomes in managed care.

To estimate the variability in outcomes attributable to therapists in clinical practice, the authors analyzed the outcomes of 6,146 patients seen by approximately 581 therapists in the context of managed care. For this analysis, the authors used multilevel statistical procedures, in which therapists were treated as a random factor. When the initial level of severity was taken into account, about 5% of the variation in outcomes was due to therapists. Patient age, gender, and diagnosis as well as therapist age, gender, experience, and professional degree accounted for little of the variability in outcomes among therapists. Whether or not patients were receiving psychotropic medication concurrently with psychotherapy did affect therapist variability. However, the patients of the more effective therapists received more benefit from medication than did the patients of less effective therapists.

Should providers of treatment be regarded as a random factor? If it ain't broke, don't "fix" it: a comment on Siemer and Joormann (2003).

In their criticism of B. E. Wampold and R. C. Serlin's analysis of treatment effects in nested designs, M. Siemer and J. Joormann argued that providers of services should be considered a fixed factor because typically providers are neither randomly selected from a population of providers nor randomly assigned to treatments, and statistical power to detect treatment effects is greater in the fixed than in the mixed model. The authors of the present article argue that if providers are considered fixed, conclusions about the treatment must be conditioned on the specific providers in the study, and they show that in this case generalizing beyond these providers incurs inflated Type I error rates.