represented in the clinical trial). Conclusions: These findings provide support for the potential utility of CT competence ratings in applied settings.
Elkin, I., Falconnier, L., Martinovich, Z. & Mahoney, C. (2006). Psychotherapy Research, 16(2),144-160.
Recent psychotherapy research literature has stressed the importance of therapist effects (i.e., the impact of the individual therapist on treatment outcome). The authors report an analysis of therapist effects in the National Institute of Mental Health Treatment of Depression Collaborative Research Program using hierarchical linear modeling. In addition to studying overall therapist effects, they investigate the possible interaction of therapists with initial patient severity and difficulty levels. There were virtually no significant findings in regard to either overall effects of therapists or the interaction with patient severity and difficulty. There was some suggestion of outliers (i.e., therapists who had especially good [or poor] rates of patient retention and recovery). Recommendations are made regarding different methodological approaches for studying outcome differences due to therapists.
Crits-Christoph, P. & Mintz, J. (1991). Journal of Consulting and Clinical Psychology, 59(1). 20-26
Technical reasons are presented as to why therapist should be included as a random design factor in the nested analysis of (co)variance (AN[C]OVA) design commonly used in psychotherapy research. Incorrect specification of the ANOVA design can, under some circumstances, result in incorrect estimation of the error term, overly liberal F ratios, and an unacceptably high risk of Type I errors. Review of studies indicates that the great majority of investigators continue to ignore this issue. Computer simulation studies revealed that considerable bias can be introduced by not specifying therapist as a random term. Finally, a reanalysis is presented of data from 10 psychotherapy outcome studies that indicated that therapist effects vary considerably and at times can be large. More recent studies that implement better quality controls appear to demonstrate less variance due to therapist. The implications of these results for the design of future studies are discussed.
Beutler, L. E., Malik, M., Alimohamed, S., Harwood, T. M., Talebi, H., Noble, S. & Wong, E. (2004). In M. J. Lambert (Ed) Bergin and Garfield’s Handbook of Psychotherapy and Behavior Change, (5th Ed.) pp. 227-306. NY, NY: Wiley.
The authors conduct an extensive review of the literature on the importance of therapist variables on psychotherapy outcome. They conclude that therapist sex, age and race are poor predictors of outcome (r<.05). Therapist training, skill, experience and style are weak contributors to outcome, but estimates of effect size are highly variable, from (r.08 to .72). The results of their meta-analysis are consistent with the lower effect sizes (r =.07). However, the author’s argue that the variability of the effect sizes deserves attention. Research on inferred traits (personality, well-being, and personal values) is sparse, but revealed a strong effect size (r’s of .12 and .13). Their review of research on inferred states (models of treatment and therapist’s contribution to the therapeutic relationship and the effect of relationship on outcome) reported values that average in the mid-.30s for different models. The authors also discuss the recent lack of research on the