Predicting therapist effectiveness from their own practice-based evidence

Differences between therapists (therapist effect) are often larger than differences between treatments (treatment effect) in explaining client outcomes, and thus should be considered relevant to providing optimal treatment to clients. However, research on therapist effectiveness has focused largely on global measures of distress as opposed to a multidimensional assessment, and has failed to risk-adjust for client characteristics. The purpose of this study was to examine the stability and predictive validity of therapist effectiveness across multiple outcome domains using risk-adjusted outcomes.

Initial and follow-up outcome data on the Treatment Outcome Package (Kraus, Seligman, & Jordan, 2005) were collected on 3,540 clients who were treated in naturalistic settings by a sample of 59 therapists. After risk-adjusting outcomes based on case-mix variables using random forest models, outcome data from the first 30 clients of each therapist were used to classify each therapist's effectiveness on 12 outcome domains. These results were then compared with outcome data from the therapist's next 30 clients.

Results demonstrated that therapist effectiveness was relatively stable, although somewhat domain specific. Therapists classified as "exceptional" were significantly more likely to remain above average with future cases, suggesting that a therapist's past performance is an important predictor of their future performance.

Clients are likely to experience differential benefit depending on the particular therapist and his or her strengths. Clinical outcomes may be improved by developing the best possible prediction model for each new client and then providing that client with referrals to therapists with well-matched strengths. (PsycINFO Database Record