This study assessed the effects of training on the performance of 65 therapists in delivering manualguided therapies to 202 cocaine-dependent patients. Changes in ratings of therapists' adherence and competence was assessed in 3 treatment modalities: supportive-expressive dynamic therapy (SB), cognitive therapy (CT), and individual drug counseling. Effects of manual-guided training on the therapeutic alliance were also assessed. Training effects were examined through a hierarchical linear modeling approach that examined changes both within cases and across training cases. A large effect across cases was detected for training in CT. Supportive-expressive therapists and individual drug counselors demonstrated statistically significant learning trends over sessions but not over training cases. Training in SE and CT did not have a negative impact on the therapeutic alliance, although alliance scores for trainees in drug counseling initially decreased but then rebounded to initial levels. The nature and success of training in psychotherapy is an issue that not only affects various training programs (e.g., clinical psychology, psychiatric residencies, and social work training)but also has implications for how best to disseminate new psychosocial treatments to existing practitioners. Stein and Lam-bert (1995) have reviewed the literature related to the impact of graduate training in psychotherapy on therapist behaviors and patient outcome. Research related to clinical supervision, a key element in any training program, has also been recently reviewed by Holloway and Neufeldt (1995).

Abstract-In this work we address the problem of static state estimation (SE) in distribution grids by leveraging historical meter data (pseudo-measurements) with real-time measurements from synchrophasors (PMU data). We present a Bayesian linear estimator based on a linear approximation of the power flow equations for distribution networks, which is computationally more efficient than standard nonlinear weighted least squares (WLS) estimators. We show via numerical simulations that the proposed strategy performs similarly to the standard WLS estimator on a small distribution network. A key advantage of the proposed approach is that it provides explicit off-line computation of the estimation error confidence intervals, which we use to explore the trade-offs between number of PMUs, PMU placement and measurement uncertainty. Since the estimation error in distribution systems tends to be dominated by uncertainty in loads and scarcity of instrumented nodes, the linearized method along with the use of high-precision PMUs may be a suitable way to facilitate on-line state estimation where it was previously impractical.

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