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Although this paper originated as an effort of the Division 12 Task Force on Psychological Interventions, we are publishing it as individuals rather than representatives of the Division.

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Despite more than 50 years of research on client attrition from therapy, obstacles to the delivery and success of treatments remain poorly understood, and effective methods to engage and retain clients in therapy are lacking. This article offers a review of the literature on attrition, highlighting the methodological challenges in effectively addressing the complex nature of this problem. Current interventions for reducing attrition are reviewed, and recommendations for implementing these interventions into psychotherapy practice are discussed.

Compared with professional psychotherapy, a manual-guided combination of intensive individual drug counseling and GDC has promise for the treatment of cocaine dependence.

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.In most psychotherapy research studies, each participating psychotherapist sees more than one patient. Over 10 years ago, Martindale (1978) presented evidence that this apparently minor methodological detail was an important statistical consideration. On the basisof reanalysesofseveral examplesdrawn from the published literature, he concluded that the failure to include the therapist as a blocking or stratification factor in the statistical design could seriously distort testsof statistical significance.The implications of Martindale's paper were sobering. His methodological opinion was that, strictly speaking, almost all of the published findings in the psychotherapy research literature applied only to the specific samples of therapists used in each study. If researchers want to generalize their results to a larger population of therapists, he argued, then they must treat therapists as a random factor in the statistical analyses. His own review of the literature, however, indicated that this practice was very much the exception rather than the rule. Unhappily, adoption of his methodological counsel would result in serious reductions in statistical power in most studies. Furthermore, Martindale's statistical reanalyses suggested strongly Preparation of this article was supported in part by National Institute of Mental Health (NIMH) Grant MH-40472 and NIMH Career Development Award MH-00756 to Paul Crits-Christoph.We wish to acknowledge the generosity of the investigators who lent us their data, including Aaron T. Beck, Tom Borkovec, Robert DeRubeis, Dolores Gallagher, Steve Hollon, Stan Imber, Bernard Liberman, Lester Luborsky, Tom McLellan, Paul Pilkonis. William Piper, Larry Thompson, George Woody, and Charlotte Zitrin. We also thank David Kenny for his helpful suggestions and comments on a draft of this article.Correspondence concerning this article should be addressed to Paul Crits-Christoph, Hospital of the University of Pennsylvania, 308 Piersol Building. 3400 Spruce Street, Philadelphia, Pennsylvania 19104-4283 that the erroneous statistical desig...

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Objective To examine the dependability of alliance scores at the patient and therapist level, to evaluate the potential causal direction of session-to-session changes in alliance and depressive symptoms, and to investigate the impact of aggregating the alliance over progressively more sessions on the size of the alliance-outcome relationship. Method We used data from a study (N=45 patients; N=9 therapists) of psychotherapy for major depressive disorder in which the alliance was measured at every treatment session to calculate generalizability coefficients and to predict change in depressive symptoms from alliance scores. Two replication samples were also used. Results At the therapist level, a large number of patients (about 60) per therapist is needed to provide a dependable therapist-level alliance score. At the patient level, generalizability coefficients revealed that a single assessment of the alliance is only marginally acceptable. Very good (> .90) dependability at the patient level is only achieved through aggregating four or more assessments of the alliance. Session-to-session change in the alliance predicted subsequent session-to-session changes in symptoms. Evidence for reverse causation was found in later-in-treatment sessions, suggesting that only aggregates of early treatment alliance scores should be used to predict outcome. Session 3 alliance scores explained 4.7% of outcome variance but the average of sessions 3 to 9 explaining 14.7% of outcome variance. Conclusion Adequately assessing the alliance using multiple patients per therapist and at least 4 treatment sessions is crucial to fully understanding the size of the alliance-outcome relationship.