The FACT-G meets or exceeds all requirements for use in oncology clinical trials, including ease of administration, brevity, reliability, validity, and responsiveness to clinical change. Selecting it for a clinical trial adds the capability to assess the relative weight of various aspects of QL from the patient's perspective.

Several systems have been developed to monitor and feedback information about a patient's responses to psychotherapy as a method of enhancing patient outcome. Feedback is generated from decision rules based on a patient's expected level of progress. Those patients who do not make expected levels of progress or whose progress in therapy is less than adequate are referred to as signal-alarm cases. Research has shown that feedback based on rationally-derived identification procedures increased the duration of treatment and improved outcomes for patients identified as potential treatment failures (signal-alarms). This paper compared two identification methods: a rationally-derived method based on clinical judgments about poor progress, and an empirical method based on statisticallyderived expected recovery curves. The concordance of these two methods was examined with regards to detecting signal-alarm cases. Results suggested that the empirically-derived method was more accurate in identifying patients who actually deteriorated. It was able to identify 100% of the cases that had deteriorated at termination, with 85% being identified by the time they had had three treatment sessions. However, the rationally-derived method was faster at identifying signal cases and more likely to identify the most seriously disturbed cases as potential treatment failures. Future directions for research in quality management were identified.

The financing, organization, and delivery of behavioral health care services has undergone dramatic change in the past 25 to 30 years. The authors trace the evolution of behavioral health care delivery in the United States over the past several decades and find (a) that the value of mental health "carve-outs" has diminished greatly and that they are being replaced by "carve-ins," (b) that primary care physicians (PCPs) are becoming a primary source of mental health care secondary to the introduction of new medications, and (c) that PCP treatment of mental health disorders is suboptimal. The authors conclude that the behavioral health care system is entering an era of flux as it experiments with ways of integrating behavioral and primary care. Opportunities for psychologists are explored.

A recent article by Hansen, Lambert, and Forman (2002) comparing outcomes in naturalistic settings and clinical trials was based on the assumption that these samples are comparable. However, up to 50% of patients in naturalistic settings are either in the normal or mild ranges whereas no patients in clinical trial samples are in the normal range. When Hansen's data are analyzed controlling for initial level of severity, outcomes in clinical trial samples and naturalistic samples are roughly comparable. Thus, Hansen's conclusion that patients in naturalistic settings do not receive adequate exposure to psychotherapy is unsupported. Rather, the Hansen data suggest that adequate outcomes can be achieved with far less exposure to psychotherapy than that suggested by consensus clinical trial data.

This article reports psychometric properties of a decision-support scale designed to quantify the decision-making process for allocating psychiatric care. The authors developed a scale to evaluate the level of care needed for patients requiring psychiatric treatment in a health maintenance organization (HMO) setting. This study examines the reliability and validity of that scale by measuring interrater agreement among utilization reviewers from the HMO and between those reviewers and the clinicians who evaluated the patients directly. Agreement (kappa) among the five clinical raters acting in a utilization review capacity on dimensions of the scale ranged from .71 to .98. Kappas for agreement between the treatment intensity proposed by the reviewer/rater and used by the treating clinician were .41, .38, .40, .35, .36, and .39, respectively. The scale is reliable in the hands of trained personnel. Although there were important differences between clinicians' ratings and those of utilization review raters, these differences do not suggest that use of the scale would limit patient access to care.