Early in treatment, peer providers may possess distinctive skills in communicating positive regard, understanding, and acceptance to clients and a facility for increasing treatment participation among the most disengaged, leading to greater motivation for further treatment and use of peer-based community services. Findings strongly suggest that peer providers serve a valued role in quickly forging therapeutic connections with persons typically considered to be among the most alienated from the health care service system.

Early in treatment, peer providers may possess distinctive skills in communicating positive regard, understanding, and acceptance to clients and a facility for increasing treatment participation among the most disengaged, leading to greater motivation for further treatment and use of peer-based community services. Findings strongly suggest that peer providers serve a valued role in quickly forging therapeutic connections with persons typically considered to be among the most alienated from the health care service system.

Disproportionate minority contact (DMC) is a pervasive problem throughout the juvenile justice system. This article explored whether mental illness may be an explanatory factor in DMC. Data such as measures of violence risk and symptoms of mental illness were taken from intake interviews with 482 detained youth in Connecticut. Results indicated that racial minorities in detention have significantly lower violence risk than Caucasians but are disproportionately represented among detention populations relative to their proportions in the general population. In addition, DMC in these data was not explained by mental illness, seriousness of charges, violence risk, age, or gender. We suggest that mandated efforts to reduce DMC will need to address more than improving behavior or reducing symptoms of mental illness among detained minority youth. Instead, efforts should be focused on reducing the racial disparity evident in decisions made within the juvenile justice system.

A recent article in this journal proposed a naturalistic approach to decision making that overcomes problems intrinsic to classical decision theory. The approach emphasizes cognitive and multi-level processes, the development of expert reasoning, and the role of decision support in individual and organizational decision making. The current paper builds on this effort by suggesting a naturalistic, multi-level, theory that can facilitate the dissemination of evidence-based practices (EBPs). The paper presents "Image Theory," a theory that has been extensively investigated in other disciplines, but has yet to be utilized in medical decision research. It is suggested that its rich, empirically tested, distinctions among kinds of cognitive and organizational processes and types of decisions and tasks make Image Theory especially valuable in describing impediments to implementing EBPs. The paper discusses how naturalistic theory can assist clinicians, administrators, researchers, and policy makers in achieving a balance between evidence-based medicine and patient-centered practice.

Structured professional judgment (SPJ) has received considerable attention as an alternative to unstructured clinical judgment and actuarial assessment, and as a means of resolving their ongoing conflict. However, predictive validity studies have typically relied on receiver operating characteristic (ROC) analysis, the same technique commonly used to validate actuarial assessment tools. This paper presents SPJ as distinct from both unstructured clinical judgment and actuarial assessment. A key distinguishing feature of SPJ is the contribution of modifiable factors, either dynamic or protective, to summary risk ratings. With modifiable factors, the summary rating scheme serves as a prognostic model rather than a classification procedure. However, prognostic models require more extensive and thorough predictive validity testing than can be provided by ROC analysis. It is proposed that validation should include calibration and reclassification techniques, as well as additional measures of discrimination. Several techniques and measures are described and illustrated. The paper concludes by tracing the limitations of ROC analysis to its philosophical foundation and its origin as a statistical theory of decision-making. This foundation inhibits the performance of crucial tasks, such as determining the sufficiency of a risk assessment and examining the evidentiary value of statistical findings. The paper closes by noting a current effort to establish a viable and complementary relationship between SPJ and decision-making theory.

A recent essay in this journal identified health care as a fertile domain for extending the reach of naturalistic decision making (NDM). It targeted the "best practices regimen, " a host of initiatives begun in the late 20th century that address problems in service delivery, skyrocketing costs, and impediments in transforming products of basic science into effective treatments. Of particular importance are efforts to base treatment decisions on empirical research findings and to gauge the quality of decisions by their conformance to evidence-based practices. The challenges that the essay identified and the ways of addressing these challenges are well known in the health care community. They have had limited impact owing to several factors, including how advocates of the best practices regimen envision clinical decision making and their tendency to equate the exercise of skill with resistance to change. This paper describes the regimen's concept of decision making and its principles and deficiencies. It also identifies a conundrum: oversimplification prevents complexity from being recognized; as a result, evidence-based recommendations frequently have unforeseeable and deleterious consequences. The paper proposes that NDM is well positioned to address these problems and make a valuable contribution to health care practice. It illustrates NDMbased theories and concepts with a research example and describes their ability to address complex issues that arise in treating chronic illnesses.

Tools that measure the impact of pain may be a more valuable screening instrument than the NRS. Further research is now needed to determine if measuring the impact of pain in clinical practice is more effective at triggering appropriate management than more restricted measures of pain such as the NRS.

Rationale-Efforts to describe how individual treatment decisions are informed by systematic knowledge have been hindered by a standard that gauges the quality of clinical decisions by their adherence to guidelines and evidence-based practices. This paper tests a new contextual standard that gauges the incorporation of knowledge into practice and develops a model of evidence-based decision making.Aims and objectives-Previous work found that the forecasted outcome of a treatment guideline exerts a highly significant influence on how it is used in making decisions. This study proposed that forecasted outcomes affect the recognition of a treatment scenario, and this recognition triggers distinct contextual decision strategies.Method-N=21 volunteers from a psychiatric residency program responded to 64 case vignettes, 16 in each of four treatment scenarios. The vignettes represented a fully balanced within-subjects design that included guideline switching criteria and patient-specific factors. For each vignette, participants indicated whether they endorsed the guideline's recommendation.Results-Clinicians employed consistent contextual decision strategies in responding to clearly positive or negative forecasts. When forecasts were more ambiguous or risky, their strategies became complex and relatively inconsistent. Conclusion-The results support a three step model of evidence-based decision making, in which clinicians recognize a decision scenario, apply a simple contextual strategy, then if necessary engage a more complex strategy to resolve discrepancies between general guidelines and specific cases. The paper concludes by noting study limitations and discussing implications of the model for future research in clinical and shared decision making, training, and guideline development.