The role of implementation organizations in scaling evidence-based psychosocial interventions.

BACKGROUND: To bring evidence-based interventions (EBIs) to individuals with behavioral health needs, psychosocial interventions must be delivered at scale. Despite an increasing effort to implement effective treatments in communities, most individuals with mental health and behavioral problems do not receive EBIs. We posit that organizations that commercialize EBIs play an important role in disseminating EBIs, particularly in the USA. The behavioral health and implementation industry is growing, bringing the implementation field to an important inflection point: how to scale interventions to improve access while maintaining EBI effectiveness and minimizing inequities in access to psychosocial intervention. MAIN BODY: We offer a first-hand examination of five illustrative organizations specializing in EBI implementation: Beck Institute for Cognitive Behavioral Therapy; Incredible Years, Inc.; the PAXIS Institute; PracticeWise, LLC; and Triple P International. We use the Five Stages of Small Business Growth framework to organize themes. We discuss practical structures (e.g., corporate structures, intellectual property agreements, and business models) and considerations that arise when trying to scale EBIs including balancing fidelity and reach of the intervention. Business models consider who will pay for EBI implementation and allow organizations to scale EBIs. CONCLUSION: We propose research questions to guide scaling: understanding the level of fidelity needed to maintain efficacy, optimizing training outcomes, and researching business models to enable organizations to scale EBIs.

Relationships between statistical measures of agreement: sensitivity, specificity and kappa.

OBJECTIVES: Cohen's kappa coefficient is presently a standard tool for the analysis of agreement on a binary outcome between two tests. In view of the ubiquity of the use of sensitivity, specificity, raw agreement and kappa in clinical studies, clearly it is advantageous to have a useful analytic relation connecting these measures of agreement. METHODS: We elaborate on previous work, comment on other results appearing in the literature and discuss analytic formulas relevant to various problems connecting specificity, sensitivity and kappa. RESULTS: For selected values of kappa that range from good to excellent, a graph of the curves representing minimal pairs of sensitivity and specificity is provided. CONCLUSIONS: The analytic formulas and graph could be potentially useful to clinicians and biostatisticians in better interpreting the outcomes of an alternative diagnostic test whenever the measures sensitivity, specificity and kappa are employed together.