Research on implementation science has increased significantly over the past decade. In particular, psychologists have looked closely at the value and importance of bridging the gap between science and practice. As evidence-based practices (EBPs) become more prevalent, concrete mechanisms are needed to bring these scientifically supported treatments and interventions to community-based settings. Intermediary and purveyor organizations (IPOs) have emerged in recent years that specialize in bringing research to practice. Using a framework developed by Franks (), this descriptive study surveyed respondents that self-identified as IPOs and focused on identifying shared definitions, functions, and activities. Results indicated that seven descriptive roles previously identified were supported by this survey and many common shared activities, goals, and functions across these organizations were observed. Further, these organizations appear to be influenced by the growing field of implementation science. Limitations and implications of this study are discussed.

Youths are using emergency departments (EDs) for behavioral health services in record numbers, even though EDs are suboptimal settings for service delivery. In this article, the authors evaluated a mobile crisis service intervention implemented in Connecticut with the aim of examining whether the intervention was associated with reduced behavioral health ED use among those in need of services.

While an increasing number of evidence-based practices and programs have been developed over the past two decades, there remains a significant gap between research and practice. Intermediary organizations help bridge this research–practice gap through various roles and functions. Intermediaries provide support to facilitate the implementation of evidence-based practices and build capacity to sustain such practices with fidelity. However, there is little guidance as to how to develop an intermediary organization and what strategies and contextual factors should be considered. The purpose of this article is to identify contextual factors that may impact the development of intermediary organizations and to recommend strategies for building the necessary capacities and competencies that correspond to the intermediary's identified roles and functions.

Table of contentsIntroduction to the 3rd Biennial Conference of the Society for Implementation Research Collaboration: advancing efficient methodologies through team science and community partnershipsCara Lewis, Doyanne Darnell, Suzanne Kerns, Maria Monroe-DeVita, Sara J. Landes, Aaron R. Lyon, Cameo Stanick, Shannon Dorsey, Jill Locke, Brigid Marriott, Ajeng Puspitasari, Caitlin Dorsey, Karin Hendricks, Andria Pierson, Phil Fizur, Katherine A. ComtoisA1: A behavioral economic perspective on adoption, implementation, and sustainment of evidence-based interventionsLawrence A. PalinkasA2: Towards making scale up of evidence-based practices in child welfare systems more efficient and affordablePatricia ChamberlainA3: Mixed method examination of strategic leadership for evidence-based practice implementationGregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. WillgingA4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiencesMaria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-GuentherA3: Mixed method examination of strategic leadership for evidence-based practice implementationGregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. WillgingA4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiencesMaria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-GuentherA5: Efficient synthesis: Using qualitative comparative analysis and the Consolidated Framework for Implementation Research across diverse studiesLaura J. Damschroder, Julie C. LoweryA6: Establishing a veterans engagement group to empower patients and inform Veterans Affairs (VA) health services researchSarah S. Ono, Kathleen F. Carlson, Erika K. Cottrell, Maya E. O’Neil, Travis L. LovejoyA7: Building patient-practitioner partnerships in community oncology settings to implement behavioral interventions for anxious and depressed cancer survivorsJoanna J. Arch, Jill L. MitchellA8: Tailoring a Cognitive Behavioral Therapy implementation protocol using mixed methods, conjoint analysis, and implementation teamsCara C. Lewis, Brigid R. Marriott, Kelli ScottA9: Wraparound Structured Assessment and Review (WrapSTAR): An efficient, yet comprehensive approach to Wraparound implementation evaluationJennifer Schurer Coldiron, Eric J. Bruns, Alyssa N. HookA10: Improving the efficiency of standardized patient assessment of clinician fidelity: A comparison of automated actor-based and manual clinician-based ratingsBenjamin C. Graham, Katelin JordanA11: Measuring fidelity on the cheapRochelle F. Hanson, Angela Moreland, Benjamin E. Saunders, Heidi S. ResnickA12: Leveraging routine clinical materials to assess fidelity to an evidence-based psychotherapyShannon Wiltsey Sti...

Emerging adults (EA), individuals between the ages of 15-26, face many challenges in their transition to a new developmental stage, especially those with behavioral health concerns who do not receive the supports they need. Many EA drop out of services at 18, which is likely due in part to the need to transition to the adult service system and the lack of available transition support services in child/adolescent service systems. Though this is a clear disparity, research on EA service utilization, especially those enrolled in Medicaid and with co-occurring conditions, is rare. This paper begins to address this gap by examining variables at age 17 that predict the service utilization of continuously Medicaid enrolled EA at age 18. Data came from an administrative dataset. The sample had 4,548 EA and 53% were female, 50% identified with a minority group, and 19% were child-welfare involved. Exploratory logistic regression analyses were used. Minority EA had lower odds of utilizing services at age 18. EA involved with child welfare had greater odds of utilizing services at age 18. EA with at least one Substance Use Disorder (SUD) and at least one mental health disorder at 17 had a higher likelihood of service utilization at 18, the opposite was true for EA with only SUDs. These findings identified predictors of service utilization for an understudied sample-EA enrolled in Medicaid. Results provided preliminary evidence that EA with SUD diagnoses access behavioral health services differently than those without a SUD diagnosis, and that it is fruitful to examine subgroups of EA when seeking to understand their service utilization patterns. Identifying predictors of service utilization during the transition period from the child to the adult system can help inform systems interventions to retain EA in services.

Objective To develop and test predictive models of discontinuation of behavioral health service use within 12 months in transitional age youth with recent behavioral health service use. Data sources Administrative claims for Medicaid beneficiaries aged 15–26 years in Connecticut. Study design We compared the performance of a decision tree, random forest, and gradient boosting machine learning algorithms to logistic regression in predicting service discontinuation within 12 months among beneficiaries using behavioral health services. Data extraction We identified 33,532 transitional age youth with ≥1 claim for a primary behavioral health diagnosis in 2016 and Medicaid enrollment of ≥11 months in 2016 and ≥11 months in 2017. Principal findings Classification accuracy for identifying youth who discontinued behavioral health service use was highest for gradient boosting (80%, AUC = 0.86), decision tree (79%, AUC = 0.84), and random forest (79%, AUC = 0.86), as compared with logistic regression (71%, AUC = 0.71). Conclusions Predictive models based on Medicaid claims can assist in identifying transitional age youth who are at risk of discontinuing from behavioral health care within 12 months, thus allowing for proactive assessment and outreach to promote continuity of care for younger persons who have behavioral health needs.

Risk assessments allow child and youth services to identify children who are at risk for maltreatment (e.g., abuse, neglect) and help determine the restrictiveness of placements or need for services among youth entering a child welfare system. Despite the use of instruments by many agencies within the U.S. to determine the appropriate placements for youth, research has shown that placement decisions are often influenced by factors such as gender, age, and severity of social–emotional and behavior problems. This study examined ratings of risk across multiple domains using a structured assessment tool used by caseworkers in the Rhode Island child welfare system. The relationship between ratings of risk and placement restrictiveness was also examined. Risk levels varied across placement settings. Multivariate analyses revealed that lower caseworker ratings of parent risk and higher ratings of youth risk were associated with more restrictive placements for youth. Implications for the child welfare system are discussed.

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