58 research outputs found

    Evaluating Treatments and Interventions: What Constitutes “Evidence-based” Treatment?

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    This chapter provides an overview of the evidence-based treatment (EBT) paradigm, beginning with definitional issues, followed by a discussion on use of the iterative process and the importance of strong academic–practice partnerships to inform the development, selection, and implementation of EBTs. The discussion then turns to the importance of attaining, measuring, and sustaining fidelity to the treatment models; and identifying common barriers to sustained EBT use. Drawing from our expertise related to interventions for children and adolescents, a few dissemination/implementation models are highlighted as examples of current efforts to achieve sustained use of EBTs among practitioners, within agencies, and across communities. This involves keeping up to date with the research and integrating the available evidence base with clinical expertise and patient characteristics, including cultural considerations and client preferences for treatment. The chapter concludes with directions for the future, including considerations for practitioners, referring agents, and agency senior leaders to promote, support, and sustain EBTs

    Treatment of child victims of abuse and neglect

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    This publication reviews the effects of and treatment for various types of child victimization experiences. It will be helpful to child protection workers, guardians ad litem, attorneys, family court judges, and others involved with children who have been abused or neglected. This information will enhance the ability of child protection professionals to recognize a need for mental health treatment and to seek appropriate treatment services. This publication will also enable other professionals to better communicate with therapists about a child’s needs and progress

    Initial Development of Tools to Identify Child Abuse and Neglect in Pediatric Primary Care

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    BACKGROUND: Child abuse and neglect (CAN) is prevalent, associated with long-term adversities, and often undetected. Primary care settings offer a unique opportunity to identify CAN and facilitate referrals, when warranted. Electronic health records (EHR) contain extensive information to support healthcare decisions, yet time constraints preclude most providers from thorough EHR reviews that could indicate CAN. Strategies that summarize EHR data to identify CAN and convey this to providers has potential to mitigate CAN-related sequelae. This study used expert review/consensus and Natural Language Processing (NLP) to develop and test a lexicon to characterize children who have experienced or are at risk for CAN and compared machine learning methods to the lexicon + NLP approach to determine the algorithm\u27s performance for identifying CAN. METHODS: Study investigators identified 90 CAN terms and invited an interdisciplinary group of child abuse experts for review and validation. We then used NLP to develop pipelines to finalize the CAN lexicon. Data for pipeline development and refinement were drawn from a randomly selected sample of EHR from patients seen at pediatric primary care clinics within a U.S. academic health center. To explore a machine learning approach for CAN identification, we used Support Vector Machine algorithms. RESULTS: The investigator-generated list of 90 CAN terms were reviewed and validated by 25 invited experts, resulting in a final pool of 133 terms. NLP utilized a randomly selected sample of 14,393 clinical notes from 153 patients to test the lexicon, and .03% of notes were identified as CAN positive. CAN identification varied by clinical note type, with few differences found by provider type (physicians versus nurses, social workers, etc.). An evaluation of the final NLP pipelines indicated 93.8% positive CAN rate for the training set and 71.4% for the test set, with decreased precision attributed primarily to false positives. For the machine learning approach, SVM pipeline performance was 92% for CAN + and 100% for non-CAN, indicating higher sensitivity than specificity. CONCLUSIONS: The NLP algorithm\u27s development and refinement suggest that innovative tools can identify youth at risk for CAN. The next key step is to refine the NLP algorithm to eventually funnel this information to care providers to guide clinical decision making

    Advice-seeking during implementation: a network study of clinicians participating in a learning collaborative

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    Abstract Background Successful implementation depends on the transfer of knowledge and expertise among clinicians, which can occur when professionals seek advice from one another. This study examines advice-seeking patterns among mental health clinicians participating in learning collaboratives (a multi-component implementation and quality improvement strategy) to implement trauma-focused cognitive behavioral therapy (TF-CBT). We apply transactive memory system theory, which explains how professionals access and retrieve knowledge, to examine factors associated with the evolution of advice-seeking relationships during implementation. Our aim is to unpack learning collaboratives’ mechanisms by investigating how and why advice-seeking networks change, which may help us understand how implementation strategies can best target networks. Methods Using social network analysis and a pretest-post-test design, we examined patterns in general and treatment-specific advice-seeking among 146 participants (including five clinical experts) from 27 agencies participating in a regional scale-up of TF-CBT. Surveys were administered in-person at the first and last of three in-person learning sessions (10 months apart) that comprise a core component of learning collaboratives. Participants nominated up to five individuals from whom they seek general and treatment-specific advice. Exponential random graph models (ERGMs) tested the likelihood of maintaining or forming advice-seeking relationships based on indicators of expertise quality, accessibility, need, and prior advice-seeking relationships. Results Participants formed or maintained advice-seeking relationships with those who possess perceived expertise (e.g., learning collaborative faculty experts, supervisors, and those with greater field experience than themselves). Participants also tended to seek advice from those within the same organization and with similar disciplinary training, highlighting the importance of expertise accessibility. Prior relationships and network structural features were associated with advice-seeking, indicating that participants built on existing social ties. Advice-seeking did not vary based on participants’ role or experience. Conclusions Given the importance of accessible clinical expertise and ongoing supervision for delivering treatment with fidelity, learning collaboratives may support implementation by promoting clinicians’ awareness of and access to others’ expertise, especially those with substantial expertise to share (e.g., faculty experts and supervisors). Future controlled studies are needed to verify the effectiveness of learning collaboratives for building networks that connect clinicians and experts and for improving implementation

    Relations Among Gender, Violence Exposure, and Mental Health: The National Survey of Adolescents

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    Using a nationally representative sample of 4,008 adolescents, this study examines gender differences in violence exposure, major depressive episode (MDE) and posttraumatic stress disorder (PTSD), and characteristics of violence incidents. It was hypothesized that there would be gender differences in the types of violence exposure reported as well as the prevalence of MDE and PTSD; and that gender would moderate the relationship between violence exposure and mental health outcomes. Results indicated significant gender differences in rates of violence exposure, PTSD and MDE. Additionally, gender was a moderating variable in the relation between sexual assault and PTSD, but not in the other violence exposure-mental health relations examined. It thus appears that the pathways for developing PTSD may be different for male and female victims of sexual abuse. Implications for interventions and future research are discussed

    Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

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    It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations

    Treating Victims of Child Sexual Abuse

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