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Clinical supervision can effectively support the use of evidence-based treatments (EBTs) in community settings. However, implementation of multiple EBTs can lead to different training experiences f...

Background Understanding the mechanisms of implementation strategies (i.e., the processes by which strategies produce desired effects) is important for research to understand why a strategy did or did not achieve its intended effect, and it is important for practice to ensure strategies are designed and selected to directly target determinants or barriers. This study is a systematic review to characterize how mechanisms are conceptualized and measured, how they are studied and evaluated, and how much evidence exists for specific mechanisms. Methods We systematically searched PubMed and CINAHL Plus for implementation studies published between January 1990 and August 2018 that included the terms “mechanism,” “mediator,” or “moderator.” Two authors independently reviewed title and abstracts and then full texts for fit with our inclusion criteria of empirical studies of implementation in health care contexts. Authors extracted data regarding general study information, methods, results, and study design and mechanisms-specific information. Authors used the Mixed Methods Appraisal Tool to assess study quality. Results Search strategies produced 2277 articles, of which 183 were included for full text review. From these we included for data extraction 39 articles plus an additional seven articles were hand-entered from only other review of implementation mechanisms (total = 46 included articles). Most included studies employed quantitative methods (73.9%), while 10.9% were qualitative and 15.2% were mixed methods. Nine unique versions of models testing mechanisms emerged. Fifty-three percent of the studies met half or fewer of the quality indicators. The majority of studies (84.8%) only met three or fewer of the seven criteria stipulated for establishing mechanisms. Conclusions Researchers have undertaken a multitude of approaches to pursue mechanistic implementation research, but our review revealed substantive conceptual, methodological, and measurement issues that must be addressed in order to advance this critical research agenda. To move the field forward, there is need for greater precision to achieve conceptual clarity, attempts to generate testable hypotheses about how and why variables are related, and use of concrete behavioral indicators of proximal outcomes in the case of quantitative research and more directed inquiry in the case of qualitative research.

Research suggests the train-the-trainer (TtT) model may be an effective approach to training community mental health providers in evidence-based practice (EBP). This study compared pre- and post-training consultation outcomes as well as standardized measures of trainer attributes and behaviors between university-based master trainers and experienced community-based supervisors, trained under the TtT approach. Findings suggest local and master trainers are equivalent in terms of clinical teaching effectiveness and trainee-perceived charisma. Master trainers may have higher trainee-perceived credibility, but training and consultation outcomes are equivalent across the types of trainers, with the exception of behavioral problems where clinicians trained by local trainers and master trainers saw significantly greater growth than those who received training and consultation by master trainers.

Although communication is widely observed to be central to the implementation process, the field of implementation science has largely overlooked the details of how communication may best be utilized to facilitate implementation. This paper draws on relevant insights from Rogers' Diffusion of Innovations Theory, which laid the foundation for explicitly attending to the role of communication as a mechanism for implementation strategies to exert their effects. To offer empirically-derived and theory-informed recommendations regarding communication processes to support the effective introduction of new clinical practices. This investigation leverages data from 61 therapists poised to undergo implementation of measurement-based care (MBC) for depressed adults receiving psychotherapy in community mental health settings. Data were collected via focus groups across 12 sites. Themes emergent in the data analysis suggest five practices to facilitate effective communication in the introduction of new clinical practices like MBC: the communication of a clear rationale for the new practice; the provision of necessary procedural knowledge; communication about the change via multiple methods; sufficient lead time to prepare for the change; and the opportunity for bidirectional engagement. In addition to indicating several best practices to improve communication prior to implementation, our results suggest that the current conceptualization of implementation strategies may not yet be complete. Components and/or methods of effective communication about new practices should be included among the growing set of implementation strategies. Existing implementation strategies might also benefit from more temporal specificity, with more attention to the exploration and preparation phases. (Trial Registration: Clinicaltrials.gov NCT02266134. Registered 12 October 2014.).There has been a great deal of attention recently to the study of implementation, or how something (e.g., a new clinical practice or initiative) is actually put into effect. Many studies have found a number of barriers to and facilitators of the implementation process. But despite this increased attention, the field of implementation science may not have paid enough attention to the role of communication. Although communication is generally acknowledged as important, precisely how it impacts implementation—and, importantly, the ways it might be improved—is typically unexplored. This study conducted focus groups with mental health therapists in 12 clinics which were about to implement a new clinical practice: measurement-based care for depressed adults receiving psychotherapy. What these therapists shared about their perspectives and experiences suggest that there are at least five ways to facilitate effective communication when introducing a new clinical practice: communicating a clear rationale for the new practice, providing necessary procedural knowledge, using multiple methods to communicate about the change, giving sufficient lead time to prepare for the change, and providing the opportunity for bidirectional engagement.

Background Training is a core component in the implementation of empirically supported treatments, especially in the case of psychosocial interventions targeting mental illness. However, common forms of training are relatively ineffective in producing behavioral changes in providers. Trainers are in a strategic position to influence the success of training, but no research, to our knowledge, has explored whether personal characteristics of trainers (e.g., enthusiasm, charisma) increase effectiveness of training empirically supported treatments in the field of mental health. To address this gap, the current study created a measure of trainer characteristics (the Measure of Effective Attributes of Trainers (MEAT)) and assessed preliminary evidence for its reliability and validity by following gold standard measure development procedures. Methods Measure development consisted of three steps: (1) An initial pool of items was generated based on extant literature, input from the target population, and expert input; (2) target users of the measure interacted with the initial item pool to ensure face validity as well as clarity of measure instructions, response options, and items; and (3) a convenience sample viewed training videos and completed the measure resulting from step 2 to establish preliminary evidence of reliability and validity. An exploratory factor analysis was performed on the measure to determine whether latent factors (i.e., subscales of characteristics) underlie the data. Results The final solution consisted of two factors that demonstrated preliminary evidence for structural validity of the measure. The first factor, labeled “Charisma,” contained items related to characteristics that facilitate a positive personal relationship with the trainee (e.g., friendly, warm), and the second factor, labeled “Credibility,” contained items related to characteristics that emphasize the qualification of the trainer (e.g., professional, experienced). There was also evidence for face validity, content validity, reliability, and known groups validity of the measure. Conclusions The MEAT demonstrated preliminary evidence of key psychometric properties. Future research is needed to further explore and contribute to its psychometric evidence, which could be done in conjunction with measures of trainee knowledge, attitudes towards empirically supported treatments, and evaluations of trainee behavior change to delineate key characteristics of trainers to be leveraged for more effective training. Electronic supplementary material The online version of this article (doi:10.1186/s13012-017-0603-y) contains supplementary material, which is available to authorized users.

Importance Measurement-based care (MBC) is the systematic evaluation of patient symptoms before or during an encounter to inform behavioral health treatment. Despite MBC’s demonstrated ability to enhance usual care by expediting improvements and rapidly detecting patients whose health would otherwise deteriorate, it is underused, with typically less than 20% of behavioral health practitioners integrating it into their practice. This narrative review addresses definitional issues, offers a concrete and evaluable operationalization of MBC fidelity, and summarizes the evidence base and utility of MBC. It also synthesizes the extant literature’s characterization of barriers to and strategies for supporting MBC implementation, sustainment, and scale-up. Observations Barriers to implementing MBC occur at multiple levels: patient (eg, concerns about confidentiality breach), practitioner (eg, beliefs that measures are no better than clinical judgment), organization (eg, no resources for training), and system (eg, competing requirements). Implementation science—the study of methods to integrate evidence-based practices such as MBC into routine care—offers strategies to address barriers. These strategies include using measurement feedback systems, leveraging local champions, forming learning collaboratives, training leadership, improving expert consultation with clinical staff, and generating incentives. Conclusions and Relevance This narrative review, informed by implementation science, offers a 10-point research agenda to improve the integration of MBC into clinical practice: (1) harmonize terminology and specify MBC’s core components; (2) develop criterion standard methods for monitoring fidelity and reporting quality of implementation; (3) develop algorithms for MBC to guide psychotherapy; (4) test putative mechanisms of change, particularly for psychotherapy; (5) develop brief and psychometrically strong measures for use in combination; (6) assess the critical timing of administration needed to optimize patient outcomes; (7) streamline measurement feedback systems to include only key ingredients and enhance electronic health record interoperability; (8) identify discrete strategies to support implementation; (9) make evidence-based policy decisions; and (10) align reimbursement structures.

Objective Although tailored implementation methods are touted as superior to standardized, few researchers have directly compared the two and little guidance regarding the specific details of each method exist. Our study compares these methods in a dynamic cluster randomized trial seeking to optimize implementation of measurement based care (MBC) for depression in community behavioral health. This specific manuscript provides a detailed, replicable account of the components of each multi-faceted implementation method. Results The standardized best practice method includes training, consultation, a clinical guideline, and electronic health record enhancements with the goal to optimize the delivery of MBC with fidelity. Conversely, the tailored, customized and collaborative method is informed by recent implementation science advancements and begins with a needs assessment, followed by tailored training that feeds back barriers data to clinicians, the formation of an implementation team, a clinician-driven clinic-specific guideline, and the use of fidelity data to inform implementation team activities; the goal of the tailored condition is to ensure the intervention and implementation strategies address unique factors of the context. The description of these methods will inform others seeking to implement MBC, as well as those planning to use standardized or tailored implementation methods for interventions beyond behavioral health. Electronic supplementary material The online version of this article (10.1186/s13104-018-3193-0) contains supplementary material, which is available to authorized users.

Implementation experts suggest tailoring strategies to the intended context may enhance outcomes. However, it remains unclear which strategies are best suited to address specific barriers to implementation, in part because few measurement methods exist that adhere to recommendations for reporting. In the context of a dynamic cluster randomized trial comparing a standardized to tailored approach to implementing measurement-based care (MBC), this study aimed to (a) describe a method for tracking implementation strategies, (b) demonstrate the method by tracking strategies generated by teams tasked with implementing MBC at their clinics in the tailored condition, and (c) conduct preliminary examinations of the relation between strategy use and implementation outcomes (i.e., self-reported fidelity to MBC). The method consisted of a coding form based on Proctor, Powell, and McMillen (2013) implementation strategy reporting guidelines and Powell et al.'s (2012) taxonomy to facilitate specification of the strategies. A trained research specialist coded digitally recorded implementation team meetings. The method allowed for the following characterization of strategy use. Each site generated 39 unique strategies across an average of six meetings in five months. There was little variability in the use of types of implementation strategies across sites with the following order of prevalence: quality management (50.00%), restructuring (16.53%), communication (15.68%), education (8.90%), planning (7.20%), and financing (1.69%). We identified a new category of strategies not captured by the existing taxonomy, labeled "communication." There was no evidence that number of implementation strategies enacted was statistically significantly associated with changes in self-reported fidelity to MBC-however, financing strategies were associated with increased fidelity. This method has the capacity to yield rich data that will inform investigations into tailored implementation approaches.

Measurement Feedback Systems (MFS) are a class of Health Information Technology (HIT) that function as an implementation support strategy for integrating measurement based care or routine outcome monitoring into clinical practice. Although many MFS have been developed, little is known about their functions. This paper reports findings from an application of Health Information Technology- Academic and Commercial Evaluation (HIT-ACE), a systematic and consolidated evaluation method, to MFS designed for use in behavioral healthcare settings. Forty-nine MFS were identified and subjected to systematic characteristic and capability coding. Results are presented with respect to the representation of characteristics and capabilities across MFS.

Background Health information technologies (HIT) have become nearly ubiquitous in the contemporary healthcare landscape, but information about HIT development, functionality, and implementation readiness is frequently siloed. Theory-driven methods of compiling, evaluating, and integrating information from the academic and commercial sectors are necessary to guide stakeholder decision-making surrounding HIT adoption and to develop pragmatic HIT research agendas. This article presents the Health Information Technologies—Academic and Commercial Evaluation (HIT-ACE) methodology, a structured, theory-driven method for compiling and evaluating information from multiple sectors. As an example demonstration of the methodology, we apply HIT-ACE to mental and behavioral health measurement feedback systems (MFS). MFS are a specific class of HIT that support the implementation of routine outcome monitoring, an evidence-based practice. Results HIT-ACE is guided by theories and frameworks related to user-centered design and implementation science. The methodology involves four phases: (1) coding academic and commercial materials, (2) developer/purveyor interviews, (3) linking putative implementation mechanisms to hit capabilities, and (4) experimental testing of capabilities and mechanisms. In the current demonstration, phase 1 included a systematic process to identify MFS in mental and behavioral health using academic literature and commercial websites. Using user-centered design, implementation science, and feedback frameworks, the HIT-ACE coding system was developed, piloted, and used to review each identified system for the presence of 38 capabilities and 18 additional characteristics via a consensus coding process. Bibliometic data were also collected to examine the representation of the systems in the scientific literature. As an example, results are presented for the application of HIT-ACE phase 1 to MFS wherein 49 separate MFS were identified, reflecting a diverse array of characteristics and capabilities. Conclusions Preliminary findings demonstrate the utility of HIT-ACE to represent the scope and diversity of a given class of HIT beyond what can be identified in the academic literature. Phase 2 data collection is expected to confirm and expand the information presented and phases 3 and 4 will provide more nuanced information about the impact of specific HIT capabilities. In all, HIT-ACE is expected to support adoption decisions and additional HIT development and implementation research.