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This article focuses on the rationale, design and methods of an effectiveness-implementation hybrid type I randomized trial of eHealth Familias Unidas Mental Health, a family-based, online delivered intervention for Hispanic families to prevent/reduce depressive and anxious symptoms, suicide ideation/behaviors, and drug use in Hispanic youth. Utilizing a rollout design with 18 pediatric primary care clinics and 468 families, this study addresses intervention effectiveness, implementation research questions, and intervention sustainment, to begin bridging the gap between research and practice in eliminating mental health and drug use disparities among Hispanic youth. Further, we will examine whether intervention effects are partially mediated by improved family communication and reduced externalizing behaviors, including drug use, and moderated by parental depression. Finally, we will explore whether the intervention's impact on mental health and drug use, as well as sustainment of the intervention in clinics, varies by quality of implementation at clinic and clinician levels. Trail registration: ClinicalTrials.gov Identifier: NCT05426057, First posted June 21, 2022., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: University of Miami and Dr. Guillermo Prado are the owners and inventor of trademarked materials used in the study and both may receive royalties for its commercialization., (Copyright: © 2023 Estrada et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Between January 2016 and June 2020, the Substance Abuse and Mental Health Services Administration rapidly distributed $7.5 billion in response to the U.S. opioid crisis. These funds are designed to increase access to medications for addiction treatment, reduce unmet treatment need, reduce overdose death rates, and provide and sustain effective prevention, treatment and recovery activities. It is unclear whether or not the services developed using these funds will be sustained beyond the start-up period. Based on 34 (64%) State Opioid Response (SOR) applications, we assessed the states' sustainability plans focusing on potential funding sources, policies, and quality monitoring. We found variable commitment to sustainability across response plans with less than half the states adequately describing sustainability plans. States with higher proportions of opioid prescribing, opioid misuse, and poverty had somewhat higher scores on sustainment. A text mining/machine learning approach automatically rated sustainability in SOR applications with an 82% accuracy compared to human ratings. Because life saving evidence-based programs and services may be lost, intentional commitment to sustainment beyond the bolus of start-up funding is essential., Competing Interests: The authors have declared that no competing interests exist.

U.S. health care systems are tasked with alleviating the burden of mental health, but are frequently underprepared and lack workforce and resource capacity to deliver services to all in need. Digital mental health interventions (DMHIs) can increase access to evidence-based mental health care. However, DMHIs commonly do not fit into the day-to-day activities of the people who engage with them, resulting in a research-to-practice gap for DMHI implementation. For health care settings, differences between digital and traditional mental health services make alignment and integration challenging. Specialized attention is needed to improve the implementation of DMHIs in health care settings so that these services yield high uptake, engagement, and sustainment. The purpose of this article is to enhance efforts to integrate DMHIs in health care settings by proposing implementation strategies, selected and operationalized based on the discrete strategies established in the Expert Recommendations for Implementing Change project, that align to DMHI-specific barriers in these settings. Guidance is offered in how these strategies can be applied to DMHI implementation across four phases commonly distinguished in implementation science using the Exploration, Preparation, Implementation, Sustainment Framework. Next steps to advance research in this area and improve the research-to-practice gap for implementing DMHIs are recommended. Applying implementation strategies to DMHI implementation will enable psychologists to systematically evaluate this process, which can yield an enhanced understanding of the factors that facilitate implementation success and improve the translation of DMHIs from controlled trials to real-world settings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

With new tools from artificial intelligence and new perspectives on personalizing interventions, we could revolutionize the way mental health services are delivered and achieve major gains in improving the public's mental health. We examine Dr. Bickman's vision around these technological and paradigm changes that would usher in major scientific, workforce training, and societal cultural changes. We argue that additional efforts in research evaluations in implementation have the potential to scale up and adapt existing interventions and scale them out to diverse populations and service systems. The next stage of this work involves testing the effectiveness of personalized interventions that are preferred by the public and integrating these choices into sustainable service systems. We note cautions on the delivery of these programs as automated algorithmic recommendations are heretofore foreign to humans.

Background: Alignment across levels of leadership within an organization is needed for successful implementation of evidence-based practice. The leadership and organizational change for implementation (LOCI) intervention is a multi-faceted multilevel implementation strategy focusing on enhancing first-level general and implementation leadership while also engaging with organization upper management to develop an organizational climate for implementation. The aim of the project is to evaluate the effectiveness of LOCI in supporting the implementation of evidence-based treatment for PTSD in child- and adult-specialized mental health clinics in health trusts in Norway., Methods: The study design is a stepped-wedge cluster randomized trial with enrollment of clinics in three cohorts. Executives, clinic leaders, and therapists will be asked to complete surveys assessing leadership and implementation climate. Surveys will be completed at baseline, 4, 8, 12, 16, and 20 months. Results from surveys will be shared with executives and clinic leaders to inform the subsequent creation of tailored leadership and climate development plans for enhanced implementation. Patients will complete surveys measuring traumatic events and post-traumatic stress symptoms during the therapy process. Therapy sessions will be audio or video recorded and scored for fidelity as part of training., Discussion: This study aims to provide knowledge on how to improve leadership and organizational climate to enhance effective implementation of evidence-based treatments in mental health services., Trial Registration: The study has been registrated in ClinicalTrials with ID NCT03719651 .

Background: Given the importance of influence networks in the implementation of evidence-based practices and interventions, it is unclear whether such networks continue to operate as sources of information and advice when they are segmented and disrupted by randomization to different implementation strategy conditions. The present study examines the linkages across implementation strategy conditions of social influence networks of leaders of youth-serving systems in 12 California counties participating in a randomized controlled trial of community development teams (CDTs) to scale up use of an evidence-based practice., Methods: Semi-structured interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. A web-based survey collected additional quantitative data on information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) to examine linkages between treatment and standard conditions., Results: Of those network members who were affiliated with a county (n = 137), only 6 (4.4%) were directly connected to a member of the opposite implementation strategy condition; 19 (13.9%) were connected by two steps or fewer to a member of the opposite implementation strategy condition; 64 (46.7%) were connected by three or fewer steps to a member of the opposite implementation strategy condition. Most of the indirect steps between individuals who were in different implementation strategy conditions were connections involving a third non-county organizational entity that had an important role in the trial in keeping the implementation strategy conditions separate. When these entities were excluded, the CDT network exhibited fewer components and significantly higher betweenness centralization than did the standard condition network., Conclusion: Although the integrity of the RCT in this instance was not compromised by study participant influence networks, RCT designs should consider how influence networks may extend beyond boundaries established by the randomization process in implementation studies., Trial Registration: NCT00880126.

What progress prevention research has made comes through strategic partnerships with communities and institutions that host this research, as well as professional and practice networks that facilitate the diffusion of knowledge about prevention. We discuss partnership issues related to the design, analysis, and implementation of prevention research and especially how rigorous designs, including random assignment, get resolved through a partnership between community stakeholders, institutions, and researchers. These partnerships shape not only study design, but they determine the data that can be collected and how results and new methods are disseminated. We also examine a second type of partnership to improve the implementation of effective prevention programs into practice. We draw on social networks to studying partnership formation and function. The experience of the Prevention Science and Methodology Group, which itself is a networked partnership between scientists and methodologists, is highlighted.

Implementation science is an emerging field of research with considerable penetration in physical medicine and less in the fields of mental health and social services. There remains a lack of consensus on methodological approaches to the study of implementation processes and tests of implementation strategies. This paper addresses the need for methods development through a structured review that describes design elements in nine studies testing implementation strategies for evidence-based interventions addressing mental health problems of children in child welfare and child mental health settings. Randomized trial designs were dominant with considerable use of mixed method designs in the nine studies published since 2005. The findings are discussed in reference to the limitations of randomized designs in implementation science and the potential for use of alternative designs.

Background: The Good Behavior Game (GBG) is a classroom behavior management strategy focused on socializing children to the role of student and aimed at reducing early aggressive, disruptive behavior, a confirmed antecedent to service use. The GBG was tested in a randomized field trial in 19 elementary schools with two cohorts of children as they attended first and second grades. This article reports on the impact of the GBG on service use through young adulthood., Methods: Three or four schools in each of five urban areas were matched and randomly assigned to one of three conditions: (1) GBG, (2) an intervention aimed at academic achievement, or (3) the standard program of the school system. Children were assigned to classrooms to ensure balance, and teachers and classrooms were randomly assigned to intervention conditions., Results: This study provides evidence of a positive impact of a universal preventive intervention on later service use by males, although not by females, for problems with emotions, behavior, or drugs or alcohol. For both cohorts, males in GBG classrooms who had been rated as highly aggressive, disruptive by their teachers in the fall of first grade had a lower rate of school-based service use than their counterparts in control classrooms. REPLICATION: The design employed two cohorts of students. Although both first- and second-grade teachers received less training and support with the second cohorts of students than with the first cohort, the impact of GBG was similar across both cohorts.

Background: The Collaborative Care Model (CoCM) is an evidence-based mental health treatment in primary care. A greater understanding of the determinants of successful CoCM implementation, particularly the characteristics of multi-level implementers, is needed. Methods: This study was a process evaluation of the Collaborative Behavioral Health Program (CBHP) study (NCT04321876) in which CoCM was implemented in 11 primary care practices. CBHP implementation included screening for depression and anxiety, referral to CBHP, and treatment with behavioral care managers (BCMs). Interviews were conducted 4- and 15-months post-implementation with BCMs, practice managers, and practice champions (primary care clinicians). We used framework-guided rapid qualitative analysis with the Consolidated Framework for Implementation Research, Version 2.0, focused on the Individuals domain, to analyze response data. These data represented the roles of Mid-Level Leaders (practice managers), Implementation Team Members (clinicians, support staff), Innovation Deliverers (BCMs), and Innovation Recipients (primary care/CBHP patients) and their characteristics (i.e., Need, Capability, Opportunity, Motivation). Results: Mid-level leaders (practice managers) were enthusiastic about CBHP (Motivation), appreciated integrating mental health services into primary care (Need), and had time to assist clinicians (Opportunity). Although CBHP lessened the burden for implementation team members (clinicians, staff; Need), some were hesitant to reallocate patient care (Motivation). Innovation deliverers (BCMs) were eager to deliver CBHP (Motivation) and confident in assisting patients (Capability); their opportunity to deliver CBHP could be limited by clinician referrals (Opportunity). Although CBHP alleviated barriers for innovation recipients (patients; Need), it was difficult to secure services for those with severe conditions (Capability) and certain insurance types (Opportunity). Conclusions: Overall, respondents favored sustaining CoCM and highlighted the positive impacts on the practice, health care team, and patients. Participants emphasized the benefits of integrating mental health services into primary care and how CBHP lessened the burden on clinicians while providing patients with comprehensive care. Barriers to CBHP implementation included ensuring appropriate patient referrals, providing treatment for patients with higher-level needs, and incentivizing clinician engagement. Future CoCM implementation should include strategies focused on education and training, encouraging clinician buy-in, and preparing referral paths for patients with more severe conditions or diverse needs. Trial registration: ClinicalTrials.gov(NCT04321876). Registered: March 25,2020. Retrospectively registered. [ABSTRACT FROM AUTHOR]

Background: Mindfulness-based interventions have been shown to improve psychological outcomes including stress, anxiety, and depression in general population studies. However, effectiveness has not been sufficiently examined in racially and ethnically diverse community-based settings. We will evaluate the effectiveness and implementation of a mindfulness-based intervention on depressive symptoms among predominantly Black women at a Federally Qualified Health Center in a metropolitan city. Methods: In this 2-armed, stratified, individually randomized group-treated controlled trial, 274 English-speaking participants with depressive symptoms ages 18–65 years old will be randomly assigned to (1) eight weekly, 90-min group sessions of a mindfulness-based intervention (M-Body), or (2) enhanced usual care. Exclusion criteria include suicidal ideation in 30 days prior to enrollment and regular (>4x/week) meditation practice. Study metrics will be assessed at baseline and 2, 4, and 6 months after baseline, through clinical interviews, self-report surveys, and stress biomarker data including blood pressure, heart rate, and stress related biomarkers. The primary study outcome is depressive symptom score after 6 months. Discussion: If M-Body is found to be an effective intervention for adults with depressive symptoms, this accessible, scalable treatment will widely increase access to mental health treatment in underserved, racial/ethnic minority communities. Trial registration: ClinicalTrials.gov NCT03620721. Registered on 8 August 2018. [ABSTRACT FROM AUTHOR]

Background: Effective and efficient implementation of the Collaborative Care Model (CoCM) for depression and anxiety is imperative for program success. Studies examining barriers to implementation often omit patient perspectives. Objectives: To explore experiences and attitudes of eligible patients referred to CoCM who declined participation or were unable to be reached, and identify implementation barriers to inform strategies. Design: Convergent mixed-methods study with a survey and interview. Participants: Primary care patients at an academic medical center who were referred to a CoCM program for anxiety and depression by their primary care clinician (PCC) but declined participation or were unable to be reached by the behavioral health care manager to initiate care (n = 80). Interviews were conducted with 45 survey respondents. Main Measures: Survey of patients' referral experiences and behavioral health preferences as they related to failing to enroll in the program. Interview questions were developed using the Consolidated Framework for Implementation Research version 2.0 (CFIR 2.0) to identify implementation barriers to enrollment. Key Results: Survey results found that patients were uncertain about insurance coverage, did not understand the program, and felt services were not necessary. Referred patients who declined participation were concerned about how their mental health information would be used and preferred treatment without medication. Men agreed more that they did not need services. Qualitative results exhibited a variety of implementation determinants (n = 23) across the five CFIR 2.0 domains. Barriers included mental health stigma, perceiving behavioral health as outside of primary care practice guidelines, short or infrequent primary care appointments, prioritizing physical health over mental health, receiving inaccurate program information, low motivation to engage, and a less established relationship with their PCC. Conclusions: Multiple barriers to enrollment led to failing to link patients to care, which can inform implementation strategies to address the patient-reported experiences and concerns. [ABSTRACT FROM AUTHOR]

Objective: The authors sought to develop and validate a suite of dimensional measures of psychiatric syndromes for use in a criminal justice population.Methods: The previously validated Computerized Adaptive Test-Mental Health (CAT-MH) was administered to a sample of 475 defendants in the Cook County Bond Court. Item-level data were used to determine which test items exhibited differential item functioning in this population compared with the population used for the original calibration.Results: After removal of nine items that exhibited differential item functioning from the CAT-MH, correlations between scores based on the original calibration from a nonjustice-involved population and the newly computed scores based on a sample of bond court defendants showed a correlation coefficient of r=0.96 to r=0.99.Conclusions: With a slight modification of the original CAT-MH, the tool was successfully used to measure severity of depression, anxiety, mania and/or hypomania, suicidality, and substance use disorder in an English- and Spanish-speaking criminal justice population. [ABSTRACT FROM AUTHOR]

Background: Sustaining prevention efforts directed at substance use and mental health problems is one of the greatest, yet least understood, challenges in the field of implementation science. A large knowledge gap exists regarding the meaning of the term "sustainment" and what factors predict or even measure sustainability of effective prevention programs and support systems.Methods/design: The U.S. Substance Abuse and Mental Health Services Administration (SAMHSA) supports a diverse portfolio of prevention and treatment grant programs that aim to improve population and individual level behavioral health. This study focuses on four SAMHSA prevention grant programs, two of which target substance abuse prevention at the state or single community level, one targets suicide prevention, and one targets prevention of aggressive/disruptive behavior in elementary schools. An examination of all four grant programs simultaneously provides an opportunity to determine what is meant by the term sustainment and identify and support both the unique requirements for improving sustainability for each program as well as for developing a generalizable framework comprised of core components of sustainment across diverse prevention approaches. Based on an analysis of qualitative and quantitative data of 10 grantees supported by these four programs, we will develop a flexible measurement system, with both general and specific components, that can bring precision to monitoring sustainment of infrastructure, activities, and outcomes for each prevention approach. We will then transform this system for use in evaluating and improving the likelihood of achieving prevention effort sustainment. To achieve these goals, we will (1) identify core components of sustainment of prevention programs and their support infrastructures; (2) design a measurement system for monitoring and providing feedback regarding sustainment within the four SAMHSA's prevention-related grant programs; and (3) pilot test the predictability of this multilevel measurement system across these programs and the feasibility and acceptability of a measurement system to evaluate and improve the likelihood of sustainment.Discussion: This project is intended to improve sustainment of the supporting prevention infrastructure, activities, and outcomes that are funded by federal, state, community, and foundation sources. [ABSTRACT FROM AUTHOR]

Background The traditional wait-listed design, where half are randomly assigned to receive the intervention early and half are randomly assigned to receive it later, is often acceptable to communities who would not be comfortable with a no-treatment group. As such this traditional wait-listed design provides an excellent opportunity to evaluate short-term impact of an intervention. We introduce a new class of wait-listed designs for conducting randomized experiments where all subjects receive the intervention, and the timing of the intervention is randomly assigned. We use the term "dynamic wait-listed designs" to describe this new class. Purpose This paper examines a new class of statistical designs where random assignment to intervention condition occurs at multiple times in a trial. As an extension of a traditional wait-listed design, this dynamic design allows all subjects to receive the intervention at a random time. Motivated by our search for increased statistical power in an ongoing school-based trial that is testing a program of gatekeeper training to identify suicidal youth and refer them to treatment, this new design class is especially useful when the primary outcome is a count or rate of occurrence, such as suicidal behavior, whose rate can fluctuate over time due to uncontrolled factors. Methods Statistical power is computed for various dynamic wait-listed designs under conditions where the underlying rate of occurrence is allowed to vary non-systematically. We also present as an example a large ongoing trial to evaluate a gatekeeper training suicide prevention program in 32 schools which we initially began as a classic randomized wait-listed design. The primary outcome of interest in this study is the count of the number of children who are identified by the school system as having suicidal thoughts or behaviors who are then validated as being suicidal by mental health professionals in the community. Results A general result shows that dynamic wait-listed designs always have higher statistical power over a traditional wait-listed design. This power increase can be substantial. Efficiency gains of 33% are easy to obtain for situations where the intervention has a small effect and the variation in rate across time is quite high. When the rate variation for an outcome is very low or the intervention effect is large, efficiency gains approach 100%. A small increase in the number of times where random assignment occurs from 2 – for the standard wait-listed design, to say 4 – can provide a large reduction in variance. Efficiency gains can also be high when converting standard wait-listed design to a dynamic one half-way into the study. Limitations As with all wait-listed designs, dynamic wait-listed designs can only be used to evaluate short-term impact. Since all subjects eventually receive the intervention, no comparison can be made after the end of the random assignment period. The statistical power benefits are primarily limited to outcomes that can be treated as count or time to event data. Conclusions A dynamic design randomly assigns units – either individuals or groups – to start the intervention at varying times during the course of the study. This design is useful in testing interventions that screen for new or existing cases, as well as testing the scalability of interventions as they are disseminated or expanded system wide. They can improve on the traditional wait-listed design both in terms of statistical power and robustness in the presence of exogenous factors. This paper demonstrates that such designs yield smaller standard errors and can achieve higher statistical power than that of a standard wait-listed design. Just as important, dynamic designs can also help reduce the logistical challenges of implementing an intervention on a wide scale. When the intervention requires that significant training resources be allocated throughout the study, the dynamic wait-listed design is likely to increase the rate of training and lead to a higher level of program implementation. [ABSTRACT FROM AUTHOR]

Every day across America, behavioral health problems in childhood and adolescence, from anxiety to violence, take a heavy toll on millions of lives. For decades the approach to these problems has been to treat them only after they've been identified – at a high and ongoing cost to young people, families, entire communities, and our nation. Now we have a 30-year body of research and more than 50 programs showing that behavioral health problems can be prevented. This critical mass of prevention science is converging with growing interest in prevention across health care, education, child psychiatry, child welfare, and juvenile justice. Together, we stand at the threshold of a new age of prevention. The challenge now is to mobilize across disciplines and communities to unleash the power of prevention on a nationwide scale. We propose a grand challenge that will advance the policies, programs, funding, and workforce preparation needed to promote behavioral health and prevent behavioral health problems among all young people – including those at greatest disadvantage or risk, from birth through age 24. Within a decade, we can reduce the incidence and prevalence of behavioral health problems in this population by 20 percent from current levels through widespread policies and programs that will serve millions and save billions. Prevention is the best investment we can make, and the time to make it is now. [ABSTRACT FROM AUTHOR]