Introduction: Clinical and Translational Science Awards (CTSAs) are positioned to enhance the integration of rigorous implementation research methods into projects across their networks, but lack a systematic, standardized process to do so. This study introduces the Dissemination and Implementation Research Capability Self Survey (DIRC-SS), a pragmatic instrument to evaluate and integrate implementation science methods in traditional research activities.Methods: We developed the 15-item DIRC-SS to assess researchers' use of implementation research methods across five key constructs. Its reliability (inter-rater agreement and internal consistency) and sensitivity (change over time) were examined in 10 NIH-funded research projects via ratings assigned by the research teams and by implementation science experts at baseline and one year later.Results: The DIRC-SS total score demonstrated good internal consistency and inter-rater reliability increased over one year. Although the research team ratings did not change significantly over time, the expert ratings significantly increased, and effect sizes across research teams and expert raters were large in this small sample study.Conclusions: The DIRC-SS demonstrated good internal consistency reliability and moderate inter-rater reliability. It effectively distinguished between different levels of implementation research methods integration. Unlike tools focused on grant proposals or final reports, the DIRC-SS can be used at any point in the research process by a research team as a self-survey, by implementation science experts in a consultation process, or across a CTSA program to characterize the implementation science methods employed across projects and highlight targeted areas for researcher education and training.

Background:Qualitative methods are widely used in health services research to derive context-specific insights and depth of understanding. Manual coding, a foundational technique in rigorous qualitative analysis, is highly resource and time-intensive and difficult to scale. This is a particular challenge in health services research, where repeated rounds of interviews are common and rapid turnaround is often required. Natural Language Processing (NLP), specifically Large Language Models (LLMs), have shown potential to enhance efficiency in qualitative analysis. However, there is limited research providing guidance on how to integrate LLMs while maintaining rigor and trustworthiness. In this proof-of-concept study, we propose, apply, and evaluate an NLP-assisted coding method in a health services research setting. Methods:We analyzed 22 interviews among public health officials, law enforcement, community organizers, and medical professionals at one California county to examine existing substance use service gaps and needs. A primarily deductive codebook was iteratively refined until two coders achieved an inter-coder reliability (ICR) > 0.95 and was applied to the transcripts using ATLAS.ti. We developed an NLP-assisted method that uses a semantic shift algorithm to segment transcripts which are then passed to GPT-4 for code assignment and explanation using the codebook and coding guidelines developed during the manual process. We evaluated the method with a quantitative assessment of agreement between human and NLP-assigned codes, a qualitative and quantitative soundness assessment by two reviewers, and a comparative efficiency analysis. Results:The NLP-assisted method had moderate agreement with human coding (modified pooled Cohen's Kappa = 0.66), and 71.8% of codes were rated as sound by reviewers. Sound codes were more often observed for high-certainty and straightforward codes, and when text chunks were semantically well defined. The NLP-assisted method had more difficulty with non-linear conversation and entity-dependent codes. Coding time was reduced significantly from ~40 hours for the traditional method to ~1 hour for the NLP-assisted method. Conclusions:These findings suggest that LLMs can be effectively incorporated into qualitative processes while maintaining rigor if humans are embedded into the process. By maintaining a human-in-the-loop workflow, our methodology allows for researchers to maintain familiarity with the data, define the research question(s) and codebook, and determine if there are results that are not sound. By incorporating LLMs into the coding stage of the process, key limitations of traditional qualitative methods in health services research can be addressed, such as scalability, and resource and time limitations.

Low-threshold care (LTC) practices for prescribing medication for opioid use disorder (MOUD) systematically remove treatment barriers, increasing access to lifesaving MOUD. Despite its promise, LTC operationalization is unclear and heterogeneous, and lacks standardized measures. To develop and test LTC composite measures as useful predictors of implementation outcomes. This prospective cohort study was embedded within a California state MOUD practice change collaborative involving safety-net primary care clinics. Data were collected at baseline, midpoint, and endpoint from 20 clinics. Clinics received a multifaceted implementation–support package designed to improve MOUD delivery. Four LTC scales (LTC12, LTC5, LTC3, LTC2) were developed and tested using team-reported one to five Likert items. Implementation outcomes included Reach (monthly new MOUD patients), Retention (monthly new MOUD patients engaged in treatment after initial diagnosis), and Adoption (active MOUD prescribers). Analyses included repeated-measures ANOVA for LTC change and Poisson GEE for incidence rate ratios, adjusting for panel size, medically underserved area designation, and time. Clinics showed significant improvements in LTC scores over time. The LTC12 scale demonstrated the largest effect size (d = 1.18, p = .003). A 1-point increase on the LTC3 index was associated with a 37

How communities impact patients taking medication for opioid use disorder (MOUD) has not been well-studied. Understanding the experience of MOUD providers allows us to better understand and measure community attitudes toward MOUD and identify strategies to increase support. We deployed an explanatory sequential mixed methods design to analyze baseline data from the SITT-MAT clinical trial. Our quantitative instrument was seven Likert-scale questions asking about community attitudes toward MOUD analyzed through means, standard deviations, and principal components. The qualitative data were semi-structured interviews coded inductively using a thematic analysis. The quantitative and qualitative results were integrated to produce the findings. We surveyed staff from 20 specialty care addiction and primary care clinics in Washington state as part of a larger clinical trial. Eleven sites were also selected to complete an interview. Participating clinics were primarily specialty addiction treatment programs (N = 14, 70

Mutual-help groups (MHGs) are an effective resource in improving health for emerging adults in addiction recovery. Collegiate recovery programs (CRPs) have the infrastructure to support mutual help meeting implementation for this high-risk priority population for substance misuse. Despite their established role as an addiction recovery resource, the implementation of MHGs within CRPs is inconsistent and highly variable across institutions. To address this gap, we explored barriers and facilitators to planning and implementing MHGs within CRPs. We conducted qualitative interviews with 18 program director and college administrator participants from five CRPs across the United States in 2023. The guide focused on four domains of the Consolidated Framework for Implementation Research 2.0: Innovation, Inner Setting, Outer Setting, and Individuals. Thematic analysis was conducted using an iterative coding approach to identify key facilitators and barriers to MHG implementation. Four cross-cutting themes shaped MHG implementation within CRPs: (1) recovery-aligned leadership and facilitation, (2) institutional positioning and infrastructure, (3) sustainability and resourcing, and (4) inclusivity and pathway fit. Across these themes, leadership advocacy and lived-experience credibility facilitated implementation, while limited staffing capacity constrained delivery. MHGs were more accessible when embedded within visible campus infrastructure aligned with student success priorities. In addition, domain level facilitators included the credibility and perceived effectiveness of MHGs (Innovation), strong institutional support from high-level leaders (Individuals), donor engagement and established recovery spaces that fostered peer connections (Inner Setting), and alignment of CRPs with broader university missions related to student retention and well-being (Outer Setting). Barriers included concerns about the accessibility and inclusivity of traditional 12-Step models (Innovation), administrative misalignment with development offices (Inner Setting), and limited institutional awareness and funding instability (Outer Setting). Implementation strategies to enhance MHG adoption in CRPs include diversifying MHG offerings, integrating CRPs into university financial structures, strengthening external treatment and recovery housing partnerships, and fostering inclusive recovery environments. Addressing these barriers could enhance accessibility and sustainability of MHGs, ultimately improving recovery support for college students with substance use disorders.

BACKGROUND:This study examined specific mental health diagnoses groupings among patients admitted to specialty addiction treatment in the United States from 2006 to 2022. METHODS:Joinpoint regression was used to examine annual data from the publicly available Treatment Episode Data Set - Admissions. Sample selection criteria included having a primary substance listed and any of the following conditions: (a) anxiety disorders, (b) bipolar disorders, (c) depressive disorders, and (d) schizophrenia and other psychotic disorders. RESULTS:Prior to sample selection, across the full dataset of 31 152 649, cases with anxiety disorders accounted for 0.1%, bipolar disorders accounted for 0.3%, depressive disorders accounted for 0.4%, and schizophrenia and other psychotic disorders accounted for 0.1%. The total sample size was N = 224 051 with: (a) 13% for anxiety disorders (n = 29 111), (b) 30.3% for bipolar disorders (n = 67 926), (c) 43.4% for depressive disorders (n = 97 293), and (d) 13.3% for schizophrenia and other psychotic disorders (n = 29 721). Count data identified significant decreases including the following: 12.29% from 2008 to 2022 among the bipolar disorder group, 16.69% from 2019 to 2022 among the depressive disorder group, and 6.96% from 2006 to 2022 among the schizophrenia and other psychotic disorders group. CONCLUSION:This study has important implications for future research and clinical care related to co-occurring mental health and substance use disorders. Its findings demonstrate the need for further studies to examine how addiction treatment facilities are screening for and recording mental health disorder diagnoses. Future research is needed to clarify the prevalence of specific mental health diagnoses in the addiction treatment setting, including diagnoses such as anorexia nervosa and generalized anxiety disorder. This research would help determine specific treatment needs by using epidemiological data to provide a snapshot of the prevalence of these co-occurring conditions.

BACKGROUND:Successful implementation and sustainment of interventions is heavily influenced by context. Yet the complexity and dynamic nature of context make it challenging to connect and translate findings across implementation efforts. Existing methods to assess context are typically qualitative, limiting potential replicability and utility. Existing quantitative measures and the siloed nature of implementation efforts limit possibilities for data poolinXg and harmonization. The Inventory of Factors Affecting Successful Implementation and Sustainment (IFASIS) was developed to be a pragmatic, quantitative, organizational-level assessment of contextual factors. The intention is to characterize context with a measure that may enhance replication and reproducibility of findings beyond single implementation case studies. Here, we present the development and validation of the IFASIS. METHODS:A literature review was conducted to identify major concepts of established theories and frameworks to be retained. IFASIS data were examined in relation to implementation outcomes gathered from two studies. Psychometric validation efforts included content and face validity, reliability, internal consistency, and predictive and concurrent validity. Predictive validity was evaluated using generalized estimating equations (GEE) for longitudinal data on three implementation outcomes: reach, effectiveness, and implementation quality. Pragmatic properties were also evaluated. RESULTS:The IFASIS is a 27-item, team-based, instrument that quantitatively operationalizes context. Two rating scales capture current state and importance of each item to an organization. It demonstrated strong reliability, internal consistency, and predictive and concurrent validity. There were significant associations between higher IFASIS scores and improved implementation outcomes. A one-unit increase in total IFASIS score corresponded to a 160% increase in the number of patients receiving a medication (reach). IFASIS domains of factors outside the organization, factors within the organization, and factors about the intervention, and subscales of organizational readiness, community support, and recipient needs and values, were predictive of successful implementation outcomes. IFASIS scores were also significantly associated with measures of implementation quality. CONCLUSIONS:The IFASIS is a psychometrically and pragmatically valid instrument to assess contextual factors in implementation endeavors. Its ability to predict key implementation outcomes and facilitate data pooling across projects suggests it can play an important role in advancing the field.

Objective Alcohol use disorder (AUD) clinical trials have traditionally prioritized abstinence, and more recently, heavy drinking cessation as primary treatment endpoints. Reductions in World Health Organization (WHO) risk drinking levels may offer a viable harm reduction-aligned alternative. Despite evidence supporting WHO risk level reductions as meaningful indicators of AUD treatment response, their utility in individuals with co-occurring posttraumatic stress disorder (PTSD) remains unknown. The present study compared 1- and 2-level WHO risk drinking reductions with abstinence and heavy drinking (HD) outcomes, and assessed their sensitivity across PTSD and substance use disorder (SUD) interventions, including behavioral and pharmacological treatments. Methods We conducted an integrative data analysis of 10 trials for adults with comorbid PTSD and SUD (PTSD+SUD). The proportion of participants achieving each of the four alcohol outcomes was calculated. Logistic regression models assessed treatment effects relative to treatment as usual (TAU). Results Across the 10 trials (N = 433; mean [SD] age, 39.7 [11.6] years; 359 [73.0 %] men), the most frequently achieved drinking outcome at end-of-treatment was a 1 +  level WHO risk reduction (82.8 %), followed by a 2 +  level reduction (72.2 %), HD cessation (65.6 %) and, least frequently, abstinence (53.0 %). Pharmacological interventions significantly outperformed TAU across all drinking outcomes. Conclusions Findings provide initial support for WHO risk drinking levels as viable endpoints in PTSD+SUD trials. Given their attainability, WHO risk levels may provide clinically relevant outcome metrics for these interventions. Future research should assess whether such reductions correspond to improvements in alcohol-related harms and broader functional outcomes.

Peer recovery specialists (PRS) are increasingly recognized as key members of the substance use disorder (SUD) treatment workforce. Recent efforts have focused on expanding PRS roles to include the delivery of behavioral evidence-based interventions (EBIs), such as motivational interviewing, cognitive-behavioral therapy techniques, and brief interventions. This scoping review aims to identify the determinants that influence the implementation of PRS-delivered behavioral EBIs and the strategies used to optimize their delivery within diverse SUD treatment contexts. A systematic search was conducted in APA PsycINFO, Web of Science, Scopus, PubMed, and Google Scholar, following PRISMA-ScR guidelines. Studies were included if they examined PRS delivering behavioral EBIs for SUD and reported on at least one implementation outcome as defined by Proctor et al. (2011). Data extraction and thematic synthesis were conducted using a hybrid deductive-inductive coding framework. Twelve studies met inclusion criteria. The most commonly studied interventions included behavioral activation, motivational interviewing, and Screening, Brief Intervention, and Referral to Treatment (SBIRT). PRS-delivered behavioral EBIs demonstrated high acceptability, appropriateness, and feasibility, with strong participant engagement and satisfaction. Facilitators of implementation included the integration of PRS within existing service structures, the adaptability of interventions, and the unique relatability of PRS. Barriers included PRS role ambiguity, gaps in training, and systemic challenges such as lack of funding and limited access to adjunctive support services. Implementation outcomes such as adoption, sustainability, and cost were infrequently assessed, highlighting gaps in the current literature. The findings suggest that PRS-delivered behavioral EBIs hold promise in expanding access to evidence-based care for individuals with SUD. However, structured training, supervision, and organizational support are critical for successful implementation. Future research should prioritize evaluating long-term sustainability, supervision, and strategies to enhance the integration of PRS within healthcare systems. Incorporating methods to address systemic barriers faced by service recipients will be essential for maximizing the impact of PRS-delivered interventions in SUD treatment.

OBJECTIVE:The Emergency Department Longitudinal Integrated Care (ED-LINC) randomized clinical trial (NCT05327166) tests a Collaborative Care-informed intervention for emergency department (ED) patients with opioid use disorder. The ED-LINC intervention was developed before the current fentanyl epidemic; less than 10% of ED-LINC pilot intervention patients reported fentanyl use. To understand fentanyl's impact on the ED-LINC protocol, we utilized a systematic rapid qualitative approach to document clinical observations related to ED-LINC patients' fentanyl use and subsequent protocol modifications. METHOD:This study utilized Rapid Assessment Procedure Informed Clinical Ethnography (RAPICE) methods to document fentanyl-related clinical observations. As participant observers, the team worked with a mixed methods consultant to analyze observations, informing adaptation to study protocol and intervention. RESULTS:From 4/12/2022 to 2/10/2023, 86 patients enrolled in the ED-LINC trial. Forty received the ED-LINC intervention and are included in this study. Investigators identified the following themes informing adaptation to the ED-LINC intervention: 1) fentanyl-related suicide risk, 2) fentanyl-catalyzed approach to Medications for Opioid Use Disorder (MOUD), 3) fentanyl-related adaptations to measurement-based care embedded in the Collaborative Care approach, 4) fentanyl-associated survival needs, and 5) engagement challenges with fentanyl. Adaptations included incorporating overdose prevention into suicide risk assessment, nontraditional MOUD induction, and shifting to a component-driven model. CONCLUSIONS:The landscape of clinical practice can change quickly and may require both researchers and healthcare providers to quickly pivot. Rapid assessment procedures integrated into clinical trial investigation allow for modifications and adaptations to study protocols to ensure salient and generalizable results given the rapidly evolving opioid epidemic.

Objectives: Efforts to increase access to highly effective medications for opioid use disorder (MOUD) have largely focused on primary care. Ironically, many specialty addiction treatment programs have yet to adopt MOUD. To bring MOUD access to scale, researchers need to better understand medication practices across these 2 major portals of care for patients with opioid use disorder (OUD). In this study, our team examined baseline prescribing data from 62 primary care clinics and specialty addiction treatment programs (SATPs) participating in MOUD implementation endeavors across 2 states. Methods: Our primary outcomes included MOUD prescribing practices, measured by the integrating medications for addiction treatment (IMAT), which includes 7 dimensions of guideline-adherent delivery of MOUD, and an additional subscale on low threshold care. We also measured reach of MOUD to patients and adoption as the number of current MOUD prescribers. Secondary outcomes included community characteristics surrounding each type of organization. Descriptive statistics and bivariate tests explored differences between primary and specialty care settings. Results: SATPs had lower MOUD capacity and implementation as compared with primary care clinics. Specialty settings also had lower organizational support for low threshold prescribing. SATPs were located in counties with higher overdose rates, higher unemployment, fewer MOUD prescribers, and with more opioid prescriptions per capita. Conclusions: SATPs have lower MOUD implementation capacity than their primary care counterparts and are more likely to be in counties with greater OUD-related needs, economic distress, and fewer treatment resources. Selecting more precise implementation support strategies for SATPs that are late adopters of MOUD is a major need.

For over 20 years, the Addiction Health Services Research (AHSR) Conference has brought together researchers, policymakers, and treatment providers to solve the problems of inequity, access, effectiveness, and implementation of addiction services. This conference has been hosted across the United States at leading institutions. The AHSR 2024 Conference took place in San Francisco, October 16 to 18, and was hosted by the Stanford Center for Dissemination and Implementation, Stanford University School of Medicine. With over 400 attendees, the Conference sought to further the positive impact of prevention and treatment services for substance misuse and use disorders. The agenda included 8 pre-conference workshops, 4 plenary sessions, 144 oral sessions, including 12 organized symposia, and 160 posters across 2 sessions. The conference supported 7 early-career investigator award recipients and registration support for over 30 early-career applicants. Over 80 students and junior faculty participated in a mentoring program. AHSR 2024 fostered important discussions of cutting-edge health services research findings and accelerated the development of collaborative relationships among attendees.

BACKGROUND:Randomized rollout trial designs, including stepped wedge designs, are commonly used to examine how well an evidence-based intervention or package is being implemented in community or healthcare settings. The multitude of implementation research questions and specific hypotheses suggest the need for diverse randomized rollout implementation trial designs, assignment principles and procedureds, and statistical modeling. METHODS:We separate key research questions and identify mixed effect models for randomized implementation rollout trials involving 1) a single implementation strategy that tests how this strategy varies over time and/or resources that are allocated, 2) comparison of two distinct implementation strategies, and 3) three distinct strategies or components tested in a single trial. Appropriate rollout designs, optimal assignment methods, and other design and analysis considerations are discussed for trials of up to three distinct implementation strategies. RESULTS:To examine improvement in implementation outcomes we present a Fixed-Length Staggered Rollout Trial Design to examine how well a sustainment period continues to produce outcomes, The Rollout Implementation Optimization (ROIO) methodology illustrates testing for quality improvement. For comparing an existing to new strategy, we focus on a Stepped Wedge design, and for comparing two new strategies we describe a Head-to-Head Rollout trial design. To test for synergy between two components, we introduce a Head-to-Head Rollout trial design, and for testing an existing strategy to a new one followed by a sustainment period, we recommend using a Three-Phase Sequential Rollout Implementation trial design. Modeling choices are described, including options for specifying random effects that capture variations in site and clustering. We discuss comparisons of superiority versus non-inferiority testing and multiple contrasts. To support uses of these six designs and analyses, we provide computational code. CONCLUSIONS:The large class of randomized rollout implementation trial designs provides rich opportunities to address research questions posed by implementation scientists. Balance in assigning sites to cohorts is important before random assignment to time of transition to a new implementation occurs. Specific hypotheses are tested with mixed effects models where fixed effects include comparisons of implementation conditions and random effects that account for variation in sites and clustering.

The opioid epidemic has prompted nationwide efforts to expand access to medications for opioid use disorder (MOUD). Primary care settings have been identified as a critical access point for patients who may benefit from MOUD treatments. Despite implementation efforts, there is limited understanding of how MOUD practice capability in primary care settings evolves over time or what factors influence clinic-level implementation trajectories. We conducted a longitudinal study of 95 primary care clinics in California from 2019 to 2024. MOUD practice capability was measured using the Integrating Medications for Addiction Treatment in Primary Care (IMAT-PC) index across three timepoints. Using latent class growth analysis, we analyzed implementation growth trajectories and examined their associations with clinic characteristics and MOUD implementation outcomes (e.g., patient reach and provider adoption). Three distinct implementation trajectory classes emerged: elevated improving (41.0

BACKGROUND:Implementation costs-the combined costs of delivering expert support and participating in an implementation endeavor-are often omitted from economic evaluations. When included, delivery and participation costs are usually combined, even though these may be covered by different funders. We propose a pragmatic micro-costing approach that separates the delivery and participation costs as well as outlines practical considerations for measuring implementation costs. METHODS:Sixty-four specialty addiction treatment programs and primary care clinics participated in a stepped sequence of implementation strategies focused on improving access to buprenorphine and naltrexone for persons with opioid use disorder. The implementation strategies deployed were: audit and feedback (A&F), a two-day workshop, internal facilitation, and external facilitation. Our micro-costing approach separately measured the cost to deliver and participate in implementation strategies, as demonstrated through the A&F case example, which was the first of four implementation strategies deployed. We applied the following practical considerations to maximize the precision and accuracy of cost data: 1) Balance the frequency and length of cost survey, 2) Cost tracking training, 3) Regular survey reminders, 4) Tailor cost surveys, 5) Perform frequent cost data validation, 6) Iterative evaluation and refinement. RESULTS:In A&F, the implementation setup cost was $32,266, and the annual recurring costs were $4,231 per clinic. While the majority of the setup cost (99%) can be attributed to A&F delivery, over half of the annual recurring costs (63%) were attributed to clinic participation in A&F. CONCLUSIONS:This micro-costing approach appears both pragmatic and meaningful. By understanding the total cost implications of implementation, decision-makers can better select the most suitable strategy based on the context, goals, and budget constraints to efficiently optimize the pace and desired outcome of an implementation endeavor. TRIAL REGISTRATION:The trial protocol is registered with ClinicalTrials.gov (NCT05343793).