Trials optimising implementation strategies are complex, assess multicomponent strategies, and cluster randomise. We define optimisation as identifying the best combination of components for multi-component implementation strategies. Multi-arm, fixed, cluster randomised control trials (cRCTs) can assess multiple implementation components but suffer from low power due to challenges of recruitment. Adaptive designs offer increased efficiency, when compared to “fixed trial” approaches. A simulation study was conducted to assess whether adaptive designs are feasible (acceptable operating characteristics and adaptive interim decisions) for implementation cRCTs with few clusters. A four-arm cRCT was simulated under varying trial properties. The trials were simulated using fixed design and adaptive design parameters (number of interim analyses, timing of interim analysis, actions at interim e.g. allowing for early stopping for futility, arm dropping) and modelled using Bayesian hierarchical models. The power and type 1 error were compared between the fixed and adaptive designs, and the number of correct interim decisions under the adaptive design were examined. When the intra-class correlation (ICC) was high, the proportion of trials that incorrectly dropped the most effective arm increased. There were small power gains for adaptive designs, without increasing type 1 error. Power gains attenuated when ICC was high and sample size was low. Type 1 error was lower comparable between adaptive and non-adaptive designs. Adaptive designs are feasible for cRCTs with few clusters. They are not as feasible when the ICC is high due to increased risk of incorrect adaptive interim decisions.

BackgroundOccupational guidelines exist to support workplaces with the prevention of mental health problems (MHP) among their staff. However, knowledge of effective implementation strategies to support their implementation is limited. This study experimentally tested whether a multifaceted implementation strategy – comprising an educational meeting, five workshops, implementation teams, small cyclical tests of change, and facilitation – improves fidelity to a guideline for preventing MHP in a school setting through the pathway of change of the Capability Opportunity Motivation-Behavior (COM-B)-model. To gain a more granular understanding of the mechanisms of change, the Theoretical Domains Framework (TDF) was used to specify mediators related to capability, opportunity, and motivation. This study tested whether the multifaceted strategy versus a discrete strategy (1) improves fidelity, (2) enhances capability, opportunity, and motivation over time, and (3) if the strategy’s effect on fidelity is mediated by capability, opportunity, and motivation.MethodsFifty-five schools were randomly assigned to a multifaceted strategy or a discrete strategy. Fidelity was measured by questionnaires at baseline and 12 months, while capability, opportunity, and motivation were assessed three times within this period (directly after the educational meeting and at three and nine months). The Determinants of Implementation Behavior Questionnaire was used to assess TDF hypothesized mediators corresponding to the COM-B components. Separate pathways were analyzed for each mediator. Linear Mixed Modeling was employed to test the strategy’s effect on fidelity, and mediation analyses were conducted using the PROCESS Macro.ResultsThe multifaceted strategy led to improved fidelity at 12 months (B = 2.81, p < .001). Multifaceted schools reported higher scores for all mediators after nine months compared to schools receiving the discrete strategy. The effect of the multifaceted strategy on fidelity was partially mediated by all TDF mediators (p = < .05) except for beliefs about consequences. Capability-related mediators, including skills (Proportion-mediated = 41%, p = < .01) and behavioral regulation (Proportion-mediated = 35%, p = < .001), accounted for the largest proportion of the effect, followed by the motivation-related mediator goals (Proportion-mediated = 34%, p = < .01).ConclusionsThe multifaceted strategy improved guideline fidelity by enhancing capability, opportunity, and motivation confirming the proposed function of COM-B. This study addresses calls for experimental evidence on how multifaceted implementation strategies achieve implementation outcomes.Trial registrationClinicalTrials.org dr.nr 2020–01214.

BackgroundPerinatal mental health conditions are the most common complication of pregnancy and childbirth (1 in 8 women). When left untreated, perinatal depression and anxiety adversely affects the entire family with pregnancy complications and negative outcomes including preterm birth, impaired mother-infant bonding, impaired lactation, substance abuse, divorce, suicide, and infanticide. Significant disparities persist in the diagnosis and treatment of perinatal depression and anxiety and these inequities are often intersectional. Preliminary research with stakeholders including community advisory boards, underrepresented and minority birthing people, and state departments of health, demonstrates the importance of social support as a mechanism for reducing disparities in perinatal depression, particularly in rural geographies. Home visiting programs (HVPs) can provide the social support needed to improve mental health outcomes in pregnant and postpartum women. Our project aims to explore the impact of context on the implementation of a mental health intervention, focusing on the lived experiences of diverse populations served by HVPs to reduce disparities in adverse maternal outcomes.MethodsUsing implementation facilitation, our study will engage multilevel stakeholders (e.g., policymakers, front-line implementers, and intervention recipients) to adapt facilitation to integrate a maternal mental health intervention (i.e., Mothers and Babies) across two midwestern, rural states (Iowa and Indiana) with multiple HVP models. Given the complexity and heterogeneity of the contexts in which Mothers and Babies will be integrated, a three variable hybrid implementation-effectiveness-context trial will test the adapted facilitation strategy compared with implementation as usual (i.e., standard education) and will assess contextual factors related to the outcomes. Using an evidence-based implementation strategy that tailors implementation delivery to the needs of the specific populations and context may improve fidelity and adoption, particularly in rural states where residents have limited access to care.DiscussionThe immediate impact of this research will be to show whether adapted facilitation can improve the uptake and fidelity of Mothers and Babies across multiple HVP models and thus positively affect depressive symptoms and perceived stress of recipients. Our implementation protocol may be used by researchers, practitioners, and policy makers to better integrate evidence-based interventions into diverse contexts, leading to more equitable implementation and improved health outcomes.Trial registrationClinicalTrials.gov Identifier: NCT06575894, registered on August 29, 2024 https://clinicaltrials.gov/study/NCT06575894?id=NCT06575894&rank=1.

BackgroundResearch on determinants of health policy implementation is limited, and conceptualizations of evidence and implementation success are evolving in the field. This study aimed to identify determinants of perceived policy implementation success and assess whether these determinants vary according to: (1) how policy implementation success is operationally defined [i.e., broadly vs. narrowly related to evidence-based practice (EBP) reach] and (2) the role of a person’s organization in policy implementation. The study focuses on policies that earmark taxes for behavioral health services.MethodsWeb-based surveys of professionals involved with earmarked tax policy implementation were conducted between 2022 and 2023 (N = 272). The primary dependent variable was a 9-item score that broadly assessed perceptions of the tax policy positively impacting multiple dimensions of outcomes. The secondary dependent variable was a single item that narrowly assessed perceptions of the tax policy increasing EBP reach. Independent variables were scores mapped to determinants in the Exploration, Preparation, Implementation, and Sustainment (EPIS) framework. Multiple linear regression estimated associations between measures of determinants and policy implementation success.ResultsPerceptions of tax attributes (innovation determinant), tax EBP implementation climate (inner-context determinant), and inter-agency collaboration in tax policy implementation (outer-context and bridging factor determinant) were significantly associated with perceptions of policy implementation success. However, the magnitude of associations varied according to how success was operationalized and by respondent organization type. For example, the magnitude of the association between tax attributes and implementation success was 42% smaller among respondents at direct service organizations than non-direct service organizations when implementation success was operationalized broadly in terms of generating positive impacts (β = 0.37 vs. β = 0.64), and 61% smaller when success was operationalized narrowly in terms of EBP reach (β = 0.23 vs. β = 0.59). Conversely, when success was operationalized narrowly as EBP reach, the magnitude of the association between EBP implementation climate and implementation success was large and significant among respondents at direct service organizations while it was not significant among respondents from non-direct service organizations (β = 0.48 vs. β=-0.06).ConclusionDeterminants of perceived policy implementation success may vary according to how policy implementation success is defined and the role of a person’s organization in policy implementation. This has implications for implementation science and selecting policy implementation strategies.

BackgroundThe implementation of clinical practice guidelines (CPGs) is a cyclical process in which the evaluation stage can facilitate continuous improvement. Implementation science has utilized theoretical approaches, such as models and frameworks, to understand and address this process. This article aims to provide a comprehensive overview of the models and frameworks used to assess the implementation of CPGs.MethodsA systematic review was conducted following the Cochrane methodology, with adaptations to the "selection process" due to the unique nature of this review. The findings were reported following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines. Electronic databases were searched from their inception until May 15, 2023. A predetermined strategy and manual searches were conducted to identify relevant documents from health institutions worldwide. Eligible studies presented models and frameworks for assessing the implementation of CPGs. Information on the characteristics of the documents, the context in which the models were used (specific objectives, level of use, type of health service, target group), and the characteristics of each model or framework (name, domain evaluated, and model limitations) were extracted. The domains of the models were analyzed according to the key constructs: strategies, context, outcomes, fidelity, adaptation, sustainability, process, and intervention. A subgroup analysis was performed grouping models and frameworks according to their levels of use (clinical, organizational, and policy) and type of health service (community, ambulatorial, hospital, institutional). The JBI’s critical appraisal tools were utilized by two independent researchers to assess the trustworthiness, relevance, and results of the included studies.ResultsDatabase searches yielded 14,395 studies, of which 80 full texts were reviewed. Eight studies were included in the data analysis and four methodological guidelines were additionally included from the manual search. The risk of bias in the studies was considered non-critical for the results of this systematic review. A total of ten models/frameworks for assessing the implementation of CPGs were found. The level of use was mainly policy, the most common type of health service was institutional, and the major target group was professionals directly involved in clinical practice. The evaluated domains differed between the models and there were also differences in their conceptualization. All the models addressed the domain "Context", especially at the micro level (8/12), followed by the multilevel (7/12). The domains "Outcome" (9/12), "Intervention" (8/12), "Strategies" (7/12), and "Process" (5/12) were frequently addressed, while "Sustainability" was found only in one study, and "Fidelity/Adaptation" was not observed.ConclusionsThe use of models and frameworks for assessing the implementation of CPGs is still incipient. This systematic review may help stakeholders choose or adapt the most appropriate model or framework to assess CPGs implementation based on their specific health context.Trial registrationPROSPERO (International Prospective Register of Systematic Reviews) registration number: CRD42022335884. Registered on June 7, 2022.

Theories have been developed by researchers in implementation science to achieve enhanced understanding and explanation of how or why implementation succeeds or fails. These theories specify the causal mechanisms of change. This chapter looks at the concept of theory and examines how implementation science-specific theories are defined. The chapter also clarifies how theories used in implementation science can be distinguished from models and frameworks in the field. Three implementation theories that are used in implementation science are described: Normalization Process Theory (NPT), Organizational Readiness for Change (ORC) and Capability Opportunity Motivation – Behaviour (COM-B).

Implementation science has seen the development of literally hundreds of theoretical approaches in the form of theories, models and frameworks for use by researchers in the field. This chapter provides an overview of the theories, models and frameworks that are available in implementation science, with the aim of describing how these approaches are applied. The chapter presents a taxonomy that distinguishes between different approaches to advance clarity and achieve a common terminology in the field. Knowledge about the theories, models and frameworks facilitates appropriate selection and application of relevant approaches in implementation science studies.

Determinant frameworks are used in implementation science to describe and categorize influences (i.e. determinants) on the implementation of evidence-based practices. Determinants are typically divided into barriers (or hindrances) and facilitators (or enablers or drivers) of implementation. Knowledge about implementation determinants is important to develop and select appropriate strategies to overcome barriers and harness facilitators to support the implementation of evidence-based interventions, programmes, services and other practices. This chapter looks at the origins, content and use of six determinant frameworks.

BackgroundDespite improvement, sepsis mortality rates remain high, with an estimated 11 million sepsis-related deaths globally in 2017 (Rudd et. al, Lancet 395:200-211, 2020). Low- and middle-income countries (LMICs) are estimated to account for 85% of global sepsis mortality; however, evidence for improved sepsis mortality in LMICs is lacking. We aimed to improve sepsis care and outcomes through development and evaluation of a sepsis treatment protocol tailored to the Tikur Anbessa Specialized Hospital Emergency Department, Ethiopia, context.MethodsWe employed a mixed methods design, including an interrupted times series study, pre-post knowledge testing, and process evaluation. The primary outcome was the proportion of patients receiving appropriate sepsis care (blood culture collection before antibiotics and initiation of appropriate antibiotics within 1 h of assessment). Secondary outcomes included time to antibiotic administration, 72-h sepsis mortality, and 90-day all-cause mortality. Due to poor documentation, we were unable to assess our primary outcome and time to antibiotic administration. We used segmented regression with outcomes as binomial proportions to assess the impact of the intervention on mortality. Pre-post knowledge test scores were analyzed using the Student’s t-test to compare group means for percentage of scenarios with correct diagnosis.ResultsA total of 113 and 300 patients were enrolled in the pre-implementation and post-implementation phases respectively. While age and gender were similar across the phases, a higher proportion (31 vs. 57%) of patients had malignancies in the post-implementation phase. We found a significant change in trend between the phases, with a trend for increasing odds of survival in the pre-implementation phase (OR 1.24, 95% CI 0.98–1.56), and a shift down, with odds of survival virtually flat (OR 0.95, 95% CI. 0.88–1.03) in the post-implementation phases for 72-h mortality, and trends for survival pre- and post-implementation are virtually flat for 90-day mortality. We found no significant difference in pre-post knowledge test scores, with interpretation limited by response rate. Implementation quality was negatively impacted by resource challenges.ConclusionWe found no improvement in sepsis outcomes, with a trend for increasing odds of survival lost post-implementation and no significant change in knowledge pre- and post-implementation. Variable availability of resources was the principal barrier to implementation.Trial registrationOpen Science Framework osf.io/ju4ga. Registered June 28, 2017