Implementation Science最新文献

Background: Implementation strategies are deliberate systematic actions used to support the uptake of innovations in health and social care. While widely used taxonomies such as ERIC and EPOC have emerged from consensus exercises, few implementation strategies are explicitly derived from theory and tested against empirical data. This study develops a taxonomy of implementation strategies grounded in Normalization Process Theory (NPT), an implementation theory that explains how new practices become embedded and sustained.

Methods: We conducted a qualitative evidence synthesis of studies that reported implementation projects informed by NPT. Studies were identified through citation tracking and database searches, screened using pre-specified criteria, and appraised for methodological quality. Using the NPT coding manual, we identified implementation mechanisms described in each study and translated these into candidate implementation strategies. These were then tested against all included studies through iterative qualitative content analysis.

Result: Searches led to 9,147 references, and we then eliminated 5,708 duplicates. After title and abstract screening a further 1,443 were eliminated. Full text screening was undertaken with 1,996 papers, and 1,411 of these were eliminated. This left 585 papers subjected to quality assessment, of which 522 were eliminated. Finally, 63 papers were included in the review. Qualitative analysis of included papers yielded 24 general strategies linked to NPT's theoretical constructs and 96 micro-strategies representing four domains of implementation activity: leadership, information, empowerment, and service user involvement. Each strategy was explicitly linked to an NPT construct.

Conclusions: This study provides a theory-based and empirically grounded set of actionable implementation strategies. These are grounded in qualitative descriptions of implementation work. These strategies support practical decision-making across the planning, delivery, and sustainment phases of implementation, and offer context-sensitive guidance for adapting interventions to diverse settings. Unlike consensus-based taxonomies, these strategies are tied to observable mechanisms of action, enabling users to better understand and respond to the dynamic and socially organised nature of implementation. The NPT taxonomy of implementation strategies can support the design, tailoring, and operationalisation of implementation efforts across varied health and social care contexts.

Background: Early detection of diseases in primary care is crucial for timely treatment and better outcomes. Complex care demands and limited resources can make early detection challenging. Clinical decision support systems (CDSS) aim to improve the diagnostic process. However, barriers to implementation have so far prevented their effective use.  This systematic review aimed to identify barriers for the implementation of CDSS for disease detection in primary care and use this to develop recommendations for implementation.

Methods: We searched MEDLINE, EMBASE, Scopus, Web of Science and Cochrane databases. Included studies reported barriers to the implementation of CDSS for the detection of undiagnosed, prevalent diseases in primary care. Two independent researchers undertook screening and data extraction. The QuADS tool was used for quality assessment. Data on barriers and facilitators were synthesised using an inductive-deductive approach based on the Theoretical Domains Framework. This was used to identify solutions via the Behaviour Change Wheel.

Results: 10498 titles and abstracts were screened, and 768 full texts were assessed. We included 99 studies describing 85 tools, mostly in high-income countries. Most studies (66, 66.7%) applied qualitative methods and described CDSS implemented in pilot studies (64, 64.7%). Included studies had very limited stakeholder involvement or theoretical underpinning.  We identified 2563 unique barriers and facilitators to implementation. Barriers were spread across the Theoretical Domains Framework including technical and workflow implementation issues at practice level, wider healthcare system issues, problems with the usability of systems, PCPs' and patients' attitudes and beliefs, a lack of skills and knowledge, and social barriers. Implementation recommendations for development teams involve selecting appropriate diagnostic challenges for CDSS, ensuring usability, engaging stakeholders and testing CDSS prior to implementation. Primary care teams need to clarify responsibilities, provide training and support patients. Underlying barriers across healthcare systems will need to be addressed at policy level.

Conclusions: The range and scale of the barriers and complexity of recommendations highlight implementation challenges for CDSS in primary care. Although recommendations can be used to improve implementation, our findings emphasise the need to carefully reflect on the feasibility of CDSS in primary care at the point of design and development.  The systematic review was preregistered using PROSPERO (CRD42024517054): https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=517054.

Background: Grounded in the Integrated Promoting Action on Research Implementation in Health Services framework (i-PARIHS) and the Replicating Effective Programs framework (REP), the goal is to determine if the use of theory, data and end-user perspectives to guide an adaptation of the Transdiagnostic Intervention for Sleep and Circadian Dysfunction (TSC) yields better outcomes and improves the "fit" of TSC to community mental health centers (CMHCs), relative to the standard version.

Methods: Ten counties in California were cluster-randomized by county to Adapted or Standard TSC. Within each county, adults who exhibited sleep and circadian dysfunction and serious mental illness (SMI) were randomized to immediate TSC or Usual Care followed by Delayed Treatment with TSC (UC-DT). Facilitation was the implementation strategy. The participants were 93 CMHC providers who delivered TSC (Standard = 30; Adapted = 63) and 396 CMHC patients (Standard = 74; Adapted = 124; UC-DT = 198). Patient assessments were completed at pre-treatment, post-treatment, and six months after treatment (6FU). Provider assessments were completed at post-training, mid-treatment, and post-treatment.

Results: TSC (combining Adapted and Standard), relative to UC-DT before delayed treatment with TSC, was associated with improvement from pre- to post-treatment in sleep disturbance (b = -10.91, p < 0.001, d = -1.52), sleep-related impairment (b = -9.52, p < 0.001, d = -1.06), sleep health composite (b = 1.63, p < 0.001, d = 0.95), psychiatric symptoms (b = -6.72, p < 0.001, d = -0.52), and overall functional impairment (b = -5.12, p < 0.001, d = -0.71). TSC's benefits for functional impairment and psychiatric symptoms were mediated by improvements in sleep and circadian problems. Adapted versus Standard TSC did not differ on provider ratings of fit and better fit did not mediate the relation between TSC condition and patient outcome.

Conclusions: TSC can be delivered by CMHC providers. Adapted and Standard TSC both fit the CMHC context. These findings are interpreted through the lens of the four core constructs of the i-PARIHS framework.

Trial registration: Clinicaltrials.gov identifier: NCT04154631. Registered on November 6, 2019. https://clinicaltrials.gov/ct2/show/NCT04154631.

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.

Background: A major gap in implementation research is guidance for designing studies to assess the impact of adaptations to interventions and implementation strategies. Many researchers regard experimental designs as the gold standard. However, the possible study designs for assessing the impact of adaptation on implementation, service and person-level outcomes is broad in scope, including descriptive and correlational research and variations of randomized controlled trials. This article provides a set of key methodological recommendations for assessing the impact of adaptations to interventions and implementation strategies on implementation outcomes.

Recommendations: We offer four key recommendations for investigating the impact of adaptations on implementation outcomes. First, we recommend defining the construct of adaptations and identifying the type and timing of adaptations. Second, we recommend that study teams identify the expected proximal and distal outcomes of adaptations. Third, we recommend that study teams consider all possible study design options and select the design that is best suited to answer the research question(s), and is feasible given practical and technical constraints, and acceptable to research partners and participants. Fourth, we recommend that study teams consider the type of adaptation and outcome data available, the goals of the adaptation study, and the complexity of the study design when selecting analytic approaches. We provide materials and examples related to the four key recommendations to help study teams plan and conduct adaptation studies.

Conclusions: This article provides methodological recommendations for assessing the impact of adaptations to interventions and implementation strategies on implementation, service, and person-level outcomes that are grounded in the practical realities of implementation research. Increasing the number of studies examining how, which, and under what conditions adaptations are associated with mechanisms and outcomes will advance research on adaptation.

Background: We conducted a cost analysis of implementing a randomized controlled trial that proved the effectiveness of a community health worker (CHW) facilitated weight loss intervention among South Asian patients with prediabetes receiving care at primary care practices in New York City. South Asians have a high prevalence of diabetes, but no study to date has evaluated the cost of implementing an evidence-based lifestyle intervention in this population. Cost estimates are necessary for an intervention's adoption and scale-up.

Methods: The first wave of the intervention was implemented in-person, followed by two waves implemented remotely during the COVID-19 pandemic. We estimated the implementation, intervention, and adaptation costs and the costs by each wave of implementation, by applying the Gold et al.'s economic framework and ERIC discrete implementation strategy compilation Costs were calculated from the perspective of a health care payer, public health agency, or health care system. The CHW intervention included group education sessions over six months. For each wave, we separately estimated the total cost, cost per practice, and cost when implemented at only one practice. Using the Bureau of Labor Statistics salary estimates, we calculated the national average (mean salary) and lower (25th percentile salary) and upper (75th percentile salary) bounds.

Results: The average total 6-month implementation costs over 3 waves, each targeting seven practices was $215,420 (range: $158,620-$257,020). Program staff salaries comprised > 93% of total costs. Adaptation cost was nearly 1/3 of start-up costs. On average, implementation at one practice would cost twice as much as the per-practice costs when implemented simultaneously at seven practices in a wave, due to spread of start-up costs across multiple sites.

Conclusions: Staff salaries comprise most of the budget to implement such an intervention. It is most efficient for an agency to implement this intervention across several practices simultaneously. Decision-makers will need to evaluate relative costs and effectiveness of other options to achieve weight loss in a minority community with constrained resources.

Clinicaltrials: GOV: This study was registered on June 15, 2017 at  https://www.

Clinicaltrials: gov as NCT03188094. https://clinicaltrials.gov/ct2/show/NCT03188094 .

Background: Clear specification and reporting of implementation strategies and their targeted healthcare professional behaviors are essential for replication, adaptation, and cumulative learning in implementation science. However, critical gaps remain in the consistent use of reporting frameworks. This study aimed to: (1) assess the completeness of implementation strategy reporting using the Template for Intervention Description and Replication (TIDieR) checklist; (2) examine trends in implementation strategy reporting over time; and (3) assess the completeness of the reporting of healthcare professional behaviors targeted for change using the Action, Actor, Context, Target, Time (AACTT) framework.

Methods: We conducted a secondary analysis of 204 trials included in a systematic review of implementation strategies aimed at changing healthcare professional behavior. Implementation strategies were assessed using the 12-item TIDieR checklist; target behaviors were characterized using the five AACTT domains. Two independent reviewers extracted and coded the data. Descriptive statistics were used to summarize reporting patterns. Data were synthesized narratively and presented in tables, with trends illustrated via a scatterplot.

Results: Assessment of implementation strategy reporting using TIDieR showed that procedural details (98%), materials used (95%), and modes of delivery (88%) were frequently reported. Critical elements such as strategy tailoring (28%), fidelity assessment (19% planned; 17% actual), and modifications (10%) were often missing. A modest improvement in reporting was observed after the publication of TIDieR, with median scores increasing from 15.0 (IQR: 13.0-16.0) pre-2014 to 16.0 (IQR: 15.0-18.0) post-2014. Assessment of target healthcare professional behavior reporting using AACTT indicated that actions (e.g., "assess illness") and actors (e.g., nurses) were generally well reported at a high level. However, key contextual and temporal details were largely absent. While physical context was documented in all studies, the emotional and social contexts of behaviors were rarely reported. Crucial information on the duration, frequency, and period of behaviors was rarely reported.

Conclusions: Implementation strategies and target behaviors are not consistently or sufficiently reported in trials. Increased adoption of structured reporting tools such as TIDieR and AACTT is essential to enhance transparency. Incorporating these frameworks during protocol development could strengthen intervention evaluation and reporting, advancing implementation science and fostering cumulative knowledge.

Trial registration: PROSPERO CRD42019130446.

Background: Type 2 diabetes (T2D) is a global health concern affecting 10.5% of the adult population and is projected to rise significantly in the coming decades. Lifestyle modification programs, such as the Diabetes Prevention Program (DPP), can effectively reduce T2D risk among individuals with prediabetes. However, their implementation in real-world healthcare settings remains poor, particularly in Spain, where T2D prevalence is the highest in Europe. The ALADIM study aims to evaluate the effectiveness and implementation of an adapted DPP in Spanish Primary Care Centers (PCCs). The primary effectiveness outcome is weight, the co-primary implementation outcome is implementation fidelity. We will also assess the effect of DPP implementation on overall prediabetes management within the PCCs (spillover) by measuring the percentage of people with prediabetes receiving lifestyle advice.

Methods: The ALADIM trial is a hybrid type II effectiveness-implementation cluster-randomized controlled trial involving 10 PCCs of Mallorca (Balearic Islands, Spain). PCCs will be randomized to the intervention (5 PCCs) or control (5 PCCs) group in a 1:1 ratio. The intervention group will receive training and materials to implement and deliver the adapted DPP over 12 months. The control group will continue providing usual care. The DPP will be culturally adapted using the Intervention Mapping-ADAPT (IM-ADAPT) approach. The implementation strategy will be designed using Implementation Mapping. Measures of effectiveness will be assessed at the participant level at baseline, 6 and 12 months during the intervention period, and 18 months after baseline. Implementation outcomes will be assessed at the PCC level at multiple time-points throughout the study period. Spillover will be assessed at PCC level at months -1, 6 and 18. An intention-to-treat analysis will assess effectiveness and spillover effect using generalized estimating equations. Implementation outcomes will be evaluated using a mixed-methods approach.

Discussion: The ALADIM study has the potential to address the gap between research and practice by employing implementation science for evaluation, adaptation and implementation of an evidence-based diabetes intervention. The findings will contribute to the development of a sustainable and scalable implementation strategy for T2D prevention, with potential implications for policy and practice at regional and national levels.

Trial registration: ClinicalTrials.gov, NCT06871059. Registered 10 March 2025, https://clinicaltrials.gov/study/NCT06871059.

Background: Occupational 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.

Methods: Fifty-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.

Results: The 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).

Conclusions: The 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 registration: ClinicalTrials.org dr.nr 2020-01214.