Opening the Black Box: A Causal Pathway Methodology for Precise Implementation Strategy Design

Opening the Black Box: A Causal Pathway Methodology for Precise Implementation Strategy Design | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Opening the Black Box: A Causal Pathway Methodology for Precise Implementation Strategy Design Sophie Pouzols, Jean-Louis Raisaro, Cédric Mabire This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7396236/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Despite the growing use of implementation frameworks, there is still limited understanding of how implementation strategies influence contextual determinants in order to produce desired outcomes. Closing this knowledge gap is essential for developing effective, theory-informed, and tailored implementation strategies. Methods This study presents a seven-step approach that links implementation determinants with adapted strategies using the Consolidated Framework for Implementation Research, the Implementation Outcomes Framework, the Behavior Change Techniques Taxonomy, and the Expert Recommendations for Implementing Change (ERIC). Causal pathway diagrams guided the process of articulating the hypothesized causal mechanisms. This methodology was applied during the pre-implementation phase of a study that aimed to integrate a computerized decision support system for preventing hospital-acquired pressure injuries in a Swiss university hospital. Results The process identified context-specific barriers and facilitators, prioritized determinants, and mapped them to implementation antecedents and mechanisms of action. Adapted and prioritized implementation strategies were co-designed with stakeholders. The result was a strategy bundle tailored to local context, validated through iterative stakeholder engagement. Conclusions This methodology provides a transparent, rigorous, and participatory approach to strategy development that can enhance implementation precision and contribute to theory building in implementation science. The integration of numerous frameworks and the incorporation of stakeholder input provides a replicable model for the design of context-sensitive implementation strategies. Causal Pathway diagram Implementation Determinants Implementation Frameworks Implementation Outcomes Implementation Strategies Mechanisms of Action Figures Figure 1 Figure 2 Figure 3 Contributions to the literature The methodology presented herein is characterized by its systematic approach, which integrates the CFIR, ERIC, BCTs, and IOF to formulate context-specific implementation strategies. This paper demonstrates the efficacy of causal pathway diagrams in mapping determinants to mechanisms of action and outcomes, thereby enhancing transparency and theoretical grounding. It provides a replicable and participatory process that supports co-design and stakeholder engagement in implementation planning. Background A critical step in successful implementation is a rigorous contextual analysis to identify implementation determinants - the factors that can either hinder or support the integration of new practices ( 1 , 2 ). Understanding these determinants allows researchers and practitioners to select, adapt, and tailor strategies to the specific needs of a given setting ( 3 – 5 ). Albright et al. emphasize the importance of the exploration and preparation phases of implementation, where contextual understanding is essential ( 2 ). Despite the progression from identifying determinants to selecting strategies, research detailing the development of these strategies and the explicit links between strategies and determinants, or implementation outcomes remains relatively limited ( 2 , 6 ). While numerous implementation strategies have been identified, a deeper understanding of how these strategies are developed and their causal pathways to outcomes is needed ( 6 – 9 ). Among the determinant frameworks, the Consolidated Framework for Implementation Research (CFIR) has become a widely used tool for characterizing contextual influences on implementation ( 2 , 10 , 11 ). The CFIR has been updated based on user feedback to improve its applicability ( 3 ). To address the CFIR determinants, the Expert Recommendations for Implementing Change (ERIC) compilation provides a structured list of implementation strategies ( 8 ). ERIC has also been the subject of refinement and adaptation efforts ( 4 , 8 , 12 – 16 ). In addition, implementation success is typically assessed using the Implementation Outcomes Framework (IOF), which defines key outcomes such as acceptability, adoption, feasibility, fidelity, dissemination, and sustainability ( 17 , 18 ). Damschroder et al. (2022) further elaborate on the conceptualization of outcomes for implementation research ( 19 ). In the CFIR Outcomes Addendum, Damschroder et al. included acceptability, appropriateness, feasibility, implementation climate and implementation readiness as “Antecedent Assessments”, measures to “predict” implementation outcomes ( 19 ). Despite the availability of these frameworks, there is limited understanding of the mechanisms through which implementation strategies influence determinants and lead to successful implementation ( 20 ). Investigating the mechanisms of action (MoAs) underlying the effectiveness of implementation strategies is an area that requires further attention. Understanding these mechanisms can improve the selection and adaptation of strategies. Beyond identifying and tailoring strategies, the field has increasingly emphasized understanding how and why implementation strategies produce change. In 2018, Lewis et al. explicitly called for the field to transition from classification to causality by articulating the mechanisms through which strategies operate and linking them to outcomes ( 20 ). This call was recently reaffirmed and reframed as a major research opportunity by Luke et al. (2024), who emphasized exploring the "bridges and mechanisms" connecting strategies to systems-level change, and by Geng et al. (2023), who emphasized developing adaptable, mechanism-focused approaches applicable across diverse contexts ( 21 , 22 ). The methodology presented in this paper directly addresses these calls by offering a structured process for specifying and linking determinants, mechanisms of action, and outcomes within a practical implementation setting. By applying a structured approach integrating CFIR, ERIC, BCT and IOF with Causal Pathway Diagram (CPD), this study seeks to provide a comprehensive and “blueprint” framework for understanding how implementation strategies operate through specific mechanisms to influence implementation determinants and outcomes. The use of CPDs is increasingly recognized as a valuable approach to explicitly articulate the hypothesized causal links between implementation strategies, their underlying mechanisms of action, and subsequent outcomes ( 7 , 20 , 23 , 24 ). These diagrams can also incorporate Behavior Change Techniques (BCTs) - the active ingredients within implementation strategies that are theorized to drive change. Resources such as the Behavior Change Technique Taxonomy (BCTTv1) and the Theory and Techniques Tool aim to facilitate the specification of BCTs ( 23 , 25 – 28 ). We validate the proposed methodology by applying it in the context of an implementation research project currently running in a Swiss University Hospital and aiming to implement a computerized decision support system (CDSS) for the early detection of hospital-acquired pressure injury (HAPI). This article specifically details the methodology employed during the pre-implementation phase and outlines the entire process within the context of this research project. Methods Sample and setting This example is drawn from a multi-method, cross-sectional study conducted between January 2024 and February 2025, in the traumatology unit of a Swiss University Hospital. An implementation team was established within the unit using a rational choice sampling approach. Aligned with the CFIR roles subdomain, the team comprises three mid-level leaders (Nurse Manager [NM]), one opinion leader (Clinical Nurse Specialist [CNS], two implementation facilitators (Nurse [RN] and Health and Community Care Assistant [HCCA]). All team members also served as deliverers of the innovation, the use of the CDSS (3). The implementation team members were consistently informed, consulted, and involved in decision-making throughout each phase and step of the study. These team members also served as the participants for the contextual analysis. Inclusion criteria for the healthcare professionals were being part of the unit's healthcare team. Exclusion criteria were being an interim RN. The healthcare professional’s population consisted of all healthcare team members within the unit. The patient population included inpatients 18 years and older hospitalized in the unit between January 1st, 2024, and December 31, 2024. Overview of the methodology The methodology is based on the CPD (7,20,23). CPDs are practical visual tools that enable researchers or practitioners to represent and evaluate their hypotheses on how implementation strategies work, by identifying causal links between determinants, mechanisms of action, and expected implementation outcomes (7,20,23). The methodology is structured in seven steps: 1) implementation determinants are identified; 2) the identified determinants are prioritized; 3) implementation antecedents are assessed; 4) the mechanisms of action of strategies to address antecedents are identified and understood; 5) implementation strategies adapted to the context are identified; 6) these strategies are prioritized; and 7) implementation strategies adapted to the context are developed (Figure 1). [Insert Figure 1 here] Figure 1. Overview of methodology guided by Causal Pathway Diagram (CPD) adapted from Klasnja et al. (23). Step 1: Determinants of the implementation Data collection Data collection was guided by the CFIR 2.0 constructs (3). Qualitative data were collected by the principal investigator (SP) and the research collaborator (ADB) through CFIR card game session with the implementation team (29). The card game consisted of 26 cards, each corresponding to one of the 26 CFIR constructs that had been translated into French and simplified. The process of simplification involved translating technical terminology into clear, direct language understandable to healthcare professionals, while ensuring the fundamental meaning of the construct was preserved, in accordance with the work of Pellet et al. (30). For each card, it had to be determined by the implementation team members whether it was: 1) a barrier or a facilitator; 2) modifiable or non-modifiable; 3) highly influential or not very influential, and a consensus had to be reached. During the session, the principal investigator was the facilitator, guiding discussions and ensuring all participants had the opportunity to contribute. Responses, comments, and observations were recorded on a CFIR card game recording sheet by the research collaborator (29). The session was audio-recorded to ensure accurate data capture. Data Analysis A rapid qualitative analysis, according to the methodology describe by Nevedal et al. in 2021, was conducted (31). The qualitative data collected during the CFIR card game session were analyzed during meeting with participants following the consensus process. The CFIR card game recording sheet served as a primary tool for this analysis. Audio recordings were used by the second research collaborator (ChM) to supplement the notes taken during the session, specifically to clarify ambiguities or expand upon essential points; however, full transcription was not conducted. This pragmatic approach was appropriate because the objective was not to conduct an in-depth thematic analysis, but rather to validate and prioritize the determinants using the participants' consensus. This approach balanced the need for detailed data with the practical constraints of time and resources. Audio recording was used to ensure the accuracy of the decisions. These findings were then reformulated and used by the principal investigator and research collaborators to prepare the next step. Step 2: Priority determinants of the implementation Data collection Consensus meeting with implementation team members were then conducted by using the Nominal Group Technique (NGT) (32–34). This method will allow the participants' involvement in the implementation process and achieve a consensus about the priority of each modifiable and highly influential determinant identified during the CFIR card game session. Each member of the implementation team rated the priority level of each determinant on a scale from zero to ten. Then, an average score was calculated and discussed within the team. The principal investigator (SP) and the research collaborators (ADB, ChM) were facilitator and observers during the session. The session was audio-recorded, and notes were taken. Data Analysis Quantitative data from the NGT sessions were analyzed during the session to calculate mean scores for each determinant, enabling prioritization. All determinants with a score higher than five were considered priorities. Qualitative data collected during the consensus meeting were analyzed collaboratively with participants. Like Step 1, audio recording was used to supplement session notes for clarification and detail, without full transcription. A rapid qualitative analysis was conducted (31). The rationale and limitations of this approach are consistent with those described in Step 1. The CPD determinant part was completed (Figure 1). Step 3 : Antecedents of implementation Data collection The Implementation antecedents are the acceptability, the appropriateness, the feasibility, the implementation climate, and the implementation readiness (19). To assess the antecedents of implantation, the qualitative data collected during the CFIR card game session (Step 1) and the consensus meeting (Step 2) were used. To provide more comprehensive contextual understanding, quantitative aggregated data were extracted from the hospital Datawarehouse and electronical health records (EHR). This extracted data included patients’ characteristics, staffs’ characteristics, and units’ characteristics. These data represent contextual factors related to the innovation, inner setting, and individuals’ domains of the CFIR 2.0 (3). Data Analysis A deductive qualitative analysis, informed by the CFIR 2.0 and the CFIR outcomes addendum (3,19) was conducted. The principal investigator and research collaborators performed a CFIR-directed content analysis with the notes and audio recordings. The principal investigator and the research collaborators coded the notes and recorded quotes. The CFIR 2.0 constructs and the antecedent of implementation according to the CFIR outcomes addendum were used for coding (19). The notes were categorized using the definitions of preconditions and moderators from the research of Klasnja et al. (23). A precondition is a necessary factor for a determinant to influence an implementation outcome. A moderator is a factor that modifies the strength of a determinant's influence (23). Data were categorized as preconditions if the response to the question, "Does the absence of this element block the determinant from influencing the antecedent?" was affirmative. In other words, without this element, the determinant cannot act as a lever to promote the antecedent of implementation and, thus, the implementation outcome. Data were considered moderators if the answer to the question, "Does this element modify the strength of the determinant's influence on the antecedent?" was affirmative. Then, the quantitative data were integrated to support this analysis. The results will be compared and discussed between the researchers (ADB, ChM, CM, SP) during meetings. The findings were then presented to the implementation team for triangulation and validation. Following validation, the CPD was completed (Figure 1) integrating both qualitative and descriptive quantitative data. Step 4: Mechanisms of Actions Data Collection The data collected for this step were the findings of previous steps validated by the implementation team. Data Analysis First, an inductive qualitative analysis was conducted based on the results of previous steps. The objective was to identify mechanisms for addressing the priority determinants. One or more mechanisms formulated for the context of the study were identified for each priority barrier or facilitator. The mechanism part of the CPD was completed (Figure 1). Next, a deductive qualitative analysis informed by BCT theory was conducted (28,35). For each mechanism identified, the principal investigator then made the link with the 26 MoAs in the BCT Theory and Techniques Tool (36). The results were then discussed and triangulated among the researchers (ADB, ChM, CM, SP). To facilitate understanding of the mechanisms, they were simplified, reformulated, and then presented to the implementation team for validation. Step 5: Implementation strategies selection Data Collection The data collected for this step were the findings of step 4, validated by the implementation team. Data Analysis Implementation strategies were identified based on the priority determinants and mechanisms identified in the previous steps. The Theory and Techniques Tool was used to identify the BCTs associated with each MoA (25). The BCTs were then translated into implementation strategies from the ERIC compilation of implementation strategies based on the work of McHugh et al. (12). Each BCT identified above was associated with one or more strategies. A simplification process was then carried out using the strategy definitions to identify those that were already in place, those that related to the research team only, and those that related to the implementation team and the unit team. This resulted in a list of implementation strategies adapted to the unit. Step 6: Implementation strategies Prioritization Data collection The list of adapted implementation strategies was reformulated for the context and presented to the implementation team. Consensus meeting with implementation team members was then conducted by using the NGT (32–34). The principal investigator (SP) and the research collaborators (ADB, ChM) were facilitators and observers during the session. The session was audio-recorded, and notes were taken. The findings of this meeting prioritized the implementation strategies. Data Analysis Quantitative data from the prioritization session were analyzed during the meetings, with mean scores calculated for each strategy to determine priority. Qualitative data from the consensus meeting were analyzed collaboratively with participants. As in previous steps, audio recordings were used to supplement session notes, focusing on clarification and key details, without full transcription. The rationale and limitations of this approach remain consistent with those previously described. The implementation strategy and precondition parts of the CPD was then completed (Figure 1). Step 7: Implementation Strategies Development Data Collection For this step, the collected data were the findings of step 6, and the notes and audio-recordings of steps 1, 2, and 6. Data Analysis Based on the priority strategies previously identified by the implementation team, strategy bundles were developed. Each priority strategy (those with a score > 5) was defined and specified according to Proctor et al.'s 2013 recommendations (37) and tailored to the specific context of the traumatology unit. The strategies were then rated using the APEASE criteria (38) to assess their acceptability, practicability, effectiveness, affordability, safety, and equity. These strategy packages were then presented to the implementation teams for validation. An implementation protocol was established and actively monitored during the implementation phase, allowing for ongoing adaptation and refinement of the strategies as needed. Ethical considerations This research involved anonymously collected or anonymized health-related data. The Federal Act on Research involving Human Beings (Human Research Act, HRA) did not apply to this research (Art. 2, Section 1, Chapter 1, HRA). This study was approved as an improvement project by the hospital's legal department and the internal research evaluation board (CEDE: Commission d’Évaluation des Demandes d’Enquêtes, registration number: 89.2023). Results To view the methodological process and promote understanding, a synthesis of results is reported in Figure 2. For clarity, only part of the results is presented for each step. [Insert Figure 2 here] Figure 2. Synthesis of results. Step 1: Determinants of the implementation During the CFIR card game session, among the 26 CFIR constructs assessed, the implementation team identified the construct Motivation from the domain of individuals like a barrier which was modifiable and with strong influence. The explication of the construct on the card was “The individuals involved in the implementation of [name of the innovation] are committed to fulfilling their roles”. The implementation team members explained their choice by pointing toward the fact that motivation among healthcare team members depended on their awareness and involvement in HAPI prevention (Figure 3). Step 2: Priority determinants of the implementation After consensus meeting using NGT, the CFIR construct Motivation was a priority with a mean score at 9.8 (Figure 3). The implementation team members explained the prioritization, saying that many healthcare team members wouldn't be motivated because they wouldn't see the need for this innovation. They believed motivation would depend on how the HAPI's issue and prevention were perceived. They said it would be necessary to support individuals by considering each person's level of awareness. Step 3 : Antecedents of implementation The implementation readiness refers to “the extent to which the internal environment is ready for implementation" (19). For the implementation team, the implementation readiness was unfavorable. “For the moment, lack of information for the team, the team is not ready.” The motivation was linked to the unreadiness. The implementation team emphasized prior awareness of the issue and prevention of HAPIs as necessary factors for motivation to promote implementation readiness (precondition). During the study period, the HAPI rate was 1.0%, and the Braden score was used to assess risk at least once by 81.43% of patients during hospitalization. Of these patients, 67.67% were at HAPI risk. Approximately 65% of patients at risk had benefited from at least one preventive measure during their hospitalization. According to the implementation team, the link between motivation and implementation readiness would be strengthened if healthcare team members received support tailored to their skill levels. The skill mix during this period was 75%, with the healthcare team consisting of three-quarters nurses and one-quarter nursing assistants and health and community care assistants (Figure 3). Step 4: Mechanisms of Actions Based on the findings of the step 3, three mechanisms for addressing the motivation determinant were identified. For this example, only one mechanism will be detailed (Figure 3). In step 3, a precondition for motivation to promote readiness was awareness of the issue and prevention of HAPIs. One of the underlying mechanisms to achieve this would be to make visible existing knowledge, abilities, and skills regarding the issue of HAPIs and their prevention. Data extraction revealed that approximately 18% of patients did not undergo risk assessment using the Braden scale, and approximately one-third of patients at risk did not receive preventive measures. Using the innovation would enable us to assess risk for all patients and take appropriate preventive measures. In line with BCT theory (28,36), this mechanism could enable users to become aware of the issue of HAPI and of the innovation (BCT MoA: Knowledge), believe in their ability to prevent HAPI and use the innovation (BCT MoA: Beliefs about Capabilities), and their consequences (BCT MoA: Beliefs about Consequences), and emphasize the skills and competencies acquired through practice (BCT MoA: Skills). Step 5: Implementation strategies selection After validation of the mechanism by the implementation team, the four MoAs linked were associated to 20 BCTs according to the BCT Theory and Techniques Tool (36). Then, based on the work of McHugh et al. 2022 (12), 17 potential ERIC strategies were identified to activate the mechanism. Among the 17 strategies, six were related to the research team and already in place, and one was not applicable. Finally, 11 strategies related to this mechanism were presented to the implementation team. To simplify the process description, only one BCT and one associated strategy will be presented in this example. The BCT “8.1 Behavioural rehearsal” was linked with two BCT MoAs: Skills and Beliefs about Capabilities (36). According to Mc Hugh et al., this BCT is probably indicated in ERIC strategy: “Model and simulate change” (12). This strategy was presented to the implementation team for prioritization. Step 6: Implementation strategies Prioritization After consensus meeting using NGT, the ERIC strategy “Model and simulate change” was a priority with a mean score at 10. According to the implementation team, this strategy would trigger the mechanism if it did not take the form of a video or simulation workshop. Rather, it should take the form of educational or informative material in a simple format, such as a pocket card or poster displayed at the desk, as well as demonstrations at existing meeting points (Figure 3). [Insert Figure 3 here] Figure 3. Synthesis results of methodological process guided by CPD adapted from Klasnja et al. (23). Step 7: Implementation Strategies Development Each priority strategy previously identified by the implementation team, was defined and specified according to Proctor et al.'s 2013 recommendations (37) and to the context (Table 1). According to the APEASE criteria (38), the strategy score was 29 out of a possible score of 30. This strategy was included in a bundle of five strategies integrated in the daily huddles. [Insert Table1 here] Table 1. Definition and specification of the strategy “Model and simulate change” Model and simulate change Definition Model or simulate the change that will be implemented prior to implementation Actor(s) Research Team – Implementation Team Action(s) • Allow the implementation team and the healthcare team to test the application several times outside of the daily care process + see educational/informative materials • Encourage or advise to imagine and compare the future results of risk assessment and prevention implementation with the innovation vs current practices Target Implementation Team – Healthcare Team Temporality • Before the deployment of the innovation in the unit • During the deployment of the innovation in the unit • During existing huddle • During meetings between research team and implementation team Dose As much as needed Implementation outcomes affected Implementation readiness Justification To make visible existing knowledge, abilities, and skills regarding the issue of hospital acquired pressure injuries and their prevention Discussion This methodology could address various challenges in the field of implementation science. It responds to the need to establish more explicit links between implementation determinants, strategies and outcomes. It also aims to improve our understanding of the mechanisms by which implementation strategies produce change, going beyond simply identifying effective strategies. Furthermore, its multi-framework and multi-theory approach enables a more comprehensive and nuanced understanding of the implementation process. Additionally, it draws on innovative and effective methods of data collection and analysis, each of which adds significant value. In summary, this study contributes to a more rigorous and theoretically grounded approach to the implementation of evidence-based practices. Previous studies have highlighted an insufficient understanding of the causal relationships between implementation strategies, determinants, and outcomes ( 6 , 21 , 22 , 24 , 39 , 40 ). This methodology uses CPDs to map determinants, mechanisms, and expected outcomes. This approach enhances transparency, enables hypothesis validation, and identifies key measurement points ( 7 , 20 , 23 , 41 ). As emphasized by Klasnja et al., CPDs help professionals grasp causality by examining the processes through which strategies operate, optimizing the match between strategies and barriers, and identifying conditions for successful implementation ( 23 ). This approach operationalizes the shift from "classification to causality" advocated by Lewis et al. and provides a practical means to identify and test the "bridges and mechanisms" described by Luke et al. and the adaptive, mechanism-oriented strategies promoted by Geng et al. ( 20 – 22 ). Integrating multiple frameworks with CPDs ensures both theoretical rigor and practical applicability. Following Proctor et al.’s recommendations for detailed strategy specification improves reproducibility and comparability ( 37 ). The methodology, grounded in BCT theory, identifies MoAs as the active components that drive change ( 28 , 36 ). Links between BCTs and MoAs, provide a foundation for testable causal models that can be refined over time. Due to the lack of empirical studies that establish causal links between strategies, mechanisms, and outcomes, this methodology provides a structured, theory-informed, and empirically testable approach to advancing research and guiding the adaptation of implementation strategies in different contexts. This methodology is based on the synergistic integration of proven-effective frameworks, theories, and taxonomies in implementation science. This multi-framework approach is a significant asset because it provides a more comprehensive and nuanced understanding of the implementation process. As Nilsen and Moullin et al. have noted, employing theoretical frameworks to direct study design, stimulate theoretical and empirical reasoning, and streamline result interpretation is paramount. These frameworks facilitate the development of a shared language and provide practical tools for planning, executing, and evaluating implementation efforts ( 42 , 43 ). The present methodology addresses the tendency among implementation science researchers to specialize in a single research approach. The present methodology integrates CFIR, ERIC, BCT, and IOF to promote an interdisciplinary approach. This approach enhances the integration and comparison of methodologies, thereby reinforcing the discipline ( 42 , 43 ). Integrating these frameworks and theories helps define the objective of the implementation effort and prioritize the determinants to be targeted. This is of paramount importance when considering funding and resource limitations ( 42 , 43 ). This methodology incorporates innovative and efficient data collection and analysis methods that add substantial value. The CFIR card game is an interactive, qualitative tool that facilitates the identification of determinants. Translated and simplified CFIR constructs make it accessible to healthcare professionals without specialist implementation knowledge ( 30 ). When used alongside the NGT, a structured consensus method that minimizes dominance effects and ensures equal participation, this approach enables the prioritization of determinants and strategies based on feasibility and perceived importance ( 33 – 35 ). Following Nevedal et al.’s methodology, rapid qualitative analysis used notes and audio recordings rather than full transcripts, reducing time and cost while maintaining rigor ( 31 ). Despite requiring expertise in qualitative methods and CFIR, this near real-time analysis was essential for timely decision-making during implementation. Combining multiple methods yielded rich, diverse data, and triangulation enhanced the validity of the results. This methodology is characterized by its complex, structured design that integrates multiple stages and theoretical frameworks from implementation science. This approach generates generalizable knowledge and robust theories. While this level of rigor provides valuable insights, it requires significant resources, including time, skilled facilitation, and sustained stakeholder engagement, and may be difficult to maintain in pragmatic or resource-limited contexts. However, the process can be adapted without losing its core logic. For example, one can focus on the most relevant CFIR constructs, streamline data collection through shorter or asynchronous formats, leverage existing data, or condense CPD mapping into a single session. A CNS can play a pivotal role in these adaptations by coordinating the identification of priority determinants, facilitating consensus, and integrating simplified CPD mapping into existing governance or quality improvement meetings. This approach maintains methodological fidelity while alleviating the burden on external teams. This balance between rigor and feasibility enables the development of context-tailored strategies, demonstrating how structured adaptation can render the "art" of implementation more systematic and less dependent on intuition. Stakeholder involvement is critical to the success of implementation projects, and this methodology emphasizes active engagement throughout the process. Using the CFIR card game ( 29 ) and consensus meetings via the NGT ( 33 , 34 ) ensured that field perspectives informed the development of strategies at every stage, thereby reinforcing their relevance and acceptability. Stakeholders provided valuable insights into workflows, infrastructure, culture, resources, and challenges. This enabled the co-design of contextually appropriate solutions, as advocated by Kirk et al. ( 13 ). Although this approach relies on research expertise, it also incorporates practical experience to ensure strategies are theoretically sound and operationally feasible. Intensive engagement demands substantial time and resources but enhances credibility, fosters ownership, and improves implementation outcomes. The facilitator plays a pivotal role in sustaining this engagement. In our case, the principal investigator’s pre-existing relationship with the team strengthened trust, but it also posed a risk of social desirability bias. This risk was mitigated through iterative consensus-building, triangulation, and validation. Conclusion While the complexity and specific context of this case study require cautious interpretation of the findings in terms of generalizability, the proposed methodology provides a structured and participatory framework for developing contextually appropriate implementation strategies, with an emphasis on understanding mechanisms of change and stakeholder engagement. This approach could be useful in advancing the science of implementation by providing a detailed model for linking theory to practice. Abbreviations BCT: Behavior Change Technique BCTTv1: Behavior Change Technique Taxonomy CDSS: Computerized Decision Support System CFIR: Consolidated Framework for Implementation Research CNS: Clinical Nurse Specialist CPD: Causal Pathway Diagram EHR: Electronic Health Record ERIC: Expert Recommendations for Implementing Change HAPI: Hospital-Acquired Pressure Injury HCCA: Health and Community Care Assistant IOF: Implementation Outcomes Framework MoA: Mechanism of Action NGT: Nominal Group Technique NM: Nurse Manager RN: Registered Nurse Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding No funding was obtained for this work. Authors' contributions Conceptualization: SP, JLR, and CM. Methodology: SP and CM. Data collection: SP. Project administration & data curation: SP and CM. Formal analysis: SP. Validation: JLR and CM. Writing – Original Draft: SP. Writing – Review & editing: JLR and CM. All authors read and approved the final manuscript. Acknowledgements The authors thank the Marter students Ana De Brito (ADB) and Charlotte Mittaz (ChM) who contributed to the collection and analysis of data. References Nilsen P, Bernhardsson S. Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes. BMC Health Services Research. 2019;19(1):189. DOI: 10.1186/s12913-019-4015-3 Albright K, Navarro EI, Jarad I, Boyd MR, Powell BJ, Lewis CC. Communication strategies to facilitate the implementation of new clinical practices: a qualitative study of community mental health therapists. Translational Behavioral Medicine. 2022;12(2):324–34. 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BMJ Open. 2021;11(10):e053474. DOI: 10.1136/bmjopen-2021-053474 Lewis CC, Klasnja P, Lyon AR, Powell BJ, Lengnick-Hall R, Buchanan G, et al. The mechanics of implementation strategies and measures: advancing the study of implementation mechanisms. Implementation Science Communications. 2022;3(1):114. DOI: 10.1186/s43058-022-00358-3 Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implementation Science. 2015;10(1):21. DOI: 10.1186/s13012-015-0209-1 McHugh SM, Riordan F, Kerins C, Curran G, Lewis CC, Presseau J, et al. Understanding tailoring to support the implementation of evidence-based interventions in healthcare: The CUSTOMISE research programme protocol . HRB Open Research; 2023. Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science. 2009;4(1):50. DOI: 10.1186/1748-5908-4-50 Damschroder LJ. Clarity out of chaos: Use of theory in implementation research. Psychiatry Research. 2020;283:112461. DOI: 10.1016/j.psychres.2019.06.036 McHugh S, Presseau J, Luecking CT, Powell BJ. Examining the complementarity between the ERIC compilation of implementation strategies and the behaviour change technique taxonomy: a qualitative analysis. Implementation Science. 2022;17(1):56. DOI: 10.1186/s13012-022-01227-2 Kirk JW, Nilsen P, Andersen O, Powell BJ, Tjørnhøj-Thomsen T, Bandholm T, et al. Co-designing implementation strategies for the WALK-Cph intervention in Denmark aimed at increasing mobility in acutely hospitalized older patients: a qualitative analysis of selected strategies and their justifications. BMC Health Services Research. 2022;22(1):8. DOI: 10.1186/s12913-021-07395-z Waltz TJ, Powell BJ, Matthieu MM, Smith JL, Damschroder LJ, Chinman MJ, et al. Consensus on strategies for implementing high priority mental health care practices within the US Department of Veterans Affairs. Implementation Research and Practice. SAGE Publications; 2021;2:26334895211004607. DOI: 10.1177/26334895211004607 Waltz TJ, Powell BJ, Fernández ME, Abadie B, Damschroder LJ. Choosing implementation strategies to address contextual barriers: diversity in recommendations and future directions. Implementation Science. 2019;14(1):42. DOI: 10.1186/s13012-019-0892-4 Yakovchenko V, Chinman MJ, Lamorte C, Powell BJ, Waltz TJ, Merante M, et al. Refining Expert Recommendations for Implementing Change (ERIC) strategy surveys using cognitive interviews with frontline providers. Implementation Science Communications. 2023;4(1):42. DOI: 10.1186/s43058-023-00409-3 Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for Implementation Research: Conceptual Distinctions, Measurement Challenges, and Research Agenda. Administration and Policy in Mental Health. 2011;38(2):65–76. DOI: 10.1007/s10488-010-0319-7 Proctor EK, Bunger AC, Lengnick-Hall R, Gerke DR, Martin JK, Phillips RJ, et al. Ten years of implementation outcomes research: a scoping review. Implementation Science. 2023;18(1):31. DOI: 10.1186/s13012-023-01286-z Damschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. Implementation Sci. BioMed Central; 2022;17(1):1–10. DOI: 10.1186/s13012-021-01181-5 Lewis CC, Klasnja P, Powell BJ, Lyon AR, Tuzzio L, Jones S, et al. From Classification to Causality: Advancing Understanding of Mechanisms of Change in Implementation Science. Front Public Health. Frontiers; 2018;6. DOI: 10.3389/fpubh.2018.00136 Luke DA, Powell BJ, Paniagua-Avila A. Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research. Annual Review of Public Health. Annual Reviews; 2024;45(Volume 45, 2024):7–25. DOI: 10.1146/annurev-publhealth-060922-040205 Geng EH, Mody A, Powell BJ. On-the-Go Adaptation of Implementation Approaches and Strategies in Health: Emerging Perspectives and Research Opportunities. Annual Review of Public Health. Annual Reviews; 2023;44(Volume 44, 2023):21–36. DOI: 10.1146/annurev-publhealth-051920-124515 Klasnja P, Meza RD, Pullmann MD, Mettert KD, Hawkes R, Palazzo L, et al. Getting cozy with causality: Advances to the causal pathway diagramming method to enhance implementation precision. Implement Res Pract. 2024;5:26334895241248851. DOI: 10.1177/26334895241248851 Lewis CC, Boyd MR, Walsh-Bailey C, Lyon AR, Beidas R, Mittman B, et al. A systematic review of empirical studies examining mechanisms of implementation in health. Implementation Sci. 2020;15(1):21. DOI: 10.1186/s13012-020-00983-3 Michie S, Atkins L, West R. The behaviour change wheel: a guide to designing interventions. Sutton: Silverback; 2014. Michie S, Carey RN, Johnston M, Rothman AJ, Bruin M de, Kelly MP, et al. From Theory-Inspired to Theory-Based Interventions: A Protocol for Developing and Testing a Methodology for Linking Behaviour Change Techniques to Theoretical Mechanisms of Action. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine. 2017;52(6):501. DOI: 10.1007/s12160-016-9816-6 Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions. Annals of Behavioral Medicine. 2013;46(1):81–95. DOI: 10.1007/s12160-013-9486-6 Carey RN, Connell LE, Johnston M, Rothman AJ, de Bruin M, Kelly MP, et al. Behavior Change Techniques and Their Mechanisms of Action: A Synthesis of Links Described in Published Intervention Literature. Annals of Behavioral Medicine. 2019;53(8):693–707. DOI: 10.1093/abm/kay078 Piat M, Wainwright M, Sofouli E, Albert H, Casey R, Rivest M-P, et al. The CFIR Card Game: a new approach for working with implementation teams to identify challenges and strategies. Implement Sci Commun. 2021;2(1):1. DOI: 10.1186/s43058-020-00099-1 Pellet J, Pouzols S, Ridde V, Mabire C. Bridging the gap: translating and simplifying CFIR 2.0 for French practitioners in implementation science. Implementation Science Communications. 2025;6(1):29. DOI: 10.1186/s43058-025-00719-8 Nevedal AL, Reardon CM, Opra Widerquist MA, Jackson GL, Cutrona SL, White BS, et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci. 2021;16(1):67. DOI: 10.1186/s13012-021-01111-5 Allen J, Dyas J, Jones M. Building consensus in health care: a guide to using the nominal group technique. Br J Community Nurs. 2004;9(3):110–4. DOI: 10.12968/bjcn.2004.9.3.12432 Cooper S, Cant R, Luders E, Waters D, Henderson A, Hood K, et al. The Nominal Group Technique: generating consensus in nursing research. J Nurs Educ. 2020;59(2):65–7. DOI: 10.3928/01484834-20200122-02 Dunham RB. Nominal group technique: a user’s guide. University of Wisconsin; 2006. Connell LE, Carey RN, de Bruin M, Rothman AJ, Johnston M, Kelly MP, et al. Links Between Behavior Change Techniques and Mechanisms of Action: An Expert Consensus Study. Annals of Behavioral Medicine. 2019;53(8):708–20. DOI: 10.1093/abm/kay082 [Internet]. The Theory and Techniques Tool | Theory and Techniques Tool [cited 2025 Jul 4]. Available from: https://theoryandtechniquetool.humanbehaviourchange.org/tool Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implementation Science. 2013;8(1):139. DOI: 10.1186/1748-5908-8-139 West R, Michie S. Unlocking Behaviour Change [Internet]. 2019. UBC Briefing 7: Evaluating behaviour change interventions using APEASE [cited 2024 Apr 22]. Available from: https://www.unlockingbehaviourchange.com/pdfs/5c766be7b6281890464249.pdf Vejnoska SF, Mettert K, Lewis CC. Mechanisms of implementation: An appraisal of causal pathways presented at the 5th biennial Society for Implementation Research Collaboration (SIRC) conference. Implementation Research and Practice. 2022;3:263348952210862. DOI: 10.1177/26334895221086271 Mody A, Filiatreau LM, Goss CW, Powell BJ, Geng EH. Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation strategies and evidence-based interventions. Implement Sci Commun. 2023;4(1):157. DOI: 10.1186/s43058-023-00536-x Lewis CC, Scott K, Marriott BR. A methodology for generating a tailored implementation blueprint: an exemplar from a youth residential setting. Implementation Science. 2018;13(1):68. DOI: 10.1186/s13012-018-0761-6 Nilsen P. Making sense of implementation theories, models and frameworks. Implementation Science. 2015;10(1):53. DOI: 10.1186/s13012-015-0242-0 Moullin JC, Dickson KS, Stadnick NA, Albers B, Nilsen P, Broder-Fingert S, et al. Ten recommendations for using implementation frameworks in research and practice. Implementation Science Communications. 2020;1:42. DOI: 10.1186/s43058-020-00023-7 Supplementary Files SupplementaryMaterialAdaptedStaRiChecklist.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7396236","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":510219606,"identity":"948c34fb-97ab-42a6-9757-1f5abd3a9da5","order_by":0,"name":"Sophie Pouzols","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIie3SvQrCMBDA8StCXQTX69RXiIsu4rNcKNSluLg4ONSlLnbvYzjqVhF0KboWXCKCs6NCERPwAxFTR4f8hxACP7iEAJhM/5kN9NgKaANTGyv8lRD4P5JnBMty4o7jlRAD6NWxuxdUbN0WBgwus++EZZsuowz6TkIe49GuMU8CZsWZhmDQRB4Bn+a0Qh7uiOU+VaxIM1iiyFURHiEVm3ICuSKhIp6NZKeSeKmWyLv4KEfqO5NjRd7Fa0yzQ7qIdYPJF3POw3avXpUvdio6LlvzkbjoBoOaWpDezlIduJPXBzCZTCbTRzchi1SXIYn7ZQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-2750-3519","institution":"University of Lausanne Faculty of Biology and Medicine: Universite de Lausanne Faculte de biologie et medecine","correspondingAuthor":true,"prefix":"","firstName":"Sophie","middleName":"","lastName":"Pouzols","suffix":""},{"id":510219607,"identity":"8c726d25-26a2-4359-86fd-4b1fb7cb5810","order_by":1,"name":"Jean-Louis Raisaro","email":"","orcid":"","institution":"Lausanne University Hospital: Centre Hospitalier Universitaire 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1","display":"","copyAsset":false,"role":"figure","size":246002,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of methodology guided by Causal Pathway Diagram (CPD) adapted from Klasnja et al. 2024\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7396236/v1/e9b45f105a27bc2fb0cd3f0f.png"},{"id":91048572,"identity":"ac1ef0fc-f4d9-4106-bc1b-b9cc6e991c4c","added_by":"auto","created_at":"2025-09-11 06:20:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":154023,"visible":true,"origin":"","legend":"\u003cp\u003eSynthesis of results\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7396236/v1/c4cbe69b92f751600df54731.png"},{"id":91048364,"identity":"989146fc-edf6-4cbf-a6be-ab8623b60ddb","added_by":"auto","created_at":"2025-09-11 06:12:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":330076,"visible":true,"origin":"","legend":"\u003cp\u003eSynthesis results of methodological process guided by Causal Pathway Diagram (CPD) adapted from Klasnja et al. 2024\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7396236/v1/e7786d575c35ee00ff98c820.png"},{"id":105752009,"identity":"a27c6c3a-1be6-48c2-9673-c52d21dd4642","added_by":"auto","created_at":"2026-03-30 15:53:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1501373,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7396236/v1/2d7bcfd9-8cbb-4734-93dc-df36fee18cd4.pdf"},{"id":91048574,"identity":"bca7daba-e1e1-4ccd-8e69-7305aac56261","added_by":"auto","created_at":"2025-09-11 06:20:01","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":212611,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialAdaptedStaRiChecklist.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7396236/v1/fef045a2c3181a37370d7a31.pdf"}],"financialInterests":"","formattedTitle":"Opening the Black Box: A Causal Pathway Methodology for Precise Implementation Strategy Design","fulltext":[{"header":"Contributions to the literature","content":"\u003cul\u003e\n \u003cli\u003eThe methodology presented herein is characterized by its systematic approach, which integrates the CFIR, ERIC, BCTs, and IOF to formulate context-specific implementation strategies.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThis paper demonstrates the efficacy of causal pathway diagrams in mapping determinants to mechanisms of action and outcomes, thereby enhancing transparency and theoretical grounding.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIt provides a replicable and participatory process that supports co-design and stakeholder engagement in implementation planning.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eA critical step in successful implementation is a rigorous contextual analysis to identify implementation determinants - the factors that can either hinder or support the integration of new practices (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Understanding these determinants allows researchers and practitioners to select, adapt, and tailor strategies to the specific needs of a given setting (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Albright et al. emphasize the importance of the exploration and preparation phases of implementation, where contextual understanding is essential (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the progression from identifying determinants to selecting strategies, research detailing the development of these strategies and the explicit links between strategies and determinants, or implementation outcomes remains relatively limited (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). While numerous implementation strategies have been identified, a deeper understanding of how these strategies are developed and their causal pathways to outcomes is needed (\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAmong the determinant frameworks, the Consolidated Framework for Implementation Research (CFIR) has become a widely used tool for characterizing contextual influences on implementation (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The CFIR has been updated based on user feedback to improve its applicability (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). To address the CFIR determinants, the Expert Recommendations for Implementing Change (ERIC) compilation provides a structured list of implementation strategies (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). ERIC has also been the subject of refinement and adaptation efforts (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). In addition, implementation success is typically assessed using the Implementation Outcomes Framework (IOF), which defines key outcomes such as acceptability, adoption, feasibility, fidelity, dissemination, and sustainability (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Damschroder et al. (2022) further elaborate on the conceptualization of outcomes for implementation research (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). In the CFIR Outcomes Addendum, Damschroder et al. included acceptability, appropriateness, feasibility, implementation climate and implementation readiness as \u0026ldquo;Antecedent Assessments\u0026rdquo;, measures to \u0026ldquo;predict\u0026rdquo; implementation outcomes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the availability of these frameworks, there is limited understanding of the mechanisms through which implementation strategies influence determinants and lead to successful implementation (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Investigating the mechanisms of action (MoAs) underlying the effectiveness of implementation strategies is an area that requires further attention. Understanding these mechanisms can improve the selection and adaptation of strategies.\u003c/p\u003e\u003cp\u003eBeyond identifying and tailoring strategies, the field has increasingly emphasized understanding how and why implementation strategies produce change. In 2018, Lewis et al. explicitly called for the field to transition from classification to causality by articulating the mechanisms through which strategies operate and linking them to outcomes (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This call was recently reaffirmed and reframed as a major research opportunity by Luke et al. (2024), who emphasized exploring the \"bridges and mechanisms\" connecting strategies to systems-level change, and by Geng et al. (2023), who emphasized developing adaptable, mechanism-focused approaches applicable across diverse contexts (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The methodology presented in this paper directly addresses these calls by offering a structured process for specifying and linking determinants, mechanisms of action, and outcomes within a practical implementation setting.\u003c/p\u003e\u003cp\u003eBy applying a structured approach integrating CFIR, ERIC, BCT and IOF with Causal Pathway Diagram (CPD), this study seeks to provide a comprehensive and \u0026ldquo;blueprint\u0026rdquo; framework for understanding how implementation strategies operate through specific mechanisms to influence implementation determinants and outcomes. The use of CPDs is increasingly recognized as a valuable approach to explicitly articulate the hypothesized causal links between implementation strategies, their underlying mechanisms of action, and subsequent outcomes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). These diagrams can also incorporate Behavior Change Techniques (BCTs) - the active ingredients within implementation strategies that are theorized to drive change. Resources such as the Behavior Change Technique Taxonomy (BCTTv1) and the Theory and Techniques Tool aim to facilitate the specification of BCTs (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe validate the proposed methodology by applying it in the context of an implementation research project currently running in a Swiss University Hospital and aiming to implement a computerized decision support system (CDSS) for the early detection of hospital-acquired pressure injury (HAPI). This article specifically details the methodology employed during the pre-implementation phase and outlines the entire process within the context of this research project.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eSample and setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis example is drawn from a multi-method, cross-sectional study conducted between January 2024 and February 2025, in the traumatology unit of a Swiss University Hospital. An implementation team was established within the unit using a rational choice sampling approach. Aligned with the CFIR roles subdomain, the team comprises \u0026nbsp;three mid-level leaders (Nurse Manager [NM]), one opinion leader (Clinical Nurse Specialist [CNS], two implementation facilitators (Nurse [RN] and Health and Community Care Assistant [HCCA]). All team members also served as deliverers of the innovation, the use of the CDSS (3). The implementation team members were consistently informed, consulted, and involved in decision-making throughout each phase and step of the study. These team members also served as the participants for the contextual analysis. Inclusion criteria for the healthcare professionals were being part of the unit\u0026apos;s healthcare team. Exclusion criteria were being an interim RN. The healthcare professional\u0026rsquo;s population consisted of all healthcare team members within the unit. The patient population included inpatients 18 years and older hospitalized in the unit between January 1st, 2024, and December 31, 2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverview of the methodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe methodology is based on the CPD (7,20,23). CPDs are practical visual tools that enable researchers or practitioners to represent and evaluate their hypotheses on how implementation strategies work, by identifying causal links between determinants, mechanisms of action, and expected implementation outcomes (7,20,23).\u003c/p\u003e\n\u003cp\u003eThe methodology is structured in seven steps: 1) implementation determinants are identified; 2) the identified determinants are prioritized; 3) implementation antecedents are assessed; 4) the mechanisms of action of strategies to address antecedents are identified and understood; 5) implementation strategies adapted to the context are identified; 6) these strategies are prioritized; and 7) implementation strategies adapted to the context are developed (Figure 1).\u003c/p\u003e\n\u003cp\u003e[Insert Figure 1 here] Figure 1. Overview of methodology guided by Causal Pathway Diagram (CPD) adapted from Klasnja et al. (23).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 1: Determinants of the implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection was guided by the CFIR 2.0 constructs (3). Qualitative data were collected by the principal investigator (SP) and the research collaborator (ADB) through CFIR card game session with the implementation team (29). The card game consisted of 26 cards, each corresponding to one of the 26 CFIR constructs that had been translated into French and simplified. The process of simplification involved translating technical terminology into clear, direct language understandable to healthcare professionals, while ensuring the fundamental meaning of the construct was preserved, in accordance with the work of Pellet et al. (30). \u0026nbsp;For each card, it had to be determined by the implementation team members whether it was: 1) a barrier or a facilitator; 2) modifiable or non-modifiable; 3) highly influential or not very influential, and a consensus had to be reached. During the session, the principal investigator was the facilitator, guiding discussions and ensuring all participants had the opportunity to contribute. Responses, comments, and observations were recorded on a CFIR card game recording sheet by the research collaborator (29). The session was audio-recorded to ensure accurate data capture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA rapid qualitative analysis, according to the methodology describe by Nevedal et al. in 2021, was conducted (31). The qualitative data collected during the CFIR card game session were analyzed during meeting with participants following the consensus process. The CFIR card game recording sheet served as a primary tool for this analysis. Audio recordings were used by the second research collaborator (ChM) to \u0026nbsp;supplement the notes taken during the session, specifically to clarify ambiguities or expand upon essential points; however, full transcription was not conducted. This pragmatic approach was appropriate because the objective was not to conduct an in-depth thematic analysis, but rather to validate and prioritize the determinants using the participants\u0026apos; consensus. \u0026nbsp;This approach balanced the need for detailed data with the practical constraints of time and resources. Audio recording was used to ensure the accuracy of the decisions. These findings were then reformulated and used by the principal investigator and research collaborators to prepare the next step.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 2: \u0026nbsp;Priority determinants of the implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsensus meeting with implementation team members were then conducted by using the Nominal Group Technique (NGT) (32\u0026ndash;34). This method will allow the participants\u0026apos; involvement in the implementation process and achieve a consensus about the priority of each modifiable and highly influential determinant identified during the CFIR card game session. Each member of the implementation team rated the priority level of each determinant on a scale from zero to ten. Then, an average score was calculated and discussed within the team. The principal investigator (SP) and the research collaborators (ADB, ChM) were facilitator and observers during the session. The session was audio-recorded, and notes were taken.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative data from the NGT sessions were analyzed during the session to calculate mean scores for each determinant, enabling prioritization. All determinants with a score higher than five were considered priorities. Qualitative data collected during the consensus meeting were analyzed collaboratively with participants. Like Step 1, audio recording was used to supplement session notes for clarification and detail, without full transcription. A rapid qualitative analysis was conducted (31). The rationale and limitations of this approach are consistent with those described in Step 1. The CPD determinant part was completed (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 3 : Antecedents of implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Implementation antecedents are the acceptability, the appropriateness, the feasibility, the implementation climate, and the implementation readiness (19). To assess the antecedents of implantation, the qualitative data collected during the CFIR card game session (Step 1) and the consensus meeting (Step 2) were used.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo provide more comprehensive contextual understanding, quantitative aggregated data were extracted from the hospital Datawarehouse and electronical health records (EHR). This extracted data included patients\u0026rsquo; characteristics, staffs\u0026rsquo; characteristics, and units\u0026rsquo; characteristics. These data represent contextual factors related to the innovation, inner setting, and individuals\u0026rsquo; domains of the CFIR 2.0 (3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA deductive qualitative analysis, informed by the CFIR 2.0 and the CFIR outcomes addendum (3,19) was conducted. The principal investigator and research collaborators performed a CFIR-directed content analysis with the notes and audio recordings. The principal investigator and the research collaborators coded the notes and recorded quotes. The CFIR 2.0 constructs and the antecedent of implementation according to the CFIR outcomes addendum were used for coding (19). The notes were categorized using the definitions of preconditions and moderators from the research of Klasnja et al. (23). A precondition is a necessary factor for a determinant to influence an implementation outcome. A moderator is a factor that modifies the strength of a determinant\u0026apos;s influence (23). Data were categorized as preconditions if the response to the question, \u0026quot;Does the absence of this element block the determinant from influencing the antecedent?\u0026quot; was affirmative. \u0026nbsp; In other words, without this element, the determinant cannot act as a lever to promote the antecedent of implementation and, thus, the implementation outcome. Data were considered moderators if the answer to the question, \u0026quot;Does this element modify the strength of the determinant\u0026apos;s influence on the antecedent?\u0026quot; was affirmative. Then, the quantitative data were integrated to support this analysis. The results will be compared and discussed between the researchers (ADB, ChM, CM, SP) during meetings. The findings were then presented to the implementation team for triangulation and validation. Following validation, the CPD was completed (Figure 1) integrating both qualitative and descriptive quantitative data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 4: Mechanisms of Actions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collected for this step were the findings of previous steps validated by the implementation team.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, an inductive qualitative analysis was conducted based on the results of previous steps. The objective was to identify mechanisms for addressing the priority determinants. One or more mechanisms formulated for the context of the study were identified for each priority barrier or facilitator. The mechanism part of the CPD was completed (Figure 1). Next, a deductive qualitative analysis informed by BCT theory was conducted (28,35). For each mechanism identified, the principal investigator then made the link with the 26 MoAs in the BCT Theory and Techniques Tool (36). The results were then discussed and triangulated among the researchers (ADB, ChM, CM, SP). To facilitate understanding of the mechanisms, they were simplified, reformulated, and then presented to the implementation team for validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 5: Implementation strategies selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collected for this step were the findings of step 4, validated by the implementation team.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImplementation strategies were identified based on the priority determinants and mechanisms identified in the previous steps. The Theory and Techniques Tool was used to identify the BCTs associated with each MoA (25). The BCTs were then translated into implementation strategies from the ERIC compilation of implementation strategies based on the work of McHugh et al. (12). Each BCT identified above was associated with one or more strategies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA simplification process was then carried out using the strategy definitions to identify those that were already in place, those that related to the research team only, and those that related to the implementation team and the unit team. This resulted in a list of implementation strategies adapted to the unit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 6: Implementation strategies Prioritization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe list of adapted implementation strategies was reformulated for the context and presented to the implementation team. Consensus meeting with implementation team members was then conducted by using the NGT (32\u0026ndash;34). The principal investigator (SP) and the research collaborators (ADB, ChM) were facilitators and observers during the session. The session was audio-recorded, and notes were taken. The findings of this meeting prioritized the implementation strategies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative data from the prioritization session were analyzed during the meetings, with mean scores calculated for each strategy to determine priority. Qualitative data from the consensus meeting were analyzed collaboratively with participants. As in previous steps, audio recordings were used to supplement session notes, focusing on clarification and key details, without full transcription. The rationale and limitations of this approach remain consistent with those previously described. The implementation strategy and precondition parts of the CPD was then completed (Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 7: Implementation Strategies Development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor this step, the collected data were the findings of step 6, and the notes and audio-recordings of steps 1, 2, and 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the priority strategies previously identified by the implementation team, strategy bundles were developed. Each priority strategy (those with a score \u0026gt; 5) was defined and specified according to Proctor et al.\u0026apos;s 2013 recommendations (37) and tailored to the specific context of the traumatology unit. The strategies were then rated using the APEASE criteria (38) \u0026nbsp;to assess their acceptability, practicability, effectiveness, affordability, safety, and equity. These strategy packages were then presented to the implementation teams for validation. An implementation protocol was established and actively monitored during the implementation phase, allowing for ongoing adaptation and refinement of the strategies as needed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research involved anonymously collected or anonymized health-related data. The Federal Act on Research involving Human Beings (Human Research Act, HRA) did not apply to this research (Art. 2, Section 1, Chapter 1, HRA). This study was approved as an improvement project by the hospital\u0026apos;s legal department and the internal research evaluation board (CEDE: Commission d\u0026rsquo;\u0026Eacute;valuation des Demandes d\u0026rsquo;Enqu\u0026ecirc;tes, registration number: 89.2023).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTo view the methodological process and promote understanding, a synthesis of results is reported in Figure 2. For clarity, only part of the results is presented for each step.\u003c/p\u003e\n\u003cp\u003e[Insert Figure 2 here] Figure 2. Synthesis of results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 1: Determinants of the implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the CFIR card game session, among the 26 CFIR constructs assessed, the implementation team identified the construct Motivation from the domain of individuals like a barrier which was modifiable and with strong influence. The explication of the construct on the card was \u0026ldquo;The individuals involved in the implementation of [name of the innovation] are committed to fulfilling their roles\u0026rdquo;. The implementation team members explained their choice by pointing toward the fact that motivation among healthcare team members depended on their awareness and involvement in HAPI prevention (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 2: \u0026nbsp;Priority determinants of the implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter consensus meeting using NGT, the CFIR construct Motivation was a priority with a mean score at 9.8 (Figure 3). The implementation team members explained the prioritization, saying that many healthcare team members wouldn\u0026apos;t be motivated because they wouldn\u0026apos;t see the need for this innovation. They believed motivation would depend on how the HAPI\u0026apos;s issue and prevention were perceived. They said it would be necessary to support individuals by considering each person\u0026apos;s level of awareness.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 3 : Antecedents of implementation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe implementation readiness refers to \u0026ldquo;the extent to which the internal environment is ready for implementation\u0026quot; (19). For the implementation team, the implementation readiness was unfavorable. \u0026ldquo;For the moment, lack of information for the team, the team is not ready.\u0026rdquo; The motivation was linked to the unreadiness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe implementation team emphasized prior awareness of the issue and prevention of HAPIs as necessary factors for motivation to promote implementation readiness (precondition). During the study period, the HAPI rate was 1.0%, and the Braden score was used to assess risk at least once by 81.43% of patients during hospitalization. Of these patients, 67.67% were at HAPI risk. Approximately 65% of patients at risk had benefited from at least one preventive measure during their hospitalization.\u003c/p\u003e\n\u003cp\u003eAccording to the implementation team, the link between motivation and implementation readiness would be strengthened if healthcare team members received support tailored to their skill levels. The skill mix during this period was 75%, with the healthcare team consisting of three-quarters nurses and one-quarter nursing assistants and health and community care assistants (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 4: Mechanisms of Actions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the findings of the step 3, three mechanisms for addressing the motivation determinant were identified. For this example, only one mechanism will be detailed (Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn step 3, a precondition for motivation to promote readiness was awareness of the issue and prevention of HAPIs. One of the underlying mechanisms to achieve this would be to make visible existing knowledge, abilities, and skills regarding the issue of HAPIs and their prevention. Data extraction revealed that approximately 18% of patients did not undergo risk assessment using the Braden scale, and approximately one-third of patients at risk did not receive preventive measures. Using the innovation would enable us to assess risk for all patients and take appropriate preventive measures. In line with BCT theory (28,36), this mechanism could enable users to become aware of the issue of HAPI and of the innovation (BCT MoA: Knowledge), believe in their ability to prevent HAPI and use the innovation (BCT MoA: Beliefs about Capabilities), and their consequences (BCT MoA: Beliefs about Consequences), and emphasize the skills and competencies acquired through practice (BCT MoA: Skills).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 5: Implementation strategies selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter validation of the mechanism by the implementation team, the four MoAs linked were associated to 20 BCTs according to the BCT Theory and Techniques Tool (36). Then, based on the work of McHugh et al. 2022 (12), 17 potential ERIC strategies were identified to activate the mechanism. Among the 17 strategies, six were related to the research team and already in place, and one was not applicable. Finally, 11 strategies related to this mechanism were presented to the implementation team.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo simplify the process description, only one BCT and one associated strategy will be presented in this example. The BCT \u0026ldquo;8.1 Behavioural rehearsal\u0026rdquo; was linked with two BCT MoAs: Skills and Beliefs about Capabilities (36). According to Mc Hugh et al., this BCT is probably indicated in ERIC strategy: \u0026ldquo;Model and simulate change\u0026rdquo; (12). This strategy was presented to the implementation team for prioritization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 6: Implementation strategies Prioritization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter consensus meeting using NGT, the ERIC strategy \u0026ldquo;Model and simulate change\u0026rdquo; \u0026nbsp;was a priority with a mean score at 10. According to the implementation team, this strategy would trigger the mechanism if it did not take the form of a video or simulation workshop. Rather, it should take the form of educational or informative material in a simple format, such as a pocket card or poster displayed at the desk, as well as demonstrations at existing meeting points (Figure 3).\u003c/p\u003e\n\u003cp\u003e[Insert Figure 3 here] Figure 3. Synthesis results of methodological process guided by CPD adapted from Klasnja et al. (23).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStep 7: Implementation Strategies Development\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEach priority strategy previously identified by the implementation team, was defined and specified according to Proctor et al.\u0026apos;s 2013 recommendations (37) and to the context (Table 1). According to the APEASE criteria (38), the strategy score was 29 out of a possible score of 30. This strategy was included in a bundle of five strategies integrated in the daily huddles.\u003c/p\u003e\n\u003cp\u003e[Insert Table1 here]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Definition and specification of the strategy \u0026ldquo;Model and simulate change\u0026rdquo;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel and simulate change\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDefinition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eModel or simulate the change that will be implemented prior to implementation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eActor(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eResearch Team \u0026ndash; Implementation Team\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eAction(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Allow the implementation team and the healthcare team to test the application several times outside of the daily care process + see educational/informative materials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Encourage or advise to imagine and compare the future results of risk assessment and prevention implementation with the innovation vs current practices\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTarget\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eImplementation Team \u0026ndash; Healthcare Team\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\"\u003e\n \u003cp\u003eTemporality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; Before the deployment of the innovation in the unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; During the deployment of the innovation in the unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; During existing huddle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026bull; During meetings between research team and implementation team\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAs much as needed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImplementation outcomes affected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eImplementation readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eJustification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTo make visible existing knowledge, abilities, and skills regarding the issue of hospital acquired pressure injuries \u0026nbsp;and their prevention\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis methodology could address various challenges in the field of implementation science. It responds to the need to establish more explicit links between implementation determinants, strategies and outcomes. It also aims to improve our understanding of the mechanisms by which implementation strategies produce change, going beyond simply identifying effective strategies. Furthermore, its multi-framework and multi-theory approach enables a more comprehensive and nuanced understanding of the implementation process. Additionally, it draws on innovative and effective methods of data collection and analysis, each of which adds significant value. In summary, this study contributes to a more rigorous and theoretically grounded approach to the implementation of evidence-based practices.\u003c/p\u003e\u003cp\u003ePrevious studies have highlighted an insufficient understanding of the causal relationships between implementation strategies, determinants, and outcomes (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). This methodology uses CPDs to map determinants, mechanisms, and expected outcomes. This approach enhances transparency, enables hypothesis validation, and identifies key measurement points (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). As emphasized by Klasnja et al., CPDs help professionals grasp causality by examining the processes through which strategies operate, optimizing the match between strategies and barriers, and identifying conditions for successful implementation (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). This approach operationalizes the shift from \"classification to causality\" advocated by Lewis et al. and provides a practical means to identify and test the \"bridges and mechanisms\" described by Luke et al. and the adaptive, mechanism-oriented strategies promoted by Geng et al. (\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Integrating multiple frameworks with CPDs ensures both theoretical rigor and practical applicability. Following Proctor et al.\u0026rsquo;s recommendations for detailed strategy specification improves reproducibility and comparability (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). The methodology, grounded in BCT theory, identifies MoAs as the active components that drive change (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Links between BCTs and MoAs, provide a foundation for testable causal models that can be refined over time. Due to the lack of empirical studies that establish causal links between strategies, mechanisms, and outcomes, this methodology provides a structured, theory-informed, and empirically testable approach to advancing research and guiding the adaptation of implementation strategies in different contexts.\u003c/p\u003e\u003cp\u003eThis methodology is based on the synergistic integration of proven-effective frameworks, theories, and taxonomies in implementation science. This multi-framework approach is a significant asset because it provides a more comprehensive and nuanced understanding of the implementation process. As Nilsen and Moullin et al. have noted, employing theoretical frameworks to direct study design, stimulate theoretical and empirical reasoning, and streamline result interpretation is paramount. These frameworks facilitate the development of a shared language and provide practical tools for planning, executing, and evaluating implementation efforts (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). The present methodology addresses the tendency among implementation science researchers to specialize in a single research approach. The present methodology integrates CFIR, ERIC, BCT, and IOF to promote an interdisciplinary approach. This approach enhances the integration and comparison of methodologies, thereby reinforcing the discipline (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). Integrating these frameworks and theories helps define the objective of the implementation effort and prioritize the determinants to be targeted. This is of paramount importance when considering funding and resource limitations (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis methodology incorporates innovative and efficient data collection and analysis methods that add substantial value. The CFIR card game is an interactive, qualitative tool that facilitates the identification of determinants. Translated and simplified CFIR constructs make it accessible to healthcare professionals without specialist implementation knowledge (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). When used alongside the NGT, a structured consensus method that minimizes dominance effects and ensures equal participation, this approach enables the prioritization of determinants and strategies based on feasibility and perceived importance (\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Following Nevedal et al.\u0026rsquo;s methodology, rapid qualitative analysis used notes and audio recordings rather than full transcripts, reducing time and cost while maintaining rigor (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Despite requiring expertise in qualitative methods and CFIR, this near real-time analysis was essential for timely decision-making during implementation. Combining multiple methods yielded rich, diverse data, and triangulation enhanced the validity of the results.\u003c/p\u003e\u003cp\u003eThis methodology is characterized by its complex, structured design that integrates multiple stages and theoretical frameworks from implementation science. This approach generates generalizable knowledge and robust theories. While this level of rigor provides valuable insights, it requires significant resources, including time, skilled facilitation, and sustained stakeholder engagement, and may be difficult to maintain in pragmatic or resource-limited contexts. However, the process can be adapted without losing its core logic. For example, one can focus on the most relevant CFIR constructs, streamline data collection through shorter or asynchronous formats, leverage existing data, or condense CPD mapping into a single session. A CNS can play a pivotal role in these adaptations by coordinating the identification of priority determinants, facilitating consensus, and integrating simplified CPD mapping into existing governance or quality improvement meetings. This approach maintains methodological fidelity while alleviating the burden on external teams. This balance between rigor and feasibility enables the development of context-tailored strategies, demonstrating how structured adaptation can render the \"art\" of implementation more systematic and less dependent on intuition.\u003c/p\u003e\u003cp\u003eStakeholder involvement is critical to the success of implementation projects, and this methodology emphasizes active engagement throughout the process. Using the CFIR card game (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and consensus meetings via the NGT (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) ensured that field perspectives informed the development of strategies at every stage, thereby reinforcing their relevance and acceptability. Stakeholders provided valuable insights into workflows, infrastructure, culture, resources, and challenges. This enabled the co-design of contextually appropriate solutions, as advocated by Kirk et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Although this approach relies on research expertise, it also incorporates practical experience to ensure strategies are theoretically sound and operationally feasible. Intensive engagement demands substantial time and resources but enhances credibility, fosters ownership, and improves implementation outcomes. The facilitator plays a pivotal role in sustaining this engagement. In our case, the principal investigator\u0026rsquo;s pre-existing relationship with the team strengthened trust, but it also posed a risk of social desirability bias. This risk was mitigated through iterative consensus-building, triangulation, and validation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWhile the complexity and specific context of this case study require cautious interpretation of the findings in terms of generalizability, the proposed methodology provides a structured and participatory framework for developing contextually appropriate implementation strategies, with an emphasis on understanding mechanisms of change and stakeholder engagement. This approach could be useful in advancing the science of implementation by providing a detailed model for linking theory to practice.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBCT:\u003c/em\u003e\u003c/strong\u003e Behavior Change Technique\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBCTTv1:\u003c/em\u003e\u003c/strong\u003e Behavior Change Technique Taxonomy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCDSS:\u003c/em\u003e\u003c/strong\u003e Computerized Decision Support System\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCFIR:\u003c/em\u003e\u003c/strong\u003e Consolidated Framework for Implementation Research\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCNS:\u003c/em\u003e\u003c/strong\u003e Clinical Nurse Specialist\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCPD:\u003c/em\u003e\u003c/strong\u003e Causal Pathway Diagram\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEHR:\u003c/em\u003e\u003c/strong\u003e Electronic Health Record\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eERIC:\u003c/em\u003e\u003c/strong\u003e Expert Recommendations for Implementing Change\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHAPI:\u003c/em\u003e\u003c/strong\u003e Hospital-Acquired Pressure Injury\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHCCA:\u003c/em\u003e\u003c/strong\u003e Health and Community Care Assistant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eIOF:\u003c/em\u003e\u003c/strong\u003e Implementation Outcomes Framework\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMoA:\u003c/em\u003e\u003c/strong\u003e Mechanism of Action\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNGT:\u003c/em\u003e\u003c/strong\u003e Nominal Group Technique\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNM:\u003c/em\u003e\u003c/strong\u003e Nurse Manager\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eRN:\u003c/em\u003e\u003c/strong\u003e Registered Nurse\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: SP, JLR, and CM. Methodology: SP and CM. Data collection: SP. Project administration \u0026amp; data curation: SP and CM. Formal analysis: SP. Validation: JLR and CM. Writing \u0026ndash; Original Draft: SP. Writing \u0026ndash; Review \u0026amp; editing: JLR and CM. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Marter students Ana De Brito (ADB) and Charlotte Mittaz (ChM) who contributed to the collection and analysis of data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNilsen P, Bernhardsson S. Context matters in implementation science: a scoping review of determinant frameworks that describe contextual determinants for implementation outcomes. BMC Health Services Research. 2019;19(1):189. DOI: 10.1186/s12913-019-4015-3\u003c/li\u003e\n\u003cli\u003eAlbright K, Navarro EI, Jarad I, Boyd MR, Powell BJ, Lewis CC. Communication strategies to facilitate the implementation of new clinical practices: a qualitative study of community mental health therapists. Translational Behavioral Medicine. 2022;12(2):324\u0026ndash;34. DOI: 10.1093/tbm/ibab139\u003c/li\u003e\n\u003cli\u003eDamschroder LJ, Reardon CM, Widerquist MAO, Lowery J. The updated Consolidated Framework for Implementation Research based on user feedback. Implementation Science. 2022;17(1):75. DOI: 10.1186/s13012-022-01245-0\u003c/li\u003e\n\u003cli\u003ePowell BJ, Beidas RS, Lewis CC, Aarons GA, McMillen JC, Proctor EK, et al. Methods to Improve the Selection and Tailoring of Implementation Strategies. J Behav Health Serv Res. 2017;44(2):177\u0026ndash;94. DOI: 10.1007/s11414-015-9475-6\u003c/li\u003e\n\u003cli\u003eWaltz TJ, Powell BJ, Matthieu MM, Smith JL, Damschroder LJ, Chinman MJ, et al. Consensus on strategies for implementing high priority mental health care practices within the US Department of Veterans Affairs. Implement Res Pract. 2021;2:26334895211004607. DOI: 10.1177/26334895211004607\u003c/li\u003e\n\u003cli\u003eLewis CC, Powell BJ, Brewer SK, Nguyen AM, Schriger SH, Vejnoska SF, et al. Advancing mechanisms of implementation to accelerate sustainable evidence-based practice integration: protocol for generating a research agenda. BMJ Open. 2021;11(10):e053474. DOI: 10.1136/bmjopen-2021-053474\u003c/li\u003e\n\u003cli\u003eLewis CC, Klasnja P, Lyon AR, Powell BJ, Lengnick-Hall R, Buchanan G, et al. The mechanics of implementation strategies and measures: advancing the study of implementation mechanisms. Implementation Science Communications. 2022;3(1):114. DOI: 10.1186/s43058-022-00358-3\u003c/li\u003e\n\u003cli\u003ePowell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implementation Science. 2015;10(1):21. DOI: 10.1186/s13012-015-0209-1\u003c/li\u003e\n\u003cli\u003eMcHugh SM, Riordan F, Kerins C, Curran G, Lewis CC, Presseau J, et al. Understanding tailoring to support the implementation of evidence-based interventions in healthcare: The CUSTOMISE research programme protocol\u003cem\u003e \u003c/em\u003e. HRB Open Research; 2023. \u003c/li\u003e\n\u003cli\u003eDamschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implementation Science. 2009;4(1):50. DOI: 10.1186/1748-5908-4-50\u003c/li\u003e\n\u003cli\u003eDamschroder LJ. Clarity out of chaos: Use of theory in implementation research. Psychiatry Research. 2020;283:112461. DOI: 10.1016/j.psychres.2019.06.036\u003c/li\u003e\n\u003cli\u003eMcHugh S, Presseau J, Luecking CT, Powell BJ. Examining the complementarity between the ERIC compilation of implementation strategies and the behaviour change technique taxonomy: a qualitative analysis. Implementation Science. 2022;17(1):56. DOI: 10.1186/s13012-022-01227-2\u003c/li\u003e\n\u003cli\u003eKirk JW, Nilsen P, Andersen O, Powell BJ, Tj\u0026oslash;rnh\u0026oslash;j-Thomsen T, Bandholm T, et al. Co-designing implementation strategies for the WALK-Cph intervention in Denmark aimed at increasing mobility in acutely hospitalized older patients: a qualitative analysis of selected strategies and their justifications. BMC Health Services Research. 2022;22(1):8. DOI: 10.1186/s12913-021-07395-z\u003c/li\u003e\n\u003cli\u003eWaltz TJ, Powell BJ, Matthieu MM, Smith JL, Damschroder LJ, Chinman MJ, et al. Consensus on strategies for implementing high priority mental health care practices within the US Department of Veterans Affairs. Implementation Research and Practice. SAGE Publications; 2021;2:26334895211004607. DOI: 10.1177/26334895211004607\u003c/li\u003e\n\u003cli\u003eWaltz TJ, Powell BJ, Fern\u0026aacute;ndez ME, Abadie B, Damschroder LJ. Choosing implementation strategies to address contextual barriers: diversity in recommendations and future directions. Implementation Science. 2019;14(1):42. DOI: 10.1186/s13012-019-0892-4\u003c/li\u003e\n\u003cli\u003eYakovchenko V, Chinman MJ, Lamorte C, Powell BJ, Waltz TJ, Merante M, et al. Refining Expert Recommendations for Implementing Change (ERIC) strategy surveys using cognitive interviews with frontline providers. Implementation Science Communications. 2023;4(1):42. DOI: 10.1186/s43058-023-00409-3\u003c/li\u003e\n\u003cli\u003eProctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for Implementation Research: Conceptual Distinctions, Measurement Challenges, and Research Agenda. Administration and Policy in Mental Health. 2011;38(2):65\u0026ndash;76. DOI: 10.1007/s10488-010-0319-7\u003c/li\u003e\n\u003cli\u003eProctor EK, Bunger AC, Lengnick-Hall R, Gerke DR, Martin JK, Phillips RJ, et al. Ten years of implementation outcomes research: a scoping review. Implementation Science. 2023;18(1):31. DOI: 10.1186/s13012-023-01286-z\u003c/li\u003e\n\u003cli\u003eDamschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. Implementation Sci. BioMed Central; 2022;17(1):1\u0026ndash;10. DOI: 10.1186/s13012-021-01181-5\u003c/li\u003e\n\u003cli\u003eLewis CC, Klasnja P, Powell BJ, Lyon AR, Tuzzio L, Jones S, et al. From Classification to Causality: Advancing Understanding of Mechanisms of Change in Implementation Science. Front Public Health. Frontiers; 2018;6. DOI: 10.3389/fpubh.2018.00136\u003c/li\u003e\n\u003cli\u003eLuke DA, Powell BJ, Paniagua-Avila A. Bridges and Mechanisms: Integrating Systems Science Thinking into Implementation Research. Annual Review of Public Health. Annual Reviews; 2024;45(Volume 45, 2024):7\u0026ndash;25. DOI: 10.1146/annurev-publhealth-060922-040205\u003c/li\u003e\n\u003cli\u003eGeng EH, Mody A, Powell BJ. On-the-Go Adaptation of Implementation Approaches and Strategies in Health: Emerging Perspectives and Research Opportunities. Annual Review of Public Health. Annual Reviews; 2023;44(Volume 44, 2023):21\u0026ndash;36. DOI: 10.1146/annurev-publhealth-051920-124515\u003c/li\u003e\n\u003cli\u003eKlasnja P, Meza RD, Pullmann MD, Mettert KD, Hawkes R, Palazzo L, et al. Getting cozy with causality: Advances to the causal pathway diagramming method to enhance implementation precision. Implement Res Pract. 2024;5:26334895241248851. DOI: 10.1177/26334895241248851\u003c/li\u003e\n\u003cli\u003eLewis CC, Boyd MR, Walsh-Bailey C, Lyon AR, Beidas R, Mittman B, et al. A systematic review of empirical studies examining mechanisms of implementation in health. Implementation Sci. 2020;15(1):21. DOI: 10.1186/s13012-020-00983-3\u003c/li\u003e\n\u003cli\u003eMichie S, Atkins L, West R. The behaviour change wheel: a guide to designing interventions. Sutton: Silverback; 2014. \u003c/li\u003e\n\u003cli\u003eMichie S, Carey RN, Johnston M, Rothman AJ, Bruin M de, Kelly MP, et al. From Theory-Inspired to Theory-Based Interventions: A Protocol for Developing and Testing a Methodology for Linking Behaviour Change Techniques to Theoretical Mechanisms of Action. Annals of Behavioral Medicine: A Publication of the Society of Behavioral Medicine. 2017;52(6):501. DOI: 10.1007/s12160-016-9816-6\u003c/li\u003e\n\u003cli\u003eMichie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The Behavior Change Technique Taxonomy (v1) of 93 Hierarchically Clustered Techniques: Building an International Consensus for the Reporting of Behavior Change Interventions. Annals of Behavioral Medicine. 2013;46(1):81\u0026ndash;95. DOI: 10.1007/s12160-013-9486-6\u003c/li\u003e\n\u003cli\u003eCarey RN, Connell LE, Johnston M, Rothman AJ, de Bruin M, Kelly MP, et al. Behavior Change Techniques and Their Mechanisms of Action: A Synthesis of Links Described in Published Intervention Literature. Annals of Behavioral Medicine. 2019;53(8):693\u0026ndash;707. DOI: 10.1093/abm/kay078\u003c/li\u003e\n\u003cli\u003ePiat M, Wainwright M, Sofouli E, Albert H, Casey R, Rivest M-P, et al. The CFIR Card Game: a new approach for working with implementation teams to identify challenges and strategies. Implement Sci Commun. 2021;2(1):1. DOI: 10.1186/s43058-020-00099-1\u003c/li\u003e\n\u003cli\u003ePellet J, Pouzols S, Ridde V, Mabire C. Bridging the gap: translating and simplifying CFIR 2.0 for French practitioners in implementation science. Implementation Science Communications. 2025;6(1):29. DOI: 10.1186/s43058-025-00719-8\u003c/li\u003e\n\u003cli\u003eNevedal AL, Reardon CM, Opra Widerquist MA, Jackson GL, Cutrona SL, White BS, et al. Rapid versus traditional qualitative analysis using the Consolidated Framework for Implementation Research (CFIR). Implement Sci. 2021;16(1):67. DOI: 10.1186/s13012-021-01111-5\u003c/li\u003e\n\u003cli\u003eAllen J, Dyas J, Jones M. Building consensus in health care: a guide to using the nominal group technique. Br J Community Nurs. 2004;9(3):110\u0026ndash;4. DOI: 10.12968/bjcn.2004.9.3.12432\u003c/li\u003e\n\u003cli\u003eCooper S, Cant R, Luders E, Waters D, Henderson A, Hood K, et al. The Nominal Group Technique: generating consensus in nursing research. J Nurs Educ. 2020;59(2):65\u0026ndash;7. DOI: 10.3928/01484834-20200122-02\u003c/li\u003e\n\u003cli\u003eDunham RB. Nominal group technique: a user\u0026rsquo;s guide. University of Wisconsin; 2006. \u003c/li\u003e\n\u003cli\u003eConnell LE, Carey RN, de Bruin M, Rothman AJ, Johnston M, Kelly MP, et al. Links Between Behavior Change Techniques and Mechanisms of Action: An Expert Consensus Study. Annals of Behavioral Medicine. 2019;53(8):708\u0026ndash;20. DOI: 10.1093/abm/kay082\u003c/li\u003e\n\u003cli\u003e[Internet]. The Theory and Techniques Tool | Theory and Techniques Tool [cited 2025 Jul 4]. Available from: https://theoryandtechniquetool.humanbehaviourchange.org/tool\u003c/li\u003e\n\u003cli\u003eProctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implementation Science. 2013;8(1):139. DOI: 10.1186/1748-5908-8-139\u003c/li\u003e\n\u003cli\u003eWest R, Michie S. Unlocking Behaviour Change [Internet]. 2019. UBC Briefing 7: Evaluating behaviour change interventions using APEASE [cited 2024 Apr 22]. Available from: https://www.unlockingbehaviourchange.com/pdfs/5c766be7b6281890464249.pdf\u003c/li\u003e\n\u003cli\u003eVejnoska SF, Mettert K, Lewis CC. Mechanisms of implementation: An appraisal of causal pathways presented at the 5th biennial Society for Implementation Research Collaboration (SIRC) conference. Implementation Research and Practice. 2022;3:263348952210862. DOI: 10.1177/26334895221086271\u003c/li\u003e\n\u003cli\u003eMody A, Filiatreau LM, Goss CW, Powell BJ, Geng EH. Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation strategies and evidence-based interventions. Implement Sci Commun. 2023;4(1):157. DOI: 10.1186/s43058-023-00536-x\u003c/li\u003e\n\u003cli\u003eLewis CC, Scott K, Marriott BR. A methodology for generating a tailored implementation blueprint: an exemplar from a youth residential setting. Implementation Science. 2018;13(1):68. DOI: 10.1186/s13012-018-0761-6\u003c/li\u003e\n\u003cli\u003eNilsen P. Making sense of implementation theories, models and frameworks. Implementation Science. 2015;10(1):53. DOI: 10.1186/s13012-015-0242-0\u003c/li\u003e\n\u003cli\u003eMoullin JC, Dickson KS, Stadnick NA, Albers B, Nilsen P, Broder-Fingert S, et al. Ten recommendations for using implementation frameworks in research and practice. Implementation Science Communications. 2020;1:42. DOI: 10.1186/s43058-020-00023-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Causal Pathway diagram, Implementation Determinants, Implementation Frameworks, Implementation Outcomes, Implementation Strategies, Mechanisms of Action","lastPublishedDoi":"10.21203/rs.3.rs-7396236/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7396236/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDespite the growing use of implementation frameworks, there is still limited understanding of how implementation strategies influence contextual determinants in order to produce desired outcomes. Closing this knowledge gap is essential for developing effective, theory-informed, and tailored implementation strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study presents a seven-step approach that links implementation determinants with adapted strategies using the Consolidated Framework for Implementation Research, the Implementation Outcomes Framework, the Behavior Change Techniques Taxonomy, and the Expert Recommendations for Implementing Change (ERIC). Causal pathway diagrams guided the process of articulating the hypothesized causal mechanisms. This methodology was applied during the pre-implementation phase of a study that aimed to integrate a computerized decision support system for preventing hospital-acquired pressure injuries in a Swiss university hospital.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe process identified context-specific barriers and facilitators, prioritized determinants, and mapped them to implementation antecedents and mechanisms of action. Adapted and prioritized implementation strategies were co-designed with stakeholders. The result was a strategy bundle tailored to local context, validated through iterative stakeholder engagement.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis methodology provides a transparent, rigorous, and participatory approach to strategy development that can enhance implementation precision and contribute to theory building in implementation science. The integration of numerous frameworks and the incorporation of stakeholder input provides a replicable model for the design of context-sensitive implementation strategies.\u003c/p\u003e","manuscriptTitle":"Opening the Black Box: A Causal Pathway Methodology for Precise Implementation Strategy Design","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 05:55:56","doi":"10.21203/rs.3.rs-7396236/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cda405de-122f-43fa-9668-bf7cd5d07c03","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-28T07:16:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 05:55:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7396236","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7396236","identity":"rs-7396236","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}