From Barriers to Breakthroughs: A Strategic Guide to Matching Implementation Strategies with Determinants

Abstract

This article provides a comprehensive guide for researchers and drug development professionals on systematically matching implementation strategies to contextual determinants. It covers foundational principles, practical methodological tools, and advanced approaches for troubleshooting and validation. By integrating the latest evidence and frameworks like the Consolidated Framework for Implementation Research (CFIR), this guide aims to enhance the precision and effectiveness of implementation efforts in biomedical and clinical settings, ultimately accelerating the translation of evidence-based interventions into practice.

Understanding the Core: Key Determinants and Implementation Strategy Fundamentals

Defining Implementation Determinants, Barriers, and Facilitators

The successful integration of evidence-based practices into routine care hinges on understanding the factors that influence the implementation process. Implementation determinants are the barriers and facilitators that predict or explain the success or failure of implementation efforts [1]. Within the broader context of matching implementation strategies to determinants, a critical first step is the systematic identification and categorization of these determinants. This protocol outlines standardized approaches for defining implementation determinants, with specific application notes for researchers in healthcare and drug development.

The Consolidated Framework for Implementation Research (CFIR) serves as a widely adopted determinant framework that includes 48 constructs and 19 subconstructs across five major domains: Innovation, Outer Setting, Inner Setting, Individuals, and Implementation Process [1]. This framework provides a systematic structure for identifying and categorizing determinants, offering a common language and taxonomy that enables comparability across studies and settings. Proper identification of determinants enables researchers to subsequently select tailored implementation strategies that address specific barriers and leverage existing facilitators [2].

Theoretical Framework and Definitions

Core Definitions and Conceptual Distinctions

Implementation Determinants: Factors that act as barriers or facilitators to implementation success, operating across multiple contextual levels [1]. These factors can be prospectively assessed to predict implementation outcomes or retrospectively evaluated to explain outcomes that have already occurred.

Barriers: Factors that impede the adoption, implementation, or sustainability of an evidence-based intervention. In a recent systematic review of mental health interventions in schools, barriers constituted 61.6% (N = 207) of identified implementation factors [3].

Facilitators: Factors that enhance or enable the adoption, implementation, or sustainability of an evidence-based intervention. These represented 38.4% (N = 129) of implementation factors in the same systematic review [3].

Implementation Outcomes: The effects of deliberate and purposive actions to implement new treatments, practices, and services, which can include adoption, fidelity, penetration, sustainability, and implementation cost [1] [4].

CFIR Domain Specifications

The updated CFIR framework organizes determinants into five domains with clearly defined boundaries [1]:

Table: CFIR Domains and Construct Specifications

Domain	Key Constructs	Definition and Boundaries
Innovation	Evidence strength, Adaptability, Design quality	The evidence-based intervention being implemented. Must be clearly distinguished from implementation strategies.
Outer Setting	Patient needs, External policies, Peer pressure	The economic, political, and social context surrounding the organization.
Inner Setting	Structural characteristics, Networks, Culture, Implementation climate	The organizational context where implementation occurs, including resources and leadership.
Individuals	Knowledge, Self-efficacy, Beliefs	The roles and characteristics of individuals involved in implementation.
Implementation Process	Planning, Engaging, Executing, Reflecting	The activities and strategies used to implement the innovation.

Diagram 1: CFIR Determinants Domain Structure. This diagram illustrates the five major domains of implementation determinants and their key constructs as defined by the Consolidated Framework for Implementation Research.

Methodological Protocols for Determinant Assessment

Mixed-Methods Assessment Approach

A mixed-methods approach combining qualitative and quantitative data collection provides the most comprehensive assessment of implementation determinants. The CFIR Leadership Team recommends a five-step process for conducting implementation research using the framework [1]:

Step 1: Study Design - Define research questions and implementation outcomes, then specify domain boundaries specific to the project context.

Step 2: Data Collection - Employ semi-structured interviews, focus groups, surveys, or observational methods to assess determinants.

Step 3: Data Analysis - Use directed content analysis informed by CFIR constructs, with rigorous coding procedures.

Step 4: Data Interpretation - Interpret findings to identify which determinants distinguish between implementation success and failure.

Step 5: Knowledge Dissemination - Report findings to inform implementation strategy selection.

Qualitative Assessment Protocol

Interview Guide Development:

• Develop semi-structured interview guides using CFIR constructs as a priori codes [5] [6]
• Include open-ended questions about experiences with the innovation and implementation process
• Probe for both barriers and facilitators across all relevant domains
• Pilot test and refine guides with content experts

Sampling Strategy:

• Employ purposive sampling to ensure representation of key stakeholders [6] [5]
• Target individuals with diverse roles, experiences, and perspectives
• Sample until reaching thematic saturation (typically 20-30 participants) [5]

Data Collection:

• Conduct individual interviews or focus groups
• Audio record and professionally transcribe interviews
• Collect demographic and contextual data to characterize the sample

Analysis Procedure:

• Use directed content analysis informed by CFIR constructs [6] [5]
• Develop a codebook with definitions for CFIR constructs
• Apply both a priori codes (CFIR constructs) and emergent codes
• Use multiple coders and establish inter-rater reliability
• Analyze data within and across interviews to identify themes
• Write analytic memos and hold team meetings to discuss emerging patterns [6]

Quantitative Assessment Protocol

Survey Development:

• Adapt existing CFIR-based instruments when available
• Develop items that operationalize CFIR constructs
• Include both closed-ended and open-ended response options
• Ensure items measure both presence and strength of determinants

Data Collection:

• Administer to larger samples to assess generalizability
• Collect data at multiple time points to track changes
• Ensure adequate response rates through follow-up procedures

Analysis Procedure:

• Conduct descriptive analyses to characterize determinants
• Perform comparative analyses to identify determinants associated with outcomes
• Use multivariate analyses to examine complex relationships
• Integrate quantitative and qualitative findings

Application Notes: Case Examples and Data Synthesis

Case Example Synthesis

Recent applications of determinant assessment across diverse healthcare contexts demonstrate consistent methodological approaches and findings:

Table: Determinant Assessment Case Examples

Study Context	Methodology	Key Barriers	Key Facilitators	Implementation Outcomes
Moral Injury Interventions for Nurses [5]	Qualitative interviews using CFIR (N=25)	Resource costs, leadership support gaps, inability to take breaks, professional image concerns	Unit-specific tailoring, team social support, desire for change, high motivation to provide quality care	Improved identification of determinants to inform intervention development
School-Based Mental Health Interventions [3]	Systematic review of 26 studies	Scheduling conflicts, low mental health prioritization, logistical challenges	Leadership support, age-appropriate design, staff engagement	Identified need for integration into school structures and alignment with academic priorities
ED Buprenorphine Initiation [6]	PRISM-guided qualitative interviews (N=28)	Organizational culture constraints, clinician training gaps, patient connection challenges	Tailored implementation, organizational commitment, training support	Informed development of multilevel implementation strategies

Determinant Rating and Prioritization Protocol

After identifying determinants, systematic rating and prioritization enables focused strategy development:

Rating Criteria:

• Strength: Intensity of the determinant's influence (low/medium/high)
• Valence: Whether the determinant acts as a barrier (-) or facilitator (+)
• Prevalence: How widely the determinant is experienced across stakeholders
• Modifiability: The extent to which the determinant can be changed

Prioritization Matrix:

• Create a 2x2 matrix with "strength of influence" and "modifiability" as axes
• Prioritize determinants with high strength and high modifiability
• Acknowledge but deprioritize determinants with low modifiability

Stakeholder Validation:

• Present preliminary findings to stakeholders for validation
• Use member checking to verify interpretation accuracy [5]
• Incorporate feedback into final determinant prioritization

Table: Implementation Determinant Research Reagent Solutions

Tool/Resource	Function	Application Notes
CFIR Technical Assistance Website (www.cfirguide.org) [1]	Repository of tools, templates, and guidance	Provides interview guides, coding guidelines, and memo templates; updated regularly by CFIR Leadership Team
CFIR Construct Coding Guidelines [1]	Standardized definitions and coding rules	Ensures consistent application of CFIR constructs across team members and studies
ERIC Implementation Strategy Taxonomy [4]	Menu of 73 implementation strategies with definitions	Enables systematic linking of determinants to potential implementation strategies
AACTT Framework [4]	Specifies implementation outcomes by Action, Actor, Context, Target, and Time	Improves alignment between determinants, strategies, and outcomes through behavioral specification
Implementation Strategy Mapping Methods [2]	Step-by-step process for linking determinants to strategies	Guides systematic matching of determinants to implementation strategies using codesign approaches

Determinant-to-Strategy Matching Framework

The ultimate goal of defining implementation determinants is to inform the selection and tailoring of implementation strategies. The following diagram illustrates the complete pathway from determinant assessment to strategy implementation:

Diagram 2: Determinant to Strategy Matching Pathway. This workflow illustrates the systematic process from initial determinant assessment through implementation strategy selection and evaluation.

The matching process involves:

• Systematic Linking: Using established matching tools like the CFIR-ERIC Matching Tool to connect specific determinants to evidence-based implementation strategies [2]

• Codesign Approach: Engaging stakeholders in collaborative sessions to contextualize and adapt strategies to local settings [2]

• Specification: Clearly defining implementation strategies using Proctor's naming, definition, and operationalization framework [4]

• Tailoring: Modifying strategy bundles to address the unique constellation of determinants in specific contexts

This systematic approach to defining implementation determinants provides the essential foundation for the broader thesis of matching implementation strategies to determinants research, enabling more effective and efficient translation of evidence into practice.

The Consolidated Framework for Implementation Research (CFIR) is one of the most highly cited determinant frameworks in implementation science, designed to predict or explain barriers and facilitators to implementation success [7] [1]. First published in 2009 and updated in 2022 based on extensive user feedback, the CFIR provides a structured, comprehensive menu of constructs that influence the implementation of evidence-based innovations across diverse settings [7] [8]. The framework consolidates constructs from multiple implementation theories and models into a single overarching framework, offering a practical guide for systematic assessment of contextual factors that impact implementation effectiveness [8].

The CFIR serves as a determinant framework that categorizes contextual factors (independent variables) that may influence implementation outcomes (dependent variables) [1]. Its overarching aim is to help researchers and practitioners identify critical barriers and facilitators that predict or explain implementation success or failure [7]. The framework has been applied extensively in healthcare settings but has also been used in education, agriculture, community settings, and low- and middle-income countries [7] [8]. As of late 2023, the original CFIR article had been cited over 10,000 times in Google Scholar and over 4,600 times in PubMed, demonstrating its substantial impact on the field [8].

The CFIR Framework: Domains and Constructs

The updated CFIR organizes 48 constructs and 19 subconstructs across five major domains that collectively capture the multidimensional nature of implementation contexts [1] [9]. The framework was revised based on feedback from experienced users obtained through both literature review and surveys, with updates addressing important critiques including better centering innovation recipients and adding determinants to equity in implementation [7]. The five domains form an interconnected system that shapes implementation outcomes.

Innovation Domain

The Innovation Domain encompasses characteristics of the "thing" being implemented—whether a clinical treatment, educational program, or service [9]. This domain includes eight key constructs that capture how stakeholders perceive the innovation itself, which significantly influences implementation success.

Table 1: Innovation Domain Constructs

Construct Name	Construct Definition
Innovation Source	The degree to which the group that developed and/or visibly sponsored use of the innovation is reputable, credible, and/or trustable
Innovation Evidence-Base	The degree to which the innovation has robust evidence supporting its effectiveness
Innovation Relative Advantage	The degree to which the innovation is better than other available innovations or current practice
Innovation Adaptability	The degree to which the innovation can be modified, tailored, or refined to fit local context or needs
Innovation Trialability	The degree to which the innovation can be tested or piloted on a small scale and undone
Innovation Complexity	The degree to which the innovation is complicated, reflected by its scope and/or the nature and number of connections and steps
Innovation Design	The degree to which the innovation is well designed and packaged, including how it is assembled, bundled, and presented
Innovation Cost	The degree to which the innovation purchase and operating costs are affordable

Outer Setting Domain

The Outer Setting Domain encompasses the larger context in which the inner setting exists, such as hospital systems, school districts, or states [9]. This domain captures external influences on implementation, including seven core constructs and associated subconstructs that shape how external factors facilitate or hinder implementation efforts.

Table 2: Outer Setting Domain Constructs

Construct Name	Construct Definition
Critical Incidents	The degree to which large-scale and/or unanticipated events disrupt implementation and/or delivery of the innovation
Local Attitudes	The degree to which sociocultural values and beliefs encourage the Outer Setting to support implementation and/or delivery of the innovation
Local Conditions	The degree to which economic, environmental, political, and/or technological conditions enable the Outer Setting to support implementation and/or delivery of the innovation
Partnerships & Connections	The degree to which the Inner Setting is networked with external entities, including referral networks, academic affiliations, and professional organization networks
Policies & Laws	The degree to which legislation, regulations, professional group guidelines and recommendations, or accreditation standards support implementation and/or delivery of the innovation
Financing	The degree to which funding from external entities (e.g., grants, reimbursement) is available to implement and/or deliver the innovation
External Pressure	The degree to which external pressures drive implementation and/or delivery of the innovation

Inner Setting Domain

The Inner Setting Domain encompasses the immediate environment where implementation occurs, such as specific hospitals, schools, or units within organizations [9]. This domain includes both general organizational characteristics and innovation-specific factors, with eleven key constructs that capture the institutional context that either enables or constrains implementation.

Table 3: Inner Setting Domain Constructs

Construct Name	Construct Definition
Structural Characteristics	The degree to which infrastructure components support functional performance of the Inner Setting
Relational Connections	The degree to which there are high quality formal and informal relationships, networks, and teams within and across Inner Setting boundaries
Communications	The degree to which there are high quality formal and informal information sharing practices within and across Inner Setting boundaries
Culture	The degree to which there are shared values, beliefs, and norms across the Inner Setting
Tension for Change	The degree to which the current situation is intolerable and needs to change
Compatibility	The degree to which the innovation fits with workflows, systems, and processes
Relative Priority	The degree to which implementing and delivering the innovation is important compared to other initiatives
Incentive Systems	The degree to which tangible and/or intangible incentives and rewards and/or disincentives and punishments support implementation and delivery of the innovation
Mission Alignment	The degree to which implementing and delivering the innovation is in line with the overarching commitment, purpose, or goals in the Inner Setting
Available Resources	The degree to which resources are available to implement and deliver the innovation
Access to Knowledge & Information	The degree to which guidance and/or training is accessible to implement and deliver the innovation

Individuals: Roles & Characteristics Domain

The Individuals Domain captures the roles and characteristics of people involved in or affected by implementation [9]. This domain is organized into two subdomains: Roles (documenting specific positions and responsibilities) and Characteristics (capturing individual attributes that influence implementation), with nine role constructs and four characteristic constructs.

CFIR Individuals Domain Structure

Implementation Process Domain

The Implementation Process Domain encompasses the activities and strategies used to implement the innovation [9]. This domain includes six key constructs that capture the active implementation efforts, distinguishing the implementation process (activities that end after implementation) from the innovation itself (which continues when implementation is complete).

Table 4: Implementation Process Domain Constructs

Construct Name	Construct Definition
Teaming	The degree to which individuals join together, intentionally coordinating and collaborating on interdependent tasks, to implement the innovation
Assessing Needs	The degree to which individuals collect information about priorities, preferences, and needs of people
Assessing Context	The degree to which individuals collect information to identify and appraise barriers and facilitators to implementation and delivery of the innovation
Planning	The degree to which individuals identify roles and responsibilities, outline specific steps and milestones, and define goals and measures for implementation success in advance
Tailoring Strategies	The degree to which individuals choose and operationalize implementation strategies to address barriers, leverage facilitators, and fit context
Engaging	The degree to which individuals attract and encourage participation in implementation and/or the innovation

Key Determinants in Implementation Success

Research has identified specific CFIR constructs that consistently emerge as key determinants with the strongest impact on implementation outcomes. A 2025 systematic review of 48 studies that used the Damschroder & Lowery rating system identified eight key determinants that most frequently play the biggest role in implementation processes [10]. This rating system quantifies qualitative data by assessing both the valence (positive or negative effect) and magnitude (strength of effect) of determinants, ranging from -2 (major barrier) to +2 (major facilitator) [10].

Table 5: Key Determinants in Implementation Processes

Key Determinant	CFIR Domain	Impact Description
Leadership Engagement	Inner Setting	Commitment, involvement, and accountability of leaders at multiple levels
Formally Appointed Internal Implementation Leaders	Individuals: Roles	Individuals with formal responsibility for leading implementation efforts
Compatibility	Inner Setting	Fit between innovation and existing workflows, systems, and processes
Available Resources	Inner Setting	Allocation of sufficient staffing, time, space, and equipment
External Change Agents	Outer Setting	Individuals outside the organization who support implementation
Champions	Individuals: Roles	Individuals who dedicate themselves to supporting and driving the implementation
Relative Advantage	Innovation	Perception that the innovation is better than current practice
Key Stakeholders	Individuals: Roles	Individuals affected by or influencing the implementation

These key determinants provide a strategic starting point for researchers and practitioners deciding where to focus assessment and intervention efforts when faced with the comprehensive list of CFIR constructs [10]. The identification of these factors across multiple studies suggests they have consistent and substantial influence on implementation success regardless of the specific innovation or context.

Application Protocols: Using CFIR in Implementation Research

The CFIR Leadership Team has developed a structured five-step approach to guide researchers in applying CFIR throughout the research process [1]. This methodology ensures systematic application of the framework from study design through knowledge dissemination, facilitating rigorous and comprehensive assessment of implementation determinants.

Step 1: Study Design

The initial phase involves defining the research focus and implementation outcome. Researchers must specify whether they are using CFIR prospectively (to assess determinants of anticipated implementation outcomes) or retrospectively (to explain actual implementation outcomes) [1]. This critical distinction shapes all subsequent methodological decisions.

Protocol 1: Defining Implementation Outcomes

• Identify the innovation being implemented and distinguish it from implementation strategies [9]
• Select appropriate implementation outcomes that measure success or failure of implementation
• Define domain boundaries specific to the project to enable accurate attribution to implementation outcomes [1]
• Document the Inner and Outer Settings including type, location, and boundaries between them [9]

Step 2: Data Collection

This phase involves selecting appropriate methods to capture CFIR constructs. While qualitative methods like semi-structured interviews and focus groups are commonly used, quantitative surveys and mixed methods approaches are also valuable [1] [11]. The selection of data collection methods should align with research questions, resources, and epistemological orientation.

Protocol 2: CFIR-Informed Data Collection

• Develop data collection instruments with questions mapped to relevant CFIR constructs [1]
• Determine sampling strategy based on units of analysis (individual, team, organizational levels) [11]
• Select participants who have power and/or influence over implementation outcomes [9]
• Pilot test instruments to ensure comprehensiveness and clarity

Step 3: Data Analysis

Analytical approaches for CFIR-informed data include both qualitative framework analysis and quantitative methods, including rating constructs based on their influence on implementation outcomes [10] [1]. The Damschroder & Lowery rating system enables quantification of qualitative findings by assessing both the direction and strength of each construct's influence.

CFIR Data Analysis Workflow

Step 4: Data Interpretation

Interpretation involves synthesizing findings to identify which determinants are most critical to address and understanding how constructs interact across domains to influence implementation outcomes [1]. This phase moves beyond describing individual constructs to developing a comprehensive understanding of their collective impact.

Protocol 3: Interpreting CFIR Findings

• Identify difference-maker constructs that strongly distinguish between implementation success and failure [1]
• Analyze construct interactions across domains to understand systemic influences
• Compare perspectives across different stakeholder groups
• Contextualize findings within the specific implementation stage and setting

Step 5: Knowledge Dissemination

The final step involves sharing findings to inform implementation practice and contribute to implementation science. Effective dissemination includes both traditional academic outputs and tailored products for stakeholders involved in implementation [1] [11].

Protocol 4: Disseminating CFIR Findings

• Share rapid feedback with stakeholders after data collection to inform refinements [11]
• Develop tailored reports addressing barriers and facilitators identified
• Publish scholarly outputs to contribute to implementation science knowledge
• Archive data and instruments for potential replication or secondary analysis

Matching Implementation Strategies to CFIR Determinants

A critical application of CFIR in implementation research is guiding the selection of implementation strategies to address specific barriers identified through context assessment. The CFIR-ERIC Implementation Strategy Matching Tool provides a systematic approach for linking barriers to potential strategies [12].

The CFIR-ERIC Matching Process

The matching process connects barriers identified using CFIR with implementation strategies from the Expert Recommendations for Implementing Change (ERIC) compilation [12]. This tool was developed based on survey responses from implementation experts who identified strategies most likely to address specific CFIR barriers.

Table 6: CFIR Barrier to Strategy Matching Examples

CFIR Barrier Domain	Example CFIR Construct	Highly Endorsed ERIC Strategies
Inner Setting	Available Resources	Access new funding, Change record systems, Fund and contract for clinical innovations
Individuals	Innovation Deliverers Capability	Conduct educational meetings, Develop educational materials, Provide ongoing consultation
Implementation Process	Assessing Needs	Assess for readiness and identify barriers and facilitators, Conduct local needs assessment
Outer Setting	Policies & Laws	Involve patients/consumers and family members, Develop partnerships

Application in Implementation Planning

The matching tool is particularly valuable during implementation planning to proactively address anticipated barriers, and during implementation to refine strategies in response to emerging challenges [12]. A case illustration from the Telephone Lifestyle Coaching program in Veterans Affairs medical centers demonstrated how seven key CFIR barriers were matched with highly-endorsed implementation strategies, with "Identify and Prepare Champions" emerging as the strategy with the highest cumulative endorsement across multiple barriers [12].

Successful application of CFIR requires leveraging available tools and resources developed by the CFIR Leadership Team and user community. These resources provide practical guidance for operationalizing the framework throughout the research process.

Table 7: Essential CFIR Research Resources

Resource Type	Description	Source/Availability
CFIR Construct Coding Guidelines	Detailed guidance for applying CFIR constructs in qualitative analysis	CFIR User Guide [1]
CFIR Technical Assistance Website	Central repository for tools, templates, and updates	www.cfirguide.org [8]
CFIR-ERIC Strategy Matching Tool	Matrix linking CFIR barriers to implementation strategies	Downloadable from CFIR website [12]
Implementation Research Worksheet	Template for documenting CFIR application throughout research process	CFIR User Guide [1]
Construct Example Questions	Interview and survey questions mapped to CFIR constructs	CFIR User Guide [1]

These resources support both novice and experienced CFIR users in applying the framework consistently and rigorously. The CFIR Leadership Team continues to develop and refine these tools based on user feedback and advancing methodological standards in implementation science [1].

The Consolidated Framework for Implementation Research provides a comprehensive, structured approach to identifying determinants that influence implementation success across diverse contexts and innovations. Its systematic organization of constructs across five domains offers researchers and practitioners a practical framework for assessing contextual factors, explaining implementation outcomes, and informing strategy selection. The continued evolution of CFIR through user feedback and methodological refinement ensures its ongoing relevance and utility for advancing implementation science and practice.

As implementation science matures, CFIR remains a foundational framework for understanding the complex interplay of factors that determine implementation success. Its application facilitates both theoretical advancement and practical improvement in implementing evidence-based innovations across healthcare and other settings, ultimately contributing to more effective translation of research into practice.

The successful implementation of evidence-based interventions in healthcare and drug development is a complex process, heavily influenced by a wide array of contextual factors. These factors, known as implementation determinants, can either act as barriers or facilitators to the adoption, integration, and sustainment of new practices [10]. While numerous determinants have been identified, the pressing challenge for researchers and practitioners lies in identifying which of these factors exert the strongest influence on implementation outcomes. A more systematic understanding of these key determinants enables the development of more effective, efficient, and tailored implementation strategies [13]. This application note synthesizes evidence from recent systematic reviews to identify the most critical determinants and provides structured protocols for integrating this knowledge into the implementation strategy matching process, a core component of advanced implementation research.

Key Findings from Systematic Reviews

Identification of Key Determinants

A pivotal 2025 systematic review conducted by Schmitt et al. analyzed 48 studies that utilized a standardized rating system to assess the magnitude and valence of implementation determinants, as defined by the Consolidated Framework for Implementation Research (CFIR) [10] [14]. This review identified eight key determinants that were found to play the most substantial and frequent role in implementation processes:

• Leadership Engagement: The involvement, commitment, and accountability of leaders and managers.
• Formally Appointed Internal Implementation Leaders: Individuals from within the organization who are formally designated with implementation responsibilities.
• Compatibility: The degree of fit between the intervention and existing values, workflows, and perceived needs.
• Available Resources: The allocation of sufficient funding, time, and other necessary assets.
• External Change Agents: Individuals from outside the organization who influence the implementation effort.
• Champions: Supportive individuals who actively and enthusiastically drive the implementation process.
• Relative Advantage: The perceived superiority of the new intervention compared to existing alternatives.
• Key Stakeholders: Individuals who are affected by or can influence the implementation effort [10] [14].

This review highlighted that while quantifying qualitative data can remove some nuance, focusing on these key determinants helps researchers and practitioners prioritize factors most likely to influence the success of their implementation efforts [10].

Evidence on Frequently Tested Implementation Strategies

Complementing the work on determinants, a 2024 systematic review of 129 experimentally tested implementation strategies provided evidence on the most commonly applied and effective strategies across diverse health and human service settings [15]. Using the Expert Recommendations for Implementing Change (ERIC) taxonomy, the review found that strategies were often used in combination, with the most frequent being:

• Distribute Educational Materials
• Conduct Educational Meetings
• Audit and Provide Feedback
• External Facilitation [15]

The review noted that nineteen implementation strategies were frequently tested and associated with significantly improved outcomes, though many others lacked sufficient testing to draw firm conclusions [15].

The table below synthesizes the key determinants and aligns them with exemplary implementation strategies, providing a foundational guide for the matching process.

Table 1: Key Implementation Determinants and Associated Implementation Strategies

Key Determinant (CFIR Construct)	Definition	Exemplary Implementation Strategies (from ERIC/ISAC)
Leadership Engagement	Involvement, commitment, and accountability of leaders and managers [10].	Secure executive sponsorship, Identify and prepare champions [15]
Formally Appointed Internal Implementation Leaders	Individuals from within the organization formally designated with implementation responsibilities [10].	Build a implementation team, Shadow other experts [13]
Compatibility	The fit between the intervention and existing values, workflows, and needs [10].	Tailor strategies, Adapt and tailor to context, Develop resource sharing agreements [13] [15]
Available Resources	The allocation of sufficient funding, time, and other necessary assets [10].	Access new funding, Alter incentive/allowance structures, Fund and contract for the EBI [13]
External Change Agents	Individuals from outside the organization who influence the implementation effort [10].	Centralize technical assistance, Facilitation, Create a learning collaborative [15]
Champions	Individuals who actively and enthusiastically drive the implementation [10].	Identify and prepare champions, Use an implementation advisor [13] [15]
Relative Advantage	The perceived superiority of the new intervention versus alternatives [10].	Conduct local consensus discussions, Develop educational materials [15]
Key Stakeholders	Individuals who are affected by or can influence the implementation [10].	Organize implementation teams, Conduct local needs assessment [13] [15]

Experimental Protocols

Protocol 1: Determinant Identification and Rating Using the CFIR Framework

Objective: To systematically identify and assess the strength and valence (positive or negative influence) of implementation determinants in a specific context prior to strategy selection.

Background: The CFIR framework offers a comprehensive, multi-level taxonomy of constructs known to influence implementation. The Damschroder & Lowery (2013) rating system allows for the quantification of these determinants, moving beyond simple identification to an assessment of their impact [10].

Materials and Reagents:

• Interview/Focus Group Guides: Semi-structured guides based on CFIR constructs.
• Data Recording Equipment: Audio recorders and transcription software.
• Qualitative Data Analysis Software: e.g., NVivo, Dedoose, or MAXQDA.
• Rating Spreadsheet: A matrix with CFIR constructs and a rating scale from -2 to +2.

Procedure:

• Planning and Preparation:
  • Form a multidisciplinary assessment team including researchers and relevant practitioners.
  • Select the CFIR constructs most relevant to your project from the original 2009 or updated 2022 framework. The eight key determinants provide a prioritized starting point [10].
• Data Collection:
  • Conduct semi-structured interviews and/or focus groups with key stakeholder groups (e.g., leadership, clinical staff, patients).
  • Probe for experiences, perceptions, and beliefs related to the implementation of the evidence-based intervention, mapping responses to CFIR constructs.
• Data Analysis and Rating:
  • Transcribe and de-identify audio recordings.
  • Code the qualitative data deductively using the selected CFIR constructs as a codebook.
  • For each construct, assign a rating based on the criteria below. This should be done by at least two independent raters, with discrepancies resolved through consensus.
    • -2: Major barrier (strong negative influence)
    • -1: Minor barrier
    • 0: Neutral/mixed influence
    • +1: Minor facilitator
    • +2: Major facilitator (strong positive influence) [10]
• Synthesis:
  • Create a determinant profile for the implementation site, highlighting the highest-rated barriers (-2) and facilitators (+2). These are the primary targets for strategy matching.

Protocol 2: The ISAC Match Process for Strategy Selection and Tailoring

Objective: To provide a pragmatic, rapid, and collaborative process for selecting and tailoring implementation strategies to address prioritized determinants in community settings, particularly within integrated research-practice partnerships (IRPPs).

Background: The ISAC Match process was developed to address the lack of community-friendly guidance for moving from determinants to strategies. It emphasizes a strength-based approach, considering both barriers and facilitators, and ensures strategies are feasible within the specific context [13].

Materials and Reagents:

• Prioritized List of Determinants: Output from Protocol 1.
• ISAC Compilation: A list of 40 implementation strategies tailored for community settings.
• ERIC Compilation: A list of 73 implementation strategies, originally developed for clinical contexts.
• Facilitation Materials: Whiteboards, sticky notes, and voting tools (e.g., dots for prioritization).

Procedure:

• Step 1: Conduct Contextual Inquiry (if needed):
  • Review existing data (e.g., from Protocol 1) on barriers and facilitators. If information is sufficient, proceed. If gaps exist, conduct rapid contextual inquiry using methods like rapid qualitative analysis or a "brainwriting premortem" to identify potential failures [13].
  • Output: A confirmed and comprehensive list of key determinants.
• Step 2: Identify Existing Implementation Strategies:
  • Engage practitioners in a discussion to identify strategies already in use within the organization that could support implementation. This builds on existing strengths and infrastructure.
  • Output: A list of current, potentially reinforcing, strategies.
• Step 3: Select New Implementation Strategies:
  • Use the ISAC guidance tool to map potential new strategies to the prioritized determinants, considering the level of the determinant (e.g., individual, organizational) and the desired implementation outcome [13].
  • If working in a clinical-community hybrid setting, supplement with the ERIC compilation.
  • Prioritize the list of potential new strategies based on feasibility and importance using a 2x2 grid or a nominal group technique [13].
  • Output: A shortlist of high-priority, candidate implementation strategies.
• Step 4: Tailor Implementation Strategies:
  • For each shortlisted strategy, conduct a tailoring session using methods like a brainwriting premortem ("Why might this strategy fail in our context?") or liberating structures [13].
  • Collaboratively refine the strategy's specifics—who, what, when, how—to ensure it fits the local context, culture, and resources.
  • Output: A set of tailored, context-specific implementation strategies with a clear plan for deployment.

Visualizations

Key Determinant Identification Workflow

The diagram below outlines the systematic process for identifying and rating key implementation determinants, from initial planning to the final synthesis used for strategy selection.

Strategy Matching and Tailoring Process

This diagram illustrates the four-step ISAC Match process, a collaborative and iterative approach for selecting and tailoring implementation strategies based on identified determinants.

The Scientist's Toolkit

Table 2: Essential Reagents and Resources for Determinants Research

Item	Category	Function/Application in Research
CFIR Codebook	Conceptual Framework	Provides standardized definitions and interview prompts for implementation determinants, ensuring consistent data collection and analysis [10].
Damschroder & Lowery Rating Scale	Analytical Tool	Enables quantification of qualitative data by assigning magnitude/valence scores (-2 to +2) to determinants, allowing for prioritization [10] [14].
ERIC Strategy Compilation	Strategy Repository	A taxonomy of 73 implementation strategies primarily developed for clinical settings; used for selecting strategies to address barriers [13] [15].
ISAC Strategy Compilation	Strategy Repository	A community-focused compilation of 40 strategies; essential for research in non-clinical settings like public health or social services [13].
Qualitative Data Analysis Software (NVivo, Dedoose)	Software	Facilitates organization, coding, and analysis of large volumes of qualitative data (interviews, focus groups) collected during contextual inquiry.
RE-AIM Framework	Evaluation Framework	Guides the assessment of implementation outcomes (Reach, Effectiveness, Adoption, Implementation, Maintenance) to evaluate strategy impact [15].

What Are Implementation Strategies? Distinguishing 'What' from 'How'

Implementation strategies are the methods and techniques used to enhance the adoption, implementation, and sustainability of evidence-based interventions. This article delineates the critical distinction between the "what" (evidence-based interventions) and the "how" (implementation strategies) within implementation science. Framed for determinants research, it provides a structured overview of strategy classifications, evidence on effectiveness, and detailed protocols for selecting and tailoring strategies to address specific implementation barriers. Designed for researchers and drug development professionals, the content includes quantitative evidence summaries, experimental protocols for strategy application, and visual tools to guide the matching of strategies to contextual determinants.

In implementation science, the core challenge is not merely discovering effective interventions but ensuring their integration into routine practice. This process hinges on a fundamental distinction: the "what" versus the "how." The "what" is the Evidence-Based Intervention (EBI)—a program, practice, drug, or policy that has been empirically shown to improve outcomes [16]. The "how" is the implementation strategy—defined as methods or techniques used to enhance the adoption, implementation, and sustainability of an EBI [17] [18]. For drug development professionals, this translates to distinguishing the therapeutic agent (the "what") from the strategies required to ensure its appropriate prescription, adherence, and integration into formularies and clinical pathways (the "how"). The precise specification of these strategies is a prerequisite for scientific reproducibility, testing, and building a cumulative evidence base on how best to implement [18].

A Framework for Classifying Implementation Strategies

Organizing the multitude of documented implementation strategies into a coherent framework is essential for selecting, reporting, and researching them. The following table summarizes a classification system that categorizes strategies based on their primary purpose and function [17] [19].

Table 1: A Classification of Implementation Strategy Types

Strategy Class	Definition	Example Actions
Dissemination Strategies	Target knowledge, awareness, and intentions to adopt an innovation by developing and sharing key messages [17].	Develop and distribute educational materials; use mass media [17] [16].
Implementation Process Strategies	Enable the planning and delivery of an innovation through distinct stages, including assessing context and engaging stakeholders [17].	Assess for readiness and identify barriers; audit and provide feedback; use an implementation team [17] [16].
Integration Strategies	Aim to weave an innovation into the fabric of a specific setting, often involving modifications to existing structures and roles [17] [19].	Revise professional roles; adapt the EBI; assess and redesign workflows [17] [16] [20].
Capacity-Building Strategies	Increase the motivation, capability, and general resources of individuals and organizations to engage in implementation [17] [19].	Conduct educational meetings; provide ongoing training; identify and prepare champions [17] [16].
Scale-Up Strategies	Build system-level capacity to implement a policy, practice, or service across multiple settings or populations [17].	Use train-the-trainer models; develop system infrastructure like data systems [17].

Another prevalent taxonomy in the field is the Expert Recommendations for Implementing Change (ERIC), which compiles 73 discrete implementation strategies grouped into clusters [16]. The following workflow diagram synthesizes these classification systems into a practical pathway for the strategy selection process, integral to determinants research.

The Evidence Base: Effectiveness of Implementation Strategies

The selection of implementation strategies should be informed by evidence of their effectiveness. A major landscape review assessed the strength of evidence for common implementation strategies, providing critical insight for researchers designing implementation trials [20]. The following tables summarize the evidence for strategies that showed the strongest support for improving implementation and health outcomes, respectively.

Table 2: Evidence for Strategies Improving Implementation Outcomes (e.g., Adoption, Fidelity)

Implementation Strategy	Percentage of Studies Showing Improvement	Overall Evidence Strength
Assess and redesign workflows	100% (8 of 8 studies)	Moderate
Conduct cyclical small tests of change	90% (9 of 10 studies)	Indirect
Audit and provide feedback	88% (14 of 16 studies)	Supportive
Prepare patients/consumers	86% (6 of 7 studies)	Supportive
Remind clinicians	86% (6 of 7 studies)	Moderate
Assess for readiness/identify barriers	85% (11 of 13 studies)	Indirect
Clinical decision support tools	83% (5 of 6 studies)	Supportive
Facilitate collaborative learning	83% (5 of 6 studies)	Moderate
Provide implementation facilitation	79% (15 of 19 studies)	Supportive
Promote adaptability within the EBP	75% (9 of 12 studies)	Supportive
Centralize technical assistance	71% (5 of 7 studies)	Limited

Table 3: Evidence for Strategies Improving Health Outcomes

Implementation Strategy	Percentage of Studies Showing Improvement	Overall Evidence Strength
Centralize technical assistance	75% (3 of 4 studies)	Limited
Conduct cyclical small tests of change	57% (4 of 7 studies)	Indirect
Clinical decision support tools	50% (2 of 4 studies)	Supportive
Prepare patients/consumers	50% (2 of 4 studies)	Supportive
Assess and redesign workflows	50% (3 of 6 studies)	Moderate
Provide implementation facilitation	45% (5 of 11 studies)	Supportive
Assess for readiness/identify barriers	38% (3 of 8 studies)	Indirect
Audit and provide feedback	36% (4 of 11 studies)	Supportive
Promote adaptability within the EBP	33% (3 of 9 studies)	Supportive
Remind clinicians	33% (1 of 3 studies)	Moderate
Facilitate collaborative learning	40% (2 of 5 studies)	Moderate

A key finding from the evidence is that implementation strategies are most often used and studied in combination. For instance, "conduct educational meetings" and "distribute educational materials" are frequently bundled with other strategies [20]. This underscores the importance of multi-faceted, tailored approaches rather than relying on single, discrete strategies.

Experimental Protocols for Matching Strategies to Determinants

A critical objective in implementation science is to move from a one-size-fits-all approach to a precision-based model where strategies are systematically matched to contextual determinants. The following protocols provide a methodological roadmap for this process.

Protocol 1: Determinant Identification using the COM-B Model

The COM-B model provides a framework for diagnosing barriers to implementation, positing that for a behavior (B) to occur, individuals and teams must have the Capability (C), Opportunity (O), and Motivation (M) to perform it [21].

• Define the Target Behavior: Formulate the core implementation behavior in specific terms. Example: "Clinical pharmacists in the cardiology clinic will initiate a conversation with physicians about switching eligible patients from Drug A to the new, more cost-effective Evidence-Based Drug B within 2 weeks of its formulary addition."
• Data Collection on Determinants: Use mixed methods to gather data on barriers and enablers.
  • Methods: Conduct semi-structured interviews and focus groups with key stakeholders (e.g., physicians, pharmacists, nurses). Supplement with quantitative surveys, such as the Organizational Readiness for Implementing Change (ORIC) or tailored questionnaires.
  • Probes: Structure inquiries around the COM-B components:
    • Capability: "Do providers know the new drug's inclusion criteria and dosing protocol?" (Psychological) "Do they have the skills to administer it?" (Physical)
    • Opportunity: "Is the new drug readily available in the automated dispensing cabinet?" (Physical) "Do social norms support its use among senior clinicians?" (Social)
    • Motivation: "Do providers believe the new drug offers a significant patient benefit over the old standard?" (Reflective) "Is there a feeling of automaticity or habit to prescribe the old drug?" (Automatic)
• Analysis and Synthesis: Thematically analyze qualitative data and triangulate with quantitative findings. Create a determinant matrix categorized by COM-B and by level (e.g., individual, team, organization).

Protocol 2: Strategy Selection using Implementation Mapping

Implementation Mapping is a systematic process for selecting and tailoring implementation strategies based on the identified determinants [22].

• Generate Strategy Options: Based on the determinant matrix from Protocol 1, brainstorm potential implementation strategies. Utilize existing compilations like the ERIC taxonomy [16] to ensure a comprehensive consideration of options.
  • Example Determinant: "Lack of knowledge about the new drug's administration schedule" (Capability Barrier).
  • Example Strategy: "Conduct interactive educational outreach visits."
• Select and Tailor Strategies: Evaluate the feasibility, practicality, and likely effectiveness of the generated strategies. Use a structured tool, such as the StrategEase Tool [22], to map strategies to specific determinants. This step involves customizing the broad strategy to the local context—for example, determining the content, format, and timing of the educational outreach visits.
• Specify Implementation Strategy Components: To ensure replicability and precise measurement, specify the operational details of each chosen strategy as recommended by Proctor et al. [18]:
  • Actor: Who performs the strategy? (e.g., clinical pharmacy specialist)
  • Action: What is the specific activity? (e.g., one-on-one, 15-minute educational visit)
  • Action Target: What determinant is being addressed? (e.g., provider knowledge about administration)
  • Temporality: When and how often? (e.g., within first month of launch, repeated for new staff)
  • Dose: Duration and intensity? (e.g., 15-minute session)
  • Implementation Outcome: What is the expected result? (e.g., increased knowledge, adoption)
• Develop a Causal Pathway Diagram (CPD): Create a visual model that hypothesizes the mechanism through which the strategy is expected to work. The CPD links the strategy to the determinant, the resultant change in behavior, and the ultimate implementation and health outcomes, making the theory of change explicit and testable [16].

The Scientist's Toolkit: Key Reagents for Implementation Research

For researchers embarking on implementation trials, the following "reagents" or core resources are essential for rigorous study design and execution.

Table 4: Essential Reagents for Implementation Science Research

Tool/Resource Name	Function in Research	Application Context
ERIC Taxonomy [18] [16]	A compiled menu of 73 defined implementation strategies.	Serves as a standardized "periodic table" of strategies for selection, naming, and reporting.
Consolidated Framework for Implementation Research (CFIR) [19]	A meta-theoretical framework of constructs that influence implementation.	Used to systematically identify and categorize determinants (barriers and enablers) across multiple levels.
Interactive Systems Framework (ISF) [19]	Distinguishes three systems: Synthesis & Translation, Support, and Delivery.	Helps classify the "actor" for a strategy, clarifying roles and necessary capacities for implementation.
Proctor's Reporting Guidelines [18]	A checklist for specifying implementation strategies (actor, action, target, etc.).	Ensures methodological precision and reproducibility in describing intervention "how-to".
Causal Pathway Diagram (CPD) [16]	A visual tool for mapping hypothesized mechanistic links between a strategy and outcomes.	Makes the theory of change explicit, guiding evaluation of strategy mechanisms and effectiveness.

The systematic application of implementation strategies is what bridges the chasm between clinical discovery and public health impact. For the drug development community, mastering the "how" is as critical as innovating the "what." This involves a disciplined, research-driven process: using frameworks like COM-B to diagnose implementation barriers, consulting evidence on strategy effectiveness, and employing structured protocols like Implementation Mapping to tailor strategies to specific determinants. By treating implementation strategies as a core, specifiable component of research and development, scientists and professionals can significantly accelerate the reliable and equitable integration of new therapies into the care that patients receive.

In implementation science, the successful adoption of evidence-based interventions (EBIs) in real-world settings hinges on a critical, often overlooked, process: the systematic matching of implementation strategies to specific contextual determinants. Implementation strategies are the "how" – the methods or techniques used to enhance the adoption, implementation, and sustainment of evidence-based interventions [16]. Their effectiveness is not universal; it is maximized when they are precisely selected to address specific barriers and leverage facilitators, known as determinants, within a given context. This application note provides researchers and drug development professionals with structured protocols and tools to master this matching process, thereby increasing the efficiency and impact of their implementation efforts.

Background and Key Concepts

Defining Core Constructs

• Evidence-Based Interventions (EBIs): The "what" that is being implemented. These are the programs, practices, principles, procedures, products, or policies that have been demonstrated to improve health behaviors or outcomes [16]. In drug development, this could be a new therapeutic protocol or a validated clinical guideline.
• Implementation Strategies: The actions taken to enhance the adoption, implementation, and sustainability of EBIs. The Expert Recommendations for Implementing Change (ERIC) project has compiled a standardized taxonomy of 73 such strategies, grouped into nine clusters for easier application [16] [23].
• Determinants of Implementation: The barriers and facilitators that influence the implementation process. These can exist at multiple levels of the social ecological model, including the individual (e.g., clinician knowledge), organizational (e.g., clinic workflow), and system levels (e.g., reimbursement policies).

The Rationale for Matching

The premise is straightforward: employing a strategy that does not target a primary barrier is an inefficient use of resources and is unlikely to succeed. For instance, if the main barrier is a lack of clinician knowledge, then an educational strategy is well-matched. However, if the barrier is a flawed payment system, the same educational strategy will fail unless paired with a financial strategy like altering incentive structures [16]. A 2024 systematic review of 129 experimentally tested implementation studies found that commonly used strategies, including Distribute Educational Materials, Conduct Educational Meetings, Audit and Provide Feedback, and External Facilitation, were often associated with significantly improved outcomes when applied appropriately [23].

Quantitative Synthesis of Experimentally Tested Strategies

The following table summarizes data from a systematic review of 129 methodologically rigorous studies (2010-2022) that experimentally tested implementation strategies, providing a quantitative evidence base for strategy selection [23].

Table 1: Experimentally Tested Implementation Strategies and Their Associated Outcomes

Implementation Strategy (ERIC Taxonomy)	Frequency in Experimental Arms (n=129 studies)	Outcomes Most Frequently Assessed	Association with Significant Improvement
Distribute Educational Materials	99	Effectiveness, Implementation	Frequently associated with positive outcomes
Conduct Educational Meetings	96	Effectiveness, Implementation	Frequently associated with positive outcomes
Audit and Provide Feedback	76	Effectiveness, Implementation	Yes
External Facilitation	59	Implementation, Adoption	Yes
Tailor Strategies	45	Reach, Adoption	Data varies
Identify and Prepare Champions	44	Implementation, Maintenance	Yes
Use Train-the-Trainer Strategies	39	Implementation	Data varies
Develop Educational Materials	37	Effectiveness	Data varies
Build a Coalition	36	Adoption	Data varies
Conduct Ongoing Training	36	Implementation, Effectiveness	Yes

Protocols for Matching Strategies to Determinants

Protocol 1: Determinant Identification and Analysis

Objective: To systematically identify and prioritize barriers and facilitators to the implementation of a specific EBI in a given context.

Methodology:

• Preparation:
  • Conduct a Literature Review: Identify known determinants for the EBI or similar interventions in comparable settings.
  • Form an Implementation Team: Assemble a multi-disciplinary team including clinicians, staff, administrators, and patient representatives.
  • Develop a Preliminary Determinant Framework: Use an established framework (e.g., Consolidated Framework for Implementation Research - CFIR) to guide data collection.

• Data Collection (Mixed-Methods):

  • Surveys: Administer quantitative surveys to a broad group of stakeholders to assess perceived barriers and facilitators across different domains (e.g., evidence strength, organizational culture).
  • Focus Groups & Interviews: Conduct qualitative focus groups and individual interviews with key informants to explore determinants in depth and understand their interrelationships.
  • Observation: Directly observe the implementation context to identify workflow and environmental barriers not captured through self-report.

• Data Analysis and Synthesis:

  • Quantitative Analysis: Use descriptive statistics from surveys to rank-order determinants by perceived strength and prevalence. Employ factor analysis to identify underlying constructs [24].
  • Qualitative Analysis: Employ thematic analysis or content analysis to code interview and focus group transcripts, identifying major themes and specific determinants [24].
  • Triangulation and Prioritization: Integrate quantitative and qualitative findings to create a consolidated list of determinants. Work with the implementation team to prioritize determinants based on their perceived impact and mutability.

Protocol 2: Strategy Selection and Specification

Objective: To select and precisely specify the implementation strategies that will be used to address the prioritized determinants.

Methodology:

• Matching Process:
  • Utilize a matching tool, such as a concept mapping approach or the ERIC compatibility matrix, to link prioritized determinants to candidate implementation strategies [16].
  • For example, if a key barrier is "forgetting to use the EBI," a matched strategy would be "provide reminders." If the barrier is "lack of motivation," a matched strategy could be "alter incentive/allowance structures" [16].

• Strategy Specification:

  • For each selected strategy, use the Proctor et al. (2013) guidelines for reporting to ensure replicability. Specify the actor, action, target, temporal, dose, and outcome for every strategy [16].
  • Example: Instead of "we will use audit and feedback," specify "the quality improvement team (actor) will generate monthly reports on EBI adherence (action) and email them to prescribing clinicians (target) for six months (temporal) with a comparison to the clinic average (dose) to increase adherence rates (outcome)."

• Causal Pathway Diagramming:

  • Develop a visual model, such as a Causal Pathway Diagram (CPD) or Logic Model, to hypothesize how the strategies will work [16].
  • This diagram should map the links between the specific strategies, the mechanisms of action (how they address determinants), intermediate outcomes (e.g., increased knowledge), and final implementation outcomes (e.g., fidelity).

Diagram Title: Causal Pathway from Determinant to Outcome

Protocol 3: Experimental Testing of Matched Strategies

Objective: To quantitatively evaluate the impact of the matched implementation strategies on implementation and effectiveness outcomes.

Methodology:

• Study Design:
  • Randomized Controlled Trials (RCTs): The gold standard for establishing efficacy. Implementation-focused RCTs often randomize at the cluster level (e.g., clinics, hospitals) to avoid contamination [25].
  • Stepped-Wedge Designs: A pragmatic design where all clusters eventually receive the implementation strategy in a staggered fashion, allowing each cluster to serve as its own control [25].
  • Interrupted Time Series (ITS): A strong quasi-experimental design used when randomization is not feasible, involving multiple measurements before and after the strategy's introduction [25].

• Outcome Measurement:

  • Classify and measure outcomes using the RE-AIM framework (Reach, Effectiveness, Adoption, Implementation, Maintenance) [23].
  • Implementation Outcome: The primary outcome is often the degree of fidelity to the EBI. This is measured through standardized checklists, chart reviews, or electronic data extraction.
  • Effectiveness Outcome: Measure the impact of the EBI on the intended patient-level outcomes (e.g., symptom reduction, biomarker levels).

• Data Analysis:

  • For RCTs and stepped-wedge designs, use multilevel regression models (e.g., mixed-effects models) to account for clustering of patients within sites, comparing outcomes between intervention and control conditions [24] [25].
  • For ITS designs, use segmented regression analysis to test for a change in level and trend following the introduction of the implementation strategy [25].
  • Report both statistical significance and effect sizes to convey the magnitude of the strategy's impact.

Diagram Title: Workflow for Experimental Testing of Strategies

The Scientist's Toolkit: Research Reagent Solutions

Table 2: Essential Resources for Implementation Strategy and Determinant Research

Resource Name/Type	Function/Purpose	Example Use Case
ERIC Taxonomy	A standardized compilation of 73 implementation strategy terms and definitions. Provides a common language for researchers and practitioners.	Used to precisely name and define the strategies being employed or tested in a study protocol or publication [16] [23].
RE-AIM Framework	An evaluation framework to classify outcomes into five dimensions: Reach, Effectiveness, Adoption, Implementation, and Maintenance.	Guides the comprehensive planning and measurement of implementation outcomes beyond simple fidelity, assessing real-world impact [23].
Determinant Frameworks (e.g., CFIR)	Theoretical frameworks that catalog potential barriers and facilitators across multiple domains (e.g., intervention, inner setting, outer setting).	Serves as a structured codebook for qualitative data analysis and ensures a comprehensive assessment of contextual factors.
Causal Pathway Diagram (CPD)	A visual tool for mapping the hypothesized causal relationships between strategies, mechanisms, and outcomes.	Used during the study design phase to articulate the theory of change and identify key mediators to measure [16].
Statistical Analysis Software (e.g., R, Stata)	Platforms capable of running advanced multilevel and time-series statistical models.	Essential for analyzing clustered data from RCTs or stepped-wedge designs and accounting for within-site correlations [24] [25].

The Practitioner's Toolkit: Methods and Processes for Effective Matching

A Stepwise Guide to Using the CFIR-ERIC Implementation Strategy Matching Tool

A fundamental challenge in implementation science is moving from the identification of contextual barriers to the selection of appropriate implementation strategies. The CFIR-ERIC Implementation Strategy Matching Tool was developed to address this challenge by providing a systematic, evidence-informed approach for selecting strategies based on identified determinants [26]. This tool bridges two key resources: the Consolidated Framework for Implementation Research (CFIR), used to assess contextual determinants (barriers and facilitators), and the Expert Recommendations for Implementing Change (ERIC), a compilation of 73 discrete implementation strategies [12] [26].

This guide provides a detailed protocol for using the CFIR-ERIC Matching Tool, framing its application within the broader context of matching implementation strategies to determinants research. The process enables researchers and implementation practitioners to tailor strategies to their specific context, thereby enhancing the potential for successful implementation of evidence-based practices [27].

Background and Development

The CFIR-ERIC Matching Tool was developed through research involving 169 implementation experts who participated in an online survey to match ERIC strategies to CFIR-based barriers [26] [28]. Participants were presented with barrier descriptions based on CFIR constructs and asked to rank up to seven ERIC strategies that would best address each barrier [26].

A key finding from this development process was the considerable heterogeneity in expert recommendations. Across the 39 CFIR barriers, an average of 47 different ERIC strategies were endorsed at least once for each barrier, indicating few consistent relationships between specific barriers and strategies [26] [28]. Despite this variability, the tool provides a structured starting point for strategy selection by aggregating expert endorsements.

Table 1: Key Development Metrics of the CFIR-ERIC Matching Tool

Development Aspect	Description	Source
Expert Participants	169 implementation researchers and practitioners	[26]
Response Rate	39% (169 of 435 invited)	[26]
CFIR Barriers Assessed	39 constructs from the CFIR framework	[26]
ERIC Strategies	73 discrete implementation strategies	[12]
Endorsement Heterogeneity	Average of 47 different strategies endorsed per barrier	[26] [28]
Consensus Strategies	33 strategy-barrier combinations endorsed by >50% of experts	[28]

Phase 1: Context Assessment and Barrier Identification

Step 1: Conduct a Context Assessment

Before using the matching tool, you must first conduct a comprehensive assessment of your implementation context using the CFIR framework. The CFIR includes 39 constructs organized across five domains: Intervention Characteristics, Outer Setting, Inner Setting, Characteristics of Individuals, and Implementation Process [26].

Protocol: Utilize CFIR-based data collection tools, such as:

• CFIR Construct Example Questions: Customizable, open-ended questions for each construct [29]
• 14-Item pCAT: A short survey for quantitative ratings of key CFIR constructs [29]
• Interview Guides: Structured questions based on CFIR constructs [30]

Data Collection Methods:

• Conduct individual interviews with key stakeholders (clinicians, administrators, patients)
• Facilitate focus groups to identify shared perspectives
• Administer surveys to assess prevalence of specific determinants
• Review relevant documents and organizational records

Step 2: Identify and Prioritize Barriers

Analyze the data collected to identify specific barriers to implementation. The CFIR Coding Guidelines can be used to systematically code qualitative data to specific CFIR constructs [29].

Protocol for Data Analysis:

• Transcribe and clean qualitative data from interviews and focus groups
• Code data to CFIR constructs using established coding guidelines [29]
• Create a determinant matrix that maps identified barriers to specific CFIR constructs using the CFIR Construct x Inner Setting Matrix Template [29]
• Prioritize barriers based on their perceived impact on implementation success, feasibility to address, and prevalence across stakeholders

Phase 2: Strategy Selection Using the Matching Tool

Step 3: Access and Navigate the Matching Tool

The CFIR-ERIC Matching Tool is available as a downloadable file from the official CFIR website [12] [31].

Protocol:

• Navigate to the CFIR guide website (cfirguide.org)
• Access the "Strategy Design" page or use the direct link to download the Updated CFIR x ERIC Matching File [12] [31]
• Provide contact information when prompted to download the tool [31]
• Open the downloaded file, which typically appears as a matrix with CFIR constructs and ERIC strategies

Step 4: Input Identified Barriers

Enter the prioritized CFIR barriers identified in Step 2 into the matching tool.

Protocol:

• Locate the section of the tool for specifying high-priority CFIR-based barriers
• Select the specific CFIR constructs that represent your identified barriers
• If using the digital tool, these selections will automatically generate a list of potential strategies

Step 5: Interpret Strategy Recommendations

The tool provides a prioritized list of ERIC strategies based on expert endorsements from the original research [26] [28].

Interpretation Protocol:

• Color-coded endorsements: The tool uses a color-coding system where:
  • GREEN indicates a strategy endorsed by a majority (>50%) of experts for a specific barrier [12]
  • YELLOW indicates endorsement by 20-49% of experts [12]
• Cumulative Percent: The "Cumulative Percent" metric indicates the strength of endorsement for a strategy across all selected barriers [12]
• Prioritization: Strategies with higher cumulative percentages and green coding should be prioritized for consideration

Table 2: Interpretation of CFIR-ERIC Matching Tool Outputs

Output Indicator	Interpretation	Action Implication
Green-coded Cell	Strategy endorsed by >50% of experts for a specific barrier	Strong candidate for inclusion in implementation plan
Yellow-coded Cell	Strategy endorsed by 20-49% of experts for a specific barrier	Moderate evidence; consider for inclusion
Cumulative Percent	Summed endorsement across all selected barriers	Higher percentage indicates broader expert support
Strategy Ranking	Ordered list of strategies based on expert endorsements	Prioritize higher-ranked strategies in implementation planning

The following diagram illustrates the complete workflow from context assessment to strategy implementation:

Phase 3: Strategy Operationalization and Tracking

Step 6: Operationalize Selected Strategies

Once strategies are selected using the matching tool, they must be fully specified and operationalized for your specific context.

Protocol for Strategy Specification: Following Proctor et al.'s recommendations for reporting implementation strategies, specify each strategy by [32] [27]:

• Actor: Who will enact the strategy?
• Action: What specific activities will be performed?
• Action Target: What is the strategy intended to change?
• Temporality: When and how often will the strategy be deployed?
• Dose: What is the duration and intensity of the strategy?
• Implementation Outcomes Affected: Which outcomes (e.g., acceptability, feasibility) is the strategy expected to influence?
• Justification: Why was this strategy selected? (Reference the CFIR-ERIC Matching Tool results)

Implementation Mapping: Fernandez et al.'s Implementation Mapping process provides a systematic approach for operationalizing strategy choices based on the matching tool, explicitly identifying and designing strategies based on hypothesized underlying change theories [28].

Step 7: Track Strategy Implementation and Modifications

Systematically track the use of implementation strategies over time to enable evaluation of their effectiveness and documentation of adaptations.

Protocol for Strategy Tracking: The Longitudinal Implementation Strategy Tracking System (LISTS) methodology provides a structured approach for this purpose [32]. LISTS includes three components:

• Strategy Assessment: Documents strategy specification, reporting, and modification elements
• Data Capture Platform: Enables consistent documentation of strategy use
• User's Guide: Procedures for using the tracking system [32]

Tracking Elements:

• Document when each strategy is initiated and concluded
• Record any modifications to strategy delivery (dose, timing, approach)
• Note contextual factors that influence strategy implementation
• Track resources required for each strategy

Case Illustration

A study implementing the Telephone Lifestyle Coaching (TLC) program across 11 Veterans Affairs medical centers used the CFIR-ERIC Matching Tool to address seven key barriers identified through a CFIR assessment [12]. The tool generated a list of potential strategies sorted by cumulative endorsement levels. "Identify and Prepare Champions" emerged as the strategy with the highest cumulative endorsement (248%) across all seven barriers [12]. This strategy was color-coded green for two specific barriers: "Engaging: Formally Appointed Internal Implementation Leader" and "Engaging: Key Stakeholders" [12].

Limitations and Considerations

When using the CFIR-ERIC Matching Tool, researchers should be aware of several important limitations:

• Expert Heterogeneity: The considerable diversity in expert recommendations means there are few universally agreed-upon strategy-barrier pairings [26] [28]
• Contextual Specificity: The tool provides general recommendations that must be adapted to local contexts and implementation goals
• Theoretical Mechanisms: The tool does not explicitly address the underlying mechanisms of change through which strategies affect barriers [28]
• Dynamic Nature: Implementation is dynamic, and strategy selection should be revisited throughout the implementation process

Table 3: Key Research Reagents and Resources for Implementation Strategy Matching

Resource/Tool	Function/Purpose	Access Point
CFIR-ERIC Matching Tool	Matrix linking CFIR barriers to ERIC implementation strategies	CFIRGuide.org/choosing-strategies/ [12]
Updated CFIR x ERIC Matching File	Updated version aligning with the revised CFIR	CFIRGuide.org/download-updated-cfirxeric-matching-file/ [31]
ERIC Implementation Strategies	Comprehensive list of 73 discrete implementation strategies with definitions	Powell et al. 2015 publication [12]
CFIR Construct Example Questions	Interview and survey questions for assessing CFIR constructs	CFIRGuide.org/tools-and-templates/ [29]
LISTS (Longitudinal Implementation Strategy Tracking System)	Methodology for tracking strategy use and modifications over time	Walsh-Bailey et al. 2023 publication [32]
Implementation Mapping Framework	5-step process for operationalizing strategy choices	Fernandez et al. 2019 publication [27] [28]

The following diagram illustrates the theoretical challenge of matching barriers to strategies, highlighting the heterogeneity found in the development research:

The CFIR-ERIC Implementation Strategy Matching Tool provides a systematic, evidence-informed approach for selecting implementation strategies based on identified contextual determinants. While the tool offers valuable guidance based on expert recommendations, users should recognize its limitations and complement its use with additional methods such as Implementation Mapping and systematic tracking using approaches like LISTS. By following the stepwise protocol outlined in this guide, researchers and implementation practitioners can enhance the precision and effectiveness of their implementation efforts, ultimately contributing to improved uptake of evidence-based practices in healthcare settings.

The Implementation Strategies Applied in Communities Matching Process (ISAC Match) addresses a significant gap in implementation science by providing a systematic, pragmatic method for selecting and tailoring implementation strategies in community (non-clinical) settings [33] [34]. Despite the critical importance of evidence-based interventions (EBIs) in public health, limited guidance exists on feasible processes for matching implementation strategies to contextual determinants in community settings where resources are often constrained and implementation-specific staff are lacking [33]. The ISAC Match framework was specifically developed to overcome the limitations of existing matching tools, such as the Expert Recommendations for Implementing Change (ERIC) compilation, which was developed in clinical settings and can be difficult to apply in community contexts due to clinical language and the overwhelming number of strategies generated [33].

This protocol outlines the application of ISAC Match within integrated research-practice partnerships (IRPPs), emphasizing its structured four-step approach to contextual inquiry, strategy identification, selection, and tailoring [33]. The process is designed to be rapid and relevant for community settings while incorporating health equity considerations to ensure implementation strategies narrow rather than widen existing health disparities [33]. The guidance presented here expands on the original ISAC Match formulation with detailed methodologies, application notes, and visual frameworks to enhance practical application for researchers and implementation practitioners.

Theoretical Framework and Positioning within Determinants Research

The ISAC Match process operates within established implementation science frameworks, explicitly addressing the "black box" of implementation strategy selection [33]. The process integrates determinant frameworks like the Consolidated Framework for Implementation Research (CFIR) to understand barriers and facilitators, while also connecting to evaluation frameworks such as RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) to assess implementation outcomes [33].

Unlike clinical settings where standardized processes often exist, community settings such as social services, faith-based organizations, education, and non-clinical public health organizations require more flexible approaches [33]. The ISAC compilation upon which the matching process is built contains 40 implementation strategies used in community settings, with 60% having similar content to ERIC strategies (but with community-appropriate language) and 40% representing unique strategies developed specifically for community contexts [33]. This makes ISAC Match particularly valuable for implementation efforts in the precise settings where traditional clinical-focused matching tools fall short.

Table: Comparison of Matching Approaches for Implementation Strategies

Feature	ISAC Match	ERIC Match Tool	Ad Hoc Selection
Primary Setting	Community, non-clinical organizations [33]	Clinical, healthcare systems [33]	Varies, often undefined
Strategy Compilation	40 community-specific strategies [33]	73 clinically-oriented strategies [33]	No formal compilation
Language & Relevance	Community-appropriate terminology [33]	Clinical terminology can be a barrier [33]	Inconsistent
Process Guidance	Structured 4-step process with tailoring [33]	Generates lists without prioritization guidance [33]	Unsystematic
Contextual Inquiry	Explicit step for barriers/facilitators [33]	Requires separate determinant identification	Often overlooked
Health Equity Integration	Explicitly considered throughout process [33]	Not inherently integrated	Variable

ISAC Match Protocol: Four-Step Application Process

Step 1: Contextual Inquiry and Determinant Identification

Purpose: To understand implementation determinants (barriers and facilitators) through systematic inquiry [33].

Protocol:

• Review Existing Evidence: Begin by reviewing available literature, previous evaluations, or internal reports on the integration of the target EBI. Determine if existing evidence adequately describes contextual factors for your setting and population [33].
• Conduct Rapid Contextual Inquiry (if needed): If existing evidence is insufficient, conduct rapid formative research using these recommended methods:
  • Rapid Qualitative Methods: Conduct focused interviews or focus groups using determinant frameworks (e.g., CFIR) to guide data collection and analysis. Deductive analysis approaches are recommended for speed [33].
  • Brainwriting Premortem: Convene key stakeholders (implementers, administrators) to brainstorm reasons why implementation might fail in the future, using the RE-AIM framework to structure the discussion around Reach, Effectiveness, Adoption, Implementation, and Maintenance [33] [34].
  • Structured Observation: Use rapid ethnography to observe current implementation practices or context where the EBI will be deployed [33].
• Barrier and Facilitator Prioritization: Use structured activities to prioritize identified determinants:
  • Card Sort: Write each barrier and facilitator on a separate card. Have stakeholders sort cards into priority groups (e.g., high, medium, low) based on importance and changeability [33].
  • Modified Conjoint Analysis: Create a 2x2 grid poster with "Importance" on one axis and "Changeability" on the other. Have stakeholders place sticky notes with each barrier/facilitator on the grid. Focus on addressing highly important and changeable factors first [33].

Application Notes:

• This step should be completed within an Integrated Research-Practice Partnership (IRPP) to ensure both research and practice perspectives inform determinant identification [33].
• The goal is sufficient (not exhaustive) understanding of key determinants to guide strategy selection. The process should not contribute to translational lag [33].

Step 2: Identification of Existing Implementation Strategies

Purpose: To document implementation strategies already in use within the organization to avoid redundancy and build on existing infrastructure [33].

Protocol:

• Review Organizational Materials: Examine existing program guides, implementation blueprints, training manuals, and support resources to identify strategies already being employed, even if not formally labeled as implementation strategies [33].
• Facilitate Stakeholder Discussion: Conduct a structured discussion with implementers and administrators using these prompts:
  • "What supports or resources do you currently use when implementing new programs?"
  • "Think about past challenges in adopting or maintaining programs. What organizational supports helped overcome these challenges?"
  • "What existing systems or processes do you have for training staff, tracking fidelity, or providing support?" [33]
• Map to ISAC Compilation: Document identified strategies and map them to the formal ISAC compilation terminology to establish a baseline of current implementation support [33].

Application Notes:

• In community settings, implementation strategies often exist without being formally recognized as such (e.g., state-level specialists supporting county-based personnel in Cooperative Extension Systems) [33].
• Identifying existing strategies allows for refining or complementing current efforts rather than developing competing strategies [33].

Step 3: Selection of Relevant Implementation Strategies

Purpose: To systematically select implementation strategies from the ISAC compilation that address prioritized determinants [33].

Protocol:

• Determinant-Strategy Mapping: Using the prioritized list of barriers and facilitators from Step 1, identify potential strategies from the ISAC compilation that directly address each determinant.
• Use Guidance Tools: Employ recommended guidance tools to facilitate the matching process, similar to the ERIC match tool but using the community-appropriate ISAC compilation [33].
• Strength-Based Approach: Ensure strategy selection addresses both barriers (to overcome challenges) and facilitators (to capitalize on strengths), as recommended for community public health settings [33].

Application Notes:

• The IRPP should collaboratively make selection decisions, valuing both research evidence and practice-based knowledge [33].
• Consider health equity implications of each strategy, selecting those most likely to narrow health disparities [33].

Step 4: Tailoring of Selected Strategies

Purpose: To adapt and refine selected implementation strategies to fit the specific context, resources, and constraints of the implementation setting [33].

Protocol:

• Assess Fit: Evaluate each selected strategy for practical fit with organizational culture, available resources, timeline, and stakeholder preferences.
• Modify Strategy Components: Identify specific modifications needed to strategy delivery, timing, intensity, or personnel to enhance contextual fit.
• Develop Tailored Implementation Blueprints: Create detailed specifications for each tailored strategy, including:
  • Who will deliver the strategy
  • What specific activities it will include
  • When it will be deployed in the implementation timeline
  • How it will be evaluated for effectiveness [33]

Application Notes:

• Tailoring occurs within the IRPP structure, with equal contribution from researchers and practitioners [33].
• Document tailoring decisions to maintain fidelity to the strategy's core components while allowing appropriate adaptations [33].

Visual Framework and Workflow

ISAC Match Process within Implementation Workflow

Case Study Application: Montana State University Extension

Background: The ISAC Match process was applied to increase Montana State University Extension Agents' adoption of built environment approaches that facilitate physical activity [33] [34].

Application of the Four-Step Process:

• Contextual Inquiry: Conducted through rapid qualitative methods to identify key barriers (e.g., limited technical expertise, time constraints) and facilitators (e.g., community partnerships, existing communication channels) for implementing built environment approaches [33].
• Existing Strategy Identification: Documented current implementation supports provided by state-level specialists to county-based extension agents, which included some technical assistance but lacked structured implementation support [33].
• Strategy Selection: Selected relevant strategies from the ISAC compilation, including "develop implementation blueprints" and "provide technical assistance" to address identified barriers [33].
• Strategy Tailoring: Adapted selected strategies to fit the Cooperative Extension context by developing tailored implementation guides specifically for built environment approaches and creating peer-to-peer technical assistance networks [33].

Outcomes: The process resulted in a tailored set of implementation strategies specifically designed to overcome contextual barriers in the state Cooperative Extension System while building on existing strengths and infrastructure [33].

Research Reagent Solutions and Essential Materials

Table: Key Resources for Applying the ISAC Match Process

Resource Category	Specific Tool/Resource	Function/Purpose
Determinant Frameworks	Consolidated Framework for Implementation Research (CFIR) [33]	Provides comprehensive taxonomy of implementation determinants across multiple domains
Evaluation Frameworks	RE-AIM Framework [33]	Guides assessment of implementation outcomes and identifies potential failure points
Implementation Strategy Compilations	ISAC Compilation (40 strategies) [33]	Community-specific repository of implementation strategies with appropriate language
Data Collection Methods	Rapid Qualitative Interview Guides [33]	Facilitates efficient contextual inquiry for identifying barriers and facilitators
Prioritization Tools	Card Sort Materials, 2x2 Grid Templates [33]	Enables stakeholder-driven prioritization of determinants based on importance and changeability
Partnership Structures	Integrated Research-Practice Partnership (IRPP) Model [33]	Establishes collaborative structure for co-designing and tailoring implementation strategies

Comparative Analysis and Protocol Validation

The ISAC Match process addresses critical limitations of earlier matching approaches by providing a community-appropriate, systematic method for strategy selection and tailoring [33]. The four-step protocol emphasizes contextual fit and practitioner-researcher collaboration through IRPPs, contrasting with traditional approaches that often select strategies without adequate understanding of contextual factors [33].

Validation of the protocol comes from successful application in community settings such as the Montana State University Extension case study, demonstrating practical utility for improving implementation of evidence-based interventions [33]. Future research is needed to systematically evaluate whether the ISAC Match process produces more efficient and impactful results compared to less community-specific matching processes [33].

Conceptual Model of ISAC Match Inputs and Outcomes

Selecting the right implementation strategies is a critical challenge in translating research evidence into real-world practice. This process involves matching methods or techniques to improve the adoption, implementation, and sustainment of evidence-based interventions with the specific contextual determinants—barriers and facilitators—that affect implementation success [33] [35]. The complexity of implementation contexts, characterized by multi-level, dynamic systems with numerous interacting factors, necessitates sophisticated approaches to strategy selection [36]. Without systematic methods, implementation efforts often default to familiar but potentially ineffective strategies or miss crucial opportunities to address key determinants [33].

This article explores two advanced participatory methods—Concept Mapping and Group Model Building (GMB)—that explicitly address this complexity. These methods provide structured approaches for engaging stakeholders in understanding implementation contexts, selecting appropriate strategies, and anticipating potential system responses [36]. When applied within the broader thesis of matching implementation strategies to determinants research, these methods move beyond simple checklist approaches to create dynamic, context-sensitive strategy selection processes.

Theoretical Foundation: From Determinants to Strategic Action

The Determinants-Strategies Nexus

Effective implementation requires understanding and addressing contextual determinants that influence implementation success. Research has identified numerous determinants operating at multiple levels (individual, organizational, community), with some consistently demonstrating strong impacts across implementation efforts. A recent systematic review of studies using the Consolidated Framework for Implementation Research (CFIR) identified eight key determinants that most commonly have the largest impact on implementation processes [35]:

• Leadership Engagement: Active involvement and commitment of organizational leaders
• Formally Appointed Internal Implementation Leaders: Individuals specifically designated to lead implementation efforts
• Compatibility: Fit between the intervention and existing values, workflows, and systems
• Available Resources: Allocation of sufficient time, money, and infrastructure
• External Change Agents: Individuals outside the organization who support implementation
• Champions: Enthusiastic supporters of the intervention at multiple levels
• Relative Advantage: Perception that the intervention is better than alternatives
• Key Stakeholders: Individuals affected by or influencing the implementation

The challenge lies in systematically selecting implementation strategies that effectively address these and other relevant determinants in specific contexts [33]. Traditional approaches often struggle with the complexity of determinant interactions and their dynamic nature over time.

The Role of Participatory Methods

Concept Mapping and Group Model Building address these challenges through structured participatory processes that engage stakeholders in developing shared understanding of implementation contexts and strategy selection. Both methods recognize that successful implementation requires integrating diverse perspectives, particularly from those who will deliver or be affected by the interventions [36] [37].

These methods are particularly valuable for addressing the "black box" of strategy selection, where the rationale for choosing specific strategies is often unclear or poorly documented [33]. By making the selection process explicit, participatory, and evidence-informed, these methods enhance both the effectiveness and study of implementation strategy selection.

Concept Mapping for Strategy Selection

Concept mapping, particularly Trochim's Group Concept Mapping, is a structured mixed-methods approach that enables diverse stakeholders to develop a conceptual framework representing their collective understanding of a complex topic [38]. The method combines qualitative group processes with multivariate statistical analyses to produce visual representations of groups' mental models.

The methodology follows six key phases [38]:

• Preparation: Defining the focus and participant groups
• Idea Generation: Brainstorming responses to a focal prompt
• Idea Structuring: Sorting and rating generated ideas
• Concept Mapping Analysis: Statistical analysis creating cluster maps
• Interpretation: Naming clusters and interpreting patterns
• Utilization: Applying results to address the original problem

This structured approach is particularly valuable for implementation strategy selection as it helps identify priorities, build consensus, and clarify relationships between determinants and potential strategies [38].

Application Protocol: Using Concept Mapping for Strategy Selection

Research Question: What implementation strategies are most appropriate and feasible for addressing key determinants in our specific context?

Materials and Setup:

• Participants: 10-30 stakeholders representing diverse perspectives (implementers, recipients, decision-makers)
• Facilitation Team: Includes lead facilitator, logistics coordinator, and technical support
• Software: Concept mapping software (e.g., Concept Systems GroupWisdom, Ariadne)
• Venue: In-person or virtual environment supporting both individual and group work

Step-by-Step Procedure:

• Preparation (2-3 weeks)

  • Define focal prompt: "What strategies would help successfully implement [EBI] in [context]?"
  • Identify and recruit diverse stakeholder participants
  • Obtain ethical approval and informed consent
  • Prepare materials and conduct facilitator training

• Idea Generation (1-2 weeks)

  • Present focal prompt to participants
  • Conduct structured brainstorming to generate strategy ideas
  • Collect 70-150 distinct strategy statements
  • Deduplicate and edit statements for clarity while preserving meaning

• Idea Structuring (1-2 weeks)

  • Participants individually sort statements into piles based on similarity
  • Participants rate each statement on importance and feasibility (1-5 scales)
  • Achieve >70% participant response rate for robust analysis

• Analysis (1 week)

  • Create similarity matrix from sort data
  • Conduct multidimensional scaling and hierarchical cluster analysis
  • Generate concept maps showing strategy clusters and ratings
  • Produce pattern matches comparing different stakeholder perspectives

• Interpretation (2 weeks)

  • Conduct interpretation session with participant representatives
  • Name clusters based on constituent statements
  • Identify priority clusters based on importance-feasibility ratings
  • Develop implementation recommendations based on findings

• Utilization (Ongoing)

  • Share results with broader implementation community
  • Integrate findings into implementation plans
  • Use cluster ratings to guide strategy sequencing
  • Monitor implementation and adapt strategies as needed

Table 1: Concept Mapping Cluster Rating Example for Implementation Strategy Selection

Strategy Cluster	Average Importance (1-5)	Average Feasibility (1-5)	Priority Score	Key Representative Strategies
Leadership & Organizational Support	4.6	3.8	17.5	Secure executive sponsorship; Align with strategic priorities
Implementation Resources	4.4	3.2	14.1	Dedicate implementation staff; Budget for training
Stakeholder Engagement	4.3	4.1	17.6	Form advisory board; Conduct needs assessment
Adaptability & Tailoring	4.1	4.3	17.6	Modify for local context; Develop local protocols
Evaluation & Feedback	3.9	3.9	15.2	Create feedback system; Monitor fidelity data

Reporting and Quality Considerations

Recent methodological advances have produced the ConMapT reporting guideline to enhance transparency and quality in concept mapping studies [38] [39]. This 27-item checklist organized under 14 headings ensures comprehensive reporting of methodology, results, and interpretations. Key reporting requirements include:

• Clear description of participant roles and numbers in each phase
• Detailed documentation of the focus prompt development process
• Transparency about analytical decisions (e.g., number of cluster solutions considered)
• Comprehensive reporting of rating results and pattern matches
• Discussion of limitations and implications for utilization

Adherence to reporting guidelines strengthens the methodological rigor and practical utility of concept mapping for implementation strategy selection.

Group Model Building for Dynamic Strategy Planning

Group Model Building is a participatory systems science approach that engages stakeholders in creating visual representations of complex systems to understand feedback dynamics and identify high-leverage intervention points [36] [37]. Unlike more linear approaches, GMB explicitly accounts for feedback loops, delays, and non-linear relationships that characterize implementation contexts.

GMB combines structured facilitation techniques ("scripts") with system dynamics modeling to help stakeholders articulate their mental models of how systems function and how interventions might affect system behavior over time [36]. This approach is particularly valuable for implementation strategy selection because it helps anticipate unintended consequences, identify reinforcing processes, and understand dynamic interactions between strategies and determinants.

Application Protocol: GMB for Strategy Selection

Research Question: How might different implementation strategies interact with our context over time to affect implementation outcomes?

Materials and Setup:

• Participants: 8-15 stakeholders with system knowledge and decision authority
• Facilitation Team: Modeler facilitator, substantive expert, community facilitator
• Materials: Virtual whiteboard, sticky notes, modeling software (e.g., Vensim, Stella)
• Venue: In-person or virtual workshop environment

Step-by-Step Procedure:

• Pre-Workshop Preparation (2-3 weeks)

  • Conduct preliminary interviews to understand system boundaries
  • Identify and recruit key stakeholders
  • Develop initial workshop design and tailor scripts
  • Prepare materials and conduct facilitator briefing

• Session 1: Building the Implementation System Map (3 hours)

  • Activity: Introductions and overview of systems thinking
  • Script: "Graphs Over Time" - Identify key implementation outcomes and trends
  • Script: "Variable Elicitation" - Brainstorm factors affecting implementation
  • Script: "Connection Circles" - Identify relationships between factors
  • Script: "Action Ideas" - Generate potential implementation strategies
  • Output: Initial causal loop diagram of implementation system

• Session 2: Identifying Feedback Dynamics (3 hours)

  • Activity: Review and refine causal loop diagram
  • Script: "Feedback Identification" - Label reinforcing and balancing loops
  • Script: "Behavior Over Time" - Discuss how loops affect outcomes
  • Script: "Leverage Points" - Identify potential intervention points
  • Output: Annotated causal loop diagram with key feedback loops

• Inter-Session Modeling (1-2 weeks)

  • Modeling team develops quantitative simulation model
  • Calibrate model with available data
  • Prepare preliminary simulations of strategy impacts

• Session 3: Strategy Testing and Selection (3 hours)

  • Activity: Review simulation model structure and assumptions
  • Script: "Simulation" - Test different strategy combinations
  • Script: "Decision Analysis" - Compare strategy impacts on outcomes
  • Script: "Policy Resistance" - Identify potential unintended consequences
  • Output: Prioritized implementation strategies with rationale

• Post-Workshop Refinement and Utilization (Ongoing)

  • Refine model based on workshop feedback
  • Develop implementation plan incorporating selected strategies
  • Establish monitoring system to track key variables
  • Schedule follow-up sessions to review and adapt strategies

Table 2: GMB Scripts for Implementation Strategy Selection Across EPIS Phases

EPIS Phase	Key GMB Scripts	Purpose in Strategy Selection	Expected Outputs
Exploration	Graphs Over Time; Variable Elicitation	Understand problem dynamics and system boundaries	List of key determinants; Preliminary system boundaries
Preparation	Connection Circles; Feedback Identification	Map relationships between determinants and identify feedback loops	Causal loop diagram; Leverage points for intervention
Implementation	Action Ideas; Simulation	Generate and test potential implementation strategies	Prioritized strategies; Anticipation of unintended consequences
Sustainment	Decision Analysis; Policy Resistance	Evaluate strategy sustainability and adaptation needs	Long-term implementation plan; Monitoring framework

Operationalizing Implementation Strategies through GMB

GMB serves not only as a method for selecting strategies but also for operationalizing them across key dimensions outlined by Proctor and colleagues [36]:

• Actors: GMB identifies who should deliver strategies based on system role and influence
• Actions: Specific strategy activities are co-designed through structured scripts
• Action Targets: GMB clarifies what mechanisms strategies should target (e.g., mental models, commitment)
• Dose: Modeling helps determine optimal intensity and duration of strategies
• Temporality: Simulations inform timing and sequencing of strategy components
• Implementation Outcomes: Models predict effects on adoption, fidelity, and sustainability
• Justification: Causal diagrams provide theoretical rationale for strategy selection

This systematic operationalization enhances both the specification and subsequent evaluation of implementation strategies.

Comparative Analysis and Integration

Method Selection Guide

Table 3: Comparative Analysis of Concept Mapping and Group Model Building for Strategy Selection

Characteristic	Concept Mapping	Group Model Building
Primary Strength	Identifying priorities and building consensus	Understanding dynamics and anticipating consequences
Theoretical Foundation	Multivariate statistics; Cluster analysis	System dynamics; Feedback theory
Time Requirement	6-10 weeks	8-16 weeks
Participant Burden	Moderate (individual and group activities)	High (extended engagement and modeling)
Key Outputs	Cluster maps; Pattern matches; Priority ratings	Causal loop diagrams; Simulation models; Leverage points
Implementation Focus	What strategies to select	How strategies interact with system dynamics
Resource Requirements	Concept mapping software; Facilitation team	Modeling software; Skilled modeler; Facilitation team
Best Suited For	Static contexts with clear determinants; Priority-setting	Dynamic contexts with feedback loops; Complex adaptation challenges

Integrated Approach: ISAC Match Process

The Implementation Strategies Applied in Communities (ISAC) Match process provides a structured framework that can incorporate both concept mapping and GMB elements for community settings [33]. This four-step process includes:

• Contextual Inquiry: Review existing information on evidence-based intervention integration and conduct additional inquiry if needed
• Identify Existing Strategies: Document implementation strategies already used in the setting
• Select Relevant Strategies: Use guided tools to match strategies to determinants
• Tailor Strategies: Adapt strategies to fit specific setting characteristics

Within this framework, concept mapping can enhance step 3 by providing systematic priority-setting, while GMB can strengthen step 4 by modeling how tailored strategies might perform in the specific context.

Visualization and Modeling

Concept Mapping Workflow

Group Model Building Causal Loop Diagram

Research Reagent Solutions: Methodological Toolkit

Table 4: Essential Research Reagents for Advanced Strategy Selection Methods

Tool Category	Specific Tools	Function in Strategy Selection	Key Features
Concept Mapping Software	Concept Systems GroupWisdom; Ariadne	Supports all concept mapping phases from brainstorming to cluster mapping	Integrated statistical analysis; Real-time collaboration; Multiple rating dimensions
System Dynamics Modeling	Vensim; Stella; AnyLogic	Develops quantitative simulation models for strategy testing	Stock-flow diagramming; Simulation capabilities; Sensitivity analysis
Virtual Collaboration Platforms	Miro; Mural; Padlet	Enables remote participatory sessions with diverse stakeholders	Digital whiteboards; Template libraries; Voting mechanisms
Determinant Frameworks	Consolidated Framework for Implementation Research (CFIR)	Provides structured approach to identifying implementation determinants	Comprehensive construct lists; Updated domains; Practical guidance
Implementation Strategy Compilations	ERIC; ISAC	Catalogs evidence-based implementation strategies	Community-specific strategies; Clear definitions; Operational details
Reporting Guidelines	ConMapT; STAND	Ensures transparent and complete methodology reporting	Standardized checklists; EQUATOR network approval; Field validation

Concept Mapping and Group Model Building represent sophisticated methodological approaches that address critical limitations in traditional implementation strategy selection processes. By engaging stakeholders in structured, participatory processes that acknowledge and address complexity, these methods enhance both the appropriateness and potential effectiveness of selected strategies.

For researchers focused on matching implementation strategies to determinants, these approaches offer:

• Systematic Processes that make strategy selection transparent and reproducible
• Stakeholder Engagement mechanisms that enhance contextual appropriateness and buy-in
• Dynamic Understanding of how strategies interact with complex implementation contexts
• Anticipatory Capacity to foresee potential unintended consequences and adaptation needs

As implementation science continues to advance, these participatory, systems-informed methods will play an increasingly important role in moving beyond simple determinant-checklist approaches toward dynamic, context-sensitive strategy selection that improves implementation outcomes across diverse settings and populations.

A core challenge in implementation science is effectively matching implementation strategies to specific barriers and facilitators (determinants) identified through preliminary research. This protocol provides a structured, mixed-method approach for quantifying the perceived impact of these determinants, thereby creating a rational and data-driven basis for selecting implementation strategies. By integrating quantitative rating exercises with qualitative insights, researchers and drug development professionals can prioritize determinants and align resources with the strategies most likely to improve the implementation of new therapies, clinical guidelines, or health interventions [40]. This document details the application notes and experimental protocols for executing this process.

Quantitative Data Analysis of Determinants

The following table summarizes hypothetical quantitative data from a determinant rating exercise, illustrating how different stakeholders might prioritize barriers to the implementation of a new heart failure guideline in an emergency department setting, inspired by a study on overcoming emergency department hurdles [40].

Table 1: Sample Impact and Modifiability Ratings for Implementation Determinants

Determinant ID	Description	Avg. Impact Rating (1-5)	Avg. Modifiability Rating (1-5)	Priority Score (Impact x Modifiability)
D01	Limited staff time for patient education	4.7	2.5	11.8
D02	Low patient health literacy	4.2	3.0	12.6
D03	Lack of standardized discharge alert system	3.8	4.5	17.1
D04	Resistance from nursing staff to new protocols	3.5	3.8	13.3

Application Notes:

• Impact Rating: Stakeholders (e.g., ED providers, nurses, leaders) rate each determinant on a Likert scale from 1 (No Impact) to 5 (Very High Impact) on the successful implementation of the intervention.
• Modifiability Rating: Stakeholders rate each determinant on a scale from 1 (Not Modifiable) to 5 (Easily Modifiable). This assesses the perceived feasibility of addressing the determinant.
• Priority Score: This calculated score (Impact x Modifiability) helps identify "high-impact, high-modifiability" targets. In this example, D03 (Lack of standardized discharge alert system) emerges as the highest-priority determinant for action, despite not having the highest impact score, because it is perceived as highly modifiable [40].

Experimental Protocols

Protocol for Mixed-Methods Data Collection

This protocol outlines the steps for gathering both quantitative ratings and qualitative context on implementation determinants.

I. Objective: To collect and analyze quantitative and qualitative data on implementation determinants to inform the selection of implementation strategies.

II. Materials and Research Reagent Solutions Table 2: Essential Materials for Data Collection and Analysis

Item Category	Specific Item/Software	Function/Benefit
Data Collection Tool	REDCap (Research Electronic Data Capture) or similar secure online survey platform	Securely administers rating surveys and collects informed consent; allows for easy data export and management [40].
Qualitative Data Management	NVivo, Dedoose, or similar Qualitative Data Analysis Software	Facilitates the organization, coding, and analysis of transcribed interview data.
Quantitative & Statistical Analysis	IBM SPSS Statistics, R, or similar statistical software	Used for calculating descriptive statistics (medians, IQRs) and conducting tests like Wilcoxon rank-sum or Kruskal-Wallis tests [41] [40].
Context Assessment Instrument	Validated survey instrument (e.g., Organizational Readiness to Change Assessment - ORCA)	Quantifies organizational context and readiness, which can be correlated with determinant ratings [40].

III. Detailed Procedure:

• Participant Recruitment and Consent: Identify and recruit a representative sample of stakeholders involved in the implementation (e.g., ED leaders, providers, nurses). Obtain informed consent using an IRB-approved form integrated into the data collection platform [40].
• Determinant Rating Survey (Quantitative): a. Develop a survey listing all previously identified determinants. b. For each determinant, include two 5-point Likert scale questions: one for Impact and one for Modifiability. c. Distribute the survey via the chosen online platform. d. Calculate descriptive statistics (median, interquartile range) for each rating and compute the Priority Score for each determinant.
• Stakeholder Interviews (Qualitative): a. Conduct semi-structured interviews with a sub-set of survey participants. b. Use interview guides informed by implementation frameworks (e.g., Consolidated Framework for Implementation Research - CFIR) to explore the "why" behind the ratings [40]. c. Probe for specific examples, perceived root causes, and ideas for potential strategies.
• Organizational Context Assessment (Quantitative): a. Administer a context assessment scale, such as the ORCA context scale, to the same group of stakeholders [40]. b. Analyze scores by professional group (e.g., providers, leaders, nurses) using non-parametric tests like the Kruskal-Wallis test to identify significant differences in perception.

IV. Data Integration and Analysis:

• Use a convergence coding matrix to jointly display quantitative and qualitative data. List determinants in rows and place quantitative ratings (impact, modifiability, priority score) alongside summarized qualitative findings in adjacent columns.
• This matrix allows for the identification of patterns. For instance, a determinant with a high impact score might be consistently described in interviews as a "major workflow bottleneck," while a determinant with low modifiability might be linked to qualitative themes of "systemic budget constraints."

Protocol for Determinant-to-Strategy Mapping

This protocol uses the results from Protocol 3.1 to guide the selection of implementation strategies.

I. Objective: To facilitate a stakeholder consensus meeting for matching high-priority determinants with evidence-informed implementation strategies.

II. Materials: Results from Protocol 3.1 (including tables and the convergence matrix), a list of implementation strategies from an established taxonomy (e.g., ERIC compilation), whiteboard or collaborative digital workspace.

III. Detailed Procedure:

• Present Findings: Share the summarized data, including Table 1 and the key qualitative themes, with stakeholders.
• Prioritize Determinants: Guide stakeholders in reviewing the priority scores and qualitative evidence to finalize a shortlist of 3-5 determinants to address initially.
• Brainstorm Strategies: For each shortlisted determinant, use the qualitative insights (which often contain solution ideas) and the taxonomy of strategies to brainstorm potential actions.
• Refine Strategies for Local Context: Discuss and refine the brainstormed strategies based on local contextual factors identified in the ORCA assessment and interviews. For example, if "leadership engagement" was a high-scoring facilitator, strategies could be designed to leverage it [40].
• Develop an Action Plan: Formalize the selected strategies into a detailed action plan, specifying roles, timelines, and resource requirements.

Mandatory Visualization

The following diagram, generated using Graphviz DOT language, illustrates the logical workflow and decision-making process for moving from determinant identification to strategy implementation, as outlined in the protocols above.

Diagram 1: Determinant to Strategy Mapping Workflow

Matching is a fundamental methodological technique used in clinical research to ensure that comparison groups are balanced with respect to key prognostic factors, particularly when random assignment to treatment groups is not feasible or ethical [42]. In observational studies or non-randomized trials, treatment groups may differ systematically in their probability of developing the outcomes under study—a problem known as susceptibility bias [42]. Matching strategies aim to minimize this bias by selecting control subjects who are similar to intervention subjects based on predetermined characteristics, thereby creating comparable groups that allow for more valid estimation of treatment effects.

The application of matching strategies has evolved significantly, with recent advances incorporating artificial intelligence (AI) and machine learning to enhance the precision and efficiency of patient-trial matching [43]. These technological innovations are particularly valuable in oncology trials, where patient identification and recruitment remain critical challenges, with fewer than 10% of cancer patients participating in clinical trials in the United States [43]. By implementing sophisticated matching algorithms, researchers can improve trial accrual while maintaining methodological rigor in scenarios where traditional randomization is not possible.

Theoretical Foundations and Matching Frameworks

Conceptual Basis for Matching

At its core, matching addresses the fundamental challenge of achieving comparability between treatment groups in non-randomized settings. Unlike randomization, which theoretically balances both known and unknown prognostic factors, matching specifically targets known confounders to create balanced comparison groups [42]. The methodological strength of matching lies in its ability to approximate the conditions of a randomized trial through careful selection of controls, thereby reducing the impact of confounding on effect estimates.

The prospective individual matching approach represents a methodologically rigorous alternative for achieving balance across treatment groups with respect to important prognostic factors [42]. This design is analogous to a matched cohort study and can be analyzed using well-established statistical models for matched designs. The application of this method to controlled clinical trials represents an important extension of this design that enhances both internal and external validity because most eligible intervention patients can be enrolled as they present [42].

Implementation Science Frameworks

The process of matching implementation strategies to determinants finds its theoretical foundation in implementation science frameworks, particularly the Consolidated Framework for Implementation Research (CFIR)-Expert Recommendations for Implementing Change (ERIC) match tool [44]. This framework helps researchers systematically identify barriers to implementation and select appropriate strategies to address them. The CFIR encompasses multiple domains (innovation, outer setting, inner setting, individuals, and implementation process) that influence adoption, implementation, or maintenance of evidence-based interventions [44].

When applied to clinical trial matching, implementation science principles highlight several critical factors for successful adoption of matching tools, including leadership engagement, knowledge and beliefs about a tool, the adaptability of a tool, and planning around implementation [45]. These factors illustrate the importance of a preliminary intake process during which design and study teams can align on knowledge, design needs, and workflow integration—a process that could improve readiness to implement by increasing transparency and reducing mistrust in unfamiliar algorithms [45].

Matching Algorithms and Methodological Approaches

Prospective Individual Matching Algorithm

The prospective individual matching method represents a sophisticated approach for achieving balance in non-randomized trials. This algorithm involves several methodical steps:

Patient Enrollment Sequence: The process begins with enrolling every eligible intervention patient first, followed by selection and enrollment of matched controls from a candidate pool [42]. This sequence is crucial when intervention assignment is beyond researchers' control, such as when hospital floor assignments are determined by bed availability rather than patient characteristics.

M Factor Selection: Investigators must select a limited set of strong prognostic factors (typically three or fewer) for matching [42]. These factors should be powerful determinants of the study outcome to ensure matching efficiency and effectiveness. Baseline prognostic indices that incorporate information from multiple variables can serve as effective composite matching factors [42].

Control-to-Intervention Ratio: Maintaining an adequate ratio of available controls to intervention patients (recommended at least 1.3:1) ensures a reasonable pair match rate [42]. This ratio provides sufficient options for finding appropriate matches without excessive screening costs.

Matching Execution: The actual matching process employs specialized algorithms to identify the most suitable control for each intervention patient based on the selected prognostic factors [42]. Successful implementation depends on the number and complexity of factors to be matched and the number of available control patients.

The following workflow illustrates the prospective individual matching process:

AI-Enhanced Clinical Trial Matching

Modern matching systems leverage artificial intelligence and natural language processing to automate and enhance the matching process. The XpertScreen system implementation at Stanford Cancer Center demonstrates a sophisticated multi-stage approach [43]:

Named Entity Recognition: The system identifies critical clinical entities using medical ontologies including age range, biomarkers, prior treatments, and laboratory values [43]. This process extracts structured information from unstructured clinical text.

Rule-Based Pattern Matching: The algorithm detects numerical constraints and captures key performance scores, lab values, and treatment histories through predefined patterns [43]. This enables the system to interpret complex eligibility criteria.

Ontology Mapping and JSON Structuring: Extracted data is converted into a standardized JSON schema, normalizing trial eligibility details across multiple data sources [43]. This structured format enables efficient filtering and retrieval of potential matches.

Integration with EHR and Clinical Systems: The system connects with electronic health records via SMART on FHIR standards and synchronizes with clinical trial management systems to maintain current trial information [43]. This integration ensures access to real-time patient data and trial status updates.

The AI-driven matching process can be visualized as follows:

Practical Application: Case Study in Delirium Prevention

Study Context and Design

The Delirium Prevention Trial successfully implemented prospective individual matching when randomization was not feasible [42]. In this study, a multicomponent intervention to prevent incident delirium was delivered on one hospital floor, with "usual care" provided on two control floors. Floor assignments were determined strictly by hospital admission procedures based on bed availability, independent of patient characteristics [42]. This scenario created a natural experiment where matching could be used to create comparable groups.

During a 2-month pilot period, the researchers discovered that using a classic randomized trial design would not be feasible—only four patients could be randomly assigned to the appropriate study floor due to frequent bed unavailability on the intended study floors [42]. The prospective individual matching approach enabled the research team to proceed with their investigation despite the constraints on random assignment.

Implementation and Outcomes

The Delirium Prevention Trial implemented the matching algorithm over a 35-month screening and enrollment period [42]. The study achieved remarkable success in creating balanced treatment groups:

• Patient Flow: 564 intervention floor patients and 756 control floor patients qualified for enrollment, yielding a control-to-intervention ratio of 1.34:1 [42].
• Match Rate: 95% of eligible intervention floor patients were successfully matched to control floor patients [42].
• Balance Achievement: The matched groups demonstrated excellent balance for both matching and non-matching factors, attributable in part to the use of a composite baseline risk score as a matching factor [42].

Table 1: Delirium Prevention Trial Matching Outcomes

Metric	Result	Implication
Intervention Patients	564	Target population for matching
Control Pool	756 patients	Adequate ratio (1.34:1) for matching
Successfully Matched	95% of interventions	High match rate minimizing selection bias
Factor Balance	Excellent for matching and non-matching factors	Effective confounding control

The implementation of this matching strategy enabled the research team to conduct a methodologically rigorous trial despite the inability to randomize patients to intervention and control groups, demonstrating the practical utility of matching in real-world clinical research constraints.

Quantitative Performance of Matching Strategies

Traditional vs. AI-Enhanced Matching

The performance of matching strategies can be evaluated through both traditional implementation metrics and modern AI-based approaches. The Delirium Prevention Trial demonstrated the effectiveness of traditional prospective matching, while the Stanford XpertScreen implementation shows the enhanced capabilities of AI-driven systems.

Table 2: Performance Comparison of Matching Approaches

Performance Metric	Prospective Individual Matching	AI-Enhanced Matching
Match Rate	95% of intervention patients [42]	Not explicitly reported
Screening Efficiency	Requires manual review of control pool	Automated ranking of trial options
Referral Volume	Not applicable	Increased from 20 to 236 annually [43]
Conversion Rate	Not explicitly reported	16-26% of referred patients [43]
Implementation Timeline	35-month enrollment period [42]	3-year staged rollout [43]

Resource Considerations and Efficiency

Both traditional and AI-enhanced matching approaches require careful consideration of resource allocation and implementation costs. The Delirium Prevention Trial highlighted the importance of maintaining an adequate control-to-intervention ratio (1.3:1 recommended) to achieve satisfactory match rates while controlling costs associated with screening unmatched controls [42]. The researchers emphasized that limiting the number of matching factors (typically three or fewer) improves matching efficiency without substantially compromising group comparability [42].

The AI-based approach at Stanford required significant initial investment in system integration, including connecting with the electronic health record via SMART on FHIR standards and synchronizing with the clinical trial management system [43]. However, this investment yielded substantial returns through increased screening requests and subsequent enrollment, with the total number of screening referrals increasing from 20 in the first year to 236 in the third year of implementation [43].

Implementation Protocols and Procedures

Protocol for Prospective Individual Matching

Step 1: Study Design Phase

• Determine that randomization is not feasible or ethical for the research context
• Identify key prognostic factors (limit to 3 or fewer strong predictors) for matching [42]
• Establish eligibility criteria for both intervention and control patients
• Determine required control-to-intervention ratio (minimum 1.3:1 recommended) [42]

Step 2: Patient Enrollment

• Enroll all eligible intervention patients first as they present
• Screen and enroll potential control patients from available pool
• Document reasons for non-enrollment to assess potential selection biases

Step 3: Matching Execution

• Apply matching algorithm to identify optimal controls for each intervention patient
• Use composite baseline risk scores when multiple factors need consideration [42]
• Validate match quality by assessing balance on both matching and non-matching factors

Step 4: Analysis Phase

• Employ statistical methods appropriate for prospectively matched designs
• Use conditional logistic regression or other matched analysis techniques
• Conduct sensitivity analyses to assess robustness of findings

Protocol for AI-Enhanced Trial Matching

Step 1: System Integration

• Establish SMART on FHIR connection with electronic health record system [43]
• Synchronize with clinical trial management system for updated trial information
• Implement natural language processing pipeline for eligibility criteria interpretation [43]

Step 2: Data Processing

• Extract and structure patient data including demographics, cancer type, stage, and mutations [43]
• Transform unstructured eligibility criteria into standardized JSON format [43]
• Update trial information regularly (minimum twice weekly) to ensure accuracy [43]

Step 3: Matching Execution

• Run matching algorithm to generate rank-ordered list of potential trials [43]
• Present matching results to healthcare provider for verification and selection
• Initiate screening request to research coordinators for preselected trials

Step 4: Referral and Tracking

• Research coordinators prescreen patients within 48 hours of referral [43]
• Track screening completion and enrollment outcomes
• Monitor platform utilization through administrative console [43]

Research Reagent Solutions and Tools

Table 3: Essential Research Reagents and Tools for Matching Implementation

Tool Category	Specific Examples	Function in Matching Process
Data Integration Tools	SMART on FHIR API, EHR connectors [43]	Enable secure exchange of patient data between electronic health records and matching systems
Natural Language Processing	Named Entity Recognition, Rule-based pattern matching [43]	Extract structured information from unstructured eligibility criteria and clinical notes
Ontology Mapping Systems	Systematized Nomenclature of Medicine, Unified Medical Language System [43]	Standardize clinical terminology across different data sources for accurate matching
Matching Algorithms	Prospective individual matching algorithm [42], AI-based ranking systems [43]	Identify optimal matches between patients and trials based on multiple criteria
Security Compliance Tools	HIPAA-compliant encryption, SOC2 Type 2 certification [43]	Ensure patient data protection throughout the matching process
Trial Management Integration	OnCore CTMS integration, ClinicalTrials.gov sync [43]	Maintain current trial information and status updates for accurate matching

Matching strategies represent a methodologically rigorous approach for creating comparable treatment groups in clinical research when randomization is not feasible. The case studies presented demonstrate that both traditional prospective individual matching and modern AI-enhanced approaches can successfully address susceptibility bias in non-randomized settings. The Delirium Prevention Trial achieved a 95% match rate using traditional methods [42], while the Stanford AI-based system increased screening referrals from 20 to 236 annually with conversion rates of 16-26% [43].

Successful implementation requires careful attention to several key factors: selecting appropriate matching variables, maintaining adequate control-to-intervention ratios, and using appropriate analytical methods for matched designs. The integration of implementation science frameworks, such as CFIR-ERIC, can enhance the adoption and effectiveness of matching strategies by addressing contextual barriers and facilitating the selection of appropriate implementation strategies [44].

As clinical research continues to evolve, matching methodologies will play an increasingly important role in generating valid evidence from non-randomized settings. The incorporation of artificial intelligence and machine learning holds particular promise for enhancing the efficiency and precision of patient-trial matching, potentially accelerating therapeutic development while maintaining methodological rigor.

Navigating Challenges and Enhancing Precision in Strategy Selection

Common Pitfalls in Barrier-Strategy Matching and How to Avoid Them

A foundational principle of implementation science is that implementation strategies must be tailored to address contextual determinants—the barriers and facilitators affecting the integration of evidence-based interventions into real-world settings [26]. Despite the availability of structured frameworks like the Consolidated Framework for Implementation Research (CFIR) for identifying determinants and compilations like the Expert Recommendations for Implementing Change (ERIC) for selecting strategies, the process of matching them is complex [44] [26]. Research indicates a "wide heterogeneity of endorsements" from experts on which strategies best address specific barriers, suggesting a lack of consistent, clear relationships between the two [26]. This application note details common pitfalls in this matching process and provides protocols to enhance methodological rigor for researchers and scientists, particularly in drug development and biomedical fields.

Common Pitfalls and Recommended Solutions

The following table summarizes the primary challenges and evidence-based solutions for effective barrier-strategy matching.

Table 1: Common Pitfalls in Barrier-Strategy Matching and Corresponding Solutions

Pitfall	Description & Consequences	Recommended Solution
1. Overreliance on Overly Generic Matching Tools	Using matching tools (e.g., CFIR-ERIC match tool) without critical adaptation for specific contexts (e.g., community vs. clinical settings) can yield irrelevant strategies [44].	Contextual Adaptation: Use tool outputs as a starting point, then refine strategies through stakeholder engagement to ensure local relevance [44].
2. Unrealistic Objective Setting	Defining implementation goals that are too ambitious given resources, timelines, or organizational capabilities leads to failure and damages credibility [46].	SMART Goal Framework: Set Specific, Measurable, Achievable, Relevant, and Time-bound objectives. Use internal capability assessments and scenario planning [46].
3. Neglecting Organizational Culture and Structure	A strategic plan will flounder if it is misaligned with the organization's inherent culture, structural processes, and norms [46].	Fit Assessment: Proactively assess organizational fit during strategy formulation. Prioritize urgent misalignments and adopt an incremental approach to cultural shifts [46].
4. Inefficient Resource Allocation	Failing to align financial, human, and technological resources with strategic needs creates a fundamental barrier to execution [46].	Gap Analysis: Conduct a formal resource gap analysis. Scale back objectives or secure additional resources, and address talent capability gaps through training or hiring [46].
5. Poor Coordination and Communication	Complex implementation efforts risk siloed initiatives and a lack of integrated effort across teams, leading to wasted resources [46].	Structured Governance: Establish clear governance, coordination mechanisms, and centralized communication channels. Use regular progress reporting and cross-functional teams [46].

Experimental Protocol for a Systematic Barrier-Strategy Matching Process

This protocol provides a detailed methodology for conducting a comprehensive and reproducible barrier-strategy matching exercise.

Protocol Title

Systematic Identification of Contextual Determinants and Tailoring of Implementation Strategies.

Author Information

This protocol outlines a mixed-methods approach to prospectively identify barriers and facilitators to implementation and systematically select implementation strategies to address them. It combines qualitative data collection with a structured expert consensus process to enhance the reproducibility and effectiveness of implementation efforts.

Key Features

• Structured Determinant Identification: Uses a established framework (CFIR) to ensure comprehensive barrier assessment.
• Stakeholder-Centered Design: Integrates perspectives from both leadership and frontline staff.
• Systematic Strategy Selection: Leverages expert compilations (ERIC) while allowing for contextual adaptation.
• Action-Oriented Output: Produces a prioritized, tailored list of implementation strategies.

Materials and Reagents

Table 2: Research Reagent Solutions and Essential Materials

Item	Function/Application
Semi-Structured Interview Guide	To conduct focus groups or interviews for identifying barriers and facilitators. Must be based on a determinant framework (e.g., CFIR).
Determinant Framework Codebook	A predefined codebook, such as the CFIR codebook, for the systematic analysis of qualitative data [44] [26].
Implementation Strategy Compilation	A comprehensive list of strategies, such as the ERIC compilation, which includes 73 discrete implementation strategies [26].
Digital Collaboration Platform	Software (e.g., Microsoft Teams, Slack, specialized strategy software) to facilitate virtual meetings and document sharing for stakeholder engagement [47].
Data Analysis Software	Qualitative data analysis software (e.g., NVivo, Dedoose) for coding and theme identification; and statistical software (e.g., R, SPSS) for quantitative surveys.

Equipment

• Audio recording equipment for focus groups/interviews.
• Computer with internet access and video conferencing capabilities.
• Data visualization tools (e.g., Microsoft Excel, Tableau).

Software and Datasets

• Qualitative data analysis software (e.g., NVivo version 14).
• Survey platform (e.g., Qualtrics, RedCap).
• The CFIR technical assistance website (cfirguide.org) for framework definitions.
• The ERIC compilation for strategy definitions [26].

Procedure

Step 1: Barrier and Facilitator Identification

• 1.1. Recruit a diverse sample of stakeholders (e.g., researchers, clinicians, patients) involved in the implementation effort.
• 1.2. Conduct focus groups or individual interviews using a semi-structured guide based on the CFIR domains [44].
• Critical: Record and transcribe interviews verbatim to ensure data integrity.
• Pause Point: Transcribed data can be stored securely before analysis.

Step 2: Qualitative Data Analysis

• 2.1. Use a directed content analysis approach. Code the transcribed data to the CFIR constructs [44] [26].
• 2.2. Identify the most salient (i.e., frequently mentioned) barriers and facilitators. Prioritize the top 5-8 barriers for the matching exercise.
• Caution: Ensure coding is performed by at least two independent researchers and calculate inter-coder reliability to ensure consistency.

Step 3: Preliminary Strategy Selection

• 3.1. Input the prioritized CFIR barrier constructs into a matching tool, such as the CFIR-ERIC match tool [44] [26].
• 3.2. Review the output list of potential strategies. Independently, have 2-3 team members select and agree on which strategies from the full ERIC compilation are most relevant to the local context [44].
• Note: Be prepared to condense or adapt strategy descriptions to better fit your setting (e.g., combining "Shadow other sites" and "Visit other sites" into a "Peer Learning" strategy) [44].

Step 4: Stakeholder Validation and Refinement

• 4.1. Present the condensed list of candidate strategies to key stakeholders in a workshop setting.
• 4.2. Use a structured method (e.g., nominal group technique, dot voting) to gather feedback on the feasibility and importance of each strategy.
• 4.3. Refine the list based on stakeholder input, creating a final, prioritized set of implementation strategies.

Step 5. Implementation and Monitoring

• 5.1. Formalize the final strategy list, specifying the actors, actions, action targets, temporality, dose, and outcomes for each.
• 5.2. Integrate these strategies into the implementation plan, ensuring alignment with resources and timelines [46].
• 5.3. Establish key performance indicators (KPIs) and a schedule for monitoring progress and making necessary adjustments [47].

Data Analysis

• Qualitative Analysis: Report on the frequency of CFIR constructs identified as salient barriers/facilitators. Use quotes to illustrate key points.
• Strategy Selection Analysis: Document the process of selecting and refining strategies, including the rationale for any adaptations made to the standard ERIC definitions.
• Outcome Evaluation: Use the KPIs established in Step 5.3 to quantitatively assess the effectiveness of the implemented strategies over time.

Validation of Protocol

This protocol is validated by its foundation in established implementation science frameworks and methods, including the CFIR and ERIC compilations [26]. The multi-step, stakeholder-engaged process is designed to increase the likelihood of selecting contextually appropriate strategies, thereby improving implementation outcomes. Evidence of robustness can be demonstrated by applying the protocol and reporting on the improved congruence between identified barriers and the strategies deployed [44].

General Notes and Troubleshooting

• Limitation: This process can be time- and resource-intensive. The timeline should be planned accordingly.
• Troubleshooting: If stakeholder consensus is difficult to achieve, consider using a formal decision-making technique like multi-criteria decision analysis.
• Variability: The applicability of certain CFIR constructs and ERIC strategies will vary significantly across different settings (e.g., clinical vs. community labs). Always prioritize local context over generic recommendations [44].

Visual Workflow of the Barrier-Strategy Matching Process

The following diagram illustrates the logical workflow of the experimental protocol, showing the sequence of steps and feedback loops for continuous refinement.

Successfully matching implementation strategies to contextual barriers is a critical yet complex endeavor. By recognizing and systematically avoiding common pitfalls—such as uncritical use of matching tools, poor resource alignment, and neglect of organizational culture—researchers can significantly enhance the impact and reproducibility of their work. The detailed experimental protocol provided here offers a structured, actionable roadmap for navigating this process, empowering scientific teams to translate evidence-based interventions into real-world practice more effectively.

Adapting Clinical Tools for Community and Public Health Settings

The translation of evidence-based interventions from clinical settings into community and public health contexts represents a critical frontier for improving population health. However, this process is fraught with challenges, primarily because clinical tools are often designed for controlled environments with specialized resources, which are not typical of community settings. The lag between research evidence and real-world practice can be 15 to 17 years, underscoring the urgent need for systematic approaches to implementation [48]. This application note addresses this gap by providing structured methodologies for adapting clinical tools for community use, framed within the broader thesis of strategically matching implementation strategies to contextual determinants.

The core challenge lies in the fundamental differences between clinical and community environments. Community settings—including social services, faith-based organizations, education, and non-clinical public health organizations—often operate with lower resources, lack implementation-specific staff, and possess different infrastructure capabilities compared to clinical settings [13]. Furthermore, social determinants of health (SDOH)—the conditions in which people are born, live, work, and age—significantly influence health outcomes and must be central to any adaptation framework [49] [50]. Successful adaptation requires not only modifying tools but also strategically selecting implementation approaches that address these contextual determinants.

Theoretical Framework: Matching Strategies to Determinants

The ISAC Match Process

The Implementation Strategies Applied in Communities Matching Process (ISAC Match) provides a pragmatic framework for selecting and tailoring implementation strategies in community settings. This four-step process is designed to be applied within integrated research-practice partnerships (IRPPs) where researchers and practitioners collaboratively address implementation challenges [13].

Table 1: The Four-Step ISAC Match Process

Step	Key Activities	Outputs
1. Contextual Inquiry	Review existing EBI integration data; Conduct rapid formative assessment; Identify barriers and facilitators	Comprehensive understanding of implementation determinants
2. Identify Existing Strategies	Engage practitioners; Review organizational materials; Document current implementation approaches	Inventory of already-used implementation strategies within the organization
3. Select Implementation Strategies	Use ISAC guidance tools; Map strategies to determinants by level and outcome; Prioritize strategies	Tailored set of implementation strategies matched to identified determinants
4. Tailor Strategies	Use brainwriting premortem; Apply nominal group techniques; Modify strategies to fit local context	Contextually adapted implementation strategies ready for testing

This process explicitly incorporates health equity considerations to ensure that implementation strategies do not perpetuate existing health disparities but rather seek to narrow them [13]. The framework addresses the noted deficiency in "pragmatic and community-friendly processes" that often leads to default strategies like "training and hoping" that are inadequate for overcoming organizational or community barriers [13].

Implementation Mapping Methodology

Complementing ISAC Match, Implementation Mapping provides a more detailed, theory-informed approach for planning implementation strategies. This five-step methodology systematically addresses the core tasks of implementation planning [48]:

• Conduct a needs assessment and identify adopters and implementers
• Identify adoption and implementation outcomes, performance objectives, and determinants, then create matrices of change
• Choose theoretical models and select or create implementation strategies
• Produce implementation protocols and materials
• Evaluate implementation outcomes

Implementation Mapping emphasizes understanding the mechanisms of change for selected strategies, thus moving beyond simple selection to a deeper understanding of how strategies work in specific contexts [48].

The following diagram illustrates the logical workflow integrating both ISAC Match and Implementation Mapping approaches for adapting clinical tools:

Application Notes: Critical Considerations for Adaptation

Addressing Social Determinants of Health

Effective adaptation of clinical tools must account for the powerful influence of social determinants of health (SDOH), which have a greater impact on health outcomes than genetic influences or healthcare access [49]. The five key SDOH domains include economic stability, education access and quality, healthcare access and quality, neighborhood environment, and social support [50] [51]. These determinants create structural barriers that directly impact patients' willingness and ability to access care, including transportation limitations, economic constraints, and experiences of discrimination [51].

Specific adaptation considerations include:

• Transportation barriers: Implement telehealth options and community-based delivery where possible, recognizing that transportation issues lead to delayed care and missed appointments, particularly among low-income and elderly populations [51].
• Economic stability: Adapt tools to account for resource constraints, including simplified protocols that require less specialized equipment or staffing.
• Health literacy: Modify educational materials and assessment tools to accommodate varying literacy levels and cultural health beliefs.
• Digital access: Provide alternative non-digital options recognizing the digital divide that affects vulnerable populations.

Community Engagement as a Foundational Element

Meaningful community engagement is not an optional component but a necessity for successful adaptation. The National Academy of Medicine conceptual model positions community engagement as central to achieving health equity and systems transformation [52]. Effective engagement requires:

• Going to communities to learn their perspectives, strengths, values, and priorities rather than expecting them to conform to external frameworks
• Amplifying and crediting community wisdom through co-authorship, co-presentation, and appropriate compensation
• Supporting community-led projects and infrastructure by positioning communities as senior investigators rather than just participants
• Practicing cultural humility and building trust through sustained relationships rather than transactional interactions [52]

The third edition of the Principles of Community Engagement emphasizes trustworthiness as a fundamental element in sustaining community engagement and advancing health equity [52]. This involves acknowledging historical injustices and power imbalances that have created distrust in health systems.

Harnessing Digital Health Technologies

The expansion of digital health technologies presents significant opportunities for adapting clinical tools in community settings. By 2025, consumer-facing wearable devices are owned by one in three Americans and incorporate medical-grade diagnostic technology [53]. These technologies enable:

• Decentralized health monitoring through wearable devices that track vital signs, activity levels, and other biomarkers
• Telehealth expansion to reach rural and underserved communities, with usage increasing from 15.4% in 2019 to 86.5% in 2021 [54]
• Mobile health applications for chronic disease management that provide personalized advice and facilitate communication with healthcare providers
• Digital health platforms for training community health workers in evidence-based practices [54] [53]

However, digital adaptation must consider connectivity limitations, technological literacy, and privacy concerns that may be more pronounced in community settings compared to clinical environments.

Experimental Protocols

Protocol 1: Contextual Inquiry for Implementation Determinants

Purpose: To rapidly identify barriers and facilitators to implementing a specific clinical tool in a community setting.

Materials:

• Recording device or note-taking equipment
• Interview/focus group guides
• Card sorting materials (if conducting in-person)
• Data analysis software (e.g., NVivo, Dedoose) or spreadsheet program

Procedure:

• Assemble Integrated Research-Practice Partnership (IRPP): Form a team of 6-10 members including researchers, community organization leaders, implementation staff, and end-users [13].
• Conduct preliminary evidence review: Identify existing literature on implementation of similar tools in comparable settings, including both peer-reviewed and gray literature [13].
• Select rapid assessment methods based on available time and resources:
  • For comprehensive assessment: Conduct 3-5 focus groups with end-users and implementers (45-60 minutes each) using semi-structured guides
  • For rapid assessment: Use deductive qualitative approaches or rapid ethnography (Table 1) [13]
  • For identifying potential failures: Implement brainwriting premortem approaches where participants silently write reasons adaptation might fail, then discuss [13]
• Analyze and prioritize determinants: Use card sorting activities or 2x2 grids rating barriers by changeability and importance to identify high-priority determinants [13].
• Synthesize findings: Create a determinant framework organized by level (individual, organizational, community) and type (barrier, facilitator).

Output: Prioritized list of implementation determinants informing strategy selection.

Protocol 2: Strategy Selection and Tailoring

Purpose: To systematically select and adapt implementation strategies addressing identified determinants.

Materials:

• ISAC compilation of implementation strategies [13]
• ERIC compilation for clinical strategies (if applicable) [13]
• Strategy prioritization worksheets
• Facilitation materials (whiteboard, sticky notes, etc.)

Procedure:

• Map determinants to strategies: Using the ISAC guidance tool, identify potential implementation strategies matched to determinant framework level and desired implementation outcomes [13].
• Identify existing organizational strategies: Document implementation strategies already in use within the organization that could be leveraged or expanded [13].
• Select candidate strategies: Choose 5-8 potential strategies that address high-priority determinants.
• Prioritize strategies: Using nominal group techniques or feasibility-importance grids, rank potential strategies based on:
  • Feasibility: Organizational capacity, resource requirements, technical complexity
  • Importance: Potential impact on implementation outcomes, reach, sustainability
  • Equity: Likelihood of reducing rather than exacerbating disparities [13]
• Tailor strategies: For each prioritized strategy, conduct brainwriting premortem to identify potential failures, then modify strategies to address identified vulnerabilities [13].
• Develop implementation protocols: Specify who will do what, when, and how for each strategy, including materials needed and timeline.

Output: Tailored implementation strategies with detailed protocols ready for testing.

Protocol 3: Evaluation of Adapted Tools

Purpose: To assess the effectiveness of adapted clinical tools and implementation strategies.

Materials:

• Implementation outcome measures (adoption, fidelity, acceptability, etc.)
• Clinical outcome measures relevant to the tool
• Data collection platforms (electronic surveys, EHR, etc.)
• Analysis software

Procedure:

• Select evaluation framework: Choose appropriate evaluation models such as RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) or PROGIS (Practice Rating of Outcomes and Goals using Implementation Science) [13].
• Establish baseline measures: Collect pre-implementation data on current processes and outcomes.
• Implement mixed-methods evaluation:
  • Quantitative: Track implementation outcomes (adoption rate, fidelity, cost) and clinical outcomes (tool effectiveness, patient outcomes)
  • Qualitative: Conduct interviews or focus groups with implementers and recipients to understand experiences and contextual factors
• Analyze data: Assess implementation success, identify ongoing barriers, and calculate cost-effectiveness where possible.
• Iterate and refine: Use evaluation findings to further refine the adapted tool and implementation strategies.

Output: Comprehensive evaluation of the adapted tool's implementation and effectiveness.

Table 2: Key Implementation Outcomes and Assessment Methods

Outcome Domain	Definition	Assessment Methods
Acceptability	Perception that implementation strategy is agreeable	Surveys, interviews, focus groups
Adoption	Initial decision to employ implementation strategy	Usage logs, organizational records
Appropriateness	Perceived fit or relevance for specific setting	Surveys, Delphi methods, interviews
Feasibility	Extent to which strategy can be successfully used	Pilot testing, usability assessment
Fidelity	Degree to which strategy was implemented as designed	Observation, audit, self-report
Penetration	Integration within service setting	EHR analysis, organizational surveys
Sustainability	Extent to which strategy is maintained	Long-term follow-up, cost analysis

The Scientist's Toolkit: Research Reagent Solutions

Table 3: Essential Resources for Adapting Clinical Tools to Community Settings

Tool/Resource	Function	Application Notes
ISAC Compilation	Catalog of 40 implementation strategies specifically for community settings	Use for strategy selection; 60% have similar content to ERIC strategies but with community-specific language [13]
Implementation Mapping Protocol	5-step methodology for planning implementation strategies	Provides structured approach from needs assessment to evaluation; enhances understanding of mechanisms of change [48]
Principles of Community Engagement	Guidelines for meaningful community partnership	Third edition emphasizes trustworthiness as fundamental element; provides continuum from outreach to shared leadership [52]
RE-AIM Framework	Evaluation model assessing Reach, Effectiveness, Adoption, Implementation, Maintenance	Use for comprehensive evaluation of adapted tools; helps balance internal and external validity concerns [13]
Digital Health Platforms	Technology for remote monitoring and management	Include wearable devices, mobile apps, telehealth; ensure accessibility for populations with limited digital literacy [54] [53]
Health Equity Assessment Tool	Framework for evaluating equity impacts	Use throughout adaptation process to ensure strategies reduce rather than exacerbate disparities [13] [49]
Rapid Assessment Methods	Approaches for efficient contextual inquiry	Include rapid ethnography, deductive qualitative analysis; essential for timely implementation [13]

Strategic Pathways for Implementation

The following diagram illustrates the strategic matching of implementation strategies to common determinants when adapting clinical tools for community settings:

Adapting clinical tools for community and public health settings requires a systematic approach that moves beyond simple modification to strategic implementation planning. The ISAC Match process and Implementation Mapping methodology provide structured frameworks for matching implementation strategies to contextual determinants, while meaningful community engagement ensures cultural relevance and sustainability. By applying these protocols and leveraging the recommended toolkit, researchers and implementation practitioners can enhance the adoption, effectiveness, and sustainment of evidence-based interventions in community settings, ultimately advancing health equity and improving population health outcomes.

Successful adaptation requires acknowledging the fundamental differences between clinical and community environments, particularly regarding resource constraints, workforce capabilities, and the powerful influence of social determinants of health. Future directions should include greater standardization in reporting implementation processes, enhanced methodological guidance for strategy tailoring, and broader evaluation of the clinical and implementation outcomes associated with these adaptation approaches.

Effective implementation of evidence-based practices and health interventions is critically influenced by contextual factors known as implementation determinants. These determinants are dynamic, often changing in their influence throughout the implementation process. A systematic review of studies using the Consolidated Framework for Implementation Research (CFIR) identified that while numerous determinants exist, some consistently demonstrate stronger impacts on implementation success than others [10] [14]. Understanding how these determinants evolve over time is essential for matching implementation strategies to the specific barriers and facilitators present at different stages of implementation. This protocol provides detailed methodologies for tracking and responding to these dynamic changes, enabling researchers and implementation practitioners to optimize their approach through adaptive implementation strategies [55].

The original CFIR framework included numerous constructs, making comprehensive assessment challenging across all potential determinants. Damschroder & Lowery (2013) developed a rating system to quantify the magnitude and valence of determinant impacts, enabling identification of key factors that most significantly influence implementation outcomes [10]. This systematic approach allows researchers to move beyond simply identifying determinants to understanding their relative importance and dynamic nature throughout the implementation process. Recent research has advanced this further through experimental designs that test adaptive implementation strategies that respond to changing contextual factors [55].

Quantitative Data Synthesis: Key Implementation Determinants

Systematic analysis of studies utilizing the Damschroder & Lowery rating criteria has identified eight key determinants that consistently demonstrate strong impacts on implementation processes. These determinants were identified through forward citation searching across three databases (PubMed, Web of Science, and Google Scholar), with 48 articles meeting inclusion criteria for the final review [10] [14]. The table below summarizes these key determinants and their characteristics:

Table 1: Key Implementation Determinants Identified Through Systematic Review

Domain	Determinant	Definition	Impact Rating
Inner Setting	Leadership Engagement	Commitment, involvement, and accountability of leaders and managers	Strong positive facilitator when present; major barrier when absent
Inner Setting	Available Resources	Level of resources dedicated for implementation and ongoing operations	Major barrier when insufficient; moderate facilitator when adequate
Inner Setting	Compatibility	Degree of fit between innovation and existing values, past experiences, and needs	Strong influence on implementation effectiveness
Implementation Process	Formally Appointed Internal Implementation Leaders	Individuals from within the organization who are formally appointed to implement the innovation	Critical differentiator between high and low implementation sites
Implementation Process	Champions	Individuals who dedicate themselves to supporting and driving the implementation	Major facilitator when present; implementation often struggles without
Implementation Process	External Change Agents	Individuals from outside the organization who influence the implementation	Positive influence, particularly in early stages
Individuals	Key Stakeholders	Individuals affected by the implementation who can influence outcomes	Their engagement strongly correlates with implementation success
Innovation Characteristic	Relative Advantage	Stakeholders' perception of the advantage of implementing the innovation	Strong positive influence on adoption and implementation

The rating system applied in these studies quantified determinant impacts using a scale from -2 (major barrier) to +2 (major facilitator), allowing for comparison across diverse implementation contexts [10]. This quantification of qualitative data enables researchers to prioritize determinants based on both the strength and direction of their influence, providing a foundation for developing targeted implementation strategies.

Experimental Protocols for Tracking Determinants Over Time

Protocol 1: Longitudinal Mixed-Methods Assessment

Purpose: To systematically track implementation determinants throughout the implementation lifecycle using quantitative ratings and qualitative contextual data.

Materials and Equipment:

• Audio recording equipment for interviews and focus groups
• Qualitative data analysis software (e.g., NVivo, MAXQDA)
• Statistical analysis software (e.g., R, SPSS, Stata)
• CFIR interview guide adapted to specific context
• Damschroder & Lowery rating scale templates

Procedure:

• Baseline Assessment (Months 0-1):
  • Conduct semi-structured interviews with key stakeholders (leadership, implementation team, end-users)
  • Administer organizational readiness surveys
  • Document initial barriers and facilitators using CFIR constructs
  • Rate determinants using -2 to +2 scale based on qualitative data

• Implementation Phase Tracking (Months 2-6):

  • Conduct brief monthly check-in interviews with implementation team
  • Administer shortened surveys to assess evolving perceptions
  • Observe implementation team meetings and document discussions of barriers/facilitators
  • Update determinant ratings based on new data

• Sustainment Phase Assessment (Months 7-12):

  • Conduct follow-up interviews with baseline participants
  • Administer organizational sustainment surveys
  • Document determinant changes and emerging factors
  • Final determinant rating assessment

• Data Analysis:

  • Thematic analysis of qualitative data using CFIR codebook
  • Quantitative analysis of determinant rating changes over time
  • Mixed-methods integration to identify patterns and relationships
  • Visualization of determinant trajectories throughout implementation

Adaptation Guidance: This protocol can be adapted for different implementation timeframes by adjusting the assessment intervals. For rapid implementations, assessments can be compressed; for longer implementations, additional assessment points can be added.

Protocol 2: Adaptive Implementation Trial Design

Purpose: To experimentally test sequential implementation strategies that adapt to changing determinants over time.

Materials and Equipment:

• Randomization protocol software
• Implementation strategy toolkit
• Fidelity assessment tools
• Data collection platform for outcome tracking
• Statistical analysis plan for adaptive designs

Procedure:

• Initial Randomization:
  • Cluster randomization of sites to different initial implementation strategy conditions
  • All sites begin with foundational implementation support (e.g., Replicating Effective Programs)

• Adaptation Decision Points:

  • Establish predefined decision rules based on implementation outcomes
  • Set thresholds for determinant ratings that trigger strategy adaptation
  • Schedule reassessment intervals (e.g., monthly, quarterly)

• Secondary Randomization:

  • For sites not meeting implementation success thresholds, randomize to augmented implementation strategies
  • Tailor strategy options to address specific determinant profiles
  • Maintain control sites in initial implementation condition

• Outcome Monitoring:

  • Track implementation outcomes (adoption, fidelity, penetration)
  • Continuously monitor determinant ratings
  • Document resource utilization for different strategy sequences

• Data Analysis:

  • Compare effectiveness of different adaptive sequences
  • Identify determinant patterns that predict need for strategy adaptation
  • Calculate cost-effectiveness of adaptive versus static approaches

This protocol is based on Sequential, Multiple-Assignment Randomized Trial (SMART) designs, which have proven effective for answering implementation optimization questions [55]. The ADEPT study provides a practical example of this approach, testing adaptive implementation of the Life Goals collaborative care model [55].

Visualization: Dynamic Determinant Tracking Framework

Dynamic Determinant Tracking Framework

The Scientist's Toolkit: Research Reagent Solutions

Table 2: Essential Research Materials for Determinant Tracking Studies

Research Tool	Function	Application Context
CFIR Interview Guide	Semi-structured interview protocol based on CFIR constructs	Collecting qualitative data on implementation barriers and facilitators
Damschroder & Lowery Rating Scale	Quantitative scale (-2 to +2) for determinant magnitude and valence	Converting qualitative data to comparable quantitative ratings
Mixed Methods Appraisal Tool (MMAT)	Quality assessment instrument for mixed methods studies	Evaluating methodological quality of included studies in systematic reviews
Adaptive Implementation Protocol	Guidelines for sequential strategy adaptation	SMART designs and other adaptive implementation trials
Determinant Trajectory Dashboard	Visualization tool for tracking determinant changes over time	Monitoring temporal patterns in determinant influence
Implementation Outcome Measures	Validated scales for adoption, fidelity, penetration, etc.	Assessing the effectiveness of implementation strategies

These tools collectively enable a comprehensive approach to tracking implementation determinants over time. The CFIR Interview Guide ensures systematic data collection across relevant determinant domains, while the Damschroder & Lowery Rating Scale facilitates quantification of qualitative findings for comparative analysis [10]. The Adaptive Implementation Protocol supports experimental approaches to testing strategy sequences that respond to changing determinants [55]. Together, these reagents form a methodological toolkit for advancing determinant science in implementation research.

Tailoring and Specifying Strategies for Maximum Contextual Fit

Successful implementation of evidence-based interventions depends not only on the interventions themselves but also on how well they match the specific contexts in which they are deployed. Contextual fit is defined as the match between the strategies, procedures, or elements of an intervention and the values, needs, skills, and resources available in a setting [56]. This application note provides researchers and drug development professionals with practical protocols for assessing contextual determinants and systematically tailoring implementation strategies to maximize fit, thereby enhancing adoption, sustainability, and effectiveness of evidence-based practices.

Key Determinants in Implementation Processes

A systematic review of studies using the Consolidated Framework for Implementation Research (CFIR) rating system identified eight key determinants that most strongly influence implementation success [10] [14]. These determinants should be prioritized during implementation planning and strategy selection.

Table 1: Key Implementation Determinants and Their Definitions

Determinant	Definition	Domain
Leadership Engagement	Commitment, involvement, and accountability of leaders and managers	Inner Setting
Formally Appointed Internal Implementation Leaders	Individuals with formal responsibility for implementing the intervention	Implementation Process
Compatibility	The degree of fit between the intervention and existing workflows, values, and norms	Innovation
Available Resources	The level of dedicated resources, including money, training, and space	Inner Setting
External Change Agents	Individuals outside the organization who facilitate implementation	Outer Setting
Champions	Individuals who informally support and drive the implementation forward	Individuals
Relative Advantage	The perceived benefit of implementing the intervention versus an alternative solution	Innovation
Key Stakeholders	Individuals who are affected by or can influence the implementation	Individuals

Protocol for Assessing Context and Selecting Strategies

This protocol provides a systematic approach for matching implementation strategies to identified contextual determinants.

Materials and Equipment

• Assessment tools (interview/focus group guides, surveys)
• Data collection and analysis software
• Multidisciplinary implementation team
• Stakeholder mapping templates
• Strategy selection worksheets

Procedure

Step 1: Contextual Assessment

Conduct a comprehensive assessment of potential barriers and facilitators using mixed methods:

• Qualitative Data Collection: Perform semi-structured interviews and focus groups with key stakeholder groups (leadership, implementers, recipients) [10].
• Determinant Rating: Utilize the Damschroder & Lowery rating system to assess the magnitude and valence (-2 major barrier to +2 major facilitator) of each determinant [10].
• Stakeholder Analysis: Map all relevant stakeholders and their influence/interest levels.

Step 2: Strategy Selection and Tailoring

Employ systematic methods to match strategies to identified determinants:

• Concept Mapping: Use this mixed-methods approach to engage stakeholders in generating, structuring, and rating potential strategies based on importance and feasibility [57].
• Group Model Building: Apply system dynamics methods to collaboratively develop causal loop diagrams that model complex implementation problems and identify leverage points for strategy implementation [57].
• Intervention Mapping: Utilize this systematic, multi-step method to develop implementation strategies that incorporate theory, evidence, and stakeholder perspectives [57].

Step 3: Contextual Fit Evaluation

Assess the proposed strategies against the eight elements of contextual fit [56]:

• Need: Does the strategy address an identified need?
• Precision: Are the core features well-defined?
• Evidence-Base: Is the strategy supported by evidence?
• Efficiency: Is the strategy practical and resource-efficient?
• Skills/Competencies: Are required skills clearly defined and attainable?
• Cultural Relevance: Does the strategy match organizational values and preferences?
• Resources: Are necessary resources available and allocated?
• Administrative Support: Is there adequate organizational support?

Step 4: Implementation and Monitoring

Execute the tailored strategies with ongoing monitoring and adaptation:

• Develop implementation metrics aligned with selected strategies
• Establish feedback mechanisms for continuous improvement
• Schedule regular strategy refinement sessions

Troubleshooting

• Resistance to Change: Engage champions early and often to build momentum [10].
• Resource Limitations: Prioritize strategies based on impact and feasibility [57].
• Poor Leadership Engagement: Present evidence of relative advantage and compatibility with organizational priorities [10].

Implementation Strategy Matching Framework

Table 2: Evidence-Based Strategy Selection for Common Determinants

Identified Determinant	Recommended Strategies	Expected Outcomes
Low Leadership Engagement	- Executive sponsorship programs- Alignment with strategic priorities- Regular implementation progress reports	Increased resource allocationSustained organizational commitment
Poor Compatibility	- Workflow integration analysis- Process adaptation committees- Pilot testing with feedback cycles	Higher adoption ratesReduced implementation resistance
Insufficient Resources	- Phased implementation approach- Cross-training programs- Resource sharing agreements	Sustainable implementationReduced staff burnout
Absence of Champions	- Champion identification and training- Recognition programs- Peer influence networks	Organic spread of supportIncreased credibility
Limited Relative Advantage Perception	- Data on comparative effectiveness- Success story dissemination- Early win celebration	Increased motivation for adoptionStronger implementation climate

Workflow Visualization

Implementation Strategy Tailoring Workflow

The Scientist's Toolkit: Essential Research Reagents

Table 3: Key Resources for Implementation Strategy Research

Resource	Function	Access Source
CFIR Construct List	Comprehensive framework for identifying implementation determinants	CFIR Guide (cfirguide.org)
Damschroder & Lowery Rating System	Tool for quantifying magnitude and valence of determinants	Implementation Science Literature [10]
Protocols.io	Open access repository for research methods and protocols	protocols.io [58]
Springer Nature Experiments	Peer-reviewed, reproducible procedures for scientific experiments	Springer Nature [58]
Wiley Current Protocols	Full-text research methods and topical overviews in life sciences	Wiley Online Library [58]
Structured, Transparent, Accessible Reporting (STAR)	Framework for standardized methods reporting	Cell Press [59]
Resource Identification Portal	Universal identification of research resources	antibodyregistry.org [59]

Engaging Stakeholders and Building Coalitions for Buy-in

Application Notes: Linking Stakeholder Engagement to Implementation Determinants

Effective implementation of evidence-based interventions in drug development hinges on strategically engaging stakeholders to overcome specific contextual barriers. This process involves a deliberate sequence of identifying key determinants, selecting appropriate engagement strategies, and executing targeted activities to build coalition buy-in. The systematic review by Schmitt et al. (2025) identifies eight key determinants that frequently have the strongest impact on implementation processes, which should serve as primary targets for engagement efforts [10] [14].

Stakeholder engagement is critical for ensuring that health guidelines and interventions are relevant, transparent, and useful, ultimately supporting their uptake and sustainability [60]. For researchers and drug development professionals, this means moving beyond token involvement to meaningful partnership with all groups affected by the recommendations, including patients, caregivers, providers, payers, policy makers, and product makers [60]. The following sections provide a structured approach to matching engagement strategies to these critical determinants.

Key Determinants from Implementation Research

The table below summarizes the eight key determinants identified through a systematic review of studies using the Consolidated Framework for Implementation Research (CFIR) rating system, which assesses the magnitude and valence (strength and direction) of factors affecting implementation [10] [14].

Table 1: Key Determinants in Implementation Processes

Key Determinant	Domain	Description of Impact
Leadership Engagement [10] [14]	Inner Setting	Commitment, involvement, and accountability from organizational leaders provides resources and legitimacy.
Formally Appointed Internal Implementation Leaders [10] [14]	Implementation Process	Individuals with dedicated responsibility and authority for managing the implementation effort.
Compatibility [10] [14]	Innovation	The degree of fit between the intervention and existing workflows, values, and perceived needs.
Available Resources [10] [14]	Inner Setting	Adequate funding, staffing, time, and infrastructure dedicated to the implementation.
External Change Agents [10] [14]	Outer Setting	Individuals outside the organization who actively work to facilitate implementation.
Champions [10] [14]	Individuals	Individuals who informally support, promote, and drive the change within their own peer groups.
Relative Advantage [10] [14]	Innovation	The perceived benefit of the new intervention compared to current practice.
Key Stakeholders [10] [14]	Individuals	Patients, providers, and others affected by the intervention, whose input is crucial for relevance and adoption.

Mapping Engagement Strategies to Determinants

Implementation strategies are the specific "how" of implementation—the actions taken to enhance the adoption and sustainability of an evidence-based intervention [16]. The following table maps recommended strategies from the Expert Recommendations for Implementing Change (ERIC) compilation to the key determinants they are designed to address [16].

Table 2: Strategy-to-Determinant Mapping for Stakeholder Engagement

Key Determinant	Recommended Implementation Strategies [16]	Primary Stakeholder Target
Leadership Engagement	• Develop formal implementation blueprints• Mandate change• Organize implementation team meetings	Senior organizational leadership, decision-makers
Formally Appointed Internal Implementation Leaders	• Conduct ongoing training• Facilitate relay of data to clinicians• Provide clinical supervision	Project managers, quality improvement staff, team leads
Compatibility	• Tailor strategies to context• Promote adaptability• Use data experts	Frontline clinicians, technical staff, end-users
Available Resources	• Alter incentive/allowance structures• Access new funding• Fund/contract for the innovation	Finance departments, funders, resource allocators
External Change Agents	• Conduct educational meetings• Build a coalition• Provide facilitation	Consultants, field experts, partner organizations
Champions	• Identify and prepare champions• Model and simulate change• Create learning collaboratives	Influential peers, respected clinical staff
Relative Advantage	• Conduct local consensus discussions• Assess for readiness and barriers• Audit and provide feedback	All stakeholders, particularly skeptics
Key Stakeholders	• Involve patients/consumers• Increase demand• Use mass media	Patients, caregivers, community representatives, providers

Experimental Protocols

Protocol 1: Determinant Identification and Rating

This protocol provides a methodology for identifying and rating the strength of implementation determinants, adapting the approach validated by Damschroder & Lowery (2013) [10].

Objective: To systematically identify and quantify contextual barriers and facilitators prior to implementing a new drug development protocol or clinical guideline.

Materials:

• Research Reagent Solutions:
  • Semi-Structured Interview Guides: Protocols with open-ended questions to elicit perceptions of the innovation and context [10] [61].
  • CFIR Construct Definitions: The 48 constructs and 19 subconstructs from the original CFIR framework to code data [10].
  • Mixed Methods Appraisal Tool (MMAT): A critical appraisal tool for evaluating the quality of studies in a systematic review [10].
  • Damschroder & Lowery Rating Scale: A system for assigning valence and magnitude scores from -2 (major barrier) to +2 (major facilitator) [10].

Procedure:

• Participant Recruitment: Recruit a representative sample of stakeholders (e.g., clinicians, project managers, patients) using purposeful sampling methods as described in FDA PFDD Guidance 1 [61].
• Data Collection: Conduct and audio-record semi-structured interviews or focus groups. The interview guide should be designed to elicit discussion around the key domains of the CFIR framework [10].
• Qualitative Coding: Transcribe interviews verbatim. Code the qualitative data using the CFIR construct definitions as a coding framework [10].
• Determinant Rating: For each CFIR construct identified, assign a rating based on the Damschroder & Lowery scale [10]:
  • -2: Strong negative influence (Major Barrier)
  • -1: Weak negative influence (Minor Barrier)
  • 0: Neutral or mixed influence
  • +1: Weak positive influence (Minor Facilitator)
  • +2: Strong positive influence (Major Facilitator)
• Analysis: Rank-order constructs by their assigned ratings. The constructs consistently receiving scores of -2, +2, or -1, +1 across multiple stakeholders or sites are designated as key determinants for that context. Quality of the process can be appraised using the MMAT [10].

Protocol 2: Multi-Stakeholder Engagement for Guideline Development

This protocol outlines a method for engaging multiple stakeholders throughout the health guideline development process, based on a Campbell systematic review protocol [60].

Objective: To ensure equitable inclusion of diverse stakeholder perspectives in the development of a clinical guideline to enhance its relevance, acceptability, and feasibility.

Materials:

• Research Reagent Solutions:
  • Stakeholder Mapping Template: A grid for identifying all groups affected by the guideline (patients, providers, payers, etc.) [60].
  • PROGRESS-Plus Framework: A checklist to ensure consideration of Place, Race, Occupation, etc., for equitable inclusion [60].
  • GIN-McMaster Guideline Development Checklist: A framework outlining 18 topics in the guideline development process [60].
  • GRADE Evidence to Decision (EtD) Framework: A structured template for formulating recommendations based on criteria like equity, acceptability, and feasibility [60].

Procedure:

• Planning:
  • Map all potential stakeholder groups using the Stakeholder Mapping Template.
  • Intentionally identify individuals from groups typically underrepresented using the PROGRESS-Plus framework to promote equity [60].
• Stakeholder Identification: Recruit stakeholders for a guideline panel, aiming for a multi-speciality group over a single-speciality group to capture a wider range of opinions [60].
• Integration throughout the Process: Engage stakeholders at multiple steps of the GIN-McMaster checklist, not just as a single step [60]. Key activities include:
  • Priority and Question Formulation: Involve patients and caregivers to ensure the guideline addresses outcomes important to them.
  • Evidence Review and Recommendation Formulation: Use the GRADE EtD framework to systematically discuss acceptability and feasibility with all stakeholder representatives [60].
  • Drafting and Peer Review: Engage peer review editors to ensure the document meets publication standards and policy makers to assess implementation feasibility [60].
• Evaluation: Document the engagement process, including which stakeholders were engaged, at which stages, and the nature of their input (e.g., advisory vs. decision-making).

Visualizations

Stakeholder Engagement Causal Pathway

Multi-Stakeholder Guideline Development Workflow

Measuring Impact and Comparing Approaches for Continuous Improvement

In implementation science, success is not solely defined by the effectiveness of a clinical intervention but by the success of the process used to integrate that intervention into real-world settings [62]. This critical distinction separates implementation outcomes from service system and clinical treatment outcomes [62]. The landmark taxonomy proposed by Proctor and colleagues established eight conceptually distinct implementation outcomes: acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration, and sustainability [62] [63]. These outcomes serve as crucial indicators of implementation success, function as proximal measures of implementation processes, and act as key intermediate outcomes that are necessary preconditions for achieving desired service and client outcomes [62]. Within the broader context of matching implementation strategies to determinants, these outcomes provide the essential metrics for evaluating whether selected strategies are effectively addressing identified barriers and facilitators [57] [64].

The Proctor Taxonomy: Defining the Core Implementation Outcomes

Proctor's taxonomy provides precise nominal definitions for each implementation outcome, enabling researchers to distinguish between them conceptually and operationally [62]. The table below summarizes these core outcomes, their definitions, and their relevance across implementation stages.

Table 1: The Proctor Taxonomy of Implementation Outcomes

Implementation Outcome	Definition	Level of Analysis	Salience by Implementation Stage
Acceptability	The perception among stakeholders that an intervention is agreeable, palatable, or satisfactory [62].	Individual provider, Individual consumer [62]	Early for adoption, Ongoing for penetration, Late for sustainability [62]
Adoption	The intention, initial decision, or action to try to employ a new intervention [62].	Individual provider, Organization or setting [62]	Early to mid [62]
Appropriateness	The perceived fit, relevance, or compatibility of the intervention for a given setting or consumer [62].	Individual provider, Individual consumer, Organization or setting [62]	Early (prior to adoption) [62]
Feasibility	The extent to which a new intervention can be successfully used or carried out within a given setting [62].	Individual providers, Organization or setting [62]	Early (during adoption) [62]
Fidelity	The degree to which an intervention was implemented as it was prescribed in the original protocol [62] [63].	Individual provider [62]	Ongoing [65]
Implementation Cost	The cost impact of an implementation effort [63].	Organization or setting [62]	Ongoing [65]
Penetration / Reach	The integration of an intervention within a service setting and its subsystems [62].	Organization or setting [62]	Mid to late [65]
Sustainability	The extent to which a newly implemented intervention is maintained or institutionalized within a setting's ongoing, stable operations [62].	Organization or setting [62]	Late [62]

These outcomes form a logical sequence where earlier outcomes (e.g., acceptability, appropriateness) often precede and influence later outcomes (e.g., penetration, sustainability) [62]. They are conceptually distinct from service outcomes (e.g., efficiency, safety, equity) and client outcomes (e.g., satisfaction, symptomatology), which they ultimately aim to positively affect [62] [63].

Quantitative Measurement of Implementation Outcomes

Quantitative evaluation is essential for summative assessments of implementation strategies, allowing researchers to characterize and quantify their overall impact [65]. The choice of measurement method must align with the specific outcome and level of analysis.

Table 2: Quantitative Measurement Methods for Implementation Outcomes

Outcome	Quantitative Measurement Methods	Example Application
Acceptability	Surveys (e.g., satisfaction scales), administrative data (e.g., refusal rates) [62] [65]	Measuring provider satisfaction with a new digital mental health tool's content and comfort level [65].
Adoption	Administrative data (e.g., usage logs), observation, surveys of intention to use [62] [65]	Tracking the proportion of clinics that initiate a new medication therapy [65].
Appropriateness	Surveys measuring perceived fit, relevance, or compatibility [62] [65]	Assessing the perceived relevance of a collaborative care model for a primary care setting [65].
Feasibility	Surveys, administrative data on actual use and resource utilization [62] [65]	Documenting the time and resources required to integrate a screening tool into an electronic health record [65].
Fidelity	Checklists, structured observations, audit of session recordings or clinical notes [62]	Using a standardized checklist to assess if a psychotherapy protocol is delivered as intended [62].
Implementation Cost	Marginal cost analysis, cost-effectiveness, cost-benefit analysis [62] [63]	Calculating the marginal cost and cost-effectiveness of implementing a new patient education program [63].
Penetration / Reach	Analysis of organizational records, patient registries to measure coverage and spread [62] [65]	Calculating the proportion of eligible patients who receive a new evidence-based intervention in a healthcare system [65].
Sustainability	Long-term administrative data tracking continued use of the intervention over time [62] [65]	Measuring the continued delivery of an intervention 2 years after initial implementation support has ended [65].

Quantitative methods are particularly valuable in later-stage implementation research, such in as between-site or rollout trials, where powered tests of implementation strategies are conducted [65]. These designs allow for aggregation and comparison of quantitative outcomes across multiple service system units, generating generalizable knowledge about strategy effectiveness [65].

Application Notes: Linking Strategies to Determinants Using Implementation Outcomes

The process of matching implementation strategies to contextual determinants is a critical step in implementation research [57] [64]. Implementation outcomes serve as the key dependent variables for evaluating whether this matching is successful. The following protocol outlines a systematic approach for this process.

Protocol: A Multi-Method Approach to Strategy Selection and Tailoring

Objective: To provide a systematic method for selecting and tailoring implementation strategies to address context-specific determinants, with the goal of improving implementation outcomes.

Background: The effectiveness of evidence-based interventions is often thwarted by implementation failure rather than intervention failure [62]. Selecting strategies based on identified barriers and facilitators enhances the likelihood of successful implementation [57] [44]. This protocol synthesizes several established methods for this purpose [57].

Step-by-Step Procedure:

• Determinant Identification: Conduct a pre-implementation assessment to identify barriers and facilitators. Use frameworks like the Consolidated Framework for Implementation Research (CFIR) to guide data collection through focus groups, interviews, or surveys [44] [12].
• Determinant Prioritization: Engage stakeholders (researchers, practitioners, patients) to prioritize the identified determinants based on their importance and mutability. Methods like concept mapping can be used here to structure group input and create a visual map of concepts [57].
• Strategy Selection: Use a matching tool, such as the CFIR-Expert Recommendations for Implementing Change (ERIC) match tool, to generate a list of potential implementation strategies that address the prioritized determinants [44] [12]. This tool links CFIR constructs to a compilation of 73 discrete implementation strategies [12].
• Strategy Tailoring: Refine the selected strategies to fit the local context. Methods like group model building or intervention mapping can be employed here. Group model building involves stakeholders in collaboratively developing causal loop diagrams to model the complex problem and identify strategic leverage points [57]. Intervention mapping provides a systematic process for operationalizing strategies based on theory, evidence, and stakeholder input [57].
• Specification and Evaluation: Clearly specify the tailored strategies using established reporting guidelines [12]. Implement the strategies and use the Proctor outcomes (e.g., adoption, fidelity, penetration) as key metrics to evaluate their effectiveness in a pilot test or full implementation study [62] [65].

Diagram: Strategy-to-Outcome Logic Pathway

Table 3: Essential Reagents and Resources for Implementation Research

Tool/Resource	Function/Description	Application in Research
CFIR-ERIC Matching Tool	A matrix that links barriers (CFIR constructs) to potential implementation strategies (from the ERIC compilation) [12].	Provides a starting point for selecting strategies to address specific contextual barriers identified in a pre-implementation assessment [44] [12].
Implementation Outcomes Repository	A repository of instruments for measuring the eight implementation outcomes [63].	Offers validated data collection tools (surveys, interview guides) for quantifying implementation success, though it does not contain instruments for cost or fidelity [63].
ERIC Strategy List	A compilation of 73 discrete implementation strategies with clear definitions [57] [12].	Standardizes the naming and description of implementation strategies, enabling better reporting, replication, and synthesis across studies [57] [64].
Concept Mapping	A mixed-methods approach that involves group brainstorming, sorting, and rating to create a visual conceptual framework [57].	Used to engage stakeholders in generating, structuring, and prioritizing implementation determinants or strategies [57] [64].
Group Model Building	A system dynamics method where stakeholders collaboratively develop causal loop diagrams [57].	Helps model complex implementation problems to identify high-leverage strategies and anticipate unintended consequences [57].

Proctor's taxonomy of implementation outcomes provides the necessary vocabulary and conceptual framework for evaluating the success of implementation efforts [62]. By clearly defining and quantitatively measuring these outcomes, researchers and practitioners can move beyond simply asking if an intervention works, to understanding how and how well it can be integrated into real-world practice [62] [65]. This is fundamental to the process of matching implementation strategies to determinants, as these outcomes serve as the critical link between the strategies employed and their ultimate impact on the healthcare system and patient well-being [62] [64]. As the field advances, continued refinement of quantitative measures and strategic matching protocols will enhance the rigor and effectiveness of implementation research across diverse clinical and community settings [65] [44] [66].

Application Notes: Integrating Determinants and Implementation Strategies

Successfully moving an evidence-based innovation from research into routine practice requires a deliberate approach to match implementation strategies to contextual determinants. The Consolidated Framework for Implementation Research (CFIR) provides a structured method for identifying these determinants across multiple domains, while implementation outcomes serve as measurable indicators of strategy effectiveness [1]. Systematic reviews have identified key determinants that most frequently impact implementation success, providing a valuable starting point for strategy selection [10].

Key Determinants Influencing Implementation Success

Recent systematic reviews synthesizing studies that used the CFIR framework have identified consistent determinants that strongly influence implementation effectiveness. These key determinants should be prioritized during both planning and evaluation phases [10]:

• Leadership Engagement: Active involvement of organizational leaders in implementation efforts
• Formally Appointed Internal Implementation Leaders: Individuals with designated responsibility for guiding implementation
• Compatibility: The degree of fit between the innovation and existing values, workflows, and systems
• Available Resources: Allocation of sufficient financial, human, and material resources
• External Change Agents: Individuals outside the organization who influence implementation
• Champions: Supportive individuals who actively promote the innovation
• Relative Advantage: Perceived superiority of the innovation compared to alternatives
• Key Stakeholders: Individuals or organizations affected by the implementation

The influence of these determinants varies significantly across resource settings. Research in mHealth interventions for stroke prevention found that "Relative Advantage" and "Access to Knowledge & Information" were emphasized in low-resource settings, while "Design Quality & Packaging" and "Reflecting & Evaluating" were more prominent in high-resource settings [67]. This highlights the critical importance of contextual adaptation when evaluating strategy effectiveness.

Quantitative Framework for Evaluating Implementation Outcomes

Evaluating strategy effectiveness requires tracking specific, measurable implementation outcomes. Proctor and colleagues provide a taxonomy of implementation outcomes that can be quantitatively measured to assess strategy effectiveness [65]:

Table 1: Quantitative Implementation Outcomes for Strategy Evaluation

Implementation Outcome	Level of Analysis	Quantitative Measurement Method	Salience by Implementation Stage
Acceptability	Individual provider, Individual consumer	Survey, Administrative data, Refused/blank items	Early for adoption, Ongoing for penetration
Adoption	Individual provider, Organization or setting	Administrative data, Observation, Survey	Early to mid implementation
Appropriateness	Individual provider, Individual consumer, Organization	Survey	Early (prior to adoption)
Feasibility	Individual providers, Organization or setting	Survey, Administrative data	Early (during adoption)
Fidelity	Individual provider, Organization or setting	Administrative data, Observation, Checklist	Mid to late implementation
Implementation Cost	Organization or setting, System	Administrative cost data, Time-motion studies	Mid implementation
Penetration/Reach	Organization or setting, System	Administrative data, Survey	Mid to late implementation
Sustainability/Sustainment	Organization or setting, System	Administrative data, Survey	Late implementation

Experimental Protocols

Protocol 1: Comprehensive Determinant Identification Using CFIR

Purpose: To systematically identify and assess implementation determinants that may influence strategy effectiveness.

Methodology:

• Study Design: Apply the updated CFIR framework, which includes 48 constructs and 19 subconstructs across five domains: Innovation, Outer Setting, Inner Setting, Individuals, and Implementation Process [1].
• Data Collection: Employ mixed methods combining qualitative interviews or focus groups with quantitative surveys. For qualitative components, use semi-structured interview guides with CFIR-based questions. For quantitative components, consider developing or adapting CFIR-based surveys [1].
• Data Analysis: Code qualitative data to CFIR constructs using established coding guidelines. Consider using magnitude and valence ratings (-2 for major barrier to +2 for major facilitator) to quantify qualitative findings [10].
• Data Interpretation: Identify which determinants distinguish between high and low implementation effectiveness sites. Create matrices comparing determinants across different contexts or settings.
• Knowledge Dissemination: Document determinants and their relationships to implementation outcomes to inform future strategy selection.

Workflow Integration:

Protocol 2: Quantitative Evaluation of Implementation Strategy Effectiveness

Purpose: To quantitatively assess the impact of implementation strategies on predefined outcomes using rigorous evaluation designs.

Methodology:

• Evaluation Design Selection: Choose from three broad design types [65]:
  • Within-site designs: Pre-post or time series comparisons within a single unit
  • Between-site designs: Comparison between two or more service system units
  • Within- and between-site designs: Hybrid approaches like stepped-wedge designs

• Indicator Development: Create specific, measurable indicators aligned with evaluation questions using SMARTIE criteria (Specific, Measurable, Achievable, Relevant, Time-bound, Inclusive, and Equity-focused) [68].

• Data Collection Strategy: Determine appropriate data sources (primary vs. secondary), ensure sufficient data quantity, and implement quality checks for accuracy, completeness, consistency, timeliness, and relevance [68].

• Implementation Outcome Measurement: Track outcomes from Table 1 using appropriate quantitative methods at relevant implementation stages.

• Data Analysis: Analyze the relationship between implementation strategies and outcomes, considering contextual factors identified in Protocol 1.

Evaluation Workflow:

Protocol 3: Strategy-Determiner Alignment Mapping

Purpose: To systematically align implementation strategies with identified determinants to optimize resource allocation and maximize effectiveness.

Methodology:

• Determinant Prioritization: Use findings from Protocol 1 to identify high-priority determinants based on their strength of impact and potential modifiability.

• Strategy Selection: Select implementation strategies from standardized taxonomies such as the Expert Recommendations for Implementing Change (ERIC) that specifically target prioritized determinants [67].

• Alignment Assessment: Evaluate the degree to which implemented strategies match expert-recommended strategies for addressing specific determinants. Research shows low-resource settings demonstrate significantly greater adoption of ERIC strategies compared to high-resource settings (9.40 vs. 7.16 matches per study) [67].

• Gap Analysis: Identify gaps between implemented and recommended strategies, with studies showing 9.53 gaps per study in low-resource settings and 8.00 gaps in high-resource settings [67].

• Effectiveness Evaluation: Assess how well the aligned strategies address determinants and contribute to implementation outcomes.

The Scientist's Toolkit: Research Reagent Solutions

Table 2: Essential Resources for Implementation Strategy Evaluation

Tool/Resource	Function	Application Context
CFIR Framework	Determinant identification and classification	Identifying barriers and facilitators across 5 domains and 48 constructs [1]
CFIR-ERIC Matching	Linking determinants to implementation strategies	Aligning identified barriers with evidence-based implementation strategies [67]
Damschroder & Lowery Rating Scale	Quantifying qualitative data on determinants	Rating determinant magnitude and valence (-2 to +2) [10]
Implementation Outcomes Taxonomy	Measuring implementation success	Tracking acceptability, adoption, appropriateness, feasibility, fidelity, cost, penetration, sustainability [65]
Mixed Methods Appraisal Tool (MMAT)	Quality assessment of included studies	Systematic reviews of implementation research [10]
SMARTIE Indicators	Developing measurable evaluation indicators	Creating Specific, Measurable, Achievable, Relevant, Time-bound, Inclusive, and Equity-focused metrics [68]

Integration with Sustainability Assessment

Evaluating strategy effectiveness must include sustainability considerations from the earliest stages. Sustainable implementation requires attention to economic, social, and environmental factors that influence long-term viability [69]. Research shows that traditional feasibility studies often overemphasize economic performance while giving insufficient attention to social and environmental performance [69]. Effective evaluation protocols should incorporate all three sustainability pillars:

• Economic Sustainability: Implementation costs, resource availability, and long-term funding viability
• Social Sustainability: Stakeholder engagement, equity considerations, and community impact
• Environmental Sustainability: Resource utilization, waste reduction, and environmental impact

The relationship between implementation determinants, strategies, and sustainability outcomes can be visualized as follows:

By systematically applying these protocols and tools, researchers and implementation practitioners can rigorously evaluate strategy effectiveness from initial feasibility through long-term sustainability, creating a robust evidence base for matching implementation strategies to determinants across diverse contexts and resource settings.

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Comparative Analysis of Matching Tools: CFIR-ERIC vs. ISAC

The systematic matching of implementation strategies to contextual determinants is a critical step in bridging the research-to-practice gap. This analysis compares two prominent approaches: the Consolidated Framework for Implementation Research - Expert Recommendations for Implementing Change (CFIR-ERIC) matching tool and the Implementation Strategies Applied in Communities (ISAC) Match process. The CFIR-ERIC tool, developed through expert consensus for clinical settings, offers a standardized, theory-informed method for linking barriers to strategies [26] [12]. In contrast, ISAC Match, developed more recently, provides a rapid, pragmatic process tailored for community settings through integrated research-practice partnerships [13]. This article provides a detailed comparative analysis of their foundational principles, operational protocols, and practical applications, supported by empirical data and structured to guide researchers and scientists in selecting the appropriate tool for their implementation efforts.

Theoretical Foundations and Development

The CFIR-ERIC and ISAC matching tools were developed to address a common challenge in implementation science—selecting strategies to overcome contextual barriers—but they originate from different settings and philosophical approaches.

1.1 CFIR-ERIC Matching Tool The CFIR-ERIC tool is grounded in a rigorous, expert-driven methodology. Its development involved surveying 169 implementation experts who ranked up to seven ERIC strategies they believed would best address each of the 39 CFIR constructs framed as barriers [26]. This process resulted in a comprehensive matrix linking barriers to potential strategies. A key characteristic of this tool is the considerable heterogeneity in expert recommendations; across the 39 CFIR barriers, an average of 47 different ERIC strategies were endorsed at least once for each barrier [26]. This lack of consistent relationships underscores the complexity of strategy matching. The tool is publicly available as an Excel-based resource and is designed to generate a prioritized list of strategies after users input high-priority CFIR-based barriers [70] [26] [12].

1.2 ISAC Matching Process (ISAC Match) ISAC Match was developed to address specific limitations observed in existing compilations like ERIC, particularly for community settings. The ISAC compilation itself includes 40 implementation strategies, of which 60% have similar content to ERIC strategies but use community-specific language, while 40% are unique to community settings [13]. The matching process was designed to be pragmatic and rapid, explicitly intended for use within Integrated Research-Practice Partnerships (IRPPs) [13]. This co-production model equally values researcher and practitioner contributions, ensuring strategies are relevant to the real-world constraints and assets of community organizations. The development of ISAC was motivated by the recognition that clinical language in ERIC and the high number of strategies generated by tools like the CFIR-ERIC matching tool can be prohibitive in community contexts with limited resources [13].

Comparative Operational Profiles

The table below summarizes the core characteristics of the CFIR-ERIC and ISAC Match tools to facilitate direct comparison.

Table 1: Comparative Profiles of CFIR-ERIC and ISAC Matching Tools

Feature	CFIR-ERIC Matching Tool	ISAC Match
Primary Setting	Clinical/Healthcare systems [26] [71]	Community settings (e.g., social services, faith-based, education) [13]
Number of Strategies	73 ERIC strategies [72] [26]	40 ISAC strategies [13]
Core Methodology	Expert opinion survey and matrix-based matching [26] [12]	Four-step process within Integrated Research-Practice Partnerships (IRPPs) [13]
Approach to Determinants	Primarily focuses on diagnosing and addressing barriers [72] [26]	Considers both barriers and facilitators (strength-based approach) [13]
Key Output	A prioritized list of expert-recommended ERIC strategies [26]	A tailored set of implementation strategies co-produced with practitioners [13]

Application Protocols and Workflows

The practical application of these tools involves distinct step-by-step protocols. The following workflows diagram the core operational processes for each.

Figure 1: CFIR-ERIC Implementation Strategy Matching Workflow. This process begins with a contextual assessment to identify CFIR-based barriers, which are then input into the tool to generate a list of expert-recommended strategies [72] [26] [12].

Figure 2: ISAC Match Four-Step Process. This iterative process is embedded within an Integrated Research-Practice Partnership and emphasizes reviewing existing evidence, identifying current strategies, and co-producing tailored solutions [13].

3.1 CFIR-ERIC Protocol in Practice A convergent parallel mixed-methods study in the Veterans Health Administration provides a robust example of the CFIR-ERIC protocol in action [72] [71]. The experimental methodology involved:

• Barrier Identification: Eighteen semi-structured focus groups with 197 providers were conducted to identify pre-implementation CFIR barriers to guideline-concordant cirrhosis care. Key barriers included care complexity and variable local leadership support [72].
• Strategy Generation: The identified barriers were entered into the CFIR-ERIC Matching Tool, which generated a list of 20 recommended strategies. These included "assessing for readiness and needs," "promoting adaptability," and "preparing champions" [72] [71].
• Evaluation: Providers were surveyed over two consecutive years on the use and effectiveness of 73 ERIC strategies. The study found that while sites did not use the top 20 recommended strategies more frequently than others, 70% of the recommended strategies were significantly positively associated with improved cirrhosis care, compared to only 48% of the actual strategies used [72] [71]. This suggests a strong connection between expert recommendations and real-world strategy effectiveness.

3.2 ISAC Match Protocol in Practice The application of the ISAC Match process is illustrated by a case study aimed at increasing the adoption of built environment approaches for physical activity in a state Cooperative Extension System [13]. The detailed protocol was:

• Contextual Inquiry (Step 1): The partnership reviewed available information and, using rapid methods, identified key determinants for the evidence-based intervention (EBI) integration.
• Identify Existing Strategies (Step 2): The team engaged with practitioners to catalog implementation strategies already in use within the organization.
• Select Strategies (Step 3): Using the ISAC guidance tool, the partnership selected new strategies to address unresolved barriers. Prioritization techniques, such as rating strategies by feasibility and importance, were employed [13].
• Tailor Strategies (Step 4): The partnership used methods like a "brainwriting premortem" (a structured exercise to identify potential reasons for failure) to adapt and refine the selected strategies for optimal fit within the Extension context [13].

The Scientist's Toolkit: Key Research Reagents

The table below outlines essential "research reagents" or core components utilized when working with these matching tools.

Table 2: Essential Reagents for Implementation Strategy Matching Research

Tool/Reagent	Primary Function	Specifications & Considerations
CFIR Framework	Determinant framework to systematically identify contextual barriers and facilitators [72] [10].	The original (2009) includes 39 constructs; the updated version (2022) has 48 constructs and 19 subconstructs [10].
ERIC Compilation	A standardized library of 73 discrete implementation strategies for clinical settings [72] [26].	Strategies are defined by expert consensus and can be clustered into nine thematic categories [72].
ISAC Compilation	A library of 40 implementation strategies designed for community settings [13].	40% of strategies are unique to community settings; others are adaptations of ERIC strategies with more accessible language [13].
Integrated Research-Practice Partnership (IRPP)	A collaborative model for co-producing and testing implementation strategies [13].	Foundational to the ISAC Match process. Effective in smaller groups (e.g., <10 members) that include both decision-makers and implementers [13].

Discussion and Future Directions

The comparative analysis reveals that the choice between CFIR-ERIC and ISAC Match is not about superiority but contextual fit. The CFIR-ERIC tool offers a validated, systematic approach highly suitable for resource-rich, clinical environments where a comprehensive list of expert-vetted strategies is valued. Its empirical validation in real-world healthcare settings, such as the VHA, strengthens its credibility [72] [71]. Conversely, ISAC Match offers a pragmatic, rapid, and participatory alternative for community settings, where resource constraints and the need for practitioner buy-in are paramount. Its strength-based approach, which leverages existing facilitators, aligns well with community-engaged research principles.

Future directions for the field include the need for more head-to-head comparisons of the efficiency and impact of these matching processes [13]. Furthermore, the development of hybrid approaches that integrate the systematic barrier assessment of CFIR with the pragmatic, co-production methodology of ISAC could yield even more powerful and adaptable tools for implementation scientists and practitioners across diverse settings.

Understanding causal pathways is fundamental to implementation science, moving beyond the question of whether a strategy works to uncover how and why it produces change. A causal pathway is the hypothesized sequence of events through which an implementation strategy operates to affect outcomes, encompassing the mechanisms, mediators, and moderators that explain its function [73]. Specifying these pathways is critical for matching implementation strategies to contextual determinants, as it allows researchers and practitioners to select and tailor strategies with a precise understanding of their mechanisms of action. This article provides application notes and protocols for visualizing and testing these pathways, offering a practical toolkit for scientists and drug development professionals engaged in translating evidence-based interventions into routine practice.

Key Concepts and Definitions

Table 1: Core Components of an Implementation Causal Pathway

Term	Definition	Role in Causal Pathway	Example from Literature
Implementation Strategy	A method or technique used to enhance the adoption, implementation, and sustainability of an evidence-based intervention [18].	The initial action or "lever" intended to trigger change within the system.	Practice facilitation to improve colorectal cancer screening [74].
Mechanism	The processes or events through which a strategy produces its effects; it explains how or why a strategy works [73].	The causal engine that links the strategy to proximal outcomes.	Increasing network density and communication frequency through network weaving [73].
Mediator	A variable that explains the relationship between a strategy and an outcome; it is part of the causal chain [73].	A measurable intermediate outcome that transmits the effect of the mechanism.	Improved interaction quality and knowledge sharing among coalition members [73].
Moderator	A factor that affects the strength or direction of the relationship between a strategy and an outcome; it explains when or for whom a strategy works [73].	A contextual condition that influences the pathway's operation.	Sector heterogeneity or the presence of key connections within an organization [73].
Proximal Outcome	An immediate or short-term result of a strategy, often closer to the implementation process [73].	An early indicator of change within the system.	Increased perceived appropriateness and adoptability of an evidence-based intervention [73].
Distal Outcome	A longer-term or ultimate result of a strategy, often related to broader impacts [73].	The ultimate goal of the implementation effort.	Sustained adoption of an intervention and improved population health [74] [73].

Application Note: Visualizing Causal Pathways with Diagrams

Causal Pathway Diagrams (CPDs) provide a structured visualization of the hypothesized relationships between strategies, mechanisms, and outcomes. They help implementers articulate their theory of change and consider the necessary preconditions and contextual factors that may enhance or diminish a strategy's effectiveness [74] [16].

The following Graphviz diagram illustrates a generic CPD structure, integrating core components from implementation science frameworks. This model can be adapted for specific implementation projects.

Figure 1: A Causal Pathway Diagram (CPD) modeling how an implementation strategy produces effects. Contextual determinants (yellow) moderate the strategy's effectiveness. The strategy (blue) activates a mechanism (red), leading to a mediator (green), which results in a sequence of outcomes (white). A dashed feedback loop illustrates how outcomes can influence future strategy application.

Experimental Protocol: Constructing and Testing a Causal Pathway

This protocol provides a detailed methodology for developing and empirically examining a causal pathway, drawing from participatory and systems-based approaches [73].

Protocol: Participatory Causal Pathway Mapping

Objective: To collaboratively identify implementation determinants, specify strategies and mechanisms, and create a testable causal pathway model with stakeholders.

Materials:

• Meeting space (virtual or in-person) with whiteboarding capabilities.
• Causal mapping software (e.g., Causal Map, Vensim, or online whiteboards).
• Audio recording equipment for qualitative data collection.

Procedure:

• Stage 1: Identify System Determinants

  • Action: Convene a multidisciplinary team, including researchers, clinicians, and community stakeholders. Conduct structured brainstorming sessions (e.g., using Group Model Building techniques) to identify barriers and facilitators to implementation.
  • Output: A comprehensive list of implementation determinants, which can be organized using established frameworks like the Consolidated Framework for Implementation Research (CFIR) [73].
  • Documentation: Record and transcribe all discussions. Compile determinants into a structured list or table.

• Stage 2: Co-specify Strategies and Map Causal Loops

  • Action: Present the list of determinants to the group. Using a determinant framework like CFIR and a strategy taxonomy like the Expert Recommendations for Implementing Change (ERIC), select and define implementation strategies designed to address high-priority determinants.
  • Output: A set of clearly specified implementation strategies, defined by actor, action, target, temporality, dose, and outcome [18].
  • Documentation: For each strategy, facilitate a discussion on the hypothesized mechanism of action. Use the whiteboard to draft a Causal Loop Diagram (CLD) that visualizes the relationships between strategies, mechanisms, and outcomes, paying special attention to reinforcing (R) and balancing (B) feedback loops [73].

• Stage 3: Develop a Quantitative Model

  • Action: Translate the qualitative CLD into a quantitative Stock-and-Flow Diagram for simulation. Identify which variables in the CLD are "stocks" (accumulations, like Number of Trained Clinicians) and which are "flows" (rates that change stocks, like Training Rate).
  • Output: A Stock-and-Flow Diagram with defined parameters and equations.
  • Documentation: Create the diagram using system dynamics software. Formulate initial equations for flows based on literature, expert opinion, or preliminary data.

• Stage 4: Simulate and Test the Model

  • Action: Run simulations using the Stock-and-Flow model to test the dynamic behavior of the system over time. Conduct "what-if" analyses by varying parameters related to the implementation strategies (e.g., changing the frequency of an activity or the strength of a mechanism).
  • Output: Model output graphs showing how key outcomes (e.g., adoption rates) change under different scenarios.
  • Documentation: Record simulation parameters and results. Compare the model's predictions with empirical data, if available, to validate and refine the causal pathway.

Validation and Analysis:

• Triangulate qualitative data from Stages 1 and 2 with quantitative simulation results from Stage 4.
• Use the model to identify potential leverage points and unintended consequences before full-scale implementation.
• The entire process is iterative; the model should be refined as new data becomes available [73].

The Scientist's Toolkit: Research Reagent Solutions

Table 2: Essential Reagents for Causal Pathway Research

Item Name	Type (Conceptual/Methodological)	Primary Function in Research	Example Application
Consolidated Framework for Implementation Research (CFIR) [35]	Conceptual Framework	Provides a standardized taxonomy of 48 constructs across 5 domains that act as potential barriers and facilitators (moderators) in a causal pathway.	Guides systematic identification of determinants during the initial mapping phase [73].
Expert Recommendations for Implementing Change (ERIC) [16]	Strategy Compilation	A refined menu of 73 discrete implementation strategies, providing a common language for specifying the "action" component of a causal pathway.	Selecting and clearly naming the strategy being tested in the model [18].
Causal Pathway Diagram (CPD) [74] [16]	Methodological Tool	A visual tool for hypothesizing and documenting the relationships between strategies, mechanisms, moderators, and outcomes.	Creating a shared mental model among the research team and stakeholders, as outlined in Figure 1.
Participatory Implementation Systems Mapping (PISM) [73]	Methodological Protocol	A structured, multi-stage protocol for engaging stakeholders in causal pathway modeling, from determinant identification to system simulation.	Applying the detailed experimental protocol described in Section 4 of this article.
Color Blind-Friendly Palette [75] [76]	Data Visualization Standard	A set of colors (e.g., Okabe & Ito, Paul Tol) chosen to ensure CPDs and result graphs are interpretable by individuals with color vision deficiency.	Applying accessible color schemes to all diagrams and data visualizations generated by the research.
Strategy Specification Guideline [18]	Reporting Standard	An 8-dimension framework (actor, action, target, etc.) for precisely defining an implementation strategy, which is a prerequisite for studying its causal pathway.	Ensuring strategies are described with sufficient detail for replication and measurement.

The successful implementation of evidence-based interventions (EBIs) is fundamentally challenged by the complex interplay between contextual determinants and the strategies designed to address them. A systematic review reveals that a "one-size-fits-all" approach is often ineffective, as the same implementation strategy can yield variable outcomes across different settings [77]. This application note provides researchers and drug development professionals with structured protocols and tools to systematically document and analyze these critical interactions. Building a robust evidence base requires moving beyond simply listing barriers and facilitators to specifying the functional mechanisms that link strategies to determinants and, ultimately, to implementation outcomes [16]. The following sections provide a structured approach, complete with quantitative summaries, experimental protocols, and visualization tools, to advance the science of matching strategies to context.

Key Determinants in Implementation Processes

Systematic identification of determinants that most strongly influence implementation success allows researchers to prioritize their efforts. A recent systematic review of studies using the Consolidated Framework for Implementation Research (CFIR) and a formal rating system to assess the strength of determinant impact identified eight key constructs [10]. These determinants consistently demonstrated the strongest influence on implementation processes across multiple studies.

Table 1: Key Implementation Determinants and Their Definitions

Key Determinant	Domain	Definition
Leadership Engagement	Inner Setting	The commitment, involvement, and accountability of leaders and managers in the implementation.
Compatibility	Innovation	The degree of perceived fit between the innovation and existing values, past experiences, and needs.
Available Resources	Inner Setting	The level of resources dedicated for implementation and ongoing operations, including money, training, and space.
Champions	Individuals	Individuals who dedicate themselves to supporting, marketing, and driving through an implementation.
Formally Appointed Internal Implementation Leaders	Implementation Process	Individuals from within the organization who are formally appointed to direct implementation efforts.
Relative Advantage	Innovation	The perceived superiority of the innovation compared to the current practice or alternative solutions.
External Change Agents	Implementation Process	Individuals who are not from the organization but who affect implementation through formal or informal influence.
Key Stakeholders	Individuals	Individuals who are affected by the implementation process or its outcomes, both within and outside the organization.

Determinant-to-Strategy Matching Logic

The relationship between key determinants and the implementation strategies chosen to address them is foundational. The following diagram visualizes this matching logic, providing a conceptual map for planning implementation efforts.

Experimental Protocol for Mechanism Testing

Protocol: Testing Mechanisms of a Multifaceted Implementation Strategy

Objective: To experimentally test whether a multifaceted implementation strategy improves fidelity to an evidence-based guideline through the pathways of change specified by the Capability Opportunity Motivation-Behavior (COM-B) model and the Theoretical Domains Framework (TDF) [77].

Background: Understanding how strategies work requires testing their underlying mechanisms of change. This protocol provides a methodology for determining if a strategy's effect on an implementation outcome (e.g., fidelity) is statistically explained (mediated) by changes in hypothesized determinants [77].

Table 2: Essential Research Reagents and Materials

Item Category	Specific Example	Function / Rationale
Validated Questionnaires	Determinants of Implementation Behavior Questionnaire (DIBQ)	To quantitatively measure TDF-based mediators (e.g., skills, beliefs, goals) with psychometric evidence [77].
Fidelity Instrument	Guideline-specific fidelity scale	To measure the primary outcome of adherence to the evidence-based intervention's core components [77].
Implementation Strategies	Educational meetings, workshops, facilitation, implementation teams	The active "ingredients" being tested, defined using standard compilations like ERIC [16].
Statistical Software	R or SPSS with PROCESS Macro	To perform Linear Mixed Modeling and mediation analysis for clustered data and mechanism testing [77].

Procedure:

• Hypothesis Specification & Causal Pathway Diagramming:

  • Action: Prior to the trial, formally specify the hypothesized mechanisms of change. This involves:
    • Identifying context-specific barriers and enablers (determinants).
    • Selecting an overarching behavioral model (e.g., COM-B) to inform broad pathways.
    • Using a granular framework (e.g., TDF) to specify individual mediators (e.g., skills, goals, environmental resources).
    • Developing a causal pathway diagram (see Section 4.1) that links the strategy to the determinants and then to the outcome [77].
  • Deliverable: A pre-registered analysis plan including a detailed causal pathway diagram.

• Study Design and Randomization:

  • Action: Employ a cluster-randomized controlled trial (cRCT) design. Randomly assign participating sites (e.g., clinics, schools) to either the multifaceted implementation strategy arm or a discrete/control strategy arm [77].
  • Rationale: The experimental design is necessary to establish temporal precedence and infer causality in the mechanism.

• Data Collection Time Points:

  • Action: Collect data at multiple time points to establish temporal sequence:
    • Baseline (T0): Measure fidelity and all hypothesized mediator variables.
    • Post-Strategy Exposure (T1, T2): Measure the mediator variables at least once, but preferably twice, after the delivery of the implementation strategy but before the final outcome assessment.
    • Final Outcome (T3): Measure fidelity again at the primary endpoint (e.g., 12 months) [77].
  • Rationale: Measuring mediators after strategy exposure and before the final outcome is critical for establishing mediation.

• Statistical Analysis:

  • Action: a. Primary Effect Analysis: Use Linear Mixed Models (LMM) to test the total effect of the implementation strategy on the fidelity outcome at T3, accounting for baseline fidelity and cluster effects. b. Mediation Analysis: Use established mediation analysis techniques (e.g., the PROCESS Macro) to test if the effect of the strategy on fidelity is statistically explained by changes in the TDF-based mediators. Report the proportion-mediated effect and its significance for each mediator [77].
  • Output: Quantitative evidence of which specific mechanisms (e.g., skills, goals) account for the strategy's effect on implementation success.

Visualization of Implementation Pathways

Causal Pathway Diagram for a Multifaceted Strategy

The following diagram illustrates a tested causal pathway, derived from a recent study, showing how a multifaceted strategy operates through specific mechanisms to improve fidelity [77]. This provides a concrete example of how to document hypothesized strategy-context interactions.

PM = Proportion Mediated [77]

Application Notes for Researchers

Strategic Guidance for Documentation and Reporting

• Specify and Report with Precision: Clearly name and define all implementation strategies using a common taxonomy, such as the Expert Recommendations for Implementing Change (ERIC) compilation, which contains 73 distinct strategies. Detail the actors, actions, action targets, dose, and justification for each strategy in all research publications [16].
• Document the Determinant-Strategy Link: Explicitly state the rationale for selecting specific strategies by linking them to the contextual barriers and facilitators they are intended to address. This documentation is essential for reproducibility and for building a generalizable evidence base on determinant-strategy matching [16].
• Quantify Determinant Impact: Move beyond simply identifying determinants. When possible, use rating systems to assess the magnitude and valence (from -2 major barrier to +2 major facilitator) of determinants. This allows for the identification of key determinants that have the strongest impact on implementation processes and should be prioritized [10].
• Embrace Mechanism Testing: To advance the field, shift focus from asking if strategies work to understanding how they work. This involves hypothesizing and empirically testing the causal mechanisms through which strategies effect change, using rigorous experimental designs and multiple time-point measurements [77].

The Scientist's Toolkit: Essential Frameworks

Table 3: Key Frameworks for Documenting Context and Strategy

Framework/Tool	Primary Function	Application Note
Consolidated Framework for Implementation Research (CFIR)	A meta-theoretical framework of 48+ constructs to categorize implementation determinants [10].	Use to systematically identify and define contextual factors. The "key determinants" provide a starting point for assessment [10].
Expert Recommendations for Implementing Change (ERIC)	A compilation of 73 clearly defined implementation strategies [16].	Use a standardized taxonomy to name and define strategies, ensuring clarity and reproducibility in reporting [16].
Capability, Opportunity, Motivation-Behavior (COM-B) Model & Theoretical Domains Framework (TDF)	A behavioral system and its granular extension to specify mechanisms of change [77].	Use to hypothesize and test how a strategy changes behavior. The TDF provides specific, measurable mediators for quantitative testing [77].
Causal Pathway Diagram (CPD)	A visual tool to map the proposed linkages between strategies, mechanisms, and outcomes [16].	Create CPDs during the study design phase to articulate theory and guide measurement. They are critical for planning mechanism-focused research [16].

Conclusion

Systematically matching implementation strategies to determinants is not a one-time event but a dynamic and iterative process crucial for successful translation of evidence into practice. Mastering foundational frameworks, applying structured methodological tools, proactively troubleshooting context-specific challenges, and rigorously validating outcomes are all essential. Future efforts must focus on developing more precise, mechanism-based matching approaches, creating tailored tools for non-clinical settings, and building a robust evidence base that documents how specific strategies effectively address key determinants like Leadership Engagement and Available Resources. For biomedical researchers, this systematic approach is key to overcoming the slow and haphazard translation of discoveries into real-world clinical impact, ultimately ensuring that innovative treatments reach patients faster and more effectively.

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