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Rethinking barriers and facilitators in implementation science: conceptual, methodological, and practical challenges,
Per Nilsen1,2
1Department of Health, Medicine and Health Sciences, Linköping University, Linköping, Sweden. per.nilsen@liu.se.
Barriers and facilitators (B&F) in implementation science are often perceived simplistically. This study critiques the traditional B&F approach, advocating for dynamic system properties to better explain real-world change.
Area of Science:
- Implementation Science
- Health Services Research
- Organizational Behavior
Background:
- Barriers and facilitators (B&F) are foundational concepts in implementation science for understanding evidence-based practice adoption.
- Established frameworks like the Consolidated Framework for Implementation Research and Theoretical Domains Framework standardize B&F terminology.
- The field's maturation reveals limitations in the traditional B&F approach.
Purpose of the Study:
- Critically examine eight challenges in identifying, measuring, and applying barriers and facilitators.
- Propose a reconceptualization of B&F to advance implementation science.
- Highlight the need for methods capturing complexity and mechanisms in implementation.
Main Methods:
- Critical analysis of theoretical, empirical, and methodological literature on barriers and facilitators.
- Examination of conceptual and methodological limitations of the traditional B&F approach.
- Review of existing determinant frameworks in implementation science.
Main Results:
- Barriers and facilitators are not simple opposites and are often perception-based rather than mechanistic.
- Exhaustive identification of B&F is often infeasible or lacks conceptual coherence.
- Measurement, prioritization, and consideration of dynamic, multi-level, and temporal aspects of implementation remain inconsistent.
Conclusions:
- The traditional B&F approach has limitations hindering progress toward explanatory and actionable implementation science.
- Reconceptualizing B&F as dynamic system properties and adopting complexity-capturing methods are crucial.
- Strengthening theory-method alignment will shift implementation research from enumeration to explanation of change.
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