Despite rapid advances in cancer control, the research to practice gap persists. Implementation science has
provided models, frameworks and taxonomies of implementation strategies that have advanced the field yet
many questions remain about how implementation strategies affect change. A persistent gap that impedes
progress in the uptake and use of cancer prevention and control evidence-based interventions (EBIs) is the
lack of a clear understanding of how implementation strategies address barriers to adoption, implementation,
and sustainment. Understanding and specifying the mechanisms of implementation strategies can accelerate
and improve the selection and tailoring of implementation strategies. The proposed study will elucidate the
mechanisms of Expert Recommendations for Implementing Change (ERIC) strategies using an
Implementation Mapping (IM) approach and will develop and pilot-test an online Implementation Mechanism
Decision-Support Tool, now referred to as Mechanisms for Accelerating Translation of Cancer Health
interventions (MATCH). The proposed tool will: 1) offer a platform for the exploration and development of
theory- and evidence-informed implementation strategies and their mechanisms, aimed at the effective
translation of cancer prevention and control interventions; and 2) provide a library of examples of all ERIC
strategies and their mechanisms drawn from implementation research and practice in cancer prevention and
control. The long-term goal of the proposed project is to enhance the design and tailoring of implementation
strategies to accelerate the translation of cancer control interventions to improve population health. The goal of
the proposed project is to improve our understanding of the ERIC strategies' mechanisms and develop
MATCH. The specific aims are as follows: Aim 1. Map the mechanisms of action (core functions) of all ERIC
strategies using IM; Aim 2. Develop a prototype of the implementation mechanism decision-support tool; Aim
3. Pilot-test and refine the prototype. Aim 1 will be achieved through expert theoretical and empirical coding,
interactive discussions, refinement, followed by a consensus building workshop with an expert panel (n=10).
Coding will be guided by A Taxonomy of Behavioral Change Methods Framework and the IM Logic Model. Aim
2 will be achieved by creating a prototype of MATCH, integrating the final match list of change methods,
determinants, and ERIC strategies with the IM Logic Model Library. Aim 3 will be achieved by conducting
usability testing of MATCH among intended cancer researchers and practitioners, followed by iterative
refinement. This study is significant because it addresses the urgent need in cancer prevention and control to
increase the adoption and use of EBIs and will advance an important implementation science research priority:
shedding light on the mechanisms of implementation strategies. By leveraging both theoretical and empirical
approaches, along with expert consensus, this project will result in an impactful tool designed for wide reach.
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