A Model to guide force-based manipulation research and practice

Abstract

Introduction Manual therapies are forms of force-based manipulations (FBM) and involve the application of mechanical force to the outside of the body with therapeutic intent. The United States National Institutes of Health (NIH) U24 FBM Taxonomy and Terminology Committee (FBM-TTC) was formed to better understand why responses to FBM differ between individuals. One objective for this multi-disciplinary working group was to develop a framework outlining factors that should be considered, measured, and reported when developing and performing studies on FBM. Methods The workgroup collaborated to develop a model outlining elements to consider during FBM research and practice. Three different models were proposed by members of the group who voted on a preferred model using a rank-ordered process and refined the selected model based on consensus and published literature. Results A 3-dimensional (3D) matrix model was chosen that includes three elements: contextual factors influencing FBM outcomes, structure and function levels focusing on biological and physiological aspects, and force parameters. Each element expands into different components and sub-levels. The model is designed to be interactive, integrative, and dynamic. Discussion The model provides a framework to guide protocol development for FBM mechanistic research and clinical outcome studies. For example, researchers can design more robust studies systematically varying force parameters by considering other matrix components, while clinicians may develop more personalized treatment plans. The model supports the complexity of mechanistic responses to FBM by integrating the multitude of intrinsic and extrinsic factors that impact responses. Detailed discussion of each element is beyond the scope of this paper; however, content experts are encouraged to expand on this dynamic model. Conclusions An innovative 3D model was developed to guide FBM research. The framework integrates foundational elements and accommodates new insights, making it a valuable tool to advance FBM science and practice.