Dataset accompanying PhD thesis: Who benefits most? Evaluating and understanding clinical and biomechanical outcomes following structured education and exercise therapy interventions for people with knee osteoarthritis
Description
This statistical code was generated for the data analysis of three research studies as part of a PhD thesis titled: Who benefits most? Evaluating and understanding clinical and biomechanical outcomes following structured education and exercise therapy interventions for people with knee osteoarthritis. Study 2 (Chapter 5) was a methods paper titled " A statistical model of agreement in subjective rating scales—an exploration of the Kellgren-Lawrence radiological grading system." This paper outlines a workflow for a statistical modelling approach for defining radiological knee OA severity and rater agreement from the Kellgren-Lawrence (KL) system. The analysis utilises the cumulative-link model as implemented in 'brms' (https://doi.org/10.1177/2515245918823199). The data generated were used in study 3 and 4. Study 3 (Chapter 6) was a clinical outcomes study titled " The relationship between radiological OA severity or body weight and outcomes following a structured education and exercise therapy program (GLA:D®) for people with knee osteoarthritis." This pre-post study of 33 participants with knee OA evaluated the relationship between a person's body weight or radiological knee compartment severity and short-term outcomes following the GLA:D® program. The data and workflow for this study have been provided which includes the R code for all models and graphics. Study 4 (Chapter 7) was a biomechanical study titled " Knee joint moment changes during walking and chair-rise and the relationship to radiological knee OA severity and body weight following a structured education and exercise intervention (GLA:D®) for knee osteoarthritis". This pre-post study of 31 participants with knee OA evaluated knee joint moment changes during walking and chair-rise and the relationship to radiological knee OA severity and body weight following the GLA:D® intervention. The documents provided includes the preprocessing workflow that imports the original csv files generated from VICON and the code to generate the secondary parameters (such as peak values and total areas under the curve).
Files
Steps to reproduce
All data manipulation and analysis were performed in R (version 4.3.1, R Core Team 2021). The ‘brms’ package https://doi.org/10.18637/jss.v080.i01, an R interface to Stan https://www.jstatsoft.org/article/view/v076i01, was used to implement the models in Chapter 5-7.