## 2 Materials and Methods
### Detailed Presentations of the Methodological Steps of the DYNAMIKOS Model
#### 2.1.1 Development of the Casual Loop Diagram via Group Modeling Building Methodology (Phase A)
The devolution of a qualitative CLD to a quantitative model will be achieved by the methodology of SEM [31]. The SEM constitutes an innovative, rigorous, and updated multivariable nonlinear statistical method that empowers the innovation of the DYNAMIKOS model. Specifically, the data will be analyzed using SEM, a powerful multivariate technique that examines the multiple simultaneous interrelationships among numerous factors and their association with KOA. Figure 3: Example of a Causal Loop Diagram (CLD) depicting the dynamic interrelationships among risk factors contributing to knee osteoarthritis (KOA). A negative sign (\(-\)) signifies that the dependent variable changes inversely to the independent variable, while a positive sign (\(+\)) indicates that the dependent variable shifts in the same direction as the independent variable. The SEM statistical methodology initially requires conducting an Exploratory Factor Analysis (EFA). A series of EFAs will be conducted using the data collected in the previous phase to extract the main factors that explain the underlying latent construct of the different measured variables [32]. EFA will categorize the measured items into a latent factor based on their associations. Then, the best factor solution extracted by the EFA will be confirmed via the Confirmatory Factor Analysis (CFA). Finally, the SEM model will be formulated to describe the nonlinear interrelationships among the factors and their direct or indirect associations with KOA development. Different model fit indices will be used to evaluate the model fit. These indices include the Root Mean Square Error of Approximation (RMSEA) and Comparative Fit Index (CFI). RMSEA is an index measuring the badness of fit, with higher values to indicate a weaker fit and zero a perfect fit. RMSEA value should be below 0.08 to be acceptable [31]. CFI values range from 0.0 to 1.0, with a value greater than 0.95 indicating a good fit for the model. The variance explained by the dependent variable in the model will be evaluated using the R-squared values. Furthermore, the statistical significance of the relationships among the risk factors in the SEM analysis will be determined at \(p<0.05\). The relevant literature shows that an appropriate sample should consist of at least 100-200 subjects for SEM analysis [31]. As mentioned, we established a target of 500 participants (250 cases and 250 control) for the DYNAMICS model development. SEM analysis will be performed on the data collected from both KOA patients and healthy control participants. Differences among SEM analysis will be reported. The statistical tools of SPSS and Analysis of Moment Structures (AMOS) software version 29 will be used for SEM analysis. 1.3 Formulation of the System Dynamics Simulation Model (DYNAMIKOS Model): Sensitivity Analysis, and Scenario Planning (Phase C)  
The main factors that better explain the KOA will be used as variables in the SD model. The core modeling team will formulate an SD model based on the risk factor and data identified by the literature review, stakeholders' opinions (CLD in Phase A), and the measured SEM results. Following the qualitative CLD formulated in Phase A, a quantitative SD model incorporating a Stock and Flow diagram will be developed. Specific equations will be introduced in the factor's relationships. The aim will be to formulate a model that better captures the complexity of KOA's risk factors. The model will predict the possibility of KOA development and progression in a population. The formulated DYNAMICS model will be calibrated based on real-world results. Finally, different scenarios will be assessed after the SD model has been calibrated and validated. Various experimental interventions will be applied to evaluate the impact of these interventions using the DYNAMICS model. The DYNAMICS model is anticipated to be a supporting tool that policymakers can use to enhance KOA prevention and management.