Global Journal of Medical Research, A: Neurology & Nervous System, Volume 23 Issue 3

suggesting that the data used for factor analysis is reasonably adequate. Bartlett's Test of Sphericity examines the correlation matrix presenting ( χ 2105 =1436.865, p< 0.001). This result suggests that the correlation matrix is significantly different from an identity matrix, indicating that the variables are likely correlated and suitable for factor analysis. The extraction communalities range from 0.363 to 0.894, indicating the amount of variance explained by the factors after extraction. The first component explains 27.533% of the variance, and cumulatively, the first three components explain 50.877% of the variance. In the rotation sums of squared loadings, the first component explains 16.845% of the variance, and cumulatively, the first three components explain 46.042% of the variance (please see Appendix 2). Based on these results, it appears that there are meaningful components or factors in the data that explain a significant proportion of the variance. c) The Effect of Disease Types on CLOX Performance One-way ANOVAs were run with Disease Diagnosis as the IV and CLOX scores as the DV (Tukey’s HSD was used for pairwise comparisons). There was a main effect of Disease Diagnosis on CLOX1 Scores (F4,272=37.599, p<.001) where pairwise comparisons showed that all Disease Diagnoses were associated with poorer performance than Healthy Controls (all at p<.001), and those with a Dementia diagnosis performed worse than those with any other Disease Diagnosis (all at p<.001 see Figure 1). Figure 1: Mean CLOX1 Score by Disease Diagnosis (error bars show 95% CI). There was also a main effect of Disease Diagnosis on CLOX2 scores (F4, 278=34.1, p<.001) where pairwise comparisons showed that all Disease Diagnoses were associated with poorer performance than Healthy Controls (all at p<.001) and those with a Dementia diagnosis performed worse than those with any other Disease Diagnosis (all at p<.001 see Figure 2). Figure 2: Mean CLOX2 Score by Disease Diagnosis (error bars show 95% CI). The results of this analysis suggest that individuals with MCI, SLE, MS, and dementia diagnoses exhibit lower performance on both the CLOX1 and CLOX2 tasks in comparison to a control group consisting of healthy individuals. Moreover, when it comes to disease diagnoses, individuals diagnosed with Dementia exhibit notably poorer performance on both tasks in comparison to individuals diagnosed with other diseases. The findings of this study indicate that the scores of CLOX1 and CLOX2 have the potential to be valuable indicators for differentiating between Healthy Controls and individuals diagnosed with SLE, MS, MCI, and specifically Dementia. 63 Year 2023 Global Journal of Medical Research Volume XXIII Issue III Version I ( D ) A © 2023 Global Journals Reliability and Validity Evaluation of the ‘’CLOX: An Executive Clock Drawing Task’’ in a Greek Population with Neurological and Autoimmune Diseases