Education, Sex, and Age Shape Rey Complex Figure Performance in Cognitively Normal Adults: An Interpretable Machine Learning Study

<b>Background</b>: Demographic factors such as education, sex, and age can significantly influence cognitive test performance, yet their impact on the Montreal Cognitive Assessment (MoCA) and Rey Complex Figure (CF) test has not been fully characterized in large, cognitively normal samples. Understanding these effects is critical for refining normative standards and improving the clinical interpretation of neuropsychological assessments. <b>Methods</b>: Data from 926 cognitively healthy adults (MoCA ≥ 24) were analyzed using supervised machine learning classifiers and complementary statistical models to identify the most predictive MoCA and CF features associated with education, sex, and age, while including race as a covariate. Feature importance analyses were conducted to quantify the relative contributions of accuracy-based and time-based measures after adjusting for demographic confounding. <b>Results</b>: Distinct patterns emerged across demographic groups. Higher educational attainment was associated with longer encoding times and improved recall performance, suggesting more deliberate encoding strategies. Sex differences were most apparent in the recall of visuospatial details and language-related subtests, with women showing relative advantages in fine detail reproduction and verbal fluency. Age-related differences were primarily reflected in slower task completion and reduced spatial memory accuracy. <b>Conclusions</b>: Leveraging one of the largest reported samples of cognitively healthy adults, this study demonstrates that education, sex, and age systematically influence MoCA and CF performance. These findings highlight the importance of incorporating demographic factors into normative frameworks to enhance diagnostic precision and the interpretability of cognitive assessments.