Background: The Montreal Cognitive Assessment (MoCA) may not be appropriately interpreted in Taiwan because of the lack of large-scale normative data. Moreover, examinees' demographic characteristics may influence their MoCA scores. However, previous studies have not adequately adjusted for these effects. This study aimed to use regression-based methods to establish demographically adjusted MoCA norms.
Methods: Participants were recruited from six hospitals and neighboring communities from all geographic areas of Taiwan. Multiple regression analyses were conducted to quantify the effects of age, education, and sex on MoCA total and domain scores, resulting in correction equations and adjusted cutoff scores.
Results: A total of 2,310 cognitively healthy participants were included in the analysis. Age and education significantly affected the total and all domain scores. Sex affected naming, language, and abstract thinking domain scores. Correction equations and corresponding cutoffs were proposed for MoCA total and domain scores to support more precise clinical interpretations.
Conclusion: This study provides regression-adjusted norms for the MoCA, improving its accuracy and clinical utility in Taiwan. An adjusted total MoCA score of 23 points is recommended as the cutoff for identifying potential cognitive impairment, with domain-specific cutoffs further supporting individualized interpretation.
Keywords: Comprehensive cognitive abilities; Demographic variables; Montreal Cognitive Assessment; Neuropsychological assessment; Normative data..
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