Equating conversion norms for the Mini-Mental State Examination and Montreal Cognitive Assessment in Healthy Subjects and Patients with Neurodegenerative Disorders

The dataset evaluated the conversion between Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores, considering different cognitive profiles in a large population of healthy older adults and individuals with cognitive decline within the spectrum of Alzheimer’s (AD) and Parkinson’s (PD) diseases. Identifying reliable conversion norms could support the development of tailored cognitive assessments and interventions. To this end, we applied log-linear smoothing equipercentile equating (LSEE) to derive conversion tables from MMSE to MoCA and vice versa. The reliability of the conversion was evaluated using the Root Mean Square Error (RMSE) within a train-test validation approach. These results provide a valuable tool for cognitive screening, facilitating the interpretation of scores across different cognitive assessment scales and supporting precision approaches in cognitive evaluation and rehabilitation.本数据集在大规模健康老年人群体，以及阿尔茨海默病（AD）、帕金森病（PD）谱系内存在认知下降的个体中，结合不同认知特征，评估了简易精神状态检查表（Mini-Mental State Examination, MMSE）与蒙特利尔认知评估量表（Montreal Cognitive Assessment, MoCA）的分数转换关系。确立可靠的分数转换常模，可为定制化认知评估与干预方案的研发提供支撑。为此，我们采用对数线性平滑等百分位等值法（log-linear smoothing equipercentile equating, LSEE），推导得到MMSE与MoCA的双向转换表。我们通过训练-测试验证法下的均方根误差（Root Mean Square Error, RMSE），评估了该分数转换方法的可靠性。本研究结果可为认知筛查提供实用工具，助力不同认知评估量表间的分数解读，并为认知评估与康复领域的精准化实践提供支持。