Rey–Osterrieth complex figure normative data for the psychiatric population

<b>Objective:</b> Appropriate normative data are crucial for competent neuropsychological assessment. Although individuals with psychiatric illness often perform more poorly than healthy adults on neuropsychological testing, data that reflect the psychiatric population are often lacking. We present a normative dataset and calculation tools for the Rey–Osterrieth Complex Figure Test (RCFT) derived from the psychiatric inpatient population. <b>Method:</b> A sample of 301 psychiatric inpatients completed the RCFT and the Test of Memory Malingering (TOMM) between 1999 and 2018. Participants were 59.5% male, 82.1% Caucasian, 13.3% black, and 4.6% identified as another racial demographic, largely consistent with recent Substance Abuse and Mental Health Services Administration (2018) data for inpatients in U.S. psychiatric facilities. Scores for RCFT Copy, Short-Delay Free Recall, Long-Delay Free Recall, Total Recognition, and Percent Retained were modeled via multiple regression with age and education as predictors. Base rates were computed for subscores comprising Total Recognition to aid clinical decision making. <b>Results:</b> Age and education served as significant individual predictors for all models except one model predicting percent retained across delay that included only age. Regression equations and regression standard errors were used to produce a score calculator using a commonly available spreadsheet software package. Healthy adult norms under-estimated performance in our sample, underscoring the importance of these normative data. <b>Conclusions:</b> These normative data for the RCFT represent a large cohort of psychiatric inpatients. For clinical practice and research, both the data and the tools provided are likely to be of particular usefulness among individuals with serious mental illness.

<b>研究目的:</b> 恰当的常模数据对于规范的神经心理学评估至关重要。尽管精神疾病患者在神经心理学测试中的表现通常劣于健康成年人，但针对精神疾病群体的常模数据往往较为匮乏。本研究基于精神科住院患者群体，构建了雷伊-奥斯特里赫复杂图形测验（Rey–Osterrieth Complex Figure Test, RCFT）的常模数据集与计算工具。<b>方法:</b> 1999年至2018年间，共301名精神科住院患者完成了雷伊-奥斯特里赫复杂图形测验（RCFT）与记忆伪装测验（Test of Memory Malingering, TOMM）。参与者中男性占比59.5%，白种人占82.1%，黑种人占13.3%，另有4.6%归属其他种族类别，该人口统计学构成与美国物质滥用与精神健康服务管理局（Substance Abuse and Mental Health Services Administration, SAMHSA）2018年发布的美国精神科住院患者相关数据大体一致。本研究以年龄与受教育程度为预测变量，通过多元回归分析对RCFT复制分、短时延迟自由回忆分、长时延迟自由回忆分、总再认分以及保持百分比进行建模；同时针对由总再认分构成的子量表计算了基础率，以辅助临床决策。<b>结果:</b> 除仅以年龄为预测变量的延迟阶段保持百分比预测模型外，年龄与受教育程度对所有模型均为显著的独立预测因子。本研究基于回归方程与回归标准误，通过通用电子表格软件开发了分数计算器。健康成人常模低估了本研究样本的表现水平，这凸显了本次发布的常模数据的重要价值。<b>结论:</b> 本次发布的RCFT常模数据基于大型精神科住院患者队列。在临床实践与研究中，本次提供的数据集与计算工具对重性精神疾病患者群体或具有尤为重要的应用价值。