Peña-Casanova Jordi, Gramunt-Fombuena Nina, Quiñones-Ubeda Sonia, Sánchez-Benavides Gonzalo, Aguilar Miquel, Badenes Dolors, Molinuevo José Luis, Robles Alfredo, Barquero Maria Sagrario, Payno María, Antúnez Carmen, Martínez-Parra Carlos, Frank-García Anna, Fernández Manuel, Alfonso Verónica, Sol Josep M, Blesa Rafael
Section of Behavioral Neurology and Dementias, Hospital del Mar, Institut Municipal d'Assistència Sanitària, Barcelona, Spain.
Arch Clin Neuropsychol. 2009 Jun;24(4):371-93. doi: 10.1093/arclin/acp041. Epub 2009 Aug 6.
The Rey-Osterrieth complex figure (ROCF) and the free and cued selective reminding test (FCSRT) are frequently used in clinical practice. The ROCF assesses visual perception, constructional praxis, and visuospatial memory, and the FCSRT assesses verbal learning and memory. As part of the Spanish Normative Studies (NEURONORMA), we provide age- and education-adjusted norms for the ROCF (copy and memory) and for the FCSRT. The sample consists of 332 and 340 participants, respectively, who are cognitively normal, community dwelling, and ranging in age from 50 to 94 years. Tables are provided to convert raw scores to age-adjusted scaled scores. These were further converted into education-adjusted scaled scores by applying regression-based adjustments. Although age and education affected the score of the ROCF and FCSRT, sex was found to be unrelated in this normal sample. The normative data presented here were obtained from the same study sample as all other NEURONORMA norms and the same statistical procedures were applied. These co-normed data will allow clinicians to compare scores from one test with all the tests included in the project.
雷伊-奥斯特里茨复杂图形测验（ROCF）和自由及线索选择回忆测验（FCSRT）在临床实践中经常被使用。ROCF评估视觉感知、构图能力和视觉空间记忆，而FCSRT评估言语学习和记忆。作为西班牙标准化研究（NEURONORMA）的一部分，我们提供了ROCF（临摹和记忆）以及FCSRT的年龄和教育程度调整后的常模。样本分别由332名和340名参与者组成，他们认知正常，居住在社区，年龄在50岁至94岁之间。提供了表格以将原始分数转换为年龄调整后的量表分数。通过应用基于回归的调整，这些分数进一步转换为教育程度调整后的量表分数。虽然年龄和教育程度影响了ROCF和FCSRT的分数，但在这个正常样本中发现性别与之无关。此处呈现的常模数据与所有其他NEURONORMA常模来自相同的研究样本，并应用了相同的统计程序。这些共同常模数据将使临床医生能够将一项测试的分数与该项目中包含的所有测试进行比较。
