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A decline in everyday cognitive functioning is important for diagnosing dementia. Informant questionnaires, such as the informant questionnaire on cognitive decline in the elderly (IQCODE), are used to measure this. Previously, conflicting results on the IQCODEs ability to discriminate between Alzheimer's disease (AD), mild cognitive impairment (MCI), and cognitively healthy elderly were found. We aim to investigate whether specific groups of items are more useful than others in discriminating between these patient groups. Informants of 180 AD, 59 MCI, and 89 patients with subjective memory complaints (SMC) completed the IQCODE. To investigate the grouping of questionnaire items, we used a two-dimensional graded response model (GRM).The association between IQCODE, age, gender, education, and diagnosis was modeled using structural equation modeling. The GRM with two groups of items fitted better than the unidimensional model. However, the high correlation between the dimensions (r=.90) suggested unidimensionality. The structural model showed that the IQCODE was able to differentiate between all patient groups. The IQCODE can be considered as unidimensional and as a useful addition to diagnostic screening in a memory clinic setting, as it was able to distinguish between AD, MCI, and SMC and was not influenced by gender or education. (JINS, 2011, 17, 674–681)
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