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The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE): socio-demographic correlates, reliability, validity and some norms
Abstract
SYNOPSIS: The IQCODE is a questionnaire which asks an informant about changes in an elderly person's everyday cognitive function. The questionnaire aims to assess cognitive decline independent of pre-morbid ability. In the present study, the IQCODE was administered to a sample of 613 informants from the general population. In addition, the questionnaire was administered to informants of 309 dementing subjects who had filled it out one year previously. A principal components analysis, using the general population sample, confirmed that the IQCODE measures a general factor of cognitive decline. The questionnaire was found to have high internal reliability in the general population sample (alpha = 0·95) and reasonably high test-retest reliability over one year in the dementing sample (r = 0·75). The total IQCODE score, as well as each of the 26-items, was found to discriminate well between the general population and dementing samples. The correlation with education was quite small (r = – 0·13), indicating that contamination by premorbid ability is not a problem.
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Metadata
- Authors
- Jorm, A. F., & Jacomb, P. A.
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 1989-11
- Volume
- 19
- Issue
- 4
- Pages
- 1015-1022
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- OpenAlex
- W2096529213
- Cited by
- 1,114
- References
- 3
- FWCI
- 2.72
- Type
- journal article
- Language
- en
- Open access
- closed
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
