Introduction Detecting functional decline from normal aging to dementia is relevant for diagnostic and prognostic purposes. Therefore, the Amsterdam IADL Questionnaire (A-IADL-Q) was developed: a 70-item proxy-based tool with good psychometric properties. We aimed to design a short version while preserving its psychometric quality. Methods Study partners of subjects (n = 1355), ranging from cognitively normal to dementia subjects, completed the original A-IADL-Q. We selected the short version items using a stepwise procedure combining missing data, Item Response Theory, and input from respondents and experts. We investigated internal consistency of the short version and concordance with the original version. To assess its construct validity, we additionally investigated concordance between the short version and the Mini–Mental State Examination (MMSE) and Disability Assessment for Dementia (DAD). Finally, we investigated differences in instrumental activities of daily living (IADL) scores between diagnostic groups across the dementia spectrum. Results We selected 30 items covering the entire spectrum of IADL functioning. Internal consistency (0.98) and concordance with the original version (0.97) were very high. Concordance with the MMSE (0.72) and DAD (0.87) scores was high. IADL impairment scores increased across the spectrum from normal cognition to dementia. Discussion The A-IADL-Q short version (A-IADL-Q-SV) consists of 30 items and has maintained the psychometric quality of the original A-IADL-Q. As such, the A-IADL-Q-SV is a concise measure of functional decline.

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doi.org/10.1016/j.dadm.2017.03.002, hdl.handle.net/1765/99405
Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring

Jutten, R. J., Peeters, C. F. W., Leijdesdorff, S., Visser, P., Maier, A., Terwee, C., … Sikkes, S. A. M. (2017). Detecting functional decline from normal aging to dementia: Development and validation of a short version of the Amsterdam IADL Questionnaire. Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring, 8, 26–35. doi:10.1016/j.dadm.2017.03.002