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Linking traditional and technological activities of daily living: Building modern, adaptable measures of daily functioning

Published online by Cambridge University Press:  25 November 2025

David Andrés González*
Affiliation:
Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
Cecilia Zuniga
Affiliation:
Department of Neurology and Mulva Clinic for the Neurosciences, University of Texas at Austin, Austin, TX, USA
Logan Marie Tufty
Affiliation:
Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA Department of Psychology, University of Illinois Chicago, Chicago, IL, USA
Robin C. Hilsabeck
Affiliation:
Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
Jared F. Benge
Affiliation:
Department of Neurology and Mulva Clinic for the Neurosciences, University of Texas at Austin, Austin, TX, USA
*
Corresponding author: David Andrés González; Email: david_a_gonzalez@rush.edu

Abstract

Objectives:

Instrumental activities of daily living (iADLs) are critical in aging and neurodegenerative research, both diagnostically (e.g., distinguishing dementia from mild cognitive impairment) and as endpoints for trials maintaining or improving functioning. However, measurement has not consistently kept pace with a changed world wherein the ability to navigate technology is pertinent to maintaining independent functioning. The current study used harmonization approaches to link traditional and technological iADLs measures using two samples.

Methods:

262 individuals (53.4% women, 91.7% non-Hispanic White, Mage = 76.2, Meducation = 15.6) completed both measures: (1), the Functional Activities Questionnaire (FAQ), and (2), the new Expanded FAQ. Item response theory (IRT) analyses extracted item parameters to characterize measure psychometrics and accurately determine individual functional ability. Harmonization was done using both nonequivalent groups anchor test (NEAT) and equipercentile linking methods with supplementary traditional iADL parameter estimates from the National Alzheimer Coordinating Center (n = 48,605).

Results:

Correlations verified the measures were sufficiently related (rs = .79), and confirmatory factor analyses and reliability determined all items assessed a single construct. Items from both measures complemented each other to provide more information about milder and more severe functional change. NEAT models converged to provide IRT linking equations and equipercentile conversation tables.

Conclusion:

This study provides critical information for harmonizing evolving technological iADLs with traditional iADLs that are assessed in longstanding cohorts. It further provides support for use of an expanded FAQ.

Information

Type
Research Article
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of International Neuropsychological Society

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