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Related Experiment Video

Updated: Jul 20, 2026

An Experimental Paradigm for Measuring the Effects of Ageing on Sentence Processing
04:30

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Published on: October 25, 2019

Category fluency test: normative data for English- and Spanish-speaking elderly.

A Acevedo1, D A Loewenstein, W W Barker

  • 1Cognitive Rehabilitation Program, Horizon Health Corporation, Mount Sinai Medical Center, Miami Beach, Florida, USA.

Journal of the International Neuropsychological Society : JINS
|December 6, 2000
PubMed
Summary

This study provides English and Spanish norms for category fluency tasks in older adults. Gender, age, and education significantly predict performance, with gender being the strongest factor.

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Area of Science:

  • Neuropsychology
  • Cognitive Assessment

Background:

  • Category fluency tasks are crucial for dementia evaluation.
  • Growing Spanish-speaking elderly population requires tailored neuropsychological tools.
  • Need for normative data in diverse elderly populations.

Purpose of the Study:

  • Provide normative data for category fluency (animals, vegetables, fruits) for English and Spanish speakers over 50.
  • Examine the influence of age, education, gender, language, and mood on fluency scores.

Main Methods:

  • Study included 702 cognitively intact elderly (424 English, 278 Spanish speakers).
  • Normative data stratified by language, age, education, and gender.
  • Analysis of factors impacting total and specific category fluency scores.

Main Results:

  • Age, education, and gender are primary predictors of total category fluency.
  • Gender is the strongest predictor after accounting for age and education.
  • English speakers scored higher on vegetable fluency than Spanish speakers; similar scores for animals and fruits.

Conclusions:

  • Normative data are essential for accurate neuropsychological assessment in diverse elderly populations.
  • Demographic factors significantly influence category fluency performance.
  • Different fluency measures are differentially affected by various predictors.