[Hopkins Verbal Learning Test-revised: normalization and standardization for Spanish population].
O Sáez-Atxukarro1, R Del Pino2,3, J Peña1
1Universidad de Deusto, Bilbao, España.
Revista De Neurologia
|January 13, 2021
Summary
This study provides updated norms for the Hopkins Verbal Learning Test-revised (HVLT-R) in the Spanish population. Performance on the HVLT-R is significantly influenced by age and education level.
Area of Science:
- Neuropsychology
- Cognitive Psychology
- Psychometrics
Background:
- The Hopkins Verbal Learning Test-revised (HVLT-R) is a widely used tool for assessing verbal memory and learning.
- Existing normative data may not accurately reflect the current Spanish population's sociodemographic characteristics.
- Re-administration of the HVLT-R is facilitated by its six alternative forms.
Purpose of the Study:
- To obtain current normative and standardized data for the HVLT-R.
- To account for sociodemographic factors, specifically age, education level, and gender, within the Spanish population.
- To create age- and education-adjusted percentiles and scalar scores for the HVLT-R.
Main Methods:
- The study involved 700 participants aged 18 to 90 years, as part of the Normacog Project.
- Performance on the HVLT-R was analyzed in relation to age, educational level, and gender.
- Percentiles and scalar scores were generated, adjusted for age and educational attainment.
Main Results:
- A significant effect of age and educational level was observed on HVLT-R performance, explaining 15-29% of the variance.
- Older age and lower educational attainment were associated with poorer performance across all HVLT-R variables.
- Gender had a significant effect only on specific variables: trial 1, total recall, and discrimination index.
Conclusions:
- This research provides updated, standardized, and normalized HVLT-R data for the Spanish population.
- The findings underscore the critical influence of age and education on HVLT-R performance.
- Clinicians and researchers can utilize these adjusted normative data for more accurate HVLT-R interpretation.
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