Normative Data Estimation in Neuropsychological Tests: A Systematic Review

Objective To quantify the evolution, impact, and importance of normative data (ND) calculation by identifying trends in the research literature and what approaches need improvement.Methods A PRISMA-guideline systematic review was performed on literature from 2000 to 2022 in PubMed, Pub-Psych, and Web of Science. Inclusion criteria included scientific articles about ND in neuropsychological tests with clear data analysis, published in any country, and written in English or Spanish. Cross-sectional and longitudinal studies were included. Bibliometric analysis was used to examine the growth, productivity, journal dispersion, and impact of the topic. VOSViewer compared keyword co-occurrence networks between 1952-1999 and 2000-2022.Results Four hundred twelve articles met inclusion and exclusion criteria. The most studied predictors were age, education, and sex. There were a greater number of studies/projects focusing on adults than children. The Verbal Fluency Test (12.7%) was the most studied test, and the most frequently used variable selection strategy was linear regression (49.5%). Regression-based approaches were widely used, whereas the traditional approach was still used. ND were presented mostly in percentiles (44.2%). Bibliometrics showed exponential growth in publications. Three journals (2.41%) were in the Core Zone. VOSViewer results showed small nodes, long distances, and four ND-related topics from 1952 to 1999, and there were larger nodes with short connections from 2000 to 2022, indicating topic spread.Conclusions Future studies should be conducted on children's ND, and alternative statistical methods should be used over the widely used regression approaches to address limitations and support growth of the field.

Automated summary

This study aims to quantify the evolution, impact, and importance of normative data (ND) calculation. The results showed that there were more studies focusing on adults than children, and age, education, and sex were the most studied predictors. Regression-based approaches were widely used, but alternative statistical methods should be considered to address limitations and support growth in the field.