title: Predictors of quantitative and qualitative Halstead finger-tapping scores in low socioeconomic status school-age children.
abstract: Two hundred and thirteen low socioeconomic school-age children in grades 1 through 8 were administered the Halstead Finger Oscillation (or Tapping) Test (HFTT). All children were age appropriate for their grade in school and were not requiring special education services. Hierarchical multiple regression analysis revealed that a composite age/grade classification score, gender, and estimated level of intelligence accounted for approximately 40% of the variability in dominant and nondominant hand scores for these children (multiple R = .627, R(2) = +.393 for the dominant and multiple R = +.607, R(2) = +.368 for the nondominant hand). Only the age/grade level of the child (R(2) = .168) predicted the ability to inhibit adjacent finger movements when performing the HFTT task. Regional normative data for low socioeconomic school-age children are presented. Neurodevelopmental changes in the cortical and subcortical systems underlying finger movement may account for some of the variability observed in children when performing the HFTT.
authors.affiliation: Division of Neurology, Barrow Neurological Institute, St Joseph's Hospital and Medical Center, Phoenix, AZ 85013, USA. gprigat@chw.edu
authors.forename: George P
authors.initials: GP
authors.lastname: Prigatano
authors.forename: Jennifer A
authors.initials: JA
authors.lastname: Gray
authors.forename: Joe
authors.initials: J
authors.lastname: Legacy
mesh_terms: D000293:Adolescent; D017677:Age Distribution; D001130:Arizona; D002648:Child; D004292:Dominance, Cerebral / Q000502:physiology; D005260:Female; D005385:Fingers / Q000502:physiology*; D006801:Humans; D007360:Intelligence / Q000502:physiology; D007361:Intelligence Tests / Q000706:statistics & numerical data; D008297:Male; D009048:Motor Skills / Q000502:physiology*; D009433:Neural Inhibition; D011237:Predictive Value of Tests; D017678:Sex Distribution; D012923:Social Class; D013647:Task Performance and Analysis