Work

A - 26 Re-establishing and Refining Baseline Neuropsychological Test Data Among Professional Hockey Players Using Regression-Based Prediction Models

Year: 2025
Type: conference-abstract
Abstract: Purpose Create contemporary culturally relevant baseline reference values for use in evaluating concussed NHL athletes using traditional and regression-based models that are co-normed with estimates of premorbid functioning and English language proficiency. Method Across two seasons five (5) players from each NHL Club (32 clubs) each season were selected at random (with oversampling of ESL athletes) and underwent testing with the NHL Neuropsychological Testing Battery: English Proficiency Questionnaire (ESL only), ToPF, HVLT-R, BVMT-R, SDMT, TMT A&B, COWAT, and Digit Span Forward/Backward. Results from these measures were merged with most recent SCAT and ImPACT baseline data. Athletes were excluded if they were exposed to pencil and paper testing in the prior 3 years. Results 305 NHL athletes underwent renorming: 114 (37.4%) were primarily English speaking, 191 had English as their second language (ESL; Czech = 33, Finnish = 33, French = 36, Russian = 35, Swedish = 37, German = 10, Slovak = 5, and one each Latvian and Norwegian). Average age was 23.45(1.6). Among ESL athletes, widespread differences were seen across language groups on some measures (e.g., Swedish: HVLT-Total 23.86(4.11) renormed v 28.87(9.68); TMT-B = 71.14(27.43) renormed v 48.97(12.69). Regression-based norms accounting for baseline ImPACT testing, baseline SCAT testing, language proficiency, and estimated premorbid abilities accounted for between approximately 15 and 40% of the variance in paper and pencil test scores. Conclusions Comparison of renormed scores to older data support the need for periodic renorming. Modern methods including regression modeling allow for more precise calculation of normative data, which may be more sensitive to subtle differences in cognitive functioning, particularly in groups with smaller sample sizes.
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: bronze
OpenAlex ID: W4411963238
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