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ObjectivesThis paper provides comprehensive normative data stratified by language preference and age on the components of the National Hockey League (NHL) Sport Concussion Assessment Tool 5 (SCAT5) in a multilingual sample of professional ice hockey players and compares the findings from a paper form of the NHL SCAT5 with an electronic (App) version of the tool.MethodsA total of 1924 male NHL and American Hockey League (AHL) players (ages 17–41) were assessed during preseason medical evaluations (baseline); 1881 were assessed with the NHL SCAT5 App via tablet and 43 received the paper version of the NHL Modified SCAT5.ResultsNo significant differences between the App and paper modes of administration emerged in a subsample of English preference players. Significant SCAT5 differences among language preference groups emerged on measures of cognitive functioning (Immediate Memory,Concentration). No language preference differences emerged on the Delayed Recall component. Using age as a continuous variable, older participants outperformed younger players on Immediate Memory, Delayed Recall and Concentration. Players wearing skates demonstrated significantly more modified Balance Error Scoring System (mBESS) total errors than barefoot players. Normative data tables for language preference groups are presented.ConclusionsSignificant differences were found between English and non-English language preference groups on the components of SCAT5, which suggest that language-specific normative data, rather than aggregated normative data, are preferable when interpreting test scores. Similarly, age-specific normative data tables may provide greater precision in data interpretation. Due to clear ceiling effects on the mBESS single leg and tandem stances, players should not be tested while wearing skates.
ObjectivesThis paper provides comprehensive normative data stratified by language preference and age on the components of the National Hockey League (NHL) Sport Concussion Assessment Tool 5 (SCAT5) in a multilingual sample of professional ice hockey players and compares the findings from a paper form of the NHL SCAT5 with an electronic (App) version of the tool.MethodsA total of 1924 male NHL and American Hockey League (AHL) players (ages 17–41) were assessed during preseason medical evaluations (baseline); 1881 were assessed with the NHL SCAT5 App via tablet and 43 received the paper version of the NHL Modified SCAT5.ResultsNo significant differences between the App and paper modes of administration emerged in a subsample of English preference players. Significant SCAT5 differences among language preference groups emerged on measures of cognitive functioning (Immediate Memory,Concentration). No language preference differences emerged on the Delayed Recall component. Using age as a continuous variable, older participants outperformed younger players on Immediate Memory, Delayed Recall and Concentration. Players wearing skates demonstrated significantly more modified Balance Error Scoring System (mBESS) total errors than barefoot players. Normative data tables for language preference groups are presented.ConclusionsSignificant differences were found between English and non-English language preference groups on the components of SCAT5, which suggest that language-specific normative data, rather than aggregated normative data, are preferable when interpreting test scores. Similarly, age-specific normative data tables may provide greater precision in data interpretation. Due to clear ceiling effects on the mBESS single leg and tandem stances, players should not be tested while wearing skates.
The interpretation of psychometric test results is usually based on norm scores. We compared semiparametric continuous norming (SPCN) with conventional norming methods by simulating results for test scales with different item numbers and difficulties via an item response theory approach. Subsequently, we modeled the norm scores based on random samples with varying sizes either with a conventional ranking procedure or SPCN. The norms were then cross-validated by using an entirely representative sample of N = 840,000 for which different measures of norming error were computed. This process was repeated 90,000 times. Both approaches benefitted from an increase in sample size, with SPCN reaching optimal results with much smaller samples. Conventional norming performed worse on data fit, age-related errors, and number of missings in the norm tables. The data fit in conventional norming of fixed subsample sizes varied with the granularity of the age brackets, calling into question general recommendations for sample sizes in test norming. We recommend that test norms should be based on statistical models of the raw score distributions instead of simply compiling norm tables via conventional ranking procedures.
We investigated whether the accuracy of normed test scores derived from non-demographically representative samples can be improved by combining continuous norming methods with compensatory weighting of test results. To this end, we introduce Raking, a method from social sciences, to psychometrics. In a simulated reference population, we modeled a latent cognitive ability with a typical developmental gradient, along with three demographic variables that were correlated to varying degrees with the latent ability. We simulated five additional populations representing patterns of non-representativeness that might be encountered in the real world. We subsequently drew smaller normative samples from each population and used an one-parameter logistic Item Response Theory (IRT) model to generate simulated test results for each individual. Using these simulated data, we applied norming techniques, both with and without compensatory weighting. Weighting reduced the bias of the norm scores when the degree of non-representativeness was moderate, with only a small risk of generating new biases.
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