A pre-longitudinal screen of performance in an integrated assessment of throwing and catching competence
Bibliographic record
Abstract
Background The ability to adapt motor skill performance to a variety of conditions is vital to success in physical activity settings. Valid and reliable measurements of motor competence (MC) are critical for understanding its impact on physical health. Many widely used MC assessments evaluate the performance of isolated motor skills, place performers in highly standardized environments, and limit opportunities to adapt performance. Consequently, evaluations of motor skill performance using these tools may not adequately differentiate motor skill levels. Assessing MC in more dynamic performance contexts may enhance the utility of MC measures.Purpose The purpose of this study was to examine the developmental validity of scores on a combined throwing and catching assessment.Data Collection and Analysis Data were collected on a convenience sample (n = 873, nfemale = 320, age = 14.7 years ± 4.2). Participants threw a regulation tennis ball against a wall from a distance three times their standing height and caught it as many times as possible in 30 s. Performers were free to use any throwing pattern (e.g. over/underarm) or task strategy (e.g. speed, trajectory of ball, ball bouncing, one- or two-handed catch). The highest number of catches between two 30-second trials was used for analysis. Descriptive statistics were calculated for the total sample and for males and females separately. Pearson correlations were used to evaluate the relationship between throw-catch assessment (TCA) scores and age. We evaluated the relationship between TCA score, sex, and age via hierarchical regression with TCA score as the dependent variable using three models: (1) Participant sex as the sole predictor, (2) sex and age as predictors, and (3) sex, age, and the quadratic term for age (age2). Additionally, we evaluated the reliability of scores on TCA assessment trials via intraclass correlations (ICCs) using a two-way, fixed effects model.Results The mean TCA score was 11.34 (± 5.44; Mfemales = 9.18 ± 4.80, Mmales = 12.59 ± 5.40). Strong relationships were observed between TCA score and age (r = .743, rfemales = .698, rmales = .746; all significant at p < .001). Significant increases in model fit were observed at each stage of the hierarchical regression (Model 1: R2 = .091, p < .01; Model 2: ΔR2 = .484, p < .01; Model 3: ΔR2 = .009, p < .01), with the final model indicating significant effects for sex (βmale = 1.95, p < .01), age (β = 2.01, p < .01) and age2 (β = –.04, p < .01) on TCA score (R2 = .584, F3,869 = 406.7, p < .001). Finally, there was good reliability between scores on the two TCA trials (ICC = .875, F872,873 = 14.97, p < .001).Discussion These data provide preliminary evidence for the developmental validity of the TCA across childhood to young adulthood. The ability to differentiate skill levels across a wide age-range can enhance the ability to track MC across the lifespan and better understand the relationship between covariates of MC across the lifespan. These data provide support for a MC assessment that can be used by researchers and practitioners to evaluate throwing and catching skill in a swift and ecologically valid way.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".