Youth intentions to provide social support to a peer with a concussion
Bibliographic record
Abstract
Objectives 1) To describe demographic factors, concussion knowledge, attitudes, subjective norms, self-efficacy and intentions to provide social support to a peer with a concussion and 2) to examine if demographic factors and concussion knowledge are associated with components of the Theory of Planned Behavior.Methods The survey was completed between October 2018 and February 2019 by 200 youth (M = 15.30 years, SD = 1.52). Questions were designed for athletes and non-athletes and inquired about various types of social support. Data analysis included descriptive statistics, Wilcoxon Rank Sum Tests and Spearman’s Rank-Order Correlation Coefficients.Results More favorable attitudes and intentions to provide social support were observed among females (W = 2576, p ≤ 0.001; W = 2411, p ≤ 0.001), older youth (rho = 0.32, p ≤ 0.001; rho = 0.41, p ≤ 0.001) and those with higher concussion knowledge (rho = 0.29, p ≤ 0.001; rho = 0.22; p ≤ 0.001). Participating in sports with a high-risk of concussion was associated with lower attitudes and intentions to provide social support (W = 6677; p ≤ 0.001; W = 6721; p ≤ 0.001). Self-reported concussion history or knowing someone with a concussion history was not significantly associated with social support intentions.Conclusion This study identified characteristics of youth who had positive intentions to provide social support. These findings identify individuals who may model providing social support to a peer, as well as opportunities for future concussion education.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 teacher head, 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".