Exploring Childrenʼs Self-efficacy Related to Physical Activity Performance After a Mild Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: To evaluate children's self-efficacy related to their practice of physical activities prior to and after a mild traumatic brain injury (mTBI), and compare these to those of noninjured children matched for age, sex, and premorbid level of physical activity. PARTICIPANTS AND METHODS: Thirty-four children (mean age: 12 +/- 3 years) in each group. Children with mTBI were assessed 1 day postinjury (to document preinjury status) and at 12 weeks post-mTBI using a self-efficacy questionnaire, the Physical Activity Questionnaire, the Athletic Competence subscale of the Self-Perception Profile for Children or Adolescents, and the Rivermead Post-Concussion Symptoms Questionnaire. Noninjured children underwent the same assessments at a corresponding time interval. RESULTS: At 12 weeks postinjury, self-efficacy scores of children with mTBI were significantly lower than initial (ie, pretraumatic) values and those of noninjured children. The children with mTBI had, however, returned to their preinjury level of participation in physical activities and maintained their athletic competence. CONCLUSIONS: After mTBI, children appear to lack confidence in their ability to perform during physical activities as compared to before their injury. Intervention strategies such as information or counseling sessions targeting children and their parents may minimize the impact of the mTBI on children's confidence in their performance in physical activities.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".