Predictors of change in participation rates following acquired brain injury: results of a longitudinal study
Bibliographic record
Abstract
AIM: The purpose of this study was (1) to examine the changes in participation rates over 1 year among children and adolescents after acquired brain injury and (2) to explore the effect of child and family factors on these changes. METHOD: The participation levels of 136 children and young people (88 males; 48 females; age range 4y 11mo-17y 6mo; mean age 11y 6mo) after acquired brain injury (3≤ Glasgow Coma Scale score ≤15; mean 12.8) were assessed three times: at their return to school, and at 8 and 12 months after returning to school. The Children's Assessment of Participation and Enjoyment measured the participants' diversity and intensity of participation in out-of-school activities. At baseline, information on general family functioning and medical and demographic information was collected as possible predictors. Mixed-effect model analyses of participation scores were performed while controlling for child's age at injury. RESULTS: The severity of the injury explained rates of change across time for participation intensity in recreational, physical, and social activities. Household income influenced changes in the intensity of recreational activities, whereas family functioning predicted changes in the diversity of skill-based activities. INTERPRETATION: Participation is a relevant outcome of recovery that needs to be assessed and monitored post brain injury. Special attention can be directed to severity of injury and family functioning when developing intervention plans.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".