Intensity of participation among children with epilepsy: an exploratory factor analysis of child components
Bibliographic record
Abstract
Although participation has been the focus of numerous studies of children and youth with Cerebral Palsy and few other chronic health conditions, very little is known about the participation of children and youth with epilepsy. The goal of this thesis is to derive primary components from a set of theoretically-derived variables thought to be related to the intensity of participation of children and youth with epilepsy. Sixteen variables were originally identified. This study uses a database of n=506 children with epilepsy to perform an exploratory factor analysis of relevant child variables from the Qualité study, a longitudinal pan-Canadian study on outcome trajectories of children with epilepsy. Results located four principal components that together, accounted for 63.41% of the total variance: Behaviors that Facilitate Interactions with Others is made up of four child social skills variables and accounts for 32.042% of variance; Behaviors that Challenge Interactions with Others, is made up of 3 variables on child externalizing behaviours and accounts for 12.058% of variance; Anticipatory Reaction to Distressing Stimuli, is made up of variables related to submissiveness, victimisation and anxiety and accounts for 9.414% of variance and Child's Social Self, comprises variables related to social support and self perception and accounts for 8.408% of variance. Further study is required to examine the relationship and impact these components have to the participation of children and youth with epilepsy.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".