Identifying Occupational Issues among Children with Intractable Epilepsy: Individualized versus Norm-Referenced Approaches
Bibliographic record
Abstract
BACKGROUND: Anecdotal and empirical evidence indicates children with intractable epilepsy have difficulty completing daily occupations. There is a paucity of literature describing these issues from a client-centred perspective. Occupational issues in childhood epilepsy have historically been assessed by disability inventories. PURPOSE: This pilot study seeks to determine similarities and differences between occupational issues identified using a disability inventory and an individualized outcome measure among children with intractable epilepsy and their parents. METHOD: Goal identification was determined using two approaches to standardized measurement with 10 child-caregiver dyads. The Canadian Occupational Performance Measure (COPM) was the individualized measure for both parents and children. The Scales of Independent Behavior-Revised (SIB-R) disability inventory was completed by parents only. Agreement between the top three issues identified by the child COPM, parent COPM, and subscales of the SIB-R were compared. FINDINGS: Although both of the outcomes employed in this study are standardized measures, they resulted in low agreement and the identification of different occupational issues for children with intractable epilepsy. IMPLICATIONS: This study provides a comparison of two different approaches to identifying goals. It also provides preliminary information on the types of occupational performance issues prioritized by children with intractable epilepsy and their parents.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".