Prophylactic academic intervention for children treated with cranial radiation therapy
Bibliographic record
Abstract
This single case study investigated the feasibility and effectiveness of a prophylactic intervention for improving academic skills in a child with a brain tumour deemed at high risk for cognitive delay and academic failure because of cranial radiation treatment (CRT). An 8 year old boy participated in a 12 week home and hospital based tutoring programme. Standardized and non-standardized measures of academic achievement were administered at pre- and post-intervention. A follow-up assessment took place 8 months post-intervention (standardized measures only). Pre-test and follow-up neuropsychological data was collected. Significant improvement was observed on the Wechsler Individual Achievement Test-2nd Edition (WIAT-II) pseudoword decoding and spelling sub-tests and on measures of single word and grapheme knowledge. There was no improvement on the WIAT-II math sub-tests. At follow-up, gains were maintained or improved for reading-related sub-tests but declined for math and spelling sub-tests. Overall, neuropsychological data showed decreased performance. The gains in reading skills were made in the context of an overall decline in neuropsychological functioning, suggesting that the intervention helped to preserve reading skills and may be protective against difficulty with skill acquisition, but did not prevent a more global decrease in functioning. This study is the first reported prophylactic intervention delivered concurrently with intensive medical treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".