Motor Proficiency and Occupational Performance in Children With Leukemia Across Age Groups: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Motor disability represents a major challenge in children with leukemia, profoundly affecting their ability to perform activities of daily living. The aim of this study is to examine the relationship between motor proficiency and the ability to perform daily tasks in children with leukemia who are not attending school during treatment. Methods: This cross-sectional study was conducted in a Pediatric Oncology Department and included 102 children with leukemia aged 6 to 17 years. Occupational performance was assessed using the Canadian Occupational Performance Measure (COPM), and motor skills were evaluated with the Bruininks-Oseretsky Test of Motor Proficiency–Short Form (BOTMP-SF). Results: Approximately half of the participants were high school students, with 54.9% being male. COPM and BOTMP-SF differed significantly between age groups ( P < .05). BOTMP-SF fine and gross motor proficiency found significant differences between primary, secondary, and high school age groups for gross motor proficiency ( P < .05). Conclusion: The relationship between motor proficiency and participation in activities of daily living in children with leukemia has a crucial impact on occupational performance. In this context, it is important to implement specific interventions that take into account the age-specific needs of children with cancer.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".