Medical service use in children with cerebral palsy: The role of child and family characteristics
Bibliographic record
Abstract
AIM: The aim of the study was to investigate the patterns of medical service use in children with cerebral palsy (CP), taking into account child and family characteristics. METHODS: Nine hundred and one parents and carers of children registered with the Victorian CP Register were invited to complete a survey. Participants were asked about their child's appointments with general practitioners and public and private paediatric medical specialists over the preceding 12 months. Information on family characteristics and finances was also collected. Data on CP severity and complexity were extracted from the CP Register. RESULTS: Three hundred and fifty parents and carers (39%) participated. Of these, 83% reported that their child had ≥1 appointment with a general practitioner over the preceding 12 months, while 84% had ≥1 appointment with a public or private paediatric medical specialist. Overall, 58% of children saw 2-5 different paediatric medical specialists, while 9% had appointments with ≥6 clinicians. Children with severe and complex CP were more likely to have had ≥1 appointment with a publically funded paediatric medical specialist and had seen a greater number of different clinicians over the study period. Family characteristics were not associated with service use. CONCLUSIONS: Children with CP are managed by a number of paediatric medical specialists, and they continue to see a range of specialists throughout adolescence. In Victoria, differences in service use are not based on family characteristics; instead the highest service users are those with severe and complex CP. For this group, care co-ordination and information sharing between treating clinicians are important, if gaps in care are to be avoided.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".