Complementary and Alternative Therapy Use in Children with Cerebral Palsy
Bibliographic record
Abstract
OBJECTIVE: To describe complementary and alternative medicine (CAM) use amongst children with cerebral palsy (CP) in Canada and to identify factors associated with CAM use. METHODS: We conducted a cross-sectional study, utilising data from the Canadian CP Registry. We explored the association between CAM use and regional, socioeconomic and CP phenotypic variables, and parental perception of the family-centredness of clinical care using the Measures of Process of Care-56 (MPOC-56). Chi-square analyses were performed, and odds ratios (OR) and 95% confidence intervals (CI) were obtained. Mann-Whitney U tests were used to compare MPOC-56 scores between CAM users and non-CAM users. RESULTS: The study sample consisted of 313 families of which 27% reported CAM use in the past year. Children with CP using CAM were more likely to reside in Western Canada (OR 3.3, 95% CI 1.6-6.7), live in a two-parent household (OR 3.5, 95% CI 1.5-8.4), have an ataxic/hypotonic or dyskinetic CP subtype (OR 3.0, 95% CI 1.5-6.1) and have a greater motor impairment (OR 2.8, 95% CI 1.7-4.9). MPOC-56 subscale scores were not significantly associated with CAM use. CONCLUSION: Physicians need to be aware of existing CAM therapies, the level of evidence supporting their efficacy (beneficence), their associated risks of adverse events (non-maleficence) and enable fair access to care that may be of benefit to each child.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".