Chiropractic care and research priorities for the pediatric population: a cross-sectional survey of Quebec chiropractors
Bibliographic record
Abstract
BACKGROUND: Chiropractors commonly treat pediatric patients within their private practices. The objectives of this study were (1) to identify the treatment techniques and health advice used by Quebec chiropractors with pediatric patients; (2) to explore the research priorities of Quebec chiropractors for the pediatric population; and (3) to identify Quebec chiropractors' training in the field of pediatric chiropractics. METHODS: A web-based cross-sectional survey was conducted among all licensed Quebec chiropractors (Qc, Canada). Descriptive statistics were used to analyze all quantitative variables. RESULTS: The results showed that among the 245 respondents (22.8% response rate), practitioners adapted their treatment techniques based on their patients' age group, thus using softer techniques with younger pediatric patients and slowly gravitating toward techniques used with adults when patients reached the age of six. In terms of continuing education, chiropractors reported an average of 7.87 h of training on the subject per year, which mostly came from either Quebec's College of Chiropractors (OCQ) (54.7%), written articles (46.9%) or seminars and conferences (43.7%). Both musculoskeletal (MSK) and viscerosomatic conditions were identified as high research priorities by the clinicians. CONCLUSIONS: Quebec chiropractors adapt their treatment techniques to pediatric patients. In light of limited sources of continuing education in the field of pediatric chiropractics, practitioners mostly rely on the training provided by their provincial college and scientific publications. According to practitioners, future research priorities for pediatric care should focus on both MSK conditions and non-MSK conditions.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".