Association between lay perception of morbidity and appropriateness of specialized health care use in adolescent idiopathic scoliosis
Bibliographic record
Abstract
In absence of school scoliosis screening programs (SSSP) in Canada, this study examined the relationships between the lay person's perception of morbidity and the appropriateness of referral in orthopedics. A cross-sectional study was conducted with all children consecutively referred in orthopedics for suspected scoliosis. The 831 participants were classified as Appropriate, Late, or Inappropriate referrals for the orthopedic setting. Perceived morbidity was operationalized by: the scoliosis detection originator, the perceptions of the seriousness of the condition and urgency to consult a physician, the perception of the general health, as well as Visible Back Deformity, Self-image, and Pain. Direct associations between the perceived morbidity and the appropriateness of referral were found in all scoliosis-specific measures; the most discriminant variable was Visible Back Deformity. Lay perceived morbidity is a good indicator of the objective morbidity, and thus reflects in the appropriateness of referral status. The important role of the lay persons in symptoms appraisal does not however insure appropriate referral. Searching for alternatives to SSSP would wisely include a health promotion and medical management program. Statement of Clinical Significance: Perceived morbidity by the lay persons is strongly associated with the objectively evaluated severity of scoliosis deformity. Therefore, in absence of SSSP, lay person awareness plays an important role in symptom recognition and search for care. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".