Clinical Decision Making Regarding Intervention Needs of Infants With Torticollis
Bibliographic record
Abstract
In Brief Purpose: Although conservative care is the standard intervention for infants with torticollis, the variation in intervention content and format proposed in the literature reflects the lack of clear understanding of this population's needs. The objective was to identify factors assessed by pediatricians and physical therapists influencing the determination of intervention needs for infants with torticollis. Methods: Focus groups and surveys were used to generate a list of factors influencing determination of intervention needs. These factors were mapped to the International Classification of Functioning, Disability and Health–Children and Youth (ICF-CY). Results: Health care professionals report that all infants presenting with torticollis require intervention. They determine needs according to factors encompassing all ICF-CY domains. An important subset of factors relates to family and environment. Conclusion: Health care professionals should rely on a family-centered assessment encompassing all domains of the ICF-CY to adequately identify intervention needs of infants with torticollis. The authors conclude that health professionals should rely on a family-centered assessment encompassing all domains of the ICF-CY to adequately identify intervention needs of infants with torticollis and they should use measurement instruments that have strong psychometric properties.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".