Development of clinical considerations for ankle-foot orthosis prescription and monitoring in young children with cerebral palsy: a Delphi study
Bibliographic record
Abstract
PURPOSE: To seek agreement on evidence-based, family-centered, clinical considerations for Ankle Foot Orthosis (AFO) prescription and monitoring for young, ambulatory children with cerebral palsy. MATERIALS AND METHODS: An online Delphi survey focusing on parent, clinician, and researcher perspectives on specific processes and outcomes concerning AFO prescription and monitoring practices was conducted over two rounds. Participants rated each survey item as critical, important but not critical, or less important. Items were included in Round 2 if >70% of participants in all three groups scored critical and <15% scored less important. A subgroup of survey respondents participated in a meeting to ratify the survey results. RESULTS: Twenty-two pediatric clinicians, seven researchers, and ten parents of young children with cerebral palsy participated in Round 1. Two clinicians and two parents dropped out in the second round. A total of 36 clinical considerations were deemed to be critically important for inclusion across contributor groups. CONCLUSIONS: The proposed clinical considerations for AFO prescription and monitoring that embeds the perspectives of families is a valuable contribution to clinical practice. They can be used by clinicians as a guide when prescribing and introducing AFOs to families of young, ambulatory children with cerebral palsy.
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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 | 0.072 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".