Symptomatic pes planus in children: a synthesis of allied health professional practices
Bibliographic record
Abstract
BACKGROUND: This study sought to explore professional perspectives on the assessment and management of symptomatic pes planus in children. METHODS: Data was collected from three professional groups (podiatrists, physiotherapists, and orthotists) with experience of managing foot problems in children. The survey was undertaken in the United Kingdom via a self-administered, online survey. Data was captured over a four-month period in 2018. RESULTS: Fifty-five health professionals completed the survey and the results highlighted that assessment techniques varied between professions, with standing tip-toe and joint range of motion being the most common. Treatment options for children were diverse and professionals were adopting different strategies as their first line intervention. All professions used orthoses. CONCLUSIONS: There were inconsistencies in how the health professionals assessed children presenting with foot symptoms, variation in how the condition was managed and differences in outcome measurement. These findings might be explained by the lack of robust evidence and suggests that more effort is needed to harmonise assessment and treatment approaches between professions. Addressing discrepancies in practice could help prioritise professional roles in this area, and better support the management of children with foot pain.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".