Power Mobility, Supported Standing and Stepping Device Use in the First Two Years of Life: A Case Report of Twins Functioning at GMFCS V
Bibliographic record
Abstract
Mobility experience has a positive impact on activity, participation, socialisation, language and cognition, but children with cerebral palsy (CP), Gross Motor Function Classification System (GMFCS) level V require assistive devices or assistance in all environments. Supported standing devices afford upright, weight-bearing positions to promote muscle, bone, joint and overall health. Supported stepping devices afford stepping and upright independent mobility, positively impacting self-esteem and participation, while power mobility is the only possibility for effective, independent community mobility. These devices and opportunities should be introduced at the age when children who are typically developing are pulling to stand, moving and exploring their environment. A detailed case description including lived experience and device use data is presented for female twins with dystonic tetraplegic CP born at 25 weeks gestational age and functioning at GMFCS level V. The feasibility of using power mobility, standing and stepping devices in home and community settings within the first two years is illustrated. The twins transitioned from spending 24 h in lying positions or being held in arms to spending more than 2 h daily in upright positions and having opportunities to move independently. Positioning and mobility devices can help to address all the F-words for child development: functioning, family, fitness, fun, friends and future.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".