Supported standing and stepping device use in young children with cerebral palsy, gross motor function classification system III, IV and V: A descriptive study
Bibliographic record
Abstract
This study described and compared use of supported-standing and stepping devices by young children with cerebral palsy, Gross-Motor Function Classification System (GMFCS) levels III-V following power mobility introduction. Data was collected at two time-points, 5-6 months apart, for 42 participants, aged 18-80 months, using the Home Use of Technology for CHildren (HUTCH). Supported-standing and stepping device choice and time in each device remained stable over 6 months. Associations between device use and three functional classifications were examined. Children with more impaired motor, postural and manual abilities were more likely to use a supine stander rather than a prone/upright stander or no stander. Children at GMFCS V tended to use hands-free stepping devices, while support-arms stepping devices were more common for children at GMFCS IV. Only children at GMFCS III used convertible stepping devices. Using power mobility, standers and supported-stepping devices was feasible and 19/34 classified at GMFCS IV/V used all three devices over 6 months. A key finding was that introduction of power mobility did not reduce use of supported-stepping devices at any GMFCS level. Use of multiple upright positioning and mobility devices may assist children with limited mobility to be actively engaged and participate in daily life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".