Supported Standing and Supported Stepping Devices for Children with Non-Ambulant Cerebral Palsy: An Interdependence and F-Words Focus
Bibliographic record
Abstract
Children functioning at Gross Motor Function Classification System (GMFCS) levels IV-V cannot maintain an aligned standing position or take steps without support. Upright positioning and mobility devices have psycho-social significance for these children and their families, enhancing use of vision, communication, functioning and emotional well-being. Standers and supported stepping devices facilitate opportunities for biomechanical loading, potentially helping to build and maintain muscle and bone integrity, and they promote physical development. However, families are often required to choose between these two devices for their young child. This study aims to synthesize evidence for use and benefits of both supported standing and stepping devices through the lens of two contemporary theoretical frameworks to support clinical reasoning and implementation. The F-words for childhood development (functioning, family, fitness, fun, friends, future) and the interdependence-Human Activity Assistive Technology (iHAAT) models were combined to illustrate the complex interactions between the child, family, caregivers, peers and contextual factors when implementing standing and stepping devices with children at GMFCS levels IV and V. Supported standing and stepping devices provide complementary benefits, and both may be necessary starting at 9-15 months. We propose they both be included ON-Time, along with other age-appropriate positioning and mobility devices, to promote more equitable developmental opportunities for children with non-ambulant cerebral palsy.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 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".