Participation among Children with Arthrogryposis Multiplex Congenita: A Scoping Review
Bibliographic record
Abstract
AIM: To explore what is currently known regarding participation among children and youth with arthrogryposis multiplex congenita (AMC) using empirical studies, gray literature, and YouTube videos. The secondary objectives included identifying activity types, outcome measures used, interventions provided, and barriers and facilitators to participation. METHOD: Empirical studies and gray literature were searched through electronic databases and videos were searched on YouTube. Articles and videos pertaining to participation and youth with AMC were included by two reviewers. Data regarding activity types, location, outcomes measures, interventions, and barriers and facilitators to participation was extracted. Data was critically appraised using specific evaluation criteria. RESULT: Eleven empirical studies, six gray literature articles and 71 videos met the inclusion criteria. The most common activity types reported in the empirical studies and YouTube videos were active-physical, social, and skill-based activities. Outcome measures included evaluations and questionnaires, none of which were designed to address participation. Interventions did not target participation although the environments could affect participation. CONCLUSION: The paucity of research indicates a need for future studies of participation in this population. Interventions should target participation and address environmental barriers. Videos provide insight for clinicians, youth, and families to help promote participation in the natural environment.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".