The Effect of Context-Based Interventions at the Systems-Level on Participation of Children with Disabilities: A Systematic Review
Bibliographic record
Abstract
AIMS: To synthesize evidence on the impact of context-based interventions on the participation of children with disabilities in the community. METHODS: A systematic review was conducted using the American Academy for Cerebral Palsy and Developmental Medicine Guidelines for systematic reviews. Seven databases were searched; articles included were on children with developmental disabilities under the age of 19 years, describing systems-level, context-based interventions aimed to improve participation and Participation-related outcomes of the Family of Participation-related Constructs framework. Intervention characteristics were coded using the Community Wellbeing Framework (CWF). RESULTS: Eleven articles were included for knowledge synthesis. Four studies were level I, II, and III based on the Center for Evidence-Based Medicine hierarchy. All four showed that context-based interventions had a positive effect on participation and participation-related outcomes. All 11 studies had intervention properties that were coded to at least one domain on the CWF. CONCLUSION: There is a scarcity of high-quality studies that focus on context-based interventions at the systems-level, as opposed to the individual-level. Albeit low-level quality, existing evidence emphasized the importance of using known facilitators to participation, such as staff training, peer mentorship, awareness-raising, and development of partnerships to change the system and promote participation.
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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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".