Factors of Service Utilization and Participation Outcomes of Children with Disabilities
Bibliographic record
Abstract
Home and community participation is measured by a multitude of determinant factors based within the context of a health system. Three studies were completed to understand relationships between environment and personal factors with service utilization and outcomes of participation among children with disabilities. In the first study, a scoping review was completed to identify factors that influenced rehabilitation service utilization among Canadian children with disabilities. Key findings of this review indicated higher rates of service utilization are associated to younger age, males and those with lower cognitive or motor functioning. Occupational therapists, physiotherapists and speech-language pathologists were the most commonly utilized disciplines. Higher perceptions of service satisfaction related to increased presence of family-centered practices. Areas requiring further research include family needs, barriers, personal health practices and participation outcomes. Based on the findings of this review, a survey was created to administer to parents using a large children’s rehabilitation treatment centre in Ontario. Findings from the survey conducted with 279 parents are reported in the second study by providing a descriptive profile of families and children using geographically-based rehabilitation services. Families using the centre typically have younger aged children, with more boys than girls, and a large proportion use the centre for speech services. Complexity scores correlated significantly and positively with service need and service utilization, indicating children with lower functioning desired and received more rehabilitation services. Age, sex, and diagnosis did not predict total time in therapy, but complexity was a significant predictor of total time in therapy. Participation frequency scores showed weaker relationships to complexity in comparison to participation involvement scores. The final study explored the relationship between environmental and personal factors of service utilization and participation using structural equation modeling. Predictors of participation include child’s age, environmental barriers, complexity, and mother’s participation. Findings support that exploring children’s complexity and promoting mother’s participation by removing environmental barriers and modifying inaccessible structures are important to examine from a young age.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".