Early intervention service intensity and young children’s home participation
Bibliographic record
Abstract
BACKGROUND: Young children with developmental disabilities and delays spend significant amounts of time at home, show decreased participation in home-based activities, and receive home-based early intervention services to improve participation in activities. Yet, knowledge about the relationship between EI service use and children's home participation in activities remains poorly understood but needed for program improvement. The purpose of this study was to understand the relationships between EI service use and children's home participation. METHODS: In a cross-sectional design, data were gathered from caregivers (N = 139) who enrolled in a pilot trial of the Young Children's Participation in Environment Measure (YC-PEM) electronic patient-reported outcome (e-PRO), as implemented within 1 month of their child's next EI progress evaluation. A series of path analytic models were used to estimate EI service intensity as a predictor of parent-reported young children's home participation 1) frequency, 2) level of involvement, and 3) desired change, adjusting for family and child social and functional characteristics. Models included caregiver perceptions of home environmental support to test its indirect (i.e., mediation) effects on the relationship between EI service intensity and each of the three home participation dimensions. RESULTS: All three models fit the data well (comparative fit index = 1.00). EI service intensity was not a significant predictor of participation frequency. However, EI service intensity had a significant direct effect on a child's participation according to level of involvement and desired change, explaining between 13.3-33.5% of the variance in home participation. Caregiver perceptions of environmental support had a small yet significant indirect effect on the relationship between EI service intensity and level of involvement and desired change; these models explained between 18.5-38.1% of the variance in home participation. CONCLUSIONS: EI service intensity has important links with involvement in and desired change for home-based activities. Caregiver perceptions of environmental support appears to be a factor in the relationship between EI service intensity and home participation. Results warrant longitudinal replication with a control group, which would be possible with the implementation of the YC-PEM e-PRO in a routine EI clinical workflow. TRIAL RETROSPECTIVELY REGISTERED: NCT03904797 .
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".