A Multisite Study Evaluating the Benefits of Early Intervention via Telepractice
Bibliographic record
Abstract
This study sought to determine the effectiveness of telepractice as a method of delivering early intervention services to families of infants and toddlers who are deaf or hard of hearing. A comparison group design was applied to ascertain the child, family, and provider outcomes via telepractice compared with traditional in-person home visits. A total of 48 children and their families, along with 15 providers from 5 early intervention programs, across the country participated. Children in the telepractice group received more intervention, although the number of prescribed sessions was equal across groups. Analyses of covariance demonstrated that children in the telepractice group scored statistically significantly higher than children in the in-person group on the PLS-5 Receptive Language subscale and PLS-5 Total Language standard scores, and the groups scored similarly on other language measures. There were no statistically significant differences between groups in regard to family outcomes of support, knowledge, and community involvement. Analysis of video recordings of telepractice versus in-person home visits resulted in higher scores for provider responsiveness and parent engagement. This study supports the effectiveness of telepractice in delivering early intervention services to families of children who are deaf or hard of hearing. Further research involving randomized trials with larger, more diverse populations is warranted.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".