Consultant perception of the feasibility and effectiveness of infant and early childhood mental health consultation services provided virtually to early care and education
Bibliographic record
Abstract
A growing body of research suggests that infant and early childhood mental health consultation (IECMHC) is effective in improving child outcomes and classroom quality in early care and education (ECE) settings. However, there is limited research regarding the provision of IECMHC virtually (e.g., by phone or video conferencing platform), and the transition to virtual services in the context of the COVID-19 pandemic provided an opportunity to learn more. This study focuses on mental health consultants' (MHCs) perceptions of the feasibility and effectiveness of providing IECMHC virtually. Using a purposive sampling method, we gathered survey data from 94 MHCs providing IECMHC in 15 states in the United States. More than two-thirds of MHCs reported consultation was as effective or more effective virtually (compared to in-person) when it involved adult or programmatic consultation, while one-third of MHCs viewed child-focused consultation as being as or more effective virtually. There was wide variation in the extent to which MHCs viewed specific consultation activities as feasible and effective when delivered virtually. Furthermore, one-third of consultants reported that the ECE programs they served experienced major barriers related to equipment and technology. We explore how these findings can inform future planning for the provision of virtual services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".