Teacher Perceptions of Screening and Mental Health Practices Survey: A Validation Study
Bibliographic record
Abstract
Approximately 80% of children with social, emotional, and behavioral challenges are not adequately identified, leading to a large gap in unmet mental health needs. The purpose of the MTSS-MH project is to identify the efficiency and acceptability of universal mental health screening in schools using screening to systematically identify all students’ behavioral and mental health needs. The Teacher Perceptions of Screening and Mental Health Practices Survey (TPSMHPS) was administered within the MTSS-MH project to assess each school’s organizational climate and teachers’ perceptions of how acceptable universal screening and their school’s utilization of it was. Data analyses were run in this validity study to measure the survey’s preliminary psychometric properties. The internal reliability of the survey was indicated moderate to high reliability (Cronbach’s alpha = 0.787). One-way ANOVAs were run to assess the survey’s ability to detect differences between schools on teachers’ mean responses about screening acceptability, intervention acceptability, and implementation of screening resources. Results indicate that the TPSMHPS survey is a valid measure of teachers’ perceptions of mental health screening, as it is shown to to have high internal consistency, however between school differences were not detected. Future studies should consider other statistical analyses to examine the survey’s sensitivity to between school differences to ensure the survey is a good measure of teacher perceptions.
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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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 |
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".