Screening for childhood mental health problems: outcomes and early identification
Bibliographic record
Abstract
BACKGROUND: Many childhood psychiatric problems are transient. Consequently, screening procedures to accurately identify children with problems unlikely to remit and thus, in need of intervention, are of major public health concern. This study aimed to develop a universal school-based screening procedure based on the answers to three questions: (1) What are the broad patterns of mental health problems from kindergarten to grade 5? (2) What are the grade 5 outcomes of these patterns? (3) How early in school can children likely to develop the most impairing patterns be identified accurately? METHODS: Mothers and teachers reported on a community sample (N = 328) of children's internalizing and externalizing symptoms in kindergarten and grades 1, 3, and 5. In grade 5, teachers reported on children's school-based functional impairments, physical health problems, and service use; mothers reported on children's specialty mental health care. RESULTS: Four patterns distinguished children who (1) never evidenced symptoms; (2) evidenced only isolated symptoms; or evidenced recurrent symptoms, either (3) without or (4) with comorbid internalizing and externalizing. By grade 5, children with recurrent comorbid symptoms had the greatest impairments, physical health problems, and service use. These children can be identified quite accurately by grade 1. CONCLUSIONS: Universal screening at school entry can effectively identify children likely to develop recurrent comorbid symptoms, and would provide a basis for developing optimal targeted intervention programs.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".