Brief multidimensional screening tools for young children’s mental health and development for administration by primary care providers: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Many young children with mental health or developmental concerns go unidentified and untreated, underscoring the need for effective screening. Primary care offers unique opportunities for screening, yet rates are low. Primary care providers often cite time constraints, insufficient training, and costs as barriers to screening. Tools designed for administration by primary care providers hold promise for facilitating personalized assessments and improving communication, collaboration, and follow-up between providers and families. To improve early identification and intervention, it is crucial to understand provider-administered screening tools that align with their practical constraints. AIM: To identify and describe the characteristics, limitations, and improvement areas of brief, multidimensional screening for young children's mental health and development, designed for administration by primary care providers. METHODS: We conducted a scoping review according to published guidelines. We searched seven electronic databases and used hand-searching strategies. We sought English-language publications on screening tools (English or French) assessing at least one mental health and one development domain in children up to 6 years, designed for administration by primary care providers in under 20 minutes. Two reviewers assessed the articles' eligibility and then extracted, charted, and summarized relevant data. RESULTS: Three screening tools from six articles were included. The tools were primarily administered by physicians or nurses to children aged 2 weeks to 4 years and required minimal training to use. The tools varied in their domains (4-6), items (10-110), psychometric properties, and scoring methods, but all included indicators of delayed or at-risk children. Article limitations included study recency and lack of data related to implementation and patient outcomes. CONCLUSIONS: This review described the development and evaluation of multidimensional screening tools for young children's mental health and development designed for administration by primary care providers. It found that few tools have been published. This review identifies several knowledge gaps and emphasizes the need for research on the implementation, cost-effectiveness, and comparative performance of screening tools, as well as the development and evaluation of new screening tools that suit providers' needs. Future studies should investigate how these screening tools can improve identification, clinical care, and health outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".