Clinical practice guidelines for monitoring children's behavioural development at the 18‐month well‐baby visit: A decision analysis comparing the expected benefit of two alternative strategies
Bibliographic record
Abstract
RATIONALE, AIMS AND OBJECTIVES: The current American Academy of Pediatrics policy calls for universal developmental screening (UDS) at the 18-month well-baby visit (18MWBV). In contrast, different clinical practice guidelines exist in other developed countries where only toddlers of concerned parents are referred for (selective) developmental screening (SDS). This study compares the expected benefit (EB) of these two strategies for monitoring children's behavioural development at the 18MWBV. METHOD: A clinical decision analysis was performed, with EB defined as gain (probability of screening when appropriate + probability of not screening when appropriate) minus cost (probability of screening when not appropriate + probability of not screening when not appropriate). Accordingly, a strategy's EB referred to its efficiency at distinguishing between toddlers who need to be referred for screening and those who do not. RESULTS: The EB of the UDS strategy was estimated at -0.242. In contrast, the EB of the SDS strategy was much greater at 0.326. In fact, the EB of the UDS strategy could only equal or surpass that of the SDS strategy if screening toddlers with a problem was considered almost five times more important than not screening well toddlers. However, our monitoring effort should be more evenly distributed between these two imperatives. Also, the evidence in favour of the SDS strategy remained largely unchanged after considering a broad range of values for the (unique) probabilities in the decision tree. CONCLUSION: There are many steps involved in the monitoring of children's early behavioural development, but when it comes to decide whether or not to use behavioural screening, there is evidence for adopting the SDS strategy, and screening only if a behavioural concern is being raised by parents.
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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 | 0.111 | 0.300 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".