The evolution of problem and social competence behaviors during toddlerhood: A prospective population‐based cohort survey
Bibliographic record
Abstract
Research in developmental psychopathology has long been preoccupied with rather broad categories of behavior, but we know little about the specific behaviors that comprise these categories. The objective of this study was to: (a) estimate the prevalence of problem and social competence behaviors in the general population of children at 17 months of age, and (b) describe the continuity and discontinuity in the degree to which children exhibit these behaviors between 17 and 29 months of age. The results show that frequent problem behaviors are not typical of children under two years of age. Further, the results suggest that it is possible to distinguish between different types of problem behaviors before two years of age. In addition, the results show that gender differences in some problem behaviors are already present before two years of age, and increase in magnitude during toddlerhood. Finally, the results show that interindividual differences in problem behaviors observed before two years of age are stable. The predictive accuracy of frequent problem behaviors in children at 17 months of age was limited, however, with often a majority of toddlers not behaving this way a year later. Overall, our results suggest that toddlerhood represents a critical period when behavioral and emotional problems of potentially clinical significance emerge. Pediatricians should routinely ask parents to report the frequency of their young children's problem behaviors during child health supervision visits so that children whose frequent problem behaviors persist over time can be identified and possibly referred for treatment.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".