Heterogeneous Trajectories of Delayed Communicative Development From 12 to 36 Months: Predictors and Consequences
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to identify distinct trajectories of delayed communicative development from 12 to 36 months and examine differences in risk factors and developmental outcomes for each trajectory. METHODS: Participants were 2192 children drawn from a prospective longitudinal pregnancy cohort in a large Canadian city. Maternal pregnancy medical records were used to determine perinatal risk factors. The Ages and Stages Questionnaire Communication subscale was administered at 12, 24, and 36 months. At 36 months, mothers reported on the child's health, cognitive, and behavioral development. RESULTS: Using growth mixture modeling, we identified 4 trajectories of communicative development. Most children (81.1%) were characterized by high and stable scores from 12 to 36 months. The remaining children fell into a low-increasing class (13.0%), a moderate-stable class (4.5%), and a low-decreasing class (1.4%). At 36 months, the low-increasing class had caught up to the high-stable group. However, by 36 months, the low-decreasing class fell under the recommended "referral" cutoff, and the moderate-stable class fell under the "monitoring" cutoff criteria. Children with continued communication problems at 36 months were more likely to have a congenital anomaly and lower family income than late-talking children who had caught up. CONCLUSION: Repeated assessments of a brief screening tool were able to differentiate patterns of communicative development over time, each with unique risk factors and developmental outcomes. Results highlight the potential for risk factors and repeated screenings to help identify children most at risk for persistent communication delays and in need of early support services.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".