Assessing the frequency with which primary care providers address sleep of infants and young children
Bibliographic record
Abstract
Sleep problems during early development are common and associated with negative health outcomes. Earlier recognition of poor sleep health permits earlier intervention and improved outcomes. This retrospective cohort study aimed to identify the frequency with which primary care providers assessed sleep health when completing the Rourke Baby Record for infants and young children during routine well-baby visits from 2002 to 2019. Using 1180 electronic medical records from an academic family medicine teaching clinic, we identified the frequency with which primary care providers assessed sleep health at three time intervals in child development: 1 week to 1 month; 2 months to 6 months; and 9 months to 12-13 months. Sleep variables were night waking, healthy sleep habits, and safe sleep. The frequency of having any aspect of sleep addressed was 85.4%, 90.2% and 66.7% at the three respective time intervals. There were no differences in the frequency with which sleep was assessed based on birthweight or sex. Children born during 2002-2015 were approximately half as likely to be assessed for sleep compared with those born during 2016-2019 at the second and third time intervals. In the first and second time intervals, children who were not exclusively breastfed had their sleep assessed significantly less than children who were exclusively breastfed. To our knowledge this is the first study to explore the area of sleep discussions and breastfeeding status in primary care during routine well-baby visits. These results are clinically relevant for clinicians and parents, due to the known associations between sleep issues and sudden infant death syndrome, childhood injuries, and emotional dysregulation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".