Daycare Attendance, Stress, and Mental Health
Bibliographic record
Abstract
OBJECTIVE: Daycare stress can be indexed by cortisol, and elevated levels of cortisol have been implicated in the onset and development of mental health disorders. Our objective was to quantify the associations between daycare and cortisol and to identify individual and environmental conditions under which daycare attendance is associated with cortisol concentrations. METHODS: We used Cohen effect size statistics to quantify these associations and to compare them across 11 published studies that were identified with MEDLINE and PsycINFO. RESULTS: Cortisol levels increased during the daycare day, whereas they decreased when children stayed at home. The mean effect size was d = 0.72. The magnitude of the daycare-stress relation seemed to vary under 3 specific conditions. First, the effect size was larger for children in low-quality daycare (d = 1.15), whereas there was essentially little or no effect for children in high-quality daycare (d = 0.10). Second, the effect size was larger for preschoolers (aged 39 to 59 months) (d = 1.17) than for infants (aged 3 to 16 months) (d = 0.11) or school-aged children (aged 84 to 106 months) (d = 0.09). Third, children with difficult temperaments in daycare were more likely to exhibit a rising pattern of cortisol, compared with children who were not difficult. CONCLUSIONS: Our review suggests that daycare attendance in relatively low-quality daycare conditions and for children with difficult temperaments may result in atypical cortisol elevation. Although the link between atypical cortisol elevation and mental health requires further study, programs aimed at improving the quality of daycare services during the preschool years are expected to lead to better physiological adaptation to daycare and to reduce the risks of mental health problems.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".