Effects of Breastfeeding on Stress Measured by Saliva Cortisol Level and Perceived Stress
Bibliographic record
Abstract
Purpose: The effects of breastfeeding on postpartum depression symptoms and stress using physiological measures require investigation. Background: Breastfeeding suppresses the secretion of cortisol. Oxytocin levels correlate negatively with symptoms of postpartum depression. Aim: To investigate the effects of breastfeeding on stress and postpartum depression. Methods: We examined 79 breastfeeding women using the Edinburgh Postnatal Depression Scale, the Perceived Stress Scale-10, and the Breastfeeding Self-Efficacy Scale, and measured the salivary cortisol levels before and after breastfeeding. Findings: There was a negative correlation between the duration of suckling and changes in salivary cortisol levels following breastfeeding (rs = −0.333, p < 0.05). Salivary cortisol levels immediately following breastfeeding were significantly lower compared to mothers who used mixed feeding methods (p < 0.001). Breastfeeding mothers had lower perceived stress than mothers using mixed feeding methods (β = −0.260, p < 0.05). There was no association between breastfeeding and postpartum depression; however, there was an association between postpartum depression and perceived stress (β = 0.622, p < 0.001). Conclusion: Salivary cortisol levels significantly decreased following breastfeeding, with longer suckling times correlating with lower cortisol levels. Breastfeeding reduced stress and increased breastfeeding self-efficacy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".