Measuring stress responses in postpartum mothers: Perspectives from studies in human and animal populations
Bibliographic record
Abstract
Reduced hypothalamic-pituitary-adrenal (HPA) responses to stress during the last week of pregnancy and lactation have been consistently observed in rat studies. Several contributing factors have been proposed for this phenomenon in lactation, including the suckling stimulus from the pups, hormones (oxytocin and prolactin) and opioids, a decrease in the ability of noradrenaline to potentiate hypothalamic responses and changes in pituitary responsiveness to ACTH secretagogues (AVP and CRF). In contrast to this vast literature using the rat model, only few studies have addressed this issue in the human population. The consensus is that women engaging in breastfeeding activities exhibit reduced anxiety, although the reductions in neuroendocrine and autonomic responses to stressors are variable, in part because of the different nature of the stressors used. Further work is required to investigate how additional factors, such as maternal parity or emotional salience of the stressor can affect stress responsiveness in postpartum women. Here, we review first the findings regarding stress responsiveness during lactation in both rat and human studies, and then discuss potential research avenues and methodological issues that could be the lead to future research protocols in human subjects. Knowing the reciprocal relationship in the mother-infant dyad, it is clear that investigation of the mechanisms regulating stress responses and mental health in postpartum mothers can only be beneficial to the development of the infant.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".