Attachment security and recent stressful life events predict oxytocin levels: a pilot study of pregnant women with high levels of cumulative psychosocial adversity
Bibliographic record
Abstract
PURPOSE: Recent reports indicate that prenatal levels of the neuropeptide oxytocin (OT) are inversely related to depressive symptomatology and positively associated with more optimal interactive behaviors in mothers with high levels of cumulative psychosocial adversity (CPA). In the present pilot study, we aimed to identify factors associated with high versus low levels of OT in pregnant women with high levels of CPA. We hypothesized that insecurely attached women, and those who recently experienced stressful life events (SLE), would have lower levels of prenatal OT. METHODS: Thirty pregnant women with mood and anxiety disorders and high levels of CPA were recruited from the perinatal mental health service of a general hospital. Participants completed self-report measures of psychosocial stress and adult attachment style, and blood was then drawn to assess OT. RESULTS AND CONCLUSIONS: Lower OT levels were found among those who were insecurely attached, and among those who experienced SLE within the last year. In a multiple linear regression, both attachment security and SLE significantly contributed to a model of prenatal OT levels. These individual difference factors explained 38% of the variance in prenatal OT, which may in turn predict poorer maternal mental health and caregiving outcomes during the postpartum period.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".