The influence of steroid and peptide hormones on cognition and mood during late pregnancy and early postpartum
Bibliographic record
Abstract
Cognitive and mood changes during pregnancy and postpartum have been subjectively reported by women and have also been objectively measured. However, evidence relating to the relationship between hormone levels and these changes is sparse and contradictory. The studies presented in this thesis were undertaken to investigate the possible influence of estradiol (E2), progesterone (P), testosterone (T), cortisol (CORT) and prolactin (PRL) levels on cognitive functioning and mood during late pregnancy and the early postpartum period. In Study 1, pregnant women were tested on a battery of neuropsychological tests once during late pregnancy and once during the early postpartum period and their scores were compared to non-pregnant controls. Results showed that the pregnancy group had significantly lower scores than the controls on tasks of verbal recall and processing speed both during the pregnancy and the postpartum test times. CORT levels were significantly associated, in an inverted-U function, with verbal recall scores during pregnancy and postpartum and with spatial abilities at postpartum. During pregnancy, negative linear associations were observed between PRL and executive function and paragraph recall scores along with an inverted-U association with paragraph recall scores. At postpartum, E2 and CORT were negatively associated, in a linear fashion, with attention scores. In Study 2, linear and non-linear associations between hormones and mood during pregnancy and postpartum were investigated while taking into consideration psychosocial factors previously found to be related to mood changes during these reproductive periods. Perceived stress, social support from friends, social support from a significant other and sleep were found to be significant predictors of mood scores. During pregnancy, a small positive linear correlation was obtained between levels of PRL and lower mood scores. At the postpartum visit, moderate U-shaped correlations were found between mood disturbances and level of E2 and P while smaller increases in the Cortisol Awakening Response were associated with poorer mood. Collectively, the present studies provide new evidence that aspects of cognitive function and mood are altered during pregnancy and the postpartum periods and may be modulated, at least in part, by hormonal and psychosocial factors during these reproductive events.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 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".