A LONGITUDINAL INVESTIGATION OF CIRCADIAN RHYTHMS AND SLEEP DISTURBANCES ACROSS THE PERINATAL PERIOD IN WOMEN AT LOW AND HIGH RISK OF POSTPARTUM DEPRESSION
Bibliographic record
Abstract
Postpartum depression (PPD) remains a serious mood disorder without a known etiology. PPD has a prevalence of 7-15% in the general population. Women with a history of a mood disorder are at an even higher risk for the development of PPD. Work over the last few decades has established a strong association between circadian rhythm and sleep disturbances and mood disorders, such as Major Depressive Disorder (MDD) and Bipolar Disorder (BD). Despite the breadth of evidence associating circadian rhythm disruption and depressive mood episodes, literature establishing a connection between circadian rhythms and changes in mood across the perinatal period is lacking. The work outlined in this thesis aimed to address this gap by examining the association between circadian rhythm and sleep disturbances across the perinatal period and their association with changes in mood in women at high and low risk of PPD development. A total of 87 women were studied, 45 healthy controls and 42 women with a mood history. Women were interviewed during the third trimester of pregnancy and between six to twelve weeks postpartum. Sleep and circadian rhythms were measured using both subjectively with self-reported questionnaires and objectively with actigraphy. Our results show that women at high and low risk showed higher disruption differ in subjective circadian rhythmicity, as well as in both subjective and objective parameters of sleep. Specifically, women at high risk for postpartum were found to have lower sleep efficiency, as measured by actigraphy, in the postpartum. In addition, subjective and objective parameters of sleep and circadian rhythms are associated with changes in depressive symptoms across the perinatal period. Our findings suggest that stabilizing circadian rhythms and improving sleep quality throughout the perinatal period can prevent postpartum mood worsening, particularly for those women at greatest risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".