The <scp>PREGO</scp> Study: A Preconception Cohort to Better Understand Perinatal Mental Health
Bibliographic record
Abstract
Studies assessing perinatal mental health often lack a prospective pre-pregnancy assessment. Administering measures in preconception could lead to a better understanding of changes occurring over time. This study sought to examine changes in mental health during preconception and the first trimester of pregnancy. The PREGO Study (N = 411 participants) includes 393 participants with preconception mental health data; of these, 174 also had data in the first trimester of pregnancy. We assessed symptoms of depression, anxiety, stress, distress and sleep health. Results of repeated measures ANOVA showed that symptoms of depression increased (F(1, 265.46) = 26.03; d adapted = 0.26) while stress (F(1, 251.24) = 5.95; d adapted = 0.12) and sleep health (F(1, 161.18) = 9.76; d adapted = 0.17) decreased from preconception to the first trimester of pregnancy. Other indicators remained stable. Our results highlight the need for mental health assessments from preconception through postpartum to better understand trajectories of perinatal mental health.
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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 | 0.001 | 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) | 0.000 | 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 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".