Trajectories of maternal depressive and anxiety symptoms from pregnancy to five years postpartum and their prenatal predictors
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Maternal depression and anxiety have distinct constellations of symptom trajectories, which are associated with factors that may vary between different groups of women. The aim of this study was to identify subgroups of women who exhibit unique longitudinal trajectory patterns of depressive and anxiety symptoms from pregnancy to 5 years postpartum and the antenatal predictors associated with these maternal groups. METHODS: The study used a longitudinal data collected from 615 women in Saskatchewan from pregnancy to 5 years postpartum. Semiparametric group-based models were used to identify latent maternal depressive and anxiety trajectory groups. Multinomial logit models were then used to assess the association between maternal characteristics and the identified latent trajectory groups. RESULTS: We identified four trajectory groups of maternal depressive symptoms: low-stable (35%); moderate-stable (54%); moderate-increasing (5%); and high-decreasing (6%), and three trajectory groups of maternal anxiety symptoms: very low-stable (13%); low-stable (58%); and moderate-stable (29%). We also identified several risk factors, most notably history of depression and stress, that were significantly associated with these trajectories. CONCLUSION: History of depression and increased stress are significant risk factors that can be identified during regular perinatal visits; therefore, clinicians should inquire about these risk factors to identify women at high risk of ongoing depression or anxiety.
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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) | 0.001 | 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 it