Prevalence, Incidence, and Persistence of Postpartum Anxiety, Depression, and Comorbidity
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence, incidence, and persistence of postpartum anxiety, depression, and comorbid symptoms over the first 6 months postpartum in a cohort of Havana women and to evaluate the sensitivity, specificity, and predictive power of the Edinburgh Postnatal Depression Scale (EPDS) and the State-Trait Anxiety Inventory (STAI) at 4 weeks postpartum on depressive and anxiety symptoms at 12 and 24 weeks. METHOD: A cohort study with 273 women in Havana, Cuba. Participants were assessed at 4, 12, and 24 weeks postpartum for anxiety, depression, and comorbid symptoms. RESULTS: Prevalence rates were highest at 4 weeks postpartum: 20.0% women reported elevated levels of anxiety and 16.4% reported depressive symptoms. The prevalence of comorbid anxiety and depression was 5.8%. While rates of anxiety steadily decreased to 13.8% at 24 weeks, rates of depression persisted to 24 weeks postpartum with 14.5% still experiencing elevated symptoms. Comorbid anxiety and depression decreased across time. There were limited sensitivity and poor predictive values for both the STAI and the EPDS. CONCLUSION: This study is the first to examine perinatal mental illness in Cuba. While anxiety and depression rates found among Cuban women are lower than those reported in other low-income countries, the rates paralleled high-income countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 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".