EPA-0063 - Antenatal therapy decreases depression and worry symptoms
Bibliographic record
Abstract
The effects of depression and worry on the pregnant woman and her unborn baby are an increasing concern. Treatment can decrease harmful symptoms, but pregnant women and careproviders are often reluctant to use medications. Therefore, we need research of non-pharmacologic treatment options. We invited pregnant women to participate in an 8-week therapy group (either mindfulness-based (MB) or interpersonal therapy (IT)) facilitated by an experienced psychologist. We collected depression, worry, and sociodemographic data on admission to the group, at the end of the group, and again one month postpartum. We subsequently matched and compared the women to 60 women who had participated in a longitudinal study of perinatal depression (age, gestation, marital status, education, medications) from the same community. We wanted to know if: 1) participating in a therapy group decreases depression and worry over the course of pregnancy into the postpartum? and 2) there was a significant change in depression, stress, and worry symptoms for the treatment group compared to a control group? Data were available on 39 women who had completed 6 groups (4 MB and 2 IT). Women who participated in either group showed significant decreases in depression (p<0.001) and worry scores (p<0.001) compared to control group. Women in the MB groups complained of less stress postpartum than the IT group, otherwise the groups were similar. Women who were unmarried had significantly higher depression scores (p<0.0001). In summary, participating in relaxation therapy groups can significantly lessen depression and worry symptoms over pregnancy and into the postpartum.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".