Maternity blues: a risk factor for anhedonia, anxiety, and depression components of Edinburgh Postnatal Depression Scale
Bibliographic record
Abstract
Background: Women undergo adaptive physical and psychological changes during pregnancy, which make them vulnerable to psychological disorders.Methods: This study used a prospective observational design and included concurrent validation analysis of the 16-item Maternity Blues Scale (MBS) Dutch version to determine the direction and magnitude on the Edinburgh Postnatal Depression Scale (EPDS) symptoms, including three factors, anhedonia, anxiety, and depression in 320 puerperae early after childbirth.Results: We found a statistically significant correlation between MBS and EPDS global scores (0.22, p < .001). Moreover, Negative affect was significantly correlated with the EPDS global score (0.23, p < .001), anhedonia (0.12, p < .05), and anxiety (0.25, p < .001); Positive affect with the EPDS global score (0.14, p < .05) and depression (0.13, p < .05); and Depression subscale with EPDS global score (0.15, p < .05), anhedonia (0.12, p < .05), and anxiety (0.12, p < .05), and depression (0.12, p < .05). In addition, the subgroup of women (n = 33, 10.3%) with EPDS > 12 presented significantly higher global MBS score (2.51 ± 0.38 versus 2.26 ± 0.38, p = .01), with negative affect (2.88 ± 0.67 versus 2.62 ± 0.38, p=.04), positive affect (2.52 ± 0.69 versus 2.32 ± 0.38, p = .04), and depression (2.09 ± 0.75 versus 1.82 ± 0.36, p = .02).Conclusion: These findings together suggest that women with higher maternity blues scores may represent a distinct subgroup at increased risk of depression.
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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 | 0.002 |
| 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) | 0.002 | 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".