Association of spiritual/religious coping with depressive symptoms in high‐ and low‐risk pregnant women
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To investigate the role of spiritual/religious coping (SRC) on depressive symptoms in high- and low-risk pregnant women. BACKGROUND: Spiritual/religious coping is associated with physical and mental health outcomes. However, only few studies investigated the role of these strategies during pregnancy and whether low- and high-risk pregnant women have different coping mechanisms. DESIGN: This study is a cross-sectional comparative study. METHODS: This study included a total of 160 pregnant women, 80 with low-risk pregnancy and 80 with high-risk pregnancy. The Beck Depression Inventory, the brief SRC scale and a structured questionnaire on sociodemographic and obstetric aspects were used. General linear model regression analysis was used to identify the factors associated with positive and negative SRC strategies in both groups of pregnant women. RESULTS: Positive SRC use was high, whereas negative SRC use was low in both groups. Although we found no difference in SRC strategies between the two groups, negative SRC was associated with depression in women with high-risk pregnancy, but not in those with low-risk pregnancy. Furthermore, positive SRC was not associated with depressive symptoms in both groups. CONCLUSIONS: Results showed that only the negative SRC strategies of Brazilian women with high-risk pregnancies were associated with worsened mental health outcomes. RELEVANCE TO CLINICAL PRACTICE: Healthcare professionals, obstetricians and nurse midwives should focus on the use of negative SRC strategies in their pregnant patients.
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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 | 0.003 |
| 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) | 0.001 | 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".