The impact of relationship factors on antenatal depression in the context of the COVID‐19 pandemic
Bibliographic record
Abstract
BACKGROUND: Antenatal depression is the most prevalent pregnancy-associated mental health disorder. Previous studies have identified several risk factors for antenatal depression, including partner support. However, during the COVID-19 pandemic, many relationship dynamics changed. This study examined the extent to which relationship factors had an impact on antenatal depression in comparison with other well-researched factors in the context of the pandemic. METHODS: A secondary analysis was conducted using data from the P3 Cohort in Calgary, a longitudinal cohort study based in Alberta, Canada. Pregnant people (n = 872) completed self-report questionnaires and validated scales about sociodemographic, psychological, and relationship characteristics. Antenatal depression was assessed using the Edinburgh Postnatal Depression Scale (EPDS). Logistic regression was used to assess the impact of reported characteristics on antenatal depression. Tests of model fit were used to examine whether the inclusion of variables related to relationship quality improved model fit after accounting for other known risk factors. RESULTS: Overall, 18.23% of participants experienced antenatal depression. Relationship factors including relationship unhappiness (OR = 1.98 [95% CI: 1.06-3.69]), having an upsetting partner (OR = 2.00 [95% CI: 1.17-3.40]), and having a lower quality of relationships with close friends and family (OR = 1.76 [95% CI: 1.14-2.73]) were associated with antenatal depression; however, inclusion of these relationship factors did not improve model fit after accounting for other known predictors. CONCLUSION: Overall, relationship factors were not associated with antenatal depression during the pandemic after accounting for other known risk factors. Stress and anxiety caused by the pandemic may have overshadowed the impact of relationship factors, or relationship factors may have contributed to higher levels of stress and anxiety more generally within our sample.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".