Mediating Mechanisms for Maternal Mental Health from Pre- to during the COVID-19 Pandemic
Bibliographic record
Abstract
Mothers have experienced a near doubling of depression and anxiety symptoms pre- to during the COVID-19 pandemic. The identification of mechanisms that account for this increase can help inform specific targets for mental health recovery efforts. The current study examined whether women with higher levels of depression and anxiety symptoms pre-pandemic, reported higher levels of depression and anxiety symptoms during the pandemic, and whether these increases were mediated by perceived stress, strained relationships, coping attitudes, participation in activities, alcohol use, and financial impact. Mothers (n = 1,333) from an ongoing longitudinal cohort (All Our Families; AOF) from Calgary, Alberta, Canada, completed online questionnaires prior to (2017–2019) and during the COVID-19 pandemic (May-July 2020). Mothers reported on depressive and anxiety symptoms pre- and during the pandemic, as well as perceived stress, engagement in physical and leisure activities, coping, alcohol use, and financial impact of the pandemic. In unadjusted analyses, maternal depression and anxiety symptoms pre-pandemic were strongly associated with COVID-19 depressive (r = 0.57, p<.01) and anxiety symptoms (r = 0.49, p<.01). Significant indirect effects between maternal depressive symptoms pre- and during COVID-19 were found for coping behavior (abcs=0.014, 95%CI=0.005, 0.022, p=.001), perceived stress (abcs=0.22, 95%CI=0.179, 0.258, p<.001), and strained relationships (abcs=0.013, 95%CI= 0.005, 0.022, p=.003). For maternal anxiety symptoms pre- and during COVID-19, significant indirect effects were observed for perceived stress (abcs=0.012, 95%CI=0.077, 0.154, p=.003) and strained relationships (abcs=0.010, 95%CI=0.001, 0.018, p=.03). Perceived stress, coping attitudes, and interpersonal relationships are three potential intervention targets for mitigating COVID-19 related mental distress in mothers.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".