Using mixed methods to explain maternal anger : examining the relationships between sleep and anger and exploring mothers' development of anger
Bibliographic record
Abstract
Maternal anger has been overlooked as a postnatal mood disturbance. The empirical literature supports a strong relationship between sleep and mental health. Proportions of women experiencing anger and whether maternal-infant sleep problems are associated with anger as a postpartum mood disturbance are unknown. Social media was used to recruit Canadian mothers of infants between 6 and 12 months of age to complete an online survey about maternal-infant sleep after receiving ethical approval. The survey inquired about maternal-infant sleep quality, maternal fatigue, cognitions about infant sleep, support, anger, and depressive symptoms. A subset of women completing the online survey participated in telephone interviews, with the goal of generating a theory about anger after childbirth. Phone interviews were transcribed and data were analyzed using grounded theory methods. Of the 278 women who completed the survey, 70% perceived their infant’s sleep as problematic. Regarding mood, 31% had high levels of anger and 26% had depressive symptoms above the cut-off score. Robust regression analysis revealed that parity (b = 1.93, p < .001), depression (b = .50, p = .008), and anger about infant sleep (b = .46, p < .001), predicted maternal postpartum anger. An interaction term between anger about infant sleep and infant age also predicted maternal anger (b = 0.13, p <.001). Eighteen mothers described their experiences of anger in their first two postpartum years. Mothers’ violated expectations, compromised needs, and being on edge contributed to feeling angry. Appropriate support from partners, family, and others, helped women manage their anger. Absent and inappropriate support prolonged maternal anger about violated expectations and compromised needs, particularly about infant sleep issues. Participants expressed or suppressed their anger with differing effects on support, relationships, and control. Anger in the postpartum period has negative effects for women and families; it can be comorbid with insomnia and depression symptoms. Clinician support around evidence-based strategies to promote maternal-infant sleep and family members’ support to help meet womens’ psychosocial and physical needs can reduce anger. Women require screening for anger and sleep problems after childbirth. Policy change required include structural support for women and families in the postnatal period.
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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 | 0.054 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".