Blessings and Curses: Exploring the Experiences of New Mothers during the COVID-19 Pandemic
Bibliographic record
Abstract
The aim of this study was to explore the postpartum experiences of new parents during the COVID-19 pandemic. The postpartum period can be a time of significant transition, both positive and negative, for parents as they navigate new relationships with their babies and shifts in family dynamics. Physical distancing requirements mandated by public health orders during the COVID-19 pandemic had the potential to create even more stress for parents with a newborn. Examining personal experiences would provide health care professionals with information to help guide support during significant isolation. Feminist poststructuralism guided the qualitative research process. Sixty-eight new mothers completed an open-ended on-line survey. Responses were analyzed using discourse analysis to examine the beliefs, values, and practices of the participants relating to their family experiences during the pandemic period. It was found that pandemic isolation was a time of complexity with both 'blessings and curses'. Participants reported that it was a time for family bonding and enjoyment of being a new parent without the usual expectations. It was also a time of missed opportunities as they were not able to share milestones and memories with extended family. Caring for a newborn during the COVID-19 pandemic where complex contradictions were constructed by competing social discourses created difficult dichotomies for families. In acknowledging the complex experiences of mothers during COVID-19 isolation, nurses and midwives can come to understand and help new parents to focus on the blessings of this time while acknowledging the curses.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".