How the COVID-19 Pandemic Changed a New Mother’s Sense of Loneliness, and Who Was Key to Helping Them Through It
Bibliographic record
Abstract
Background: We report here on new mothers' changing sense of loneliness before and after the first year of the coronavirus disease 2019 (COVID-19) pandemic and assess what and who they felt were important to them for reducing their loneliness. Methods: We conducted an online survey of mothers. The questionnaire had sections regarding the home childcare environment, her anxiety and sense of loneliness levels, and whether or not she could consult with. Results: It revealed that 58.6% of mothers had felt lonely more often than they had before COVID-19 pandemic and that 45.0% had felt lonely within recent 30 days. Mothers who were not working, or who could not get anyone's help for the first month after childbirth, or who had anxiety about child-rearing or their economic situation, or whose family was unable to respond to her feelings or support her, or who did not have anyone to consult with, or who did not have sufficient opportunities to consult with her friends and neighbors, or who could not consult with, or had refrained from consulting with, pediatric clinic, felt loneliness more often. Mothers who could not consult with their husband, mother, father, brothers, and sisters, mother-in-law, neighborhood friends, or business colleagues felt loneliness more. Conclusions: A new mother's perception that her needs were not being met, or whether she could consult with her neighborhood friends or work colleagues as well as her husband, parents, and/or mother-in-law, was associated with more loneliness. Stronger involvement of family and friend in her child-rearing should be promoted. J Clin Gynecol Obstet. 2022;11(4):101-107 doi: https://doi.org/10.14740/jcgo824
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".