Exploring the pressure to “bounce back” to pre-pregnancy weight after birth
Bibliographic record
Abstract
Weight stigma is defined as negative attitudes and beliefs towards individuals based on their weight, which can manifest as stereotypes, rejection, and prejudice. During the postpartum period, societal pressures to quickly lose weight are intensified and often glorify rapid weight loss. These pressures can have a negative impact on maternal mental health, contributing to postpartum depression, anxiety, and impaired mother-infant bonding. This study aimed to identify the sources of potential pressure to 'bounce back' to pre-pregnancy weight among women who have recently given birth. The study involved an online survey, comprised of closed- and open-ended questions, completed by 114 women who were on average 71.0 (12.3) weeks postpartum. Data were assessed descriptively, and a content analysis was performed for open-ended questions. Sources of postpartum weight loss pressure included: Self-motivation (30%), Body Image Dissatisfaction (25%), Society (40%), Family (18%), Media (28%), and Other Postpartum Women (14%). Most (70%) participants were concerned about their postpartum weight, with 43% considering it very important to return to their pre-pregnancy weight. Participants commonly used exercise and nutrition as strategies for weight loss. These findings highlight the multifaceted sources of pressure women may face to conform to societal norms surrounding quick weight loss after childbirth. This study underscores the need for interventions to dismantle postpartum thin body ideals or celebration of rapid weight loss, and instead, encourage safe and inclusive management of postpartum weight retention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".