Developing a new measure of retrospective body dissatisfaction: links to postnatal bonding and psychological well-being
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Pregnancy is a transformative time for women and their bodies, and therefore thoughts and feelings about the body understandably change during this period. While previous research has established the impact of body dissatisfaction on factors like antenatal attachment and maternal mental health, there is a notable gap in understanding its long-term effects on postnatal factors. This is often due to high attrition rates in longitudinal studies. Using retrospective measures could address this issue, however a measure of retrospective pregnant body dissatisfaction has not yet been identified. AIMS: This paper aimed to create a retrospective measure of pregnancy body dissatisfaction by adapting a previously validated measure. It also aimed to investigate the relationship between retrospective accounts of body dissatisfaction during pregnancy and postnatal anxiety, depression, and bonding. METHOD: = 404). FINDINGS: An exploratory and confirmatory factor analysis identified a two-factor model of retrospective body dissatisfaction, adapted from the Body Understanding Measure for Pregnancy Scale, which was equivalent to two of the original subscales. Using this factor structure, linear regressions demonstrated that higher levels of retrospective pregnant body dissatisfaction were associated with elevated rates of postnatal anxiety and depression and lower bonding scores. CONCLUSIONS: This study successfully established a measure for assessing retrospective pregnant body dissatisfaction, potentially aiding future research. Additionally, it has highlighted the link between pregnant body dissatisfaction and postnatal levels of depression, anxiety, and bonding. Thus, improving the pregnant bodily experience may have the potential to enhance the postnatal experience.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it