Making the cut: Investigating body image and well-being among female powerlifters
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
In weight-category sports, purposeful weight loss (PWL) is often undertaken preceding a competition to gain a performance advantage at a lower body weight. Researchers investigating PWL among powerlifters have identified associations to psychological outcomes. Yet investigations considering the psychological outcomes of PWL can be expanded to include (1) broader conceptualizations of psychological concepts and (2) greater nuance for the dynamics of PWL. Moving towards addressing these research gaps, the purpose of this study was to examine body image and well-being in female powerlifters during a period of PWL surrounding competition. Using a non-experimental longitudinal design, female powerlifters ( N = 12; Mage = 29.42, SD age = 9.23 years) self-reported body weight, body image, and well-being at five timepoints over 10 weeks. Body image was measured using the Body Appreciation Scale-2 along with a single-item indicator of shape and weight satisfaction. Well-being was measured using the Warwick Edinburgh Mental Well-Being Scale. At the time of official competition weigh-in, participants lost an average of 3.44 kg of body weight ( SD = 1.14 kg). One pooled time series regression analysis was used per response variable (body appreciation/shape satisfaction/weight satisfaction/well-being) to test the temporal association with body weight. Body weight predicted weight satisfaction ( B = 0.40, p < .001) and well-being ( B = –0.19, p < .001). It can be concluded that during a nine-week period of PWL female powerlifters reported improvements in weight satisfaction and well-being. These findings help to understand psychological outcomes for gradual weight loss practices among female powerlifters when preparing to compete.
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.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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