Muscle Up: Male Athletes’ and Non-Athletes’ Psychobiological Responses to, and Recovery From, Body Image Social-Evaluative Threats
Bibliographic record
Abstract
Negative body image often occurs as a result of social evaluation of the physique in men. Social self-preservation theory (SSPT) holds that social-evaluative threats (SETs) elicit consistent psychobiological responses (i.e., salivary cortisol and shame) to protect one’s social-esteem, status, and standing. Actual body image SETs have resulted in psychobiological changes consistent with SSPT in men; however, responses in athletes have yet to be examined. These responses may differ as athletes tend to experience fewer body image concerns compared with non-athletes. The purpose of the current study was to examine psychobiological (i.e., body shame and salivary cortisol) responses to an acute laboratory body image SET in 49 male varsity athletes from non-aesthetic sports and 63 male non-athletes from a university community. Participants (age range 18–28 years) were randomized into a high or low body image SET condition, stratified by athlete status; measures of body shame and salivary cortisol were taken across the session (i.e., pre, post, 30-min post, 50-min post-intervention). There were no significant time-by-condition interactions, such that athletes and non-athletes had significant increases in salivary cortisol ( F 3,321 = 3.34, p = .02), when controlling for baseline values, and state body shame ( F 2.43,262.57 = 4.58, p = .007) following the high-threat condition only. Consistent with SSPT, body image SETs led to increased state body shame and salivary cortisol, although there were no differences in these responses between non-athletes and athletes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".