Perfectionism in athletes and non-athletes: Effects on social physique anxiety and body satisfaction
Bibliographic record
Abstract
In today's culture, the body appears to have become a main focus. Increased use of image based social media sites appear to reinforce a focus on body ideals and related body image concerns. Nonetheless, individuals appear to differ with regard to vulnerability to such influences. The purpose of the present study was to examine how perfectionism [self-oriented (SOP) or socially-prescribed (SPP)] and athletic status (athlete vs non-athlete) might interact to influence body satisfaction, appearance investment and social physique anxiety in individuals. Athletic status was assessed using both a perceived athlete and an objective athlete definition based on responses to related questions. Participants included a post-secondary sample of 208 men and women aged 17-24 years. They agreed to participate in an online study of how personality and athletic status influence feelings towards oneself and related behaviours. Findings revealed both significant interaction and main effects on the outcome variables of interest, with the pattern of results differing based on athletic status definition and the specific perfectionism facet. Implications of these findings are discussed. Additionally, these results provide evidence for more closely examining the role of one's perceived athletic status as a unique risk factor in appearance and body related concerns. The findings of this study may assist in better identifying individuals at risk for negative self-body perceptions and their related compensatory behaviours, such as the use of appearance and performance enhancing drugs.Acknowledgments: Chantal Arpin-Cribbie
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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".