Personality, Sexuality, and Beauty Standards: A Cross-Cultural Exploration of Canadian and German Women's Cosmetic Surgery Behaviours and Attitudes
Bibliographic record
Abstract
This study investigated the impact of various psychosocial factors on behaviours and attitudes towards cosmetic surgery among Canadian (n=97) and German (n=115) women, considering cultural differences and beauty standards. The primary objective was to provide valuable insights for physicians and psychologists when selecting suitable candidates for elective procedures, as current pre-surgical assessments often fail to integrate the psychological perspective. A correlation analysis was undergone and revealed that neuroticism moderately influenced interest and motivation for cosmetic surgery in both populations. Additionally, the Canadian group exhibited a moderate negative correlation between motivation for cosmetic surgery and early sexual experiences, effectively destigmatizing cosmetic surgery as a social indicator of early sexual behaviours. However, this correlation was not observed in the German cohort. Notably, Canadians reported a higher overall motivation for undergoing cosmetic surgery compared to Germans, as confirmed by a t-test. Surgeons should inquire about sexuality and personality in pre-surgical consultations to determine candidates who may benefit from the procedure and minimize harm. Future research should develop a standardized test for replication and include diverse demographics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".