Psychological Aspects of Cosmetic Surgery Among Females: A Media Literacy Training Intervention
Bibliographic record
Abstract
INTRODUCTION: The present study examined the favorable attitude of a sample of female university students regarding elective cosmetic surgery, body dysmorphic disorder, self-esteem and body dissatisfaction following a media literacy training intervention. METHODS: This study was a quasi-experimental type. The study sample included 140 female university students who were allocated to either the intervention (n=70) or the control group (n=70). Attitude toward cosmetic surgery, body dysmorphic disorder, self-esteem and, body satisfaction was measured in both groups before the intervention and 4 weeks later. Four media literacy training sessions were conducted over 4 weeks for the intervention group. The data was analyzed through analysis of covariance, student's paired-samples t test, and Pearson correlation. RESULTS: Our findings showed that favorable attitude, body dysmorphic disorder and body dissatisfaction scores were significantly lower (p<0.05) in the intervention group than the control group. Furthermore, self-esteem score increased significantly in the intervention group. CONCLUSIONS: Our results underscores the importance of media literacy intervention in decreasing female's favorable attitude towards elective cosmetic surgery, body dysmorphic disorder and body dissatisfaction as well as increasing self-esteem.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".