Attitude and Practice of Aesthetic Surgery among Plastic Surgeons in Nigeria
Bibliographic record
Abstract
BACKGROUND: Aesthetic surgery in developed countries is growing at an exponential rate. There is an increasing demand for cosmetic procedures in Nigeria but still, the practice is at a slow pace. Significant clients from Nigeria seek for these procedures outside Nigeria. OBJECTIVE: This study aimed at determining the attitude and practice of aesthetic surgery among plastic surgeons in Nigeria METHOD: We conducted a cross-sectional study among the attendees of the annual conference of the National Association of Plastic Reconstructive and Aesthetic Surgeons held at Calabar, Nigeria, using a questionnaire on consented participants. RESULTS: A total of 73 out of 84 Plastic surgeons participated in the study with a response rate of 86.9%. The mean age of the respondents was 45.4±7.2 years. Only 14 (19.2%) had undergone extra training in cosmetic surgery. Most respondents 53.4% prefer Nigerian over foreign hospitals for cosmetic surgery for various reasons. Poor awareness (42.5%) and religious beliefs (42.5%) contributed most to the poor acceptability of cosmetic surgery in Nigeria. The vast majority (97%) of Nigerian plastic surgeons want the public to be engaged in awareness sensitization on cosmetic surgery and their preferred mode of sensitization was through internet / social media (80.8%), television (74%), and radio (65.8%). Scar revision (78.1%) abdominoplasty (69.9%) and breast reduction (67.1) were the common cosmetic procedures performed by Nigerian plastic surgeons. CONCLUSION: The attitude of Plastic surgeons in Nigeria to cosmetic surgery is influenced by the low acceptance of cosmetic surgery procedures by Nigerians. Attitudinal change programs, especially through social and other mass media, are desired to increase awareness and acceptance of cosmetic surgery in Nigeria.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".