Pop Culture’s Influence on Aesthetic Treatment Trends in Canada and the United States: A Premium Doctors’ Scientific Literature Review
Bibliographic record
Abstract
1: PhD, Founder of Premium Doctors and Academic Director, Premium College, Toronto, CanadaCorresponding author: Reza Ghalamghash. Tel: +1 (647) 822-9570, E-mail: Reza@PremiumDoctors.orgORCID: 0009-0004-1745-1315 AbstractBackground: Pop culture, including celebrity endorsements, reality television, and social media, significantly influences aesthetic treatment trends in Canada and the United States. This review examines how these cultural forces shape beauty ideals and patient expectations, driving demand for minimally invasive procedures. It also explores the psychological and ethical implications for patients and practitioners, highlighting the need for robust regulatory frameworks and culturally competent practice.Methods: A systematic literature search was conducted across PubMed, Embase, Scopus, Web of Science, and Cochrane Library, using MeSH terms and keywords such as "aesthetic medicine," "pop culture," and "social media." Peer-reviewed articles published from 2015 to 2025 were prioritized, focusing on studies relevant to Canada and the United States. Data were extracted and synthesized thematically to identify mechanisms of influence, psychological impacts, and ethical challenges.Results: Findings indicate a shift toward minimally invasive procedures, driven by pop culture’s destigmatization of aesthetic treatments. Social media algorithms exacerbate body dissatisfaction, contributing to conditions like Body Dysmorphic Disorder (BDD) and creating a self-perpetuating demand cycle. Ethical challenges include managing unrealistic expectations, combating misinformation, and addressing commercialization. Practitioners report higher trust in board-certified professionals over influencers, emphasizing the need for evidence-based practice.Conclusions: Pop culture significantly shapes aesthetic trends, necessitating holistic, patient-centric care that integrates psychological screening and ethical communication. Future research should focus on longitudinal psychological impacts, intervention efficacy, and ethical implications of emerging technologies like AI and regenerative therapies to ensure patient well-being and professional integrity.Keywords: Aesthetic Medicine, Pop Culture, Social Media, Body Image, Canada, United States.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".