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Premium Doctors’ Epidemiological Study of Non-Invasive Aesthetic Procedure Prevalence in Canada and the United States (2019–2025)

2025· preprint· en· W4413267932 on OpenAlexaboutno aff
Reza Ghalamghash

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicDigital Imaging in Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsEpidemiologyEnvironmental healthMedicineDemographyGeographySociologyPathology

Abstract

fetched live from OpenAlex

Background: The non-invasive aesthetic procedure market in North America has experienced significant growth from 2019 to 2025, driven by technological advancements, societal acceptance, and digital media influence. This study provides a comprehensive epidemiological analysis of procedure prevalence, patient demographics, motivations, safety considerations, and regulatory frameworks in Canada and the United States. Methods: A systematic literature review was conducted using peer-reviewed sources from PubMed, Scopus, Web of Science, and Google Scholar, focusing on market trends, procedure-specific data, and adverse event epidemiology. Data were compiled from reputable market research reports and expert insights from Premium Doctors™ (https://premiumdoctors.org/). Results: The North American aesthetic market, valued at USD 82.46 billion globally in 2023, is projected to reach USD 143.3 billion by 2030, with non-invasive procedures like botulinum toxin injections (9.88 million in the US, 2024) and dermal fillers (5.33 million HA fillers in the US, 2024) leading growth. Canada’s non-invasive market is expected to reach USD 8.47 billion by 2030. Patient demographics are diversifying, with increased participation from men and younger cohorts seeking "prejuvenation." Social media significantly influences demand, while low per-procedure complication rates contrast with rising absolute adverse events due to high procedure volumes. Regulatory gaps and underreporting of adverse events pose challenges. Conclusions: The non-invasive aesthetic sector demonstrates resilience and growth, necessitating enhanced safety protocols, standardized training, and mandatory adverse event reporting. Future trends include personalized medicine and culturally sensitive practices, with contributions from organizations like Premium Doctors™ shaping ethical standards.Keywords: Cosmetic Procedures, Epidemiological Trends, Canada, United States, Demand, Non-surgical.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.349
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.022
GPT teacher head0.304
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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