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Record W3170975490 · doi:10.1177/22925503211019607

Why Do Canadians Travel Abroad for Cosmetic Surgery? A Qualitative Analysis on Motivations for Cosmetic Surgery Tourism

2021· article· en· W3170975490 on OpenAlexaffabout
Emilie Robertson, Scott W. Moorman, Lisa Korus

Bibliographic record

VenuePlastic Surgery · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Healthcare and Medical Tourism
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsThematic analysisQualitative researchMedicinePsychologyTourismAdvertisingSurgerySociologyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Background: Canadians are increasingly engaging in medial tourism. The purpose of this study was to review Canadians’ experiences with travelling abroad for cosmetic surgery, including primary motivations for seeking care outside of Canada. Methods: A qualitative analysis was conducted using semistructured interviews following a pre-determined topic guide. People who had undergone cosmetic surgery outside of Canada were interviewed. The interviews were transcribed and coded to determine motivational themes. Patients were recruited until thematic saturation was achieved. Results: Thematic saturation was achieved after recruitment of 11 patients. The most common motivational themes identified in this study for seeking cosmetic surgery outside of Canada included cost, post-operative care provided, marketing/customer service, and word-of-mouth. Member checking and theory triangulation were validation techniques used to verify identified themes. Mexico was the most common location for cosmetic tourism. The most common procedures were breast augmentation, mastopexy, and abdominoplasty. Participants gathered pre- and post-operative information primarily through pamphlets and contact with surgeons’ offices. Follow-up was only available for half of the participants in this study, and only 5 of the participants felt that they had received informed consent. Conclusions: The majority of participants engaged in cosmetic tourism due to cost reasons and the level of post-operative care provided.

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)0.004
metaresearch head score (Gemma)0.079
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.079
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.120
GPT teacher head0.450
Teacher spread0.329 · 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.

Study designNot applicable
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

Citations9
Published2021
Admission routes2
Has abstractyes

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