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Record W4390580592 · doi:10.2196/46515

Prevalence of Body Dysmorphic Disorder in the Spanish Population: Cross-Sectional Web-Based Questionnaire Study

2024· article· en· W4390580592 on OpenAlexvenueno aff
Álvaro Loewen, Hilario Blasco‐Fontecilla, Chao Li, Marcos Bella-Fernández, Belén Ruíz‐Antorán

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBody dysmorphic disorderMedicineCross-sectional studyQuality of life (healthcare)Mental healthPopulationDescriptive statisticsDemographyPsychiatryClinical psychologyPathologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Body dysmorphic disorder (BDD) is defined as excessive concern with mild or nonexistent defects in personal physical appearance, which are not perceived by others. The worldwide prevalence of BDD ranges between 0.5% and 3.2%, with no differences across genders. The mean age of onset of BDD is 16.9 years. BDD is typically associated with young age, psychiatric disorders, and dermatological procedures. Patients with BDD typically display poorer mental health status than patients diagnosed with other mental disorders. OBJECTIVE: The aim of this study was to estimate the prevalence of BDD in Spain and to identify the variables associated with BDD. METHODS: We performed a cross-sectional descriptive study by collecting data through an anonymous web-based survey targeting the Spanish population aged 18 years or older. The measures in this study were (1) sociodemographic variables, (2) variables associated with dermatological and psychiatric disorders and cosmetic procedures, (3) scales measuring quality of life (12-item Short Form health survey, version 2) and (4) BDD (BDD Questionnaire). Statistical analysis was performed with SPSS software version 21. P values less than .05 were considered significant. RESULTS: Of the 2091 participants who took the survey, 322 (15.2%) met the criteria of having BDD. The mean age of the participants with BDD was 23.5 (SD 9.6) years. In terms of BDD prevalence, women accounted for 19.9% (284/1421), men accounted for 5.2% (34/653), and students accounted for 25.2% (263/1043). Approximately 46.6% (150/322) of the participants with BDD reported a history of psychiatric comorbidities, including anxiety disorders, depressive disorders, and eating disorders. BDD was significantly associated with female gender, younger age (18-24 years), students, monthly income of less than €500 (€1=US $1.11), and the presence of dermatological and some psychiatric disorders such as depression, anxiety, and eating disorders (P<.05). The number of body parts of concern in participants with BDD was significantly higher than that in those without BDD (4.6 vs 2.2, respectively; P<.001). Regarding the body parts of concern, body fat was the most common concern for both groups with BDD and without BDD, followed by thighs, face, hips, and skin in the BDD group and thighs, teeth, and hair in the non-BDD group. Participants with BDD showed a significantly poorer self-perception of their mental health, irrespective of the presence of any mental disorder (P<.001). CONCLUSIONS: Our findings showed that the prevalence of BDD in Spain was higher than expected. Further, BDD is frequently associated with other psychiatric disorders, particularly depressive disorder, anxiety disorder, and eating disorder. Participants with BDD had a poorer perception of quality of life associated with mental but not physical health problems. Finally, the perception of quality of mental health life in participants with BDD was independent of diagnosis of any mental disorder.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.461
Teacher spread0.397 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2024
Admission routes1
Has abstractyes

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