The goal of this observational study is to evaluate the effectiveness of an AI-powered screening tool for Body Dysmorphic Disorder (BDD) among patients seeking aesthetic surgery. The study aims to determine if the AI system can effectively identify patients at risk for BDD and assess the impact of early psychological intervention on surgical decision-making and outcomes. Participants will complete a comprehensive AI-based risk assessment, which includes the Body Dysmorphic Disorder Questionnaire (BDDQ). The study will track the correlation between BDD, age, stress levels, and gender to better understand the prevalence and implications of BDD in cosmetic surgery.

This observational study evaluates an AI-powered screening tool for Body Dysmorphic Disorder (BDD) in patients seeking elective aesthetic surgery. The study is designed to assess the effectiveness of the AI system in identifying individuals at risk for BDD, facilitating timely psychological interventions, and improving surgical outcomes.

Study Overview:

Study Population and Inclusion Criteria: Patients aged 18 and older seeking elective cosmetic surgery at a solo practice are included. All participants complete a comprehensive AI-based risk assessment, which includes the Body Dysmorphic Disorder Questionnaire (BDDQ) integrated within the AI system.

AI-Based Risk Assessment: The AI system utilizes data from the BDDQ, along with demographic and psychological factors, to generate a risk score for BDD. This risk score informs the clinical decision-making process, particularly in determining the eligibility for surgery and the need for psychological intervention.

Data Collection and Management: Data is collected through a secure online platform where participants complete the necessary questionnaires. The AI system analyzes the data to generate individualized risk profiles. The study implements rigorous quality assurance processes, including automated data validation checks and source data verification, to ensure the reliability and accuracy of the data.

Statistical Analysis: The study employs correlation analysis to explore the relationships between BDD, age, gender, and stress levels. Chi-square tests are used to assess the statistical significance of differences between demographic groups. The analysis plan includes handling missing data through imputation techniques and conducting sensitivity analyses to validate the robustness of the findings.

Outcome Measures: Primary outcomes include the prevalence of BDD among the study population and the correlations between BDD and key demographic factors. Secondary outcomes focus on the effectiveness of the AI system in enhancing surgical decision-making and improving patient satisfaction.

Ethical Considerations: The study adheres to ethical guidelines, including obtaining informed consent from all participants and anonymizing data to protect privacy. The study is conducted in accordance with the Declaration of Helsinki, and institutional review board approval was deemed unnecessary due to the non-invasive nature of the screening.

Study Limitations: The study acknowledges potential limitations, including the relatively small number of patients who proceeded with surgery, which may affect the generalizability of the findings. Further research is recommended to explore the AI system's effectiveness across diverse populations and clinical settings.

Inclusion Criteria:

• Patients aged 18 years or older
• Completion of the AI-based Body Dysmorphic Disorder Questionnaire (BDDQ)

Exclusion Criteria:

• Individuals under the age of 18 years
• Incomplete or refusal to complete the BDDQ

The study population includes individuals aged 18 years or older who are seeking elective cosmetic surgery at a private practice in Buenos Aires, Argentina. All participants are required to complete an AI-based Body Dysmorphic Disorder (BDD) screening questionnaire as part of the preoperative evaluation. The study aims to assess the prevalence of BDD and its correlation with various risk factors within this population.

Individual participant data (IPD) that underlie the results reported in this study will be shared after de-identification. Data will be available to other researchers upon reasonable request, subject to approval by the principal investigator, Dr. Williams Erik Bukret. The data will be shared through a secure data-sharing platform.

IPD and supporting information will be available starting 6 months after publication of the study results and will remain available for 1 year.

IPD and supporting information will be available to researchers who provide a methodologically sound proposal, which must be approved by the principal investigator, Dr. Williams Erik Bukret. Access will be granted for the purpose of academic research, and the data will be shared through a secure data-sharing platform upon request.