Ignite Creation Date:
2024-10-26 @ 3:39 PM
Last Modification Date:
2024-10-26 @ 3:39 PM
Study NCT ID:
NCT06584305
Status:
COMPLETED
Last Update Posted:
None
First Post:
2024-08-30
Brief Title:
AI Screening for BDD in Aesthetic Surgery Enhancing Safety and Outcomes
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Artificial Intelligence Screening for Body Dysmorphic Disorder in Aesthetic Surgery Improving Patient Safety and Outcomes
Status:
COMPLETED
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
AI
Brief Summary:
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
Detailed Description:
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 system39s effectiveness across diverse populations and clinical settings
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 system39s effectiveness across diverse populations and clinical settings
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None