RESUMEN
Self-immolation, a form of self-harm involving setting oneself on fire, is associated with high mortality, morbidity, and healthcare burden. This study aimed to characterize potential clinical correlates and predisposing factors for self-immolation based on burn severity using Total Body Surface Area (TBSA) percentage scoring. Additional objectives included identifying motivational elements, associated risk factors, and clinical characteristics to optimize patient care and reduce future self-immolation incidents. A retrospective review of admissions to the Arizona Burn Center from July 2015 to August 2022 identified 103 self-immolation patients for the study. Burn severity was categorized as mild to moderate (TBSA < 20%) or severe (TBSA ≥ 20%) based on TBSA. This study population had a mortality rate of 21%. Positive urine drug screens were found in 44% of subjects, and 63% having chronic substance use, with methamphetamine (37%) and alcohol (30%) being the most prevalent. Underlying psychiatric illnesses were present in 83% of patients. Suicidal intent strongly predicted severe burns (p < 0.001) among the 68 severe burn cases identified. In conclusion, this study emphasizes that the presence of suicidal intent among self-immolation patients significantly correlates with burn severity. These findings highlight the importance of involving psychiatric services early in patient care to improve outcomes and reduce the recurrence of self-immolation acts.
RESUMEN
This article investigates the limitations of Chat Generative Pre-trained Transformer (ChatGPT), a language model developed by OpenAI, as a study tool in dermatology. The study utilized ChatPDF, an application that integrates PDF files with ChatGPT, to generate American Board of Dermatology Applied Exam (ABD-AE)-style questions from continuing medical education articles from the Journal of the American Board of Dermatology. A qualitative analysis of the questions was conducted by two board-certified dermatologists, assessing accuracy, complexity, and clarity. Out of 40 questions generated, only 16 (40%) were deemed accurate and appropriate for ABD-AE study preparation. The remaining questions exhibited limitations, including low complexity, lack of clarity, and inaccuracies. The findings highlight the challenges faced by ChatGPT in understanding the domain-specific knowledge required in dermatology. Moreover, the model's inability to comprehend the context and generate high-quality distractor options, as well as the absence of image generation capabilities, further hinders its usefulness. The study emphasizes that while ChatGPT may aid in generating simple questions, it cannot replace the expertise of dermatologists and medical educators in developing high-quality, board-style questions that effectively evaluate candidates' knowledge and reasoning abilities.
