Prompt engineering: The next big skill in rheumatology research.

Large language models (LLMs) like GPT-4 and Claude are catalyzing transformation across medical research including rheumatology. This review examines their applications, highlighting the pivotal role of prompt engineering in effectively guiding LLMs. Key aspects explored include literature synthesis, data analysis, manuscript drafting, coding assistance, privacy considerations, and generative artificial intelligence integrations. While LLMs accelerate workflows, reliance without apt prompting jeopardizes accuracy. By methodically constructing prompts and gauging model outputs, researchers can maximize relevance and utility. Locally run open-source models also offer data privacy protections. As LLMs permeate rheumatology research, developing expertise in strategic prompting and assessing model limitations is critical. With proper oversight, LLMs markedly boost scholarly productivity.

A study on impostor phenomenon, personality, and self-esteem of medical undergraduates and interns.

Introduction: Impostor phenomenon (IP) is a psychological experience where an individual considers their achievements to be fraudulent. IP in medical professionals is of paramount importance since it affects their self-confidence and communication skills. It has been associated with burnouts, low self-esteem, and neuroticism. Aim: This research aimed to study the prevalence of IP, personality traits, and self-esteem and to look at gender differences in medical undergraduate students and interns of an urban medical college along with the correlation of IP with personality traits and self-esteem in them. Methodology: An online survey via Google Groups was conducted among MBBS students and interns of a medical college after informed consent and ethics approval were received. Four hundred sixteen participants completed the survey questionnaire which included demographic variables along with the the Clance Impostor Phenomenon Scale, the Big Five Inventory, and the Rosenberg Self-Esteem Scale. Results: IP was found in 236 (56.7%) students and interns. Personality domain mean scores were extraversion (26.4 ± 5.12), agreeableness (33.5 ± 5.4), conscientiousness (29.9 ± 5.7), neuroticism (21.6 ± 5.7), and openness (35.1 ± 4.9). The self-esteem mean score was 18.37 ± 6.14; only 16.11% had high self-esteem. Interns and first-year MBBS students scored higher on IP and low on self-esteem among all groups. Significant gender differences were seen in females on agreeableness, conscientiousness, and neuroticism as compared to the males. IP negatively correlated with self-esteem, extraversion, agreeableness, and conscientiousness and positively with neuroticism. Conclusion: This study throws some light on the IP experiences of medical undergraduates which have not been extensively researched in India.