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INTRODUCTION: ChatGPT is a Large Language Model (LLM) which allows for natural language processing and interactions with users in a conversational style. Since its release in 2022, it has had a significant impact in many occupational fields, including medical education. We sought to gain insight into the extent and type of usage of ChatGPT at a Caribbean medical school, the American University of Antigua College of Medicine (AUA). METHODS: We administered a questionnaire to 87 full-time faculty at the school via email. We quantified and made graphical representations of the results via Qualtrics Experience Management software (QualtricsXM, Qualtrics, Provo, UT). Survey results were investigated using bar graph comparisons of absolute numbers and percentages for various categories related to ChatGPT usage, and descriptive statistics for Likert scale questions. RESULTS: We found an estimated 33% of faculty were currently using ChatGPT. There was broad acceptance of the program by those who were using it and most believed it should be an option for students. The primary task ChatGPT was being used for was multiple choice question (MCQ) generation. The primary concern faculty had was incorrect information being included in ChatGPT output. CONCLUSION: ChatGPT has been quickly adopted by a subset of the college faculty, demonstrating its growing acceptance. Given the level of approval expressed about the program, we believe ChatGPT will continue to form an important and expanding part of faculty workflows at AUA and in medical education in general.
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People with severe mental illness (SMI) have reduced life expectancy compared with the general population, which can be explained partly by their increased risk of diabetes. We conducted a meta-analysis to determine the clinical effectiveness of pharmacological and non-pharmacological interventions for improving glycaemic control in people with SMI (PROSPERO registration: CRD42015015558). A systematic literature search was performed on 30/10/2015 to identify randomised controlled trials (RCTs) in adults with SMI, with or without a diagnosis of diabetes that measured fasting blood glucose or glycated haemoglobin (HbA1c). Screening and data extraction were carried out independently by two reviewers. We used random effects meta-analysis to estimate effectiveness, and subgroup analysis and univariate meta-regression to explore heterogeneity. The Cochrane Collaboration's tool was used to assess risk of bias. We found 54 eligible RCTs in 4,392 adults (40 pharmacological, 13 behavioural, one mixed intervention). Data for meta-analysis were available from 48 RCTs (n = 4052). Both pharmacological (mean difference (MD), -0.11mmol/L; 95% confidence interval (CI), [-0.19, -0.02], p = 0.02, n = 2536) and behavioural interventions (MD, -0.28mmol//L; 95% CI, [-0.43, -0.12], p<0.001, n = 956) were effective in lowering fasting glucose, but not HbA1c (pharmacological MD, -0.03%; 95% CI, [-0.12, 0.06], p = 0.52, n = 1515; behavioural MD, 0.18%; 95% CI, [-0.07, 0.42], p = 0.16, n = 140) compared with usual care or placebo. In subgroup analysis of pharmacological interventions, metformin and antipsychotic switching strategies improved HbA1c. Behavioural interventions of longer duration and those including repeated physical activity had greater effects on fasting glucose than those without these characteristics. Baseline levels of fasting glucose explained some of the heterogeneity in behavioural interventions but not in pharmacological interventions. Although the strength of the evidence is limited by inadequate trial design and reporting and significant heterogeneity, there is some evidence that behavioural interventions, antipsychotic switching, and metformin can lead to clinically important improvements in glycaemic measurements in adults with SMI.
