ChatGPT as an item calibration tool: Psychometric insights in a high-stakes examination.

INTRODUCTION: ChatGPT has attracted a lot of interest worldwide for its versatility in a range of natural language tasks, including in the education and evaluation industry. It can automate time- and labor-intensive tasks with clear economic and efficiency gains. METHODS: This study evaluated the potential of ChatGPT to automate psychometric analysis of test questions from the 2020 Portuguese National Residency Selection Exam (PNA). ChatGPT was queried 100 times with the 150 MCQ from the exam. Using ChatGPT's responses, difficulty indices were calculated for each question based on the proportion of correct answers. The predicted difficulty levels were compared to the actual difficulty levels of the 2020 exam MCQ's using methods from classical test theory. RESULTS: ChatGPT's predicted item difficulty indices positively correlated with the actual item difficulties (r (148) = -0.372, p < .001), suggesting a general consistency between the real and the predicted values. There was also a moderate significant negative correlation between the difficulty index predicted by ChatGPT and the number of challenges (r (148) = -0.302, p < .001), highlighting ChatGPT's potential for identifying less problematic questions. CONCLUSION: These findings unveiled ChatGPT's potential as a tool for assessment development, proving its capability to predict the psychometric characteristics of high-stakes test items in automated item calibration without pre-testing in real-life scenarios.

Designing and building OSCEBot ® for virtual OSCE - Performance evaluation.

With AI's advancing technology and chatbots becoming more intertwined in our daily lives, pedagogical challenges are occurring. While chatbots can be used in various disciplines, they play a particularly significant role in medical education. We present the development process of OSCEBot ®, a chatbot to train medical students in the clinical interview approach. The SentenceTransformers, or SBERT, framework was used to develop this chatbot. To enable semantic search for various phrases, SBERT uses siamese and triplet networks to build sentence embeddings for each sentence that can then be compared using a cosine-similarity. Three clinical cases were developed using symptoms that followed the SOCRATES approach. The optimal cutoffs were determined, and each case's performance metrics were calculated. Each question was divided into different categories based on their content. Regarding the performance between cases, case 3 presented higher average confidence values, explained by the continuous improvement of the cases following the feedback acquired after the sessions with the students. When evaluating performance between categories, it was found that the mean confidence values were highest for previous medical history. It is anticipated that the results can be improved upon since this study was conducted early in the chatbot deployment process. More clinical scenarios must be created to broaden the options available to students.

Insights into Nanomedicine for Head and Neck Cancer Diagnosis and Treatment.

Head and neck cancers rank sixth among the most common cancers today, and the survival rate has remained virtually unchanged over the past 25 years, due to late diagnosis and ineffective treatments. They have two main risk factors, tobacco and alcohol, and human papillomavirus infection is a secondary risk factor. These cancers affect areas of the body that are fundamental for the five senses. Therefore, it is necessary to treat them effectively and non-invasively as early as possible, in order to do not compromise vital functions, which is not always possible with conventional treatments (chemotherapy or radiotherapy). In this sense, nanomedicine plays a key role in the treatment and diagnosis of head and neck cancers. Nanomedicine involves using nanocarriers to deliver drugs to sites of action and reducing the necessary doses and possible side effects. The main purpose of this review is to give an overview of the applications of nanocarrier systems to the diagnosis and treatment of head and neck cancer. Herein, several types of delivery strategies, radiation enhancement, inside-out hyperthermia, and theragnostic approaches are addressed.

Applicability and validation of the Reaction to Tests Scale (RTT) in a sample of Portuguese medical students.

BACKGROUND: Test anxiety is a crucial factor in determining academic outcomes, and it may lead to poor cognitive performance, academic underachievement, and psychological distress, interfering specifically with their ability to think and perform during tests. The main objective of this study was to explore the applicability and psychometric properties of a Portuguese version of the Reactions to Tests scale (RTT) in a sample of medical students. METHOD: A sample of 672 medical students completed the RTT. The sample was randomly split in half to allow for independent Exploratory Factor Analysis (EFA) and to test the best fit model-Confirmatory Factor Analysis (CFA). CFA was used to test both the first-order factor structure (four subscales) and second-order factor structure, in which the four subscales relate to a general factor, Test Anxiety. The internal consistency of the RTT was assessed through Cronbach's alpha, Composite reliability (CR) and Average Variance Extracted (AVE) for the total scale and each of the four subscales. Convergent validity was evaluated through the correlation between RTT and the State-Trait Anxiety Inventory (STAI-Y).To explore the comparability of measured attributes across subgroups of respondents, measurement invariance was also studied. RESULTS: Results from exploratory and confirmatory factor analyses showed acceptable fits for the Portuguese RTT version. Concerning internal consistency, results indicate that RTT was found to be reliable to measure test anxiety in this sample. Convergent validity of the RTT with both state and trait anxiety STAI-Y's subscales was also shown. Moreover, multigroup analyses showed metric invariance across gender and curriculum phase. CONCLUSION: Our results suggest that the RTT scale is a valid and reliable instrument for the measurement of test anxiety among Portuguese Medical Students.

Magnetoliposomes Containing Calcium Ferrite Nanoparticles for Applications in Breast Cancer Therapy.

Magnetoliposomes containing calcium ferrite (CaFe2O4) nanoparticles were developed and characterized for the first time. CaFe2O4 nanoparticles were covered by a lipid bilayer or entrapped in liposomes forming, respectively, solid or aqueous magnetoliposomes as nanocarriers for new antitumor drugs. The magnetic nanoparticles were characterized by UV/Visible absorption, XRD, HR-TEM, and SQUID, exhibiting sizes of 5.2 ± 1.2 nm (from TEM) and a superparamagnetic behavior. The magnetoliposomes were characterized by DLS and TEM. The incorporation of two new potential antitumor drugs (thienopyridine derivatives) specifically active against breast cancer in these nanosystems was investigated by fluorescence emission and anisotropy. Aqueous magnetoliposomes, with hydrodynamic diameters around 130 nm, and solid magnetoliposomes with sizes of ca. 170 nm, interact with biomembranes by fusion and are able to transport the antitumor drugs with generally high encapsulation efficiencies (70%). These fully biocompatible drug-loaded magnetoliposomes can be promising as therapeutic agents in future applications of combined breast cancer therapy.