Background: ChatGPT (Open AI) is a state-of-the-art large language model that uses artificial intelligence (AI) to address questions across diverse topics. The American Society of Clinical Oncology Self-Evaluation Program (ASCO-SEP) created a comprehensive educational program to help physicians keep up to date with the many rapid advances in the field. The question bank consists of multiple choice questions addressing the many facets of cancer care, including diagnosis, treatment, and supportive care. As ChatGPT applications rapidly expand, it becomes vital to ascertain if the knowledge of ChatGPT-3.5 matches the established standards that oncologists are recommended to follow. Objective: This study aims to evaluate whether ChatGPT-3.5’s knowledge aligns with the established benchmarks that oncologists are expected to adhere to. This will furnish us with a deeper understanding of the potential applications of this tool as a support for clinical decision-making. Methods: We conducted a systematic assessment of the performance of ChatGPT-3.5 on the ASCO-SEP, the leading educational and assessment tool for medical oncologists in training and practice. Over 1000 multiple choice questions covering the spectrum of cancer care were extracted. Questions were categorized by cancer type or discipline, with subcategorization as treatment, diagnosis, or other. Answers were scored as correct if ChatGPT-3.5 selected the answer as defined by ASCO-SEP. Results: Overall, ChatGPT-3.5 achieved a score of 56.1% (583/1040) for the correct answers provided. The program demonstrated varying levels of accuracy across cancer types or disciplines. The highest accuracy was observed in questions related to developmental therapeutics (8/10; 80% correct), while the lowest accuracy was observed in questions related to gastrointestinal cancer (102/209; 48.8% correct). There was no significant difference in the program’s performance across the predefined subcategories of diagnosis, treatment, and other (P=.16, which is greater than .05). Conclusions: This study evaluated ChatGPT-3.5’s oncology knowledge using the ASCO-SEP, aiming to address uncertainties regarding AI tools like ChatGPT in clinical decision-making. Our findings suggest that while ChatGPT-3.5 offers a hopeful outlook for AI in oncology, its present performance in ASCO-SEP tests necessitates further refinement to reach the requisite competency levels. Future assessments could explore ChatGPT’s clinical decision support capabilities with real-world clinical scenarios, its ease of integration into medical workflows, and its potential to foster interdisciplinary collaboration and patient engagement in health care settings.

Objective: The goals of the present study are (1) to identify sociodemographic and psychosocial predictors of human papillomavirus (HPV)-related stigma and (2) to examine the relationship between HPV-related stigma in predicting HPV vaccine decision-making among college males. Participants: Six hundred and eighty college males aged 18–26 from 3 Canadian universities were recruited from September 2013 to April 2014. Methods: Participants completed a self-report survey assessing HPV-related stigma, psychosocial predictors of HPV-related stigma, and HPV vaccine decision-making. The results were analyzed using variance analyses and linear regressions. Results: Ethnicity, province of residence, and perceived severity of HPV were found to significantly influence HPV-related stigma. In addition, HPV-related stigma was higher in those unaware of the availability of the HPV vaccine for males. Conclusions: Promotion efforts should concentrate on Asian minorities and should avoid HPV severity messaging, as these may lead to higher HPV-related stigma, which in turn may act as a barrier to vaccination.

Patients consistently rate cancer-related fatigue (CrF) as the most prevalent and debilitating symptom. CrF is an important but often neglected patient concern, partly due to barriers to implementing evidence-based interventions. This study explored what an ideal intervention for CrF would look like from the perspectives of different stakeholders and the barriers to its implementation. Three participant populations were recruited: healthcare providers (HCPs; n = 32), community support providers (CSPs; n = 14), and cancer patients (n = 16). Data were collected via nine focus groups and four semi-structured interviews. Data were coded into themes using content analysis. Two main themes emerged around addressing CrF: “It takes a village” and “This will not be easy”. Participants discussed an intervention for CrF could be anywhere, offered by anyone and everyone, and provided early and frequently throughout the cancer experience and could include peer support, psychoeducation, physical activity, mind–body interventions, and interdisciplinary care. Patients, HCPs, and CSPs described several potential barriers to implementation, including patient barriers (i.e., patient variability, accessibility, online literacy, and overload of information) and systems barriers (i.e., costs, lack of HCP knowledge, system insufficiency, and time). As CrF is a common post-treatment symptom, it is imperative to offer patients adequate support to manage CrF. This study lays the groundwork for the implementation of a patient-centered intervention for CrF in Canada and possibly elsewhere.