To evaluate the factual accuracy and citation fidelity of Scopus AI's outputs in response to a single health care-related research question about the importance of human trafficking prevention education for professionals. This study employed a mixed-methods content verification approach. A single health care-related research question was entered into Scopus AI (Elsevier), which generated a summary, expanded summary, and concept map. Quantitative data were collected by classifying each statement in the Scopus AI output as accurate, misleading, or incorrect. Qualitative analysis provided contextual insights into citation use, source type, and interpretation of content. Of the 30 statements analyzed from the Scopus AI output, 27 (90.0%) were rated as accurate, and 3 (10.0%) were categorized as misleading. No incorrect or hallucinated content was detected. Qualitative analysis revealed that Scopus AI consistently cited legitimate, peer-reviewed sources. However, in 2 cases, the tool referenced secondary sources without clarification, raising questions about source hierarchy. Though Scopus AI produced largely reliable academic content, this study underscores the need for user verification and scholarly judgment, particularly regarding secondary sources and citation transparency. The findings highlight the importance of teaching students to critically evaluate artificial intelligence (AI)-generated material. In response to the findings, a classroom activity titled "Fact-Check the Bot" was developed to promote critical AI literacy. This activity guides learners in assessing AI-generated claims using a verification matrix and original literature and can be adapted for use with other AI tools. This study demonstrates the potential and the limitations of generative AI in academic research and offers a model for integrating verification practices into educational settings to enhance students' critical engagement with AI tools.

To encourage health profession students to reflect on and share an important aspect of their educational experience and analyze students' responses for common themes. This qualitative exploratory interprofessional education project used photovoice methodology. Images and reflections were collected from 13 radiation therapy students and 44 physical therapy students exploring the most important aspect of their educational experience. The students were responsible for submitting an original photograph and a written reflection in response to a prompt and explaining why they chose that photograph. Photographs and reflections were collected and analyzed by all researchers, and themes were identified. The themes of stress and feeling overwhelmed were identified by all researchers, which sparked further examination into academic burnout. Subsequent themes, which correlated with the theme of academic burnout, were coping strategies and gratefulness. Reports of mental illness, depression, and anxiety among college students are increasing. Increased awareness and requests for faculty support require educators to ensure students also are mentally prepared for graduation and entry-level practice. Implementing this low-stress interprofessional education project provided faculty with the opportunity to observe their students' worlds more deeply and gain a greater respect for their struggles and perseverance. Self-reflection projects, such as the one described in this study, allow health profession students to explore and share key feelings, experiences, and insights. Exercises like this help reduce stress, isolation, and academic burnout among students and provide educators with insights into their students' lives.

This phantom-based study aimed to identify acceptable velocity encoding (VENC) settings for flow measurements in straight-tube and aortic aneurysm phantoms using 4-D flow magnetic resonance (MR) imaging. A pulse flow pump was connected to 2 types of plastic phantoms (straight-tube and aortic aneurysm) to create steady and pulsatile flow, respectively. The validity of flow measurements with 4-D flow MR imaging using 2 VENC settings (16 and 32 cm/s) was examined, using flow meter measurements as the gold standard. The optimal VENC setting was 16 cm/s. Equivalence tests were conducted to identify acceptable VENC settings using an equivalence margin of 25%. A P value of less than .05 was considered significant. Using either steady or pulsatile flow in the straight phantom, it was found that the 4-D flow MR imaging measurement results with a VENC of 32 cm/s (P < .008)and 16 cm/s (P < .049)were acceptable (ie, within the range of equivalence). 4-D flow MR imaging measurements with VENC of 32 cm/s showed equivalence with flow meters under all conditions except for the aneurysm form and pulsatile flow conditions (P < .008). None of the VENC settings were acceptable using pulsatile flow in the aneurysm phantom because of overestimation (VENC of 16 cm/s) or underestimation (VENC of 32 cm/s). In the case of straight-tube morphology, acceptable measurement results can be obtained even with VENC settings twice the actual flow velocity. However, in the context of aortic aneurysm morphology, the authors speculated that achieving precise measurements with a VENC setting tailored to a straight tube would be challenging. Twice the optimal VENC is acceptable in straight vessels. However, an appropriate VENC setting would be difficult for measuring pulsatile flow in an aneurysm.