Background: Artificial intelligence (AI) is increasingly integrated into education and health care, raising questions about how students use these technologies and how AI influences their learning. In health education, understanding these trends is particularly important because student learning directly impacts future clinical skills. Objective: This study aimed to explore the use of AI tools by health sciences students at the University of Ottawa. More specifically, it sought to identify the most frequently used AI tools, describe students’ usage habits, determine which tools support knowledge acquisition and skill development, and gather students’ recommendations for effective strategies to raise awareness and train their peers on the responsible use of AI. Methods: A qualitative approach was used with students from 10 health professions who reported using AI in their studies. Data were collected through semistructured interviews and an open-ended qualitative online survey. Inductive thematic analysis within an interpretive paradigm was applied to capture patterns, perceptions, and emergent themes. Results: A total of 51 health professions students participated in the study. Most were women between the ages of 20 and 29 years. ChatGPT (OpenAI) emerged as the most frequently used AI tool. Students perceived AI as a complementary tool that facilitated knowledge acquisition, skill development, writing, and problem-solving. AI adoption was driven by curiosity, peer influence, and the desire to improve work efficiency. Students critically evaluated AI results, integrated the tools into their learning processes, and emphasized the importance of technical skills, critical thinking, and digital literacy. Peer learning, hands-on demonstrations, and access to online resources were recommended for effective AI training. Conclusions: This research demonstrates that health professions students actively use AI tools, particularly ChatGPT, to support learning, skill development, and academic tasks. Although AI is valuable as an educational aid and its use varies by student and context, this highlights the need for structured guidance, critical evaluation skills, and peer-supported training. These findings highlight the importance of thoughtfully integrating AI into educational programs to enhance learning outcomes, foster skill acquisition, and ensure responsible and effective adoption.

Introduction: Interprofessional education (IPE) is essential for fostering collaboration among health care professionals, yet its implementation in academic settings faces significant challenges. To facilitate stakeholder engagement in adapting a competency framework at the institutional level, we used Barr's categorization model to prioritize key collaborative competencies. This study explored expert perspectives on competency selection to inform the development of an IPE curriculum tailored to institutional needs. Method: A modified Delphi method was employed to collect input from a diverse panel of 26 health care professionals with expertise in teaching, precepting, and curriculum development. Panel members prioritized 40 competencies from the Canadian Interprofessional Health Collaborative framework, identifying those that should be emphasized as core collaborative competencies for guiding the development of local IPE curricula. The process unfolded over three rounds, allowing experts to refine their responses based on group feedback. Results: The study identified 26 core competencies for inclusion in the IPE curriculum. Despite a high consensus rate, comments and narrative feedback highlighted the importance of ensuring foundational knowledge is developed in uniprofessional programs before transitioning to interprofessional settings. Experts emphasized the need for holistic competency frameworks and noted challenges in sequencing, teachability, and assessment, particularly for competencies requiring experiential learning, such as conflict resolution and trust‐building. Conclusion: This paper outlines the development of a shared institutional competency framework, emphasizing instructors' priorities and concerns in creating an IPE curriculum across health‐related programs at a bilingual university. The findings suggest that Barr's competency categorization is most effective when applied holistically, as isolating core IPE competencies can lead to confusion and misalignment with uniprofessional curricula. Moving forward, institutional support and active engagement with workplace learning stakeholders will be essential for successful implementation and long‐term sustainability.

Background: Neuromuscular blockade (NMB) is frequently used in moderate-to-severe acute respiratory distress syndrome (ARDS) to optimize ventilatory synchrony and minimize ventilator-induced lung injury. However, comparative real-world data on different NMB strategies remain limited. Objective: To describe patterns of neuromuscular blockade use in ARDS and describe clinical outcomes across four NMB strategies: intermittent rocuronium, continuous cisatracurium, escalation from rocuronium to cisatracurium, and de-escalation from cisatracurium to rocuronium. Methods: A retrospective chart review was conducted in an 18-bed tertiary ICU at Hôpital Montfort (Ottawa, Canada) between November 2021 and March 2025. Adult ARDS patients who received NMB for >24 h were included. Continuous variables (age, ventilation time, ICU stay) were summarized as means ± SD and median [IQR]; categorical variables (sex, ARDS etiology, mortality) as counts and percentages. Inferential testing was limited to baseline characteristics; clinical outcomes were summarized descriptively. Results: Fifty-one patients met inclusion criteria: rocuronium (n = 20), cisatracurium (n = 14), rocuronium→cisatracurium (n = 8), and cisatracurium→rocuronium (n = 9). Mean ventilation durations were 280, 195, 272, and 262 h, respectively; corresponding ICU stays were 245, 237, 380, and 299 h. Mortality ranged from 25% to 56%. Escalation from rocuronium to cisatracurium typically reflected persistent dyssynchrony or worsening oxygenation, whereas de-escalation occurred in improving patients with residual ventilatory drive. Variability in corticosteroid use, adjunctive proning, and epoprostenol were potential confounders. Conclusions: Distinct NMB use patterns in ARDS reflect bedside clinical judgment rather than predefined thresholds. Patient trajectory and dyssynchrony severity appear to drive NMBA escalation decisions more than oxygenation indices alone. These findings highlight the need for prospective studies defining standardized criteria for NMB initiation, escalation, and weaning in ARDS.