Shaniff Esmail

Background/Objectives: Digital technologies and data-driven approaches are rapidly transforming healthcare practice and enabling more personalized and preventive care. As personal health data becomes increasingly embedded in healthcare systems, understanding how future healthcare professionals interpret these developments is essential for shaping responsive health education. This study aims to identify the factors that students in health-related programs consider important regarding the increasing use of personal health data in healthcare. Methods: An exploratory qualitative focus group study was conducted between March 2024 and July 2025 across five higher education institutions in Australia, Canada, and the Netherlands. Seven focus groups were conducted with forty students from health-related programs, including nursing, public health, occupational therapy, and social work. Participants discussed the use of personal health data in healthcare and reflected on short fictional future scenarios designed to stimulate discussion about possible developments in data-driven healthcare. Data were analyzed using reflexive thematic analysis using ATLAS.ti. Results: Three overarching domains were identified: (1) personalization and prevention, (2) data quality and ethical considerations, and (3) organizational implications and conditions. Students described personal health data as a powerful tool for personalization, prevention, and informed decision-making. At the same time, they raised concerns about data reliability, overreliance on automated systems, patient anxiety, potential dehumanization of care, privacy risks, and emerging inequalities related to access to and representation within data systems. Overall, students appeared neither purely techno-optimistic nor technophobic, but articulated nuanced ethical, cultural, and professional tensions surrounding data-driven care. Conclusions: Preparing future healthcare professionals for data-driven healthcare requires integrating critical data literacy, ethical reflection, interdisciplinary collaboration and opportunities to critically engage with the societal and professional implications of data-driven technologies into health professional education, while ensuring that organizational conditions support the responsible use of personal health data.

Background: Immersive virtual reality (VR) and artificial intelligence have been used to determine whether a simulated clinical exam setting can reduce anxiety in first-year occupational therapy students preparing for objective structured clinical examinations (OSCEs). Test anxiety is common among postsecondary students, leading to negative outcomes such as increased dropout risk, lower grades, and limited employment opportunities. Students unfamiliar with specific testing environments are particularly prone to anxiety. VR simulations of OSCEs may allow students to become familiar with the exam setting and reduce anxiety. Objective: This study aimed to assess the efficacy of a VR simulation depicting clinical settings to reduce student anxiety about a clinical exam while gathering perspectives on their first-year coursework experiences to better understand their learning environment. Methods: An experimental, nonrandomized controlled trial compared state anxiety, trait test anxiety, and OSCE grades in 2 groups of first-year occupational therapy students analyzed using independent t tests (2-tailed). Group 1 (NoVR) was not exposed to the VR simulation and acted as a control group for group 2 (YesVR), who were exposed to the VR simulation. The VR used artificial intelligence in the form of a generative pretrained transformer to generate responses from virtual patients as students interacted with them in natural language. Self-reported psychometric scales measured anxiety levels 3 days before the OSCE. YesVR students completed perceived preparation surveys at 2 time points—3 weeks and 3 days before the OSCE—analyzed using dependent t tests. Semistructured interviews and focus groups were conducted within 1 week after the OSCE. Student perspectives on their classes and VR experiences were summarized using interpretative thematic analysis. Results: In total, 60 students—32 (53%) in the NoVR group and 28 (47%) in the YesVR group—participated in the study, and the YesVR group showed a significant reduction in state anxiety (t58=3.96; P<.001; Cohen d=1.02). The mean difference was 11.96 units (95% CI 5.92-18.01). Trait test anxiety and OSCE scores remained static between groups. There was an increase in all perceived preparedness variables in the YesVR group. In total, 42% (25/60) of the participants took part in interviews and focus groups, providing major themes regarding factors that affect OSCE performance, including student experience and background, feedback and support, fear of unknown, self-consciousness, and knowledge of the exam environment. Conclusions: Intolerance of uncertainty may lead students to interpret ambiguous exam situations as overly precarious. Findings suggest that VR simulation was associated with reduced state anxiety, although results from this small, nonrandomized sample should be interpreted cautiously. Qualitative data indicated that VR helped students gain familiarity with clinical exam settings, potentially decreasing uncertainty-based anxiety. Future research with larger or randomized samples is needed to confirm these findings and explore advanced VR tools offering feedback to enhance learning.

Background: The prevalence of dementia is expected to rise with an aging population, necessitating accessible early detection methods. Serious games have emerged as potential cognitive screening tools. They provide not only an engaging platform for assessing cognitive function but also serve as valuable indicators of cognitive health through engagement levels observed during play. Objective: This study aims to examine the differences in engagement-related behaviors between older adults with and without dementia during serious gaming sessions. Further, it seeks to identify the key contributors that enhance the effectiveness of machine learning for dementia classification based on engagement-related behaviors. Methods: This was an exploratory proof-of-concept study. Over 8 weeks, 20 older adults, 6 of whom were living with dementia, were enrolled in a single-case design study. Participants played 1 of 4 “Vibrant Minds” serious games (Bejeweled, Whack-A-Mole, Mah-jong, and Word-Search) over 8 weeks (16 30-min sessions). Throughout the study, sessions were recorded to analyze engagement-related behaviors. This paper reports on the analysis of the engagement-related behaviors of 15 participants. The videos of these 15 participants (10 cognitively intact, 5 with dementia) were analyzed by 2 independent raters, individually annotating engagement-related behaviors at 15-second intervals using a coding system. This analysis resulted in 1774 data points categorized into 47 behavior codes, augmented by 54 additional features including personal characteristics, technical issues, and environmental factors. Each engagement-related behavior was compared between older adults living with dementia and older adults without dementia using the χ² test with a 2×2 contingency table with a significance level of .05. Codes underwent one-hot encoding and were processed using random forest classifiers to distinguish between participant groups. Results: Significant differences in 64% of engagement-related behaviors were found between groups, notably in torso movements, voice modulation, facial expressions, and concentration. Including engagement-related behaviors, environmental disturbances, technical issues, and personal characteristics resulted in the best model for classifying cases of dementia correctly, achieving an F₁-score of 0.91 (95% CI 0.851‐0.963) and an area under the receiver operating curve of 0.99 (95% CI 0.984‐1.000). Conclusions: Key features distinguishing between older adults with and without dementia during serious gameplay included torso, voice, facial, and concentration behaviors, as well as age. The best performing machine learning model identified included features of engagement-related behavios, environmental disturbances, technical challenges, and personal attributes. Engagement-related behaviors observed during serious gaming offer crucial markers for identifying dementia. Machine learning models that incorporate these unique behavioral markers present a promising, noninvasive approach for early dementia screening in a variety of settings.

BACKGROUND Immersive virtual reality (VR) and artificial intelligence have been used to determine whether a simulated clinical exam setting can reduce anxiety in first-year occupational therapy students preparing for objective structured clinical examinations (OSCEs). Test anxiety is common among postsecondary students, leading to negative outcomes such as increased dropout risk, lower grades, and limited employment opportunities. Students unfamiliar with specific testing environments are particularly prone to anxiety. VR simulations of OSCEs may allow students to become familiar with the exam setting and reduce anxiety. OBJECTIVE This study aimed to assess the efficacy of a VR simulation depicting clinical settings to reduce student anxiety about a clinical exam while gathering perspectives on their first-year coursework experiences to better understand their learning environment. METHODS An experimental, nonrandomized controlled trial compared state anxiety, trait test anxiety, and OSCE grades in 2 groups of first-year occupational therapy students analyzed using independent t tests (2-tailed). Group 1 (NoVR) was not exposed to the VR simulation and acted as a control group for group 2 (YesVR), who were exposed to the VR simulation. The VR used artificial intelligence in the form of a generative pretrained transformer to generate responses from virtual patients as students interacted with them in natural language. Self-reported psychometric scales measured anxiety levels 3 days before the OSCE. YesVR students completed perceived preparation surveys at 2 time points—3 weeks and 3 days before the OSCE—analyzed using dependent t tests. Semistructured interviews and focus groups were conducted within 1 week after the OSCE. Student perspectives on their classes and VR experiences were summarized using interpretative thematic analysis. RESULTS In total, 60 students—32 (53%) in the NoVR group and 28 (47%) in the YesVR group—participated in the study, and the YesVR group showed a significant reduction in state anxiety (t58=3.96; P<.001; Cohen d=1.02). The mean difference was 11.96 units (95% CI 5.92-18.01). Trait test anxiety and OSCE scores remained static between groups. There was an increase in all perceived preparedness variables in the YesVR group. In total, 42% (25/60) of the participants took part in interviews and focus groups, providing major themes regarding factors that affect OSCE performance, including student experience and background, feedback and support, fear of unknown, self-consciousness, and knowledge of the exam environment. CONCLUSIONS Intolerance of uncertainty may lead students to interpret ambiguous exam situations as overly precarious. Findings suggest that VR simulation was associated with reduced state anxiety, although results from this small, nonrandomized sample should be interpreted cautiously. Qualitative data indicated that VR helped students gain familiarity with clinical exam settings, potentially decreasing uncertainty-based anxiety. Future research with larger or randomized samples is needed to confirm these findings and explore advanced VR tools offering feedback to enhance learning.

Introduction Cervical arterial dissections are important causes of ischemic stroke. However, the outcomes of carotid artery (CA) versus vertebral artery (VA) dissections have not been previously compared, nor has the impact of endovascular intervention been studied, on a nationwide level. Methods Ischemic stroke admissions in the National Inpatient Sample (NIS) from 2016-2019 were retrospectively analyzed. Patient characteristics, presence and site of cervical arterial dissection, and outcomes were collected. Multivariable linear and logistic regression analyses adjusting for patient characteristics, endovascular and thrombolytic therapy, and complex sampling methodology were performed. Results Of 536,540 patients with acute ischemic stroke (AIS) were identified, 5,351 (1%) had dissections; 2,789 (52%) with CA and 2,562 (48%) with VA dissection. CA dissection patients had significantly higher rates of concurrent traumatic brain injury (3.2% vs 1.5%; pConclusions Despite a similar prevalence among patients admitted for AIS, CA dissections are associated with a higher rate of endovascular intervention and poorer short-term outcomes compared to VA dissections. This study provides essential epidemiologic and outcome data for the cerebrovascular neurosurgeon. Comparison of clinical characteristics and outcomes among patients presenting with acute ischemic stroke due to carotid or vertebral artery dissections Multivariable regression analyses of short-term outcomes. ICH/SAH = Intracerebral hemorrhage/subarachnoid hemorrhage; CI = Confidence Interval; OR = Odds Ratio Disclosures M. Brandel: None. C. McCann: None. A. Wali: None. V. Wu: None. S. Esmail: None. J. Steinberg: None. S. Olson: None. J. Pannell: None. A. Khalessi: None. D. Santiago-Dieppa: None.

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