Background: Stroke often leads to persistent impairments that limit daily functioning and psychosocial well-being. Virtual reality (VR) has emerged as a promising adjunct in stroke rehabilitation, although research has largely focused on clinical outcomes, with limited attention to user involvement and the experiences of multiple stakeholders in the design process.
Objective: This study aimed to explore the challenges and benefits of co-designing and using VR to support home-based poststroke rehabilitation.
Methods: A qualitative co-design case study was applied to gain an in-depth understanding of the challenges and benefits. Rapid co-design principles were used in developing VR prototypes delivered via head-mounted displays through 3 workshops with participants with stroke, health care professionals, and VR developers from November 2023 to May 2024. A design prototype revision was done based on feedback from the workshops. Data were collected via audio-taped co-design workshops with all participants and 10 successive semistructured interviews with health care professionals and VR developers conducted in a rehabilitation hospital. A thematic analysis was performed on transcribed recordings.
Results: In total, five main themes emerged: (1) adaptability for stroke-related impairments in home rehabilitation, (2) safety and ease of use, (3) goal orientation, (4) motivation, and (5) VR as a complementary tool. One of the primary challenges identified lies in the adaptability of VR systems for individuals with hemiparesis. Additionally, customization and safety concerns remain a complex barrier, as VR solutions must be capable of addressing a wide range of stroke-related impairments and aligning specific rehabilitation goals. VR demonstrated potential to enhance rehabilitation by simulating real-life tasks that encourage goal-oriented and motivating therapy. As a complementary tool, VR can enhance traditional rehabilitation by increasing the intensity and volume of therapy.
Conclusions: This study offers insight into how VR can be effectively integrated into rehabilitation practices. Its integration into rehabilitation requires alignment with established therapeutic principles within VR applications, such as adjustable task-specific training and meaningful outcomes tailored to individual needs, to ensure clinical relevance and user engagement. VR should complement, rather than replace, conventional therapy by increasing training intensity, reducing therapist workload, and extending rehabilitation into the home. Thoughtful co-design with stakeholders is key to creating VR tools that bridge the gap between structured clinical care and independent recovery, offering continuous support throughout the rehabilitation process.
Background: Diabetic foot ulceration (DFU) is the leading cause of nontraumatic amputations in people with diabetes. Research shows that improving patient awareness can result in short-term improvements, but Cochrane reviews report insufficient high-quality evidence.
Objective: This study aims to investigate the effects of multimedia presentation and smartphone alerts to enhance long-term knowledge and foot care behaviors in individuals at moderate-to-high risk of DFU.
Methods: Participants were randomized to a control group, receiving usual diabetic foot care advice (n=40), or an intervention group, receiving a multimedia diabetic foot care presentation and regular "foot alerts" through the MyU smartphone app on top of usual care (n=37). Patient's knowledge and behaviors related to diabetic foot care were assessed at baseline and after 12 months. Repeated measures ANOVA was conducted in both intention-to-treat and per-protocol analyses to evaluate the intervention's effectiveness.
Results: The findings were consistent across intention-to-treat and per-protocol analyses. In the intervention group, the number of podiatry visits was positively correlated with improved foot care behavior (r=0.408; P=.02), while the control group showed a negative correlation (r=-0.402; P=.02). No significant correlations were observed with knowledge scores. Although no significant time×group interactions were seen, the main effects of time were found for both knowledge (η²=0.12; P=.004) and behavior scores (η²=0.31; P<.001). Post hoc analysis showed a decline in knowledge scores in the control group (Cohen d=-0.24; P=.007) and improvements in behavior scores in both groups (Cohen d: intervention=0.61, control=0.63; all P<.001).
Conclusions: The MyU app-based multimedia intervention was associated with improved foot care behaviors over 12 months, indicating potential benefits as an adjunct to usual diabetic foot care. However, no significant changes in diabetic foot care knowledge were observed. These findings suggest that while the applied digital multimedia tool may support behavior change, further research is needed to enhance knowledge retention and clinical impact. The study revealed that multimedia education alone may not be effective for long-term improvement in foot self-care knowledge and behavior among individuals at moderate-high DFU risk, but the reinforcement of educational material during follow-up podiatry visits could be effective.
Background: The emergence of artificial intelligence (AI) is driving digital transformation and reshaping medical education in China. Numerous medical schools and institutions are actively implementing AI tools for case-based learning, literature analysis, and lecture support. This expanding application is accelerating the adoption of localized AI platforms, which are poised to become integral components in the coming years.
Objective: The primary aim of this study was to investigate the current use of AI tools among medical students, including usage frequency, commonly used platforms, and purposes of use. The second aim was to explore students' needs and expectations toward AI-powered medical education platforms by collecting and assessing student feedback, and to identify practical requirements across disciplines and academic stages to inform more effective platform design.
Methods: Based on the task-technology fit model and 5 hypotheses, an anonymous online questionnaire was conducted to assess AI usage in learning, gather student feedback on AI-powered medical education platforms, and evaluate expected functionalities. The survey was conducted from March 1 to May 31, 2025, using a convenience sampling method to recruit medical students from various disciplines across Shanghai, China. The sample size was determined at 422, accounting for a 10% rate of invalid responses. The questionnaire was developed and distributed online via Wenjuanxing and promoted through WeChat groups and in-person interviews. Data analysis was conducted employing IBM SPSS Statistics (v 27.0).
Results: A total of 428 valid questionnaires were collected. The average frequency of AI-assisted learning among medical students was 5.06 (SD 2.05) times per week. Over 90% (388/428) of the students used more than 2 AI tools in their daily tasks. Students from different disciplines, educational stages, and academic systems demonstrated different usage patterns and expectations for AI-powered medical education platforms.
Conclusions: AI technology is widely accepted by medical students and is extensively applied across various aspects of medical education. Significant differences are observed in usage patterns across disciplines, educational stages, and academic systems. Understanding the actual needs of students is crucial for the construction of AI-powered medical education platforms.
Background: Dementia increases the risk of individuals getting lost due to cognitive decline, impacting daily functioning and heightening caregiver worry. Traditional search methods are often time-consuming and stressful, whereas GPS-based technologies face limitations such as battery dependency. A crowdsourcing Internet of Things (IoT) technology using energy-efficient Bluetooth Low Energy (BLE) offers a potential solution to locate missing individuals with dementia more effectively by harnessing the power of the crowd and fostering a caring and inclusive community.
Objective: This study aimed to evaluate the effectiveness of a BLE-based privacy-preserving crowdsourcing IoT system consisting of a BLE tag and an Android and iOS app in improving lost-related behavior and psychological well-being by facilitating searches, after-care arrangements, and reducing caregiver worry, as well as to assess its usability among caregivers of individuals with dementia in Hong Kong.
Methods: A single-arm, prospective observational study was conducted from November 2020 to October 2023. Caregivers (N=1034) of individuals with dementia used a staff-assisted crowdsourcing IoT technology comprising a BLE tag, mobile app sensor, and location cloud server. Outcomes included search strategies, post-getting lost care arrangements, caregiver worry and distress (10-point scale), and usability (modified Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 survey). Data were collected at 6- and 12-month follow-ups and analyzed using generalized estimating equations and linear mixed models.
Results: Of the 1034 participants, 143 (13.82%) reported lost episodes, with 51 (35.7%) using BLE tags for searches. Worry about future lost episodes decreased significantly over time (P=.008), especially among BLE tag users (P=.04). There was an association between BLE tag use and adoption of proactive search strategies (eg, going out to search: adjusted odds ratio 2.78, 95% CI 1.33-5.82; P=.007) and preventative measures (eg, IoT devices or CCTV: adjusted odds ratio 2.92, 95% CI 1.61-5.29; P<.001). Usability satisfaction was high for design and data security, whereas approximately half of the participants (309/707, 43.7%) were satisfied with accuracy.
Conclusions: The BLE crowdsourcing system may reduce caregiver worry and encourage proactive search behaviors, although accuracy depends on broader community adoption. Integration into dementia care plans could enhance safety and autonomy. Further research with a randomized controlled trial design is needed to confirm these findings.
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