Background: Virtual reality (VR) is increasingly used for adjunctive relaxation training in psychiatric care. However, evidence remains limited among hospitalized patients with depressive disorders, particularly in routine inpatient settings in China, and little is known about whether improvement varies by session frequency. Objective: This retrospective study examined whether adjunctive VR-based relaxation training was associated with changes in depressive and anxiety symptoms among inpatients with depressive disorders and whether improvement differed by session frequency. Methods: We conducted a retrospective, nonrandomized natural-group comparison using complete anonymized medical records from patients hospitalized in Lishui Second People’s Hospital between January 1 and December 31, 2022. Patients met () diagnostic criteria for depressive episodes or recurrent depressive disorders and were screened using predefined criteria. The analytic sample included 133 inpatients: 63 (47.4%) received adjunctive VR-based relaxation training plus usual care and 70 (52.6%) received usual care only. Usual care included pharmacotherapy and physiotherapy. The VR intervention consisted of 25-minute immersive relaxation sessions delivered approximately 3 times per week. Symptoms were assessed at admission and discharge using the 17-item Hamilton Depression Scale and Hamilton Anxiety Rating Scale. Response was defined as a reduction of 50% or more from baseline, and remission was defined as a total score of 7 or less. Baseline characteristics, outcome scores, response and remission rates, and exploratory session-frequency subgroups were compared. All analyzed variables were checked against complete medical records; no missing values were identified, and no imputation was performed. Results: The VR and control groups did not differ significantly in baseline depressive or anxiety scores. At discharge, adjunctive VR-based relaxation training was associated with lower depressive and anxiety symptom scores than usual care alone. The VR group also showed higher response rates for both depressive and anxiety symptoms and a higher anxiety remission rate, whereas depression remission was similar. Exploratory session-frequency analyses suggested that anxiety improvement may be more consistently associated with VR exposure than depression remission; however, the pattern was not strictly linear and should be interpreted cautiously because treatment frequency was linked to hospitalization duration and routine care factors. Conclusions: This study is innovative in evaluating structured VR-based relaxation training as an adjunct to routine inpatient depression care and in providing preliminary observations on session-frequency patterns in a real-world Chinese psychiatric setting. Unlike many previous VR studies conducted in noninpatient, nonclinical, or short-term experimental contexts, this study reflects everyday clinical practice among hospitalized patients with depressive disorders. The findings contribute practical evidence for integrating immersive relaxation into comprehensive inpatient care, particularly when additional anxiety relief is desired. Because the study was retrospective and nonrandomized, the findings indicate associations rather than causal effects and should be confirmed in prospective randomized controlled trials.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/3f676641d2a71ff688fdee4dc02b8592" />
Exploring Informal Caregivers’ Perception of the Olera Digital Caregiving Assistance Platform for Dementia Care: Mixed Methods Evaluation Study
Background: Informal caregivers of people living with dementia often experience high rates of caregiver burnout while providing care. Although there are many websites and mobile apps available to help caregivers, many do not use digital tools. The Olera platform was developed to be an easily adoptable web-based support tool, connecting caregivers with long-term services and supports, financial assistance, and educational resources. The platform was developed based on the Build-Measure-Learn framework with input from caregiver needs assessments and usability studies. Objective: This study aims to evaluate the quantitative and qualitative feedback of informal caregivers of people living with dementia on the second iteration of the Olera platform. The primary objective was to assess caregivers’ acceptance of this caregiving platform. The secondary objective was to use qualitative methods to explore (1) the study cohort’s challenges in daily caregiving to determine and compare them with prior literature, (2) their experience when using the Olera platform, and (3) their attitudes toward integrating artificial intelligence in caregiver services for future studies and platform development. Methods: Caregivers were recruited through various sources and screened for eligibility through an initial survey. Participants used the platform for 4 weeks and completed a survey with an adapted Technology Acceptance Survey (TAS) and qualitative open-ended questions at the end of the testing period. TAS responses were summarized with descriptive statistics, while ANOVAs, tests, and linear regressions were used to compare the differences in the overall TAS scores by caregiver characteristics. Qualitative feedback data on the platform’s usefulness were analyzed via a thematic analysis framework approach. Results: A total of 65 caregivers in the United States completed the study, with a mean age of 59.9 (SD 9.8) years. The majority were female (61/65, 95.3%), non-Hispanic or Latino White (45/65, 69.2%), and the adult child of their care recipient (42/65, 64.6%). Evaluation of the Olera platform showed a high acceptance rate, with each TAS item scoring above 5.0 and an overall TAS score of 5.83 (SD 0.85) out of 7. Higher platform use frequency was associated with higher TAS ratings in technology acceptance (=7.88, <.001). Thematic analyses elicited the caregiving challenges, evaluation of the Olera platform, and feedback on artificial intelligence–assisted support. Conclusions: The Olera platform is an example of a beneficial web-based tool, though key features were requested to be included in the next iteration. Additionally, data supported prior findings regarding informal caregiver challenges and the insufficiency of conventional support mechanisms, indicating a need for more innovative digital solutions. Future research and development efforts using the Build-Measure-Learn approach are necessary to further iterate the platform’s key features, enhance the tool, involve more informal caregivers in its improvements, and serve as a model for customizable, person-centered online care support. International Registered Report Identifier (IRRID): RR2-10.2196/64127
Linguistic Fidelity and Classification Performance of Large Language Models for Generating Synthetic Operative Notes: Evaluation Study
Background: Machine learning models for surgical applications require large, diverse datasets; however, data scarcity remains a critical limitation due to privacy regulations, institutional variability, and the rarity of many surgical procedures. Large language models (LLMs) offer a potential solution through synthetic data generation, but their performance and reliability in specialized surgical domains remain underexplored. Objective: This study aimed to evaluate the linguistic fidelity of LLM-generated operative notes for cleft lip and palate procedures and to assess their impact on natural language processing classifier performance under varying data availability conditions. Methods: A total of 630 authentic operative notes were obtained from cleft procedures (86 primary cleft lip repairs, 101 primary cleft palate repairs, and 62 primary alveolar bone grafting [ABG] procedures) performed between 2013 and 2024. GPT-4o generated matched synthetic notes using multishot prompting with anonymized examples. Linguistic fidelity was evaluated using BERTScore for semantic similarity, Jensen-Shannon divergence of part-of-speech trigrams for syntactic structure, and Bilingual Evaluation Understudy (BLEU) scores for lexical overlap. Binary classifiers using ClinicalBERT embeddings and logistic regression were trained under both full data and data-scarce (retaining 5% or 10% of positive training cases while retaining the full negative training set) conditions, with and without synthetic augmentation at approximate ratios of synthetic to real notes (1:1, 2:1, 5:1, and 10:1). Results: Synthetic notes demonstrated high semantic fidelity across all procedures (BERTScore -score: 0.86‐0.88) and low syntactic divergence (Jensen-Shannon divergence: 0.06‐0.08). BLEU scores indicated moderate lexical variation (0.14‐0.19), reflecting distinct but contextually consistent phrasing. With full datasets, synthetic augmentation did not meaningfully affect classifier performance. Under data-scarce conditions retaining 5% of positive training cases while preserving the full negative training set, the area under the curve improved from 0.915 (SD 0.056) to 0.929 (SD 0.033) for cleft lip and from 0.935 (SD 0.036) to 0.949 (SD 0.033) for cleft palate, with smaller gains for ABG (mean 0.983, SD 0.014 to mean 0.987, SD 0.015). When retaining 10% of positive training cases, performance changes were minor across procedures (cleft lip: mean 0.952, SD 0.036 to mean 0.948, SD 0.028; cleft palate: mean 0.945, SD 0.044 to mean 0.956, SD 0.036; and ABG: mean 0.989, SD 0.008 to mean 0.985, SD 0.012). Conclusions: LLM-generated operative notes exhibit strong semantic and syntactic fidelity to authentic documentation and can enhance model performance in a task-dependent manner when authentic data are limited. These findings suggest that synthetic data generation may address data scarcity challenges in specialized surgical domains, particularly for rare or underrepresented procedures, enabling robust machine learning model development.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/3f3ea2f32d3d41246da633a50d5c7ff4" />
Automatic Speech Recognition and Acoustic Analysis for Dysarthria Assessment in Telerehabilitation: User-Centered Design and Usability Study
Background: Dysarthria is a frequent motor speech disorder following a stroke, affecting up to 42% of survivors and resulting in reduced speech intelligibility and diminished quality of life. Clinical assessments, such as the Frenchay Dysarthria Assessment, Second Edition (FDA-2), rely heavily on the subjective judgment of speech-language pathologists (SLPs), which limits comparability and scalability. Telepractice solutions have the potential to extend access to care, but validated digital tools that combine automatic analysis with clinically usable interfaces remain scarce. Objective: This study aimed to develop and evaluate a web-based application that integrates automatic speech recognition (ASR) and acoustic analysis into a user-centered dashboard for SLPs. Specifically, we investigated: (1) whether ASR can provide intelligibility scores comparable to those of human listeners; (2) the usability of the system in 2 iterative cycles with SLPs; and (3) the feasibility of presenting clinically relevant acoustic features to support telerehabilitation. Methods: A user-centered design process was followed, involving contextual inquiry, requirements gathering, prototype development, and iterative testing with SLPs. The analytical core of the prototype included an ASR module (Whisper Large-v3) to compute intelligibility scores, combining word error rate–based accuracy with sentence-level and word-level alignment. Phoneme-level error highlighting was implemented to identify frequent substitution or deletion patterns. In parallel, an acoustic module extracted clinically relevant measures, including fundamental frequency (mean and range), intensity (mean and variability), and vowel formants (F1–F2 space), supplemented by sustained phonation duration. A pilot validation compared ASR-based intelligibility scores with transcriptions from 8 lay listeners for 3 patients with dysarthria performing the Frenchay Dysarthria Assessment–2 word and sentence tasks. Usability was evaluated in 2 cycles with 8 and 4 SLPs, respectively, using the System Usability Scale and structured questionnaires. Results: In the pilot validation, ASR performance was comparable to, and in some cases better than, untrained human listeners for individuals with mild and moderate dysarthria, though performance declined with severe cases. Both usability cycles yielded excellent System Usability Scale scores (cycle 1: mean 88.4, SD 4.6; cycle 2: mean 91.7, SD 4.1). Core workflow elements, including navigation, session upload, and intelligibility score presentation, were consistently rated highly. Feedback evolved from bug reports and requests for clearer terminology in cycle 1 to suggestions for advanced analytic features in cycle 2, such as additional voice-quality indices and integrated note-taking. Conclusions: The prototype demonstrates that automatic intelligibility scoring and acoustic analysis can be integrated into a clinically usable, web-based dashboard. While current limitations include reliance on English-only phoneme analysis, limited advanced acoustic features, and lack of regulatory compliance, the application achieved excellent usability and shows promise for scalable telerehabilitation. Future work should expand multilingual support, incorporate additional acoustic measures, and validate the tool in larger clinical cohorts.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/49585758e826cc9217603b3b543a5cc4" />
Digital Cognitive Behavioral Therapy for Older Adults With Symptoms of Depression: Feasibility Cohort Study
Background: Depressive symptoms are common among older adults and can significantly impact their quality of life. However, many older adults face barriers to accessing psychological treatment. Internet-based cognitive behavioral therapy (iCBT) is a promising alternative to face-to-face treatments, but its feasibility among older adults has been less extensively studied than in adult populations. Objective: This study evaluated the feasibility of guided iCBT for adults aged 55 years and older with mild to moderate depressive symptoms recruited from the general population. Methods: This study is a feasibility study with a single-group, pretest-posttest design (n=21), in which all participants received guided iCBT for 8 weeks. Assessments were conducted at baseline (T0) and after the intervention (T1). The primary outcome was feasibility, conceptualized as satisfaction, usability, engagement, and uptake of iCBT. Secondary outcome measures included depression severity, working alliance, and technical alliance. Results: Participants were mostly highly educated (13/21, 61.9%), female (18/21, 85.7%), had an average age of 59.85 (SD 4.19; range 55-68) years, and reported moderate digital literacy. Feasibility outcomes indicated high satisfaction and engagement and moderate usability. Working alliance was rated as good by both participants and coaches, and technical alliance was rated as moderate by the participants. There was a nonsignificant modest decrease in depressive symptoms (Cohen <i>d</i>=0.47). Of the 20 participants who started the intervention, all completed the first 2 modules, but completion declined across the remaining 6 modules, with only 1 (5%) participant completing all modules. Conclusions: This study found that guided iCBT has the potential to be a feasible option for older adults experiencing depressive symptoms, with participants reporting generally positive satisfaction, moderate engagement, and a moderate therapeutic bond with their coaches. However, below-average usability ratings and a moderate technical alliance suggest that some aspects of the platform require improvement. Future research should focus on improving usability and adherence, as well as testing the intervention in a larger and more diverse population.
A device that revives eyeballs from dead donors could make eye transplants possible
It’s not easy to transplant a whole human eye. The surgery is difficult. And the eyes themselves start to degenerate as soon as they’ve left the body. When surgeons attempted it a few years ago, the newly-transplanted eye wasn’t able to see.
But researchers believe they might have a solution: a device that maintains and revives freshly removed eyeballs using a technique called perfusion. Perfusion works by providing surgically-removed organs with some of the oxygen and nutrients they typically get when they’re inside a body. Treated eyes don’t degrade as quickly, and appear to retain the ability to transmit electrical signals, and potentially see. The device could one day make eye transplantations a viable possibility.
“It’s really cool,” says Shannon Tessier at Massachusetts General Hospital, who was not involved in the research but studies perfusion of other organs. “It could be a new frontier for retina preservation.”
Pia Cosma at the Centre for Genomic Regulation at the Barcelona Institute of Science and Technology in Spain and her colleagues have spent years developing their device. The Eye-in-a-Care-Box (ECaBox), as they call it, delivers an oxygen-rich supply of fluid through the artery that normally supplies the eye with blood.
The eye itself sits on a “bed,” and excess fluids are drained away. And while the device itself is sealed to maintain a specific temperature and pressure, a clear window on its side allows researchers to study and image the eye while it’s inside.
Cosma and her colleagues started experimenting with pig eyes, which are anatomically similar to human eyes but easier to get hold of (the team got theirs from a local slaughterhouse).
Pig eyes that are kept at room temperature outside of the device start to degenerate pretty quickly. The team found that cells in the eye shrank, and the eyes started to lose their structure. Cooling the organs didn’t help preserve them, either—the eyes degenerated within 24 hours even when they were kept at 4°C (39°F).
But eyes kept in the EcABox fared much better. 24 hours later, tests suggested the prefused eyes were “significantly more viable” than eyes that hadn’t been maintained in the device.
The perfused eyes also seemed to be able to respond to light, suggesting they might technically be able to see if they were transplanted. Untreated pig eyes lost this ability as soon as they were removed from the animal. But it came back after about 15 minutes of perfusion, according to the scientists behind the work. A few of the treated eyes kept going for 10 hours or more.
Cosma and her colleagues described the work in a preprint article that has not yet been peer reviewed, and did not want to comment on the work.
After success with the pig eyes, the team members then tested their device on human eyes. They first collected 12 eyes from six people who had died. In each case, one of each pair of eyes was put in the device, while the other was not. Again, the perfused eyes did better—and their retinas were preserved.
Cosma and her colleagues hope that their device could offer scientists a new way to study eye treatments—one that doesn’t involve experimenting on living animals. They also hope that, with some improvements, the ECaBox might provide a way to maintain and revive donated human eyes for whole-eye transplantation.
Whole-eye transplants have been attempted in the past, mostly in research animals, with limited success. In May 2023, a team at NYU Langone transplanted an eye along with part of a face to a man who had survived a high-voltage electrical accident that resulted in the loss of much of the left side of his face, including his left eye, two years earlier. Although the man recovered well, he wasn’t able to see out of the transplanted eye.
We won’t know whether eyes treated in the ECaBox could do any better until they have been transplanted, says Tessier.
In the meantime, Cosma and her colleagues plan to use a newer version of their device to collect more human eyes for research. “We are planning to develop a portable, surgery-room ECaBox to minimize [degradation] in heart-beating donor eyes, when they become available,” they write.
Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study
Background: In recent years, artificial intelligence (AI) has ushered in a promising era in medicine, particularly in medical education. However, studies assessing the knowledge, attitudes, and practices related to AI among medical students in Vietnam remain limited. Objective: This study aimed to evaluate AI knowledge, attitudes, and practices among Vietnamese medical students in learning and research, and to identify factors associated with their AI practices. Methods: A cross-sectional study was conducted among medical students at Thai Binh University of Medicine and Pharmacy from November to December 2025. Data were collected using an online structured questionnaire covering demographic characteristics and AI knowledge, attitudes, and practices. The main outcome of interest was AI practices in learning and research. Descriptive statistics and multivariable linear regression were used to examine associated factors. Regression coefficients (β), 95% CIs, and values are reported. Results: A total of 1002 medical students (mean age 21.00, IQR 19.00-23.00 years; n=596, 59.5% female) were included. The median percentage of maximum possible (POMP) score of AI knowledge was 66.67 (IQR 33.33‐83.33), with a high level of familiarity with common tools (n=798, 79.6%). AI attitudes were generally positive (median POMP score 70.00, IQR 53.33‐76.67). AI-related practices were lower (median POMP score 50.00, IQR 46.88-71.88), with AI being used primarily for information retrieval and literature research support. In the multivariable analysis, knowledge POMP score (β=0.12, 95% CI 0.08-0.16) and attitudes POMP score (β=0.42, 95% CI 0.34-0.51) were significantly associated with AI practices POMP score (<.001). Age, gender, major, grade point average classification, and having participated in an AI seminar or training were not associated with AI practices. Conclusions: Medical students showed favorable knowledge and positive attitudes, but their AI practices remained limited. Integrating AI into medical curricula, including fundamentals, applications, and ethical aspects, is essential to prepare future physicians for AI-driven health care.
High-altitude hypoxic cues and cerebral ischemic tolerance: an evidence-graded translational framework for stroke research
High altitude exposes the brain to heterogeneous hypoxic, hemodynamic, rheological, inflammatory, and healthcare-access conditions. This heterogeneity makes altitude biologically informative for stroke research, but it does not justify treating natural altitude exposure as a single protective or harmful state. In this structured narrative review, we searched and organized the literature to ask which altitude-associated hypoxic cues resemble or reveal mechanisms compatible with cerebral ischemic tolerance, and what level of evidence supports that claim. We separate long-term adaptation, short-term acclimatization, chronic or excessive environmental hypoxia, and experimental hypoxic conditioning; define direct, supportive, and indirect evidence tiers; and integrate neurovascular-unit biology with multi-omics and stroke pathophysiology. Experimental hypoxic preconditioning remains the clearest direct evidence that a defined sublethal hypoxic stimulus can induce a time-limited tolerant state. In contrast, human high-altitude epidemiology, physiology, and genetics mainly constrain the clinical context and nominate candidate pathways rather than prove stroke-specific protection. We also emphasize that chronic hypoxia can be maladaptive through endothelial dysfunction, oxidative stress, erythrocytosis, thrombogenicity, blood–brain barrier impairment, and microvascular injury. Across neurovascular-unit cell types, a transparent evidence-weighting framework prioritizes endothelial biology because of its direct connection to BBB stability, effective reperfusion, hemorrhagic transformation risk, and no-reflow, while neurons, astrocytes, microglia, oligodendrocyte-lineage cells, and pericytes require different degrees of causal and human validation. We argue that the most productive path forward is not to label altitude as protective, but to use altitude-related biology to prioritize testable, stroke-facing hypotheses regarding BBB stability, microvascular patency, metabolic support, inflammatory thresholds, white-matter resilience, and biomarker-defined conditioning windows.
Synaptic output from suprachiasmatic nucleus cholecystokinin neurons regulates locomotor rhythmicity
BackgroundThe mammalian suprachiasmatic nucleus (SCN) serves as the master circadian pacemaker, which coordinates daily behavioral and physiological rhythms through functionally diverse neuronal subtypes. Cholecystokinin (CCK) is expressed in a subset of SCN neurons; however, its role in locomotor activity rhythms remains poorly understood.MethodsTo study the functional contribution of SCN CCK-expressing (SCNCCK) neurons, we selectively blocked synaptic transmission by injecting a Cre-dependent tetanus toxin (TeNT) viral vector into the SCN of CCK-IRES-Cre mice. Before and after the virus injection, spontaneous locomotor activity was continuously recorded under a 12:12 h light–dark (LD) cycle. Subsequently, we used Cre-dependent fluorescent reporter (mYongHong) to label SCNCCK neurons and performed whole-brain projection mapping to characterize their downstream connectivity.ResultsSynaptic inhibition of SCNCCK neurons significantly attenuated the strength of locomotor rhythmicity, resulting in reduced rhythm organization and a more uniform distribution of activity. This disruption was mainly driven by a significant decrease in dark-phase locomotor activity, while light-phase activity remained unchanged. Anatomically, SCNCCK neurons are widely projected along the anterior and posterior axes to multiple hypothalamic, thalamic, and limbic regions, including the medial preoptic area (MPA), paraventricular thalamic nucleus (PVT), paraventricular hypothalamic nucleus (PVH), anterior hypothalamic area (AHC), dorsomedial hypothalamic nucleus (DMH), ventromedial hypothalamic nucleus (VMH), and medial amygdala nucleus (MeA). Quantitative analysis revealed projections to these downstream regions, with moderate variation in projection density across targets.ConclusionTogether, these findings identify SCNCCK neurons as an important neuronal subpopulation, which contributes to the robustness and consolidation of spontaneous locomotor rhythms, likely through a wide range of downstream circuits.
Focal volume, steering, and aberration correction in transcranial focused ultrasound: reconsidering the tradeoffs between single-element transducers, phased arrays, and acoustic holograms
Transducer architecture is an increasingly important design consideration in transcranial focused ultrasound, where focal precision, electronic steering, skull-aberration correction, workflow complexity, and cost must be balanced. Under matched aperture, transmit frequency, focal depth, effective source geometry, and equivalent aberration correction, subdividing an aperture into multiple independently driven elements does not by itself reduce the diffraction-limited focal volume. Phased arrays provide important capabilities that single-element transducers generally lack, including electronic steering, dynamic phase correction, and flexible control of energy deposition. These capabilities can improve the realized intracranial field, particularly when skull-induced aberrations would otherwise broaden, shift, or split the focus. Single-element systems may also be extended through patient-specific acoustic holograms or lenses, which impose spatially varying phase delays to compensate for aberrations, steer the focus, or shape the pressure field. These approaches may reduce system complexity but are typically static and less adaptable than phased arrays. We therefore frame transducer selection as an application-driven design-matching problem: the relevant question is not which architecture is inherently “more focused” under matched conditions, but which best meets a study’s requirements for steering, skull-aberration correction, temporal reconfigurability, spatial degrees of freedom, workflow burden, cost, positioning robustness, and safety.