Anxiety-Free Public Dentistry for Adults With Disabilities by Using Head-Mounted Virtual Reality Technology: Protocol for a Feasibility Mixed Methods Study.

Background Learning and applying anatomy are essential but are studied and done through 2D tools and imaging techniques. This study aims to verify the usefulness of an additional 3D technique and ensure an improvement in the visualization of anatomical structures and pathological findings. Objective The study aims to examine the usefulness of virtual reality (VR) technology as an additional tool in medical diagnostics. Groups of students, residents, and specialists in surgery, radiology, and internal medicine evaluated magnetic resonance imaging (MRI) by answering a multiple-choice questionnaire. Subsequently, a virtual 3D display was used for processing. The questionnaire focused on topographical conditions and the transfer of academic knowledge into clinical application. The main objective was to determine anatomical understanding in a comparison between sectional image (2D) presentation and additional VR (3D) presentation, measured through correctly answered questions and processing time. The system usability scale (SUS) was integrated as another criterion for VR usability. Methods The cross-over study assessed 63 participants regarding their knowledge of liver anatomy and pathologies based on an interindividual comparison. Group formation according to the respective level of medical training was as follows: students (n=35), residents (n=15), and specialists (n=13). Participants answered 25 multiple-choice questions first using sectional imaging (MRI) in a 2D environment (computer screen) and afterward with the respective segmented 3D model visualized in a VR simulation. The main criteria for the analyses were the number of correctly answered questions and processing time. A customized SUS was used to analyze VR usability. Missing data analysis showed that there were no accounted missing data. Results The rate of correct answers improved significantly with the additional use of VR (F1,59=314.376; P<.001). Using MRI, a significant difference was observed between students and residents (P=.04) and between students and specialists (P<.001). In the VR condition, no significant differences between groups were found. In the MRI condition, significant differences in processing time were observed between students and specialists (P=.02) and between residents and specialists (P=.04). No differences existed between students and residents. With VR, processing time decreased significantly in all groups (F1,59=280.700; P<.001). Significant differences between students and specialists (P=.02) and between students and residents (P=.004) remained. No notable differences between residents and specialists (P=.72) were found. The SUS showed a subjectively simplified answerability of the questions with additional use of VR. The usefulness and benefits for an additional use of VR were stated. Conclusions The additional use of VR suggests statistically significant improvements across all groups. VR seems to enable students and residents to participate in diagnostics and create treatment plans at an early stage. Transferred to clinical practice, this may lead to improvement in diagnostics and interventions. The lack of randomization and a potential learning effect are the main limitations to be addressed in future studies.

In dentistry comparative studies of diffusion of disease preventive innovations are rare and usually atheoretical. For these reasons the present study was designed 1) to determine whether or not normal distribution assumptions applied to decisions to adopt caries preventive fluoride programs in a public dental service; 2) to compare rates of adoption of two school-based and one clinic-based fluoride program, and 3) to look for evidence indicating which type of decision-making may have been involved. The programs studied were school-based fluoride brushing 4-5 times per year, fluoride mouthrinsing at least once a month, and professional topical fluoride applications at least once a year. Data were collected by postal questionnaires from public dental officers in Norway in 1972, 1977 and 1982. To determine the length of time which had elapsed from the time of innovation of the technologies to adoption, the dental literature was reviewed. The adoption curves for school-based fluoride brushing and rinsing, as well as for clinic-based topical fluoride application did not comply with the normal distribution assumption. The time lapse from innovation to adoption was in excess of 10 yr and the rates of adoption differed between programs. Decision-making would appear to have been primarily individual or collective. It was concluded that generalization beyond the innovations studied and the social and organizational setting of this particular investigation is inadmissible. Consequently, there is a need for more and larger scale comparative analytical studies to increase our understanding of diffusion and adoption of innovations in dentistry.

IntroductionPost-stroke hand motor impairment is a major cause of long-term functional disability and reduced quality of life, with approximately 70% of stroke survivors experiencing persistent limitations in fine motor control. Conventional rehabilitation is constrained by low adherence, subjective assessment, and insufficient individualization, which limits exploitation of the neuroplasticity window for motor relearning. To address these challenges, we propose a bio–AI–VR integrated hand rehabilitation system that fuses biosignal sensing (bio), AI-based analysis, and virtual reality (VR) interaction to realize an efficient, adaptive, and quantifiable closed-loop training process. The integration rationale is grounded in three theoretical pillars: (i) multimodal data fusion theory—combining heterogeneous biosignal and behavioral data through AI to overcome single-modality limitations; (ii) closed-loop adaptive control theory—dynamically balancing challenge and capability via real-time feedback; (iii) neuroplasticity multisensory enhancement theory—coordinating visual, proprioceptive, and motor pathways to strengthen cortical reorganization. This work addresses three testable hypotheses: (RQ1) Can multimodal biosignal fusion achieve real-time assessment with and latency ms? (RQ2) Does bio-AI-VR integration yield FMA-UE improvement points (minimal clinically important difference) with effect size ? (RQ3) Are all three components (bio, AI, VR) necessary, with ablation causing performance degradation?MethodsA lightweight hand exoskeleton ( g, 3 DoF/finger) integrates a 6-axis IMU (100 Hz) and 16-channel sEMG (1 kHz) to synchronously acquire kinematics and muscle activation. Extended Kalman filtering fuses sensor streams before AI processing. Features include range of motion (ROM), smoothness metrics (SPARC, LDLJ), sEMG root-mean-square (RMS), median frequency (MDF), and co-contraction index (CCI). A hybrid model combining random forests (200 trees, depth 8) and support vector regression (RBF kernel, , ) outputs a real-time composite score via multi-task learning with GroupKFold cross-validation, mapped to clinical scales through Sigmoid normalization. FMA-UE proxy labels for window-level training were constructed via linear interpolation (80%), biomechanical anchoring (15%), and expert annotation (5%, inter-rater ). A cloud AI engine communicates bidirectionally with Unity-based VR over MQTT to close the perception-assessment-assistance loop. The assistance-as-needed (AAN) algorithm adjusts exoskeleton torque () and VR difficulty () using as control input with hysteresis, dead zone, and rate limiting to ensure smooth adaptation. Twenty-four stroke survivors (3–12 months post-stroke, FMA-UE 15–50) underwent 4-week training (5 sessions/week, 20 min/session). Outcomes included FMA-UE (primary), ARAT, grip strength, normalized ROM, task success rate, and System Usability Scale (SUS). Statistical analysis employed paired -tests with Hedges’ correction for effect sizes, Bonferroni adjustment for multiple comparisons, and leave-one-subject-out cross-validation (LOSOCV) to assess model generalization.ResultsAll 24 participants completed the study with one missed session (479 of 480 scheduled sessions, 8,946 annotated segments); end-to-end latency median 38 ms (IQR 33–42 ms), decomposed as: sampling ms, preprocessing ms, network ms, AI inference ms, control ms, command return ms. Offline model performance: (GroupKFold), MAE 3.2 points, Spearman with FMA-UE (); LOSOCV: ; test-retest ICC(2,1) 0.84 [0.76, 0.91]. AAN algorithm reduced assist torque (), increased VR difficulty (), improved task success ( pp). Clinical outcomes (paired -test): FMA-UE [6.7, 11.5], ; ARAT [5.2, 10.0], ; grip kg [2.5, 5.7], ; ; SPARC . Subgroup analysis: moderate-to-severe () showed greater FMA-UE gain ( vs in mild-to-moderate, ). Ablation experiments confirmed synergistic necessity: Bio only (, FMA-UE ), VR only (, ), Bio-AI (, , compliance 68%), complete system (, , compliance 88%). SUS ; no serious adverse events.DiscussionResults validate all three hypotheses: (i) multimodal fusion exceeded technical targets (, latency 38 ms ms); (ii) clinical efficacy surpassed MCID with large effect sizes (FMA-UE points, ), exceeding published spontaneous recovery rates (2–4 points); (iii) ablation experiments demonstrated degradation when removing any component, confirming non-additive synergistic effects of bio-AI-VR integration. Compared to recent brain-computer interface systems using EEG-based motor imagery, this approach achieves paradigm shift toward execution-based rehabilitation with direct motor intent capture and real-time physical feedback. The AAN control law elevates from low-level motion control to high-level rehabilitation strategy, spanning multiple temporal scales (window to course-level) and dual channels (physical assistance cognitive challenge). Limitations include single-arm design limiting causal inference, small sample size (), short intervention period (4 weeks), FMA-UE proxy construction via linear interpolation, and controlled clinical setting vs. real-world deployment. Future work requires larger RCTs with active control arms, extended follow-up (3–6 months), dense longitudinal assessments, exploration of deep learning architectures for temporal modeling, and validation in home-based telerehabilitation settings. The bio–AI–VR system demonstrates feasibility of data-driven, multimodal closed-loop rehabilitation, offering a wearable, low-latency, and personalized solution for post-stroke hand recovery that bridges the gap between laboratory innovation and clinical translation.

Purpose This study investigated undergraduate nursing students’ perceptions of integrating virtual reality (VR) technology into a community nursing course, specifically home and environmental patient safety assessments. Design This study used a mixed-methods approach with an explanatory design. Methods Participants were recruited from a community health course. The students engaged in a VR simulation involving home visits using the vizHome platform. Quantitative and qualitative data were gathered using the Technology Acceptance Model (TAM) and the System Usability Scale (SUS). Semi-structured interviews were conducted. Quantitative data were collected through Qualtrics and secure Zoom connections for the interviews. The data were analyzed with SPSS and MAXQDA. Findings The results indicated that participants perceived VR as valuable and easy to use for learning home assessment skills. The System Usability Scale (SUS) score revealed room for improvement. Technical limitations were identified as challenges that must be addressed to enhance the user experience. Conclusion Participants acknowledged VR’s potential to supplement traditional learning methods, providing safe and realistic exposure to diverse home environments. While VR was seen as beneficial, it was not considered a replacement for actual home visits in community nursing education. Clinical evidence This study provided clinical teaching evidence on the usability and student perceptions of VR in community courses.

BackgroundTelerehabilitation allows patients to engage in therapy away from healthcare facilities, often in the comfort of their homes. Studies have suggested that it can effectively improve motor and cognitive function. However, its applicability may be limited to patients with severe impairments who require physical assistance. The proposed study aims to evaluate the feasibility and effects of a home-based rehabilitation program for post-stroke patients, based on the use of a planar robot, able to overcome the limitations posed by the COVID-19 pandemic.MethodsWe enrolled 20 patients with stroke (11 men, aged 66.1 ± 9.2 years). Patients underwent 20 one-hour robotic upper limb rehabilitation sessions, consisting of the execution of planar point-to-point reaching exercises, using a robotic device in their own home, with the remote supervision of a physical therapist. We assessed the feasibility of this intervention by examining adverse events, patient satisfaction (measured on a Likert scale), usability (using the System Usability Scale, SUS), acceptability (evaluated through the Technology Acceptance Model questionnaire, TAM+), and pain onset (measured with the Numeric Rating Scale). To gauge the clinical effects of the treatment, we analyzed changes in the motor and sensory components of the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) before and after the intervention.ResultsThe approach was safe, as we did not observe any adverse events, and patients did not experience an increase in pain levels. Patients expressed their appreciation for the treatment, providing an average Likert scale score of 8 out of 10. The usability of the treatment received high marks, with an average SUS score of 78 ± 12. Similarly, the treatment acceptability was favorable, with all examined domains scoring above 4, indicating a positive attitude towards the proposed solution. Moreover, we observed a statistically significant improvement in the motor part of the FMA-UE (p < 0.001).ConclusionOur results demonstrate the feasibility, safety, and effectiveness of employing a rehabilitation robot for upper limb rehabilitation in post-stroke patients within a home-based environment. These findings mark a significant step in advancing innovative and easily accessible rehabilitation options for stroke survivors, ensuring uninterrupted care and creating new opportunities to enhance their functional abilities.Trial registrationclinicaltrial.gov (NCT05250934).

The development of Virtual Reality (VR) technology for competency assessment with multiple users is a breakthrough in the assessment of skills. The Multi-User Virtual Environment for Professional Certification Assessment (MUVE PCA) is a VR-based application that provides a VR experience to users. This study aimed to obtain information on the usefulness of the application and whether it can be accepted by users using the Virtual Reality System Usability Questionnaire (VRSUQ) and the System Usability Scale (SUS). Data collection was carried out by piloting the MUVE PCA application installed on the Oculus Head Mounted Device (HMD) to vocational school students, vocational school teachers, students, and lecturers in the field of Information Technology (IT) in computer network environments. The results showed a SUS score of 70.41, slightly above the global SUS standard, indicating that the system is considered acceptable. The average VRSUQ score of 3.52 is slightly below the standards, indicating that the system needs to be improved in some areas, especially in terms of convenience.

This research includes the study of the existing head-mounted display (HMD)enabled interface program and suggests improved interface scheme of HMD-enabled virtual reality (VR) games. The traditional keyboard and mouse based input schemes need to be replaced by user-friendly interface scheme such as the HMD. The higher the immersion degree of game users is expected, the less user intervention is desired to capture a user input and to give an output to users. For this reason, a user-centric VR environment has been built, where users’ motions such as turning head and raising hands are recognized as meaningful input to the system with the wellknown contact type, Hydra, and non-contact type, Kinect system. Especially, three multiple Kinects are arranged to improve the motion recognition rate. The proposed HMD interface not only aims to increase the degree of mutual interaction between game players and VR games, but also enhances usability of the HMD. Diverse users’ gestures are recognized in combination with newly suggested interfaces. The improved interfaces have been integrated with both representative testbed games which belong to action and sports genres. Action game has been developed and interfaced with non-wearable (non-contact) interface, whereas sports game has been integrated with both contact and non-contact interfaces. After then, the effectiveness and usability of the interface have been assessed according to the empirical evaluation scheme with modified system usability scale (SUS) statements. The SUS test result shows that the proposed interface enhanced the system usability as well as the system interactivity in terms of user satisfaction.

Virtual reality (VR) technology is increasingly employed in medical settings to provide innovative solutions for complex surgeries. In this study, we introduced and compared OpVerse, a multifunctional new VR platform developed for surgical simulations, with established software Synapse 3D to assess its efficacy in facilitating complex thoracic surgeries. Patient-specific VR digital twin thoracic models were created based on computed tomography scans of 9 patients with large thoracic neoplasms and 4 requiring tracheobronchial reconstruction. Twelve doctors as system testers were enlisted to evaluate the usability and user acceptance of OpVerse and Synapse 3D using the System Usability Scale (SUS) and the Technology Acceptance Model; they provided qualitative feedback through interviews. OpVerse achieved higher scores than Synapse 3D in SUS (73.3 ± 14.6 vs 53.8 ± 11.6, P = 0.0006), as well as perceived usefulness (4.5 ± 0.4 vs 4.1 ± 0.5, P = 0.0134), perceived ease of use (4.2 ± 0.4 vs 3.8 ± 0.6, P = 0.0364) and attitude towards using and behavioural intention to use (4.6 ± 0.4 vs 3.6 ± 0.7, P = 0.0002) in Technology Acceptance Model, compared to Synapse 3D, indicating enhanced efficiency and user engagement with the new system. Participants favoured OpVerse for its immersive qualities, intuitive interface (particularly rotation and enhanced visual transparency effects) and ability to enhance comprehension of complex 3D anatomical structures. OpVerse, our streaming VR simulation platform, enables the manipulation and visualization of patient-specific digital twin thoracic models through features such as rotation, enhanced visual transparency effects and measurement. Preliminary results suggest that OpVerse may offer advantages in terms of immersion, ease of use and understanding of 3D anatomical structures compared to Synapse 3D.

BackgroundTechnology-based assessments using 2D virtual reality (VR) environments and goal-directed instrumented tasks can deliver digital health metrics describing upper limb sensorimotor function that are expected to provide sensitive endpoints for clinical studies. Open questions remain about the influence of the VR environment and task complexity on such metrics and their clinimetric properties.MethodsWe aim to investigate the influence of VR and task complexity on the clinimetric properties of digital health metrics describing upper limb function. We relied on the Virtual Peg Insertion Test (VPIT), a haptic VR-based assessment with a virtual manipulation task. To evaluate the influence of VR and task complexity, we designed two novel tasks derived from the VPIT, the VPIT-2H (VR environment with reduced task complexity) and the PPIT (physical task with reduced task complexity). These were administered in an observational longitudinal study with 27 able-bodied participants and 31 participants with multiple sclerosis (pwMS, VPIT and PPIT only) and the value of kinematic and kinetic metrics, their clinimetric properties, and the usability of the assessment tasks were compared.ResultsIntra-participant variability strongly increased with increasing task complexity (coefficient of variation + 56%) and was higher in the VR compared to the physical environment (+ 27%). Surprisingly, this did not translate into significant differences in the metrics’ measurement error and test–retest reliability across task conditions (p > 0.05). Responsiveness to longitudinal changes in pwMS was even significantly higher (effect size + 0.35, p < 0.05) for the VR task with high task complexity compared to the physical instrumented task with low task complexity. Increased inter-participant variability might have compensated for the increased intra-participant variability to maintain good clinimetric properties. No significant influence of task condition on concurrent validity was present in pwMS. Lastly, pwMS rated the PPIT with higher usability than the VPIT (System Usability Scale + 7.5, p < 0.05).ConclusionThe metrics of both the VR haptic- and physical task-based instrumented assessments showed adequate clinimetric properties. The VR haptic-based assessment may be superior when longitudinally assessing pwMS due to its increased responsiveness. The physical instrumented task may be advantageous for regular clinical use due to its higher usability. These findings highlight that both assessments should be further validated for their ideal use-cases.

Article Figures and data Abstract Editor's evaluation Introduction Materials and methods Results Discussion Data availability References Decision letter Author response Article and author information Metrics Abstract Background: The risk of adult onset cardiovascular and metabolic (cardiometabolic) disease accrues from early life. Infection is ubiquitous in infancy and induces inflammation, a key cardiometabolic risk factor, but the relationship between infection, inflammation, and metabolic profiles in early childhood remains unexplored. We investigated relationships between infection and plasma metabolomic and lipidomic profiles at age 6 and 12 months, and mediation of these associations by inflammation. Methods: Matched infection, metabolomics, and lipidomics data were generated from 555 infants in a pre-birth longitudinal cohort. Infection data from birth to 12 months were parent-reported (total infections at age 1, 3, 6, 9, and 12 months), inflammation markers (high-sensitivity C-reactive protein [hsCRP]; glycoprotein acetyls [GlycA]) were quantified at 12 months. Metabolic profiles were 12-month plasma nuclear magnetic resonance metabolomics (228 metabolites) and liquid chromatography/mass spectrometry lipidomics (776 lipids). Associations were evaluated with multivariable linear regression models. In secondary analyses, corresponding inflammation and metabolic data from birth (serum) and 6-month (plasma) time points were used. Results: At 12 months, more frequent infant infections were associated with adverse metabolomic (elevated inflammation markers, triglycerides and phenylalanine, and lower high-density lipoprotein [HDL] cholesterol and apolipoprotein A1) and lipidomic profiles (elevated phosphatidylethanolamines and lower trihexosylceramides, dehydrocholesteryl esters, and plasmalogens). Similar, more marked, profiles were observed with higher GlycA, but not hsCRP. GlycA mediated a substantial proportion of the relationship between infection and metabolome/lipidome, with hsCRP generally mediating a lower proportion. Analogous relationships were observed between infection and 6-month inflammation, HDL cholesterol, and apolipoprotein A1. Conclusions: Infants with a greater infection burden in the first year of life had proinflammatory and proatherogenic plasma metabolomic/lipidomic profiles at 12 months of age that in adults are indicative of heightened risk of cardiovascular disease, obesity, and type 2 diabetes. These findings suggest potentially modifiable pathways linking early life infection and inflammation with subsequent cardiometabolic risk. Funding: The establishment work and infrastructure for the BIS was provided by the Murdoch Children's Research Institute (MCRI), Deakin University, and Barwon Health. Subsequent funding was secured from National Health and Medical Research Council of Australia (NHMRC), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women's Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Minderoo Foundation, the Ilhan Food Allergy Foundation, GMHBA, Vanguard Investments Australia Ltd, and the Percy Baxter Charitable Trust, Perpetual Trustees. In-kind support was provided by the Cotton On Foundation and CreativeForce. The study sponsors were not involved in the collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication. Research at MCRI is supported by the Victorian Government's Operational Infrastructure Support Program. This work was also supported by NHMRC Senior Research Fellowships to ALP (1008396); DB (1064629); and RS (1045161) , NHMRC Investigator Grants to ALP (1110200) and DB (1175744), NHMRC-A*STAR project grant (1149047). TM is supported by an MCRI ECR Fellowship. SB is supported by the Dutch Research Council (452173113). Editor's evaluation This paper provides data from a population-based cohort study on early life infection and proinflammatory, atherogenic metabolomic and lipidomic profiles at 12 months of age. The authors generated matched infection, metabolomics and lipidomics data from 555 infants in a pre-birth longitudinal cohort and they showed that frequent infant infections are associated with adverse metabolomic and lipidomic profiles. They also report that similar profiles are noted with higher glycoprotein acetyls (GlycA), but not hsCRP. The paper is interesting and assesses the role of infection and markers of inflammation on lipid and metabolic profile of patients. It provides a comprehensive analysis of lipids and metabolites in infants in response to infection. https://doi.org/10.7554/eLife.75170.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Infectious diseases are ubiquitous in infancy and childhood, with potential long-term impacts on health across the life course. Infection has been recognised as a potential contributor to atherosclerotic cardiovascular disease (CVD), one of the leading causes of adult morbidity and mortality, since the 19th century (Nieto, 1998). More recent adult studies link previous infection with long-term risks of disease (Bergh et al., 2017; Cowan et al., 2018; Wang et al., 2017). The mechanisms are largely unknown, but likely include immune activation and heightened inflammation (Shah, 2019), which are pathways central to CVD pathogenesis (Donath et al., 2019b; Ferrucci and Fabbri, 2018) and therefore offer potentially druggable targets in high-risk individuals (Donath et al., 2019a; Ridker et al., 2017). High-sensitivity C-reactive protein (hsCRP) has been extensively used as a marker of chronic inflammation in adult studies but is an acute phase reactant in children and may not reflect chronic inflammation in early life. Glycoprotein acetyls (GlycA) is a nuclear magnetic resonance (NMR) composite measure that is suggested to better reflect cumulative, chronic inflammation (Connelly et al., 2017). GlycA is an emerging biomarker for cardiometabolic risk (Connelly et al., 2017) that outperforms hsCRP as a predictor of CVD events and mortality (Akinkuolie et al., 2014; Duprez et al., 2016), and of infection-related morbidity and mortality (Ritchie et al., 2015). For example, in the Multi-Ethnic Study of Atherosclerosis (n = 6523), higher GlycA was associated with increased risk of incidence CVD and death, even after adjustment for hsCRP and other inflammatory markers. Conversely, prediction of these outcomes by hsCRP attenuated to null after mutual adjustment (Duprez et al., 2016). Cardiovascular and metabolic (cardiometabolic) disease pathogenesis begins in early life and accrues across the life course (Nakashima et al., 2008). Infections occur disproportionally in early childhood (Cromer et al., 2014; Grüber et al., 2008; Troeger et al., 2018; Tsagarakis et al., 2018), and there is a dose-response relationship between childhood infections, adverse cardiometabolic phenotypes (Burgner et al., 2015c), and CVD events (Burgner et al., 2015a) in adulthood. Infection is linked to proatherogenic metabolic perturbations in later childhood and adulthood (Feingold and Grunfeld, 2019; Khovidhunkit et al., 2000), including higher triglycerides and oxidised low-density lipoprotein (LDL), and lower high-density lipoprotein (HDL) cholesterol and apolipoprotein A1 (ApoA1) (Liuba et al., 2003; Pesonen et al., 1993), and to acute and chronic inflammation (Burgner et al., 2015b; Ritchie et al., 2015), but little is known about these relationships in early life, when most infections occur. We therefore aimed to characterise metabolomic and lipidomic profiles at 6 and 12 months of age and their relationship to infection burden during the first year of life. We also investigated the extent to which inflammation mediated the relationship between infection burden and metabolomic and lipidomic differences. Materials and methods Study cohort Request a detailed protocol This study used available data from 555 mother-infant dyads in the Barwon Infant Study (BIS), a population-based pre-birth longitudinal cohort (n = 1074 mother-infant dyads). The cohort details and inclusion/exclusion criteria have been detailed elsewhere (Vuillermin et al., 2015); in brief, mothers were eligible if they were residents of the Barwon region in south-east Australia and planned to give birth at the local public or private hospital. Mothers were recruited at approximately 15 weeks' gestation and provided informed consent. They were excluded if they were not a permanent Australian resident, aged <18 years, required an interpreter to complete questionnaires, or had previously participated in BIS. Infants were excluded if they were very preterm (<32 completed weeks gestation) or had a serious illness or major congenital malformation identified during the first few days of life. Ethics approval was granted by the Barwon Health Human Research Ethics Committee (HREC 10/24). Parent-reported infections Request a detailed protocol At the 4-week, 3-month, 6-month, 9-month, and 12-month time points following birth, mothers were asked to report each episode of infant illness or infection since the previous time point using standardised online questionnaires. The number of parent-reported infections from birth to 12 months was defined as the total number of respiratory tract infections, gastroenteritis, conjunctivitis, and acute otitis media episodes. In secondary analyses, numbers of parent-reported infections from birth to 6 months and from 6 to 12 months were considered. It was not possible to identify the proportion of parent-reported infections that lead to health service utilisation (Rowland et al., 2021). Other maternal and infant measures Request a detailed protocol Questionnaires during pregnancy and at birth were used to collect self-reported data on maternal age, household income, maternal education, and prenatal smoking (considered here as a dichotomous any/none exposure). Residential postcode was used to determine neighbourhood disadvantage using the Index of Relative Socio-Economic Disadvantage (IRSD) from the 2011 Socio-Economic Indexes for Areas (SEIFA) (Pink, 2013), with a lower score corresponding to greater socioeconomic disadvantage. Pre-eclampsia (based on International Association of Diabetes and Pregnancy Study Groups criteria; Tranquilli et al., 2014) and gestational diabetes (based on International Society for the Study of Hypertension in Pregnancy criteria; Nankervis et al., 2013) diagnoses were extracted from hospital records. Infant gestational age, birth weight, and mode of delivery (categorised as vaginal, planned caesarean section, or unplanned caesarean section delivery) were collected from birth records, and the age- and sex-standardised birth weight z-score was calculated using the 2009 revised British United Kingdom World Health Organisation (UK-WHO) growth charts (Cole et al., 2011). Postnatal smoking data was collected from questionnaire data, with mothers asked the average number of hours each day someone smoked near or in the same room as the child (Gray et al., 2019). This was dichotomised as any postnatal smoke exposure if >0 hr reported at any time point up to 12 months of age, or no postnatal smoke exposure. Breastfeeding duration up to 12 months of age was collected from maternal questionnaire data. As most evidence for the protective effect of breastfeeding on early life infection is from comparisons between any breastfeeding and no breastfeeding (Victora et al., 2016), and in light of previous evidence in BIS for an association between even a short duration of breastfeeding and lower odds of infection in early infancy (Rowland et al., 2021), we first looked at breastfeeding as a binary (any/none) measure in models (presented in the main text). As most infants (98.2%) were breastfed to some extent, and it is unknown the degree to which breastfeeding, and the timing of breastfeeding, might affect infant metabolomics and lipidomics, we also considered duration of breastfeeding as a continuous variable for sensitivity analyses. Metabolomic and lipidomic profiling Request a detailed protocol Venous peripheral blood was collected from infants at the 6- and 12-month time points in sodium heparin and generally processed within 4 hr, with a minority (197 of 555) of 12-month samples processed after 4 hr (median time for those 197 samples = 19.9 hr, inter-quartile range [IQR] [18.7, 21.4]). The time interval between collection and post-processing storage of samples was included as a covariate in analyses. Due to the bimodal distribution of 12-month sample collection times as samples were either processed same day of collection or the following day, sensitivity analysis excluding participants with a plasma storage time greater than 4 hr (197 out of 555 infants, predominantly processed the following day) was performed, as described in the Statistical analysis section below. Plasma was stored at –80°C, and aliquots were shipped on dry ice to Nightingale Health (Helsinki, Finland) for NMR metabolomic quantification and Baker IDI (Melbourne, Australia) for liquid chromatography/mass spectrometry (LC/MS) lipidomic quantification, as described below. For secondary analyses investigating possible 'reverse causality', that is, whether metabolomic or lipidomic profile at birth was associated with number of parent-reported infections from birth to 6 months of age, metabolomics and lipidomics data using the same platforms from venous cord blood collected at birth, as previously described (Burugupalli et al., 2022; Mansell et al., 2021), was used. The NMR-based metabolomics platform has been described in detail (Kettunen et al., 2016; Soininen et al., 2015), and quantified a broad range of metabolic measures including lipoprotein size subclasses, triglycerides, cholesterols, fatty acids, amino acids, ketone bodies, glycolysis metabolites, and GlycA. In brief, plasma samples were mixed with a sodium phosphate buffer prior to NMR measurements with Bruker AVANCE III 500 MHz and Bruker AVANCE III HD 600 MHz spectrometers (Bruker, Billerica, MA). Samples were kept at 6°C using the SampleJet sample changer (Bruker) to prevent degradation. After initial measurements, samples went through a multiple-step lipid extraction procedure using saturated sodium chloride solution, methanol, dichloromethane, and deuterochloroform. The lipid extracts were then analysed using the 600 MHz instrument (Soininen et al., 2015). The utility of this platform in epidemiological research has been detailed elsewhere (Würtz et al., 2017). Using the Nightingale Health 2016 bioinformatics protocol, 228 metabolomic measures were generated for the 12-month samples. From a subset of participants, replicate samples were quantified, and these showed a low percentage coefficient of variation (<10%). Subsequently, the Nightingale Health 2020 bioinformatics protocol was used to generate 250 metabolomic measures for the 6-month samples, with 224 of these measures also present in the 12-month data. As a large proportion of the NMR metabolomic measures are ratios and are strongly correlated with each other in children and adults (Ellul et al., 2019), an informative subset of 51 measures that captured the majority of variation in the metabolomic dataset, primarily absolute metabolite concentrations, were included in analysis presented in the main text. Analyses for excluded metabolomic measures are presented as supplementary data. To complement GlycA as a measure of inflammation, hsCRP was also quantified in 6- and 12-month plasma using enzyme-linked immunosorbent assay (ELISA) (R&D Systems, Minneapolis, MN, cat. no. DY1707), as per the manufacturer's instruction. The details of the high-performance LC/MS lipidomics platform have been described elsewhere (Beyene et al., 2020). In addition, we used medronic acid to passivate the LC/MS system to avoid peak tailing for acidic phospholipids (Hsiao et al., 2018). In brief, this platform quantified 776 lipid features in 36 lipid classes, including sphingolipids, glycerophospholipids, sterols, glycerolipids, and fatty acyls. Analysis was performed on an Agilent 6490 QQQ mass spectrometer with an Agilent 1290 series high-performance liquid chromatography system and two ZORBAX eclipse plus C18 column (2.1 × 100 mm 1.8 mm) (Agilent, Santa Clara, CA) with the thermostat set at 45°C. Mass spectrometry analysis was performed in both positive and negative ion mode with dynamic scheduled multiple reaction monitoring. Quantification of lipid species was determined by comparison to the relevant internal standard. Lipid class total concentrations were calculated as the sum of individual lipid species concentrations, except in the case of triacylglycerols (TGs) and alkyl-diacylglycerols, where we measured both neutral loss and single ion monitoring (SIM) peaks, and subsequently used the SIM species concentrations for summation purposes. Statistical analysis Request a detailed protocol Analyses were performed in R (version 3.6.3) (R Development Core Team, 2018). All metabolomic and lipidomic measures had their lowest observed non-zero value (considered the lower limit of detection) added to their value before they were natural log-transformed and scaled to a standard distribution (standard deviation units). Pearson's correlations were calculated for number of infections from birth to 12 months with 12-month GlycA and hsCRP. The estimated effect of number of parent-reported infections from birth to 12 months as an exposure on 12-month metabolomic and lipidomic profile was investigated using linear regression models for each metabolomic/lipidomic measure. Standard errors were used to calculate 95% confidence intervals for estimated effects. All models were adjusted for infant sex, exact age at 12-month time point, birth weight z-score, gestational age, maternal household income, exposure to maternal smoking during pregnancy, breastfeeding, and time from collection to storage for the plasma sample. Linear regression models adjusted for the same covariates were used to investigate 12-month GlycA and hsCRP as exposures and each metabolomic/lipidomic measure as an outcome. Two-tailed p-values were adjusted for multiple comparisons within each dataset (NMR metabolomics, LC/MS lipidomic species, and LC/MS lipidomic classes) using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995). To investigate the robustness of the estimates, mean model coefficients and bias-corrected accelerated percentile bootstrap confidence intervals were calculated from nonparametric bootstrap resampling (1000 iterations) using the 'boot' package (Davison and Hinkley, 1997) (version 1.3–25) in R, included in Source Data. The assumption of linearity was investigated post hoc using plots of residual values for the top 10 metabolomic and lipidomic differences (ranked by p-value) for each of number of infections, GlycA, and hsCRP. To further investigate the other sources of potential confounding and variation that could affect findings from the primary models, several sensitivity analyses were performed. These were: (i) additional adjustment of the primary model for postnatal smoking exposure, gestational diabetes, and pre-eclampsia; (ii) analyses excluding twins (five infants); (iii) analyses excluding infants with hsCRP >5 mg/L (24 infants) as a marker of acute infection (Lemiengre et al., 2018; et al., analyses excluding plasma samples with hr from collection to storage (197 and analyses for breastfeeding duration of any Analyses of the primary models adjusted for measures of socioeconomic or maternal of household were also considered. These models are presented as supplementary plots analyses to investigate 6-month of infections were performed. The birth to 6-month models investigated the relationship between infections up to 6 months of age, 6-month inflammation, and 6-month metabolomic/lipidomic The 6- to 12-month models investigated the relationship of infections between 6 and 12 months of age, 12-month inflammation, and 12-month metabolomic/lipidomic with adjustment for the corresponding 6-month For secondary analyses to investigate regression models et al., were either for (i) each metabolomic/lipidomic measure from cord blood at birth as exposure and total number of infections from birth to 6 months of age as or (ii) each 6-month metabolomic/lipidomic measures as exposure and total number of infections from 6 to 12 months of age as the with adjustment for number of infections from birth to 6 months of age. All secondary models were adjusted for the same covariates as the primary models described that is, infant sex, gestational age, exact age 6- or 12-month time birth weight z-score, maternal household income, exposure to maternal smoking during pregnancy, and sample time between collection and post-processing with birth metabolomic/lipidomic measures as the exposure were adjusted for mode of which is associated with differences across NMR metabolomic measures in cord in this cohort et al., 2021). To investigate the potential role of inflammation in mediating associations between infection and metabolic the package et al., 2017) (version in R was then used in a to the natural effect mediated by and natural effect by of infection. 12-month GlycA or hsCRP were considered as for the effect of number of infections from birth to 12 months of age on metabolomic and lipidomic differences at 12 months, for metabolomic and lipidomic measures associated with number of infections with an adjusted from the linear regression models described mediation was calculated as the estimated natural effect by the total effect effect plus natural of the mediation model is in for model investigated in this The natural effect by glycoprotein acetyls or C-reactive protein and natural effect mediated by of parent-reported infections on metabolomic and lipidomic measures were with adjustment for were considered to for associations to exposure to and to As models investigating described suggested that 6-month GlycA or lipidomic measures may number of infections from 6 to 12 months of age, we performed mediation analyses to the percentage mediation of 12-month GlycA and hsCRP for the effect of number of infections from 6 to 12 months of age on 12-month metabolomic and lipidomic with additional adjustment for the corresponding 6-month measures of infections from birth to 6 months of age, 6-month GlycA or and the 6-month metabolomic/lipidomic Results The for the 555 infants included in this study is in and the cohort for these infants are in The number of total parent-reported infections from birth to 12 months of age was = infections from birth to 6 months of age was 2 and infections from 6 to 12 months of age was 12-month hsCRP and GlycA were mg/L and number of parent-reported infections between birth and 12 months of age was more strongly correlated with 12-month GlycA = than hsCRP = The of metabolomic and lipidomic measures at each time point for the cohort are in and (n = age at delivery smoking during pregnancy diabetes (n = (n = household to to to to (n = than year 10 of 10 of or 12 of or of birth caesarean caesarean postnatal smoke exposure to 12 months (n = of duration to weeks age weight weight at 6-month time point at 6 months z-score at 6 at 12-month time point at 12 months z-score at 12 of parent-reported infections from birth to 12 Infections from birth to 6 Infection from 6 to 12 GlycA at 6 months at 6 months at 12 months at 12 months All = 555 infants had complete covariate data for primary models, data of secondary exposures is to the relevant measure. lower value greater socioeconomic disadvantage on 2 of Barwon Infant Study participants included this study participants had complete infection data from time points between birth and 12 months of age, and 12-month plasma nuclear magnetic resonance (NMR) metabolomics data. included participants (n = out of 555) had 12-month plasma liquid chromatography/mass spectrometry (LC/MS) lipidomics data. Infection and inflammation burden and plasma NMR metabolomic profile at 12 months was evidence for higher number of infections with higher inflammatory markers per infection, 95% and hsCRP lower HDL to to and to cholesterols, lower to lower to higher and to a extent with higher triglycerides and lower to In models with GlycA as the marker of inflammation metabolomic differences observed for higher GlycA were largely similar but more those for parent-reported including HDL per in GlycA to higher and lipoprotein to higher apolipoprotein higher total fatty higher total triglycerides and amino and lower to metabolites lower to and lower to were generally similar to standard regression for models. effect were generally similar across most sensitivity analyses excluding samples with time greater than 4 hr the of estimated of parent-reported infections on HDL and hsCRP was associated with lower HDL cholesterol per in to to and to and higher to as observed for GlycA, and with lower of most other amino and to and higher triglycerides with 2 in 12-month plasma nuclear magnetic resonance (NMR) metabolomic measures for each in parent-reported infection to 12 and for each in 12-month glycoprotein acetyls (GlycA) (n = plots of the estimated 12-month metabolomic differences for each additional parent-reported infection from birth to 12 months or 12-month GlycA from adjusted linear regression models, and the

With the development of virtual reality (VR) hardware in recent years, a number of industries have led a renewed interest in adopting VR in their fields. Virtual reality therapy (VRT) is one of the domains expecting the effective use of VR technologies because of their presence and vividness. In terms of art therapy, VR has the potential to facilitate creative artwork, not only for individuals but also for groups. However, in art therapy, we have limited knowledge of how to support user experiences, particularly in multi-user VR environments. This study aims to examine user-centred design requirements for successful multi-user VRAT system development. The research collected user-centred data from the perspectives of participants and therapists. The objective of the proposed system is to improve the social skills of teenagers through group VRAT. For data collection, therapists and teenagers were involved in a three-week VRAT session as a group by adopting a variety of research methods: video recording, subjective questionnaire based on five-point Likert scales, System Usability Scale (SUS) and in-depth interviews. As a result, it was found that a multi-user VRAT system can encourage individual creativity and provide new experiences through social interactions. On the other hand, the study points out that solely adding multi-user features to an existing VR drawing/painting application cannot achieve therapeutic goals.

Questionnaires are used for evaluating virtual, augmented, and mixed reality (MR) in healthcare. Utilizing the perfect one to meet the needs is a challenge for researchers and examiners. Hence, this study aimed to review and determine the frequently used questionnaires for evaluating mentioned services. The PubMed and Web of science databases were searched for conducting this review. Original observational and interventional studies that used a referenced questionnaire to evaluate virtual reality (VR), augmented reality (AR), and MR in healthcare were included. Data were analyzed using descriptive statistics. Totally, 179 studies were included in this research. The questionnaires are mostly used for evaluating usability (39%) and cybersickness (37.5%). System Usability Scale (28%), Simulator Sickness Questionnaire (27.5%), and Presence Questionnaire (9.5%) were the most used questionnaires. The use of special, need-based, and targeted questionnaires to evaluate the various outcomes of VR, AR, and MR can help in better evaluation of these services.

Aiming is key for virtual reality (VR) interaction, and it is often done using VR controllers. Recent eye-tracking integrations in commercial VR head-mounted displays (HMDs) call for further research on usability and performance aspects to better determine possibilities and limitations. This paper presents a user study exploring gaze aiming in VR compared to a traditional controller in an aim and shoot task. Different speeds of targets and trajectories were studied. Qualitative data was gathered using the system usability scale (SUS) and cognitive load (NASA TLX) questionnaires. Results show a lower perceived cognitive load using gaze aiming and on par usability scale. Gaze aiming produced on par task duration but lower accuracy on most conditions. Lastly, the trajectory of the target significantly affected the orientation of the HMD in relation to the target's location. The results show potential using gaze aiming in VR and motivate further research.

BackgroundResuscitative endovascular balloon occlusion of the aorta (REBOA) is a potentially life-saving procedure for bleeding trauma patients. Being a rare and complex procedure performed in extreme situations, repetitive training of REBOA teams is critical. Evidence-based guidelines on how to train REBOA are missing, although simulation-based training has been shown to be effective but can be costly and complex. We aimed to determine the feasibility and acceptance of REBOA training using a fully immersive virtual reality (VR) REBOA simulation, as well as assess the confidence in conducting the REBOA procedure before and after the training.MethodsProspective feasibility pilot study of prehospital emergency physicians and paramedics in Bern, Switzerland, from November 2020 until March 2021. Baseline characteristics of trainees, prior training and experience in REBOA and with VR, variables of media use (usability: system usability scale, immersion/presence: Slater-Usoh-Steed, workload: NASA-TLX, user satisfaction: USEQ) as well as confidence prior and after VR training were accessed.ResultsREBOA training in VR was found to be feasible without relevant VR-specific side-effects. Usability (SUS median 77.5, IQR 71.3–85) and sense of presence and immersion (Slater-Usoh-Steed median 4.8, IQR 3.8–5.5) were good, the workload without under-nor overstraining (NASA-TLX median 39, IQR 32.8–50.2) and user satisfaction high (USEQ median 26, IQR 23–29). Confidence of trainees in conducting REBOA increased significantly after training (p < 0.001).ConclusionsProcedural training of the REBOA procedure in immersive virtual reality is possible with a good acceptance and high usability. REBOA VR training can be an important part of a training curriculum, with the virtual reality-specific advantages of a time- and instructor-independent learning.

Current technology trend in providing a creative and exciting learning assistance range from augmented reality, virtual reality as well as mixed reality. Students demand innovative application to assist or complement their current learning resources. To date, students are still having problems when they learn history. Among the complaints included students easily feel bored and could not relate what they have learned from the textbook. SejarAR is a mobile application developed to solve high school students’ history learning experience. Before we can recommend this application to the students, several evaluations must be conducted to make sure the mobile application is usable, and its AR features does make an improvement to their learning experience. The evaluations which comprised of both formative and summative had been applied to SejarAR mobile application. The participants involved in both evaluations were the high school students and teachers. We allowed them to use SejarAR mobile application then interviewed as well as gave them the System Usability Scale (SUS) to evaluate SejarAR. As anticipated, it has scored 74 when used System Usability Scale (SUS), which means the SejarAR mobile application is deemed acceptable by high school students. We also received many positive feedbacks from qualitative evaluation approach that we conducted. To sum up, SejarAR mobile application is usable as well as enjoyable application for high school students to use as a tool to assist them in learning history subject.