Use of digital patient decision-support tools for atrial fibrillation treatments: a systematic review and meta-analysis.

OBJECTIVES: To assess the effects of digital patient decision-support tools for atrial fibrillation (AF) treatment decisions in adults with AF. STUDY DESIGN: Systematic review and meta-analysis. ELIGIBILITY CRITERIA: Eligible randomised controlled trials (RCTs) evaluated digital patient decision-support tools for AF treatment decisions in adults with AF. INFORMATION SOURCES: We searched MEDLINE, EMBASE and Scopus from 2005 to 2023.Risk-of-bias (RoB) assessment: We assessed RoB using the Cochrane Risk of Bias Tool 2 for RCTs and cluster RCT and the ROBINS-I tool for quasi-experimental studies. SYNTHESIS OF RESULTS: We used random effects meta-analysis to synthesise decisional conflict and patient knowledge outcomes reported in RCTs. We performed narrative synthesis for all outcomes. The main outcomes of interest were decisional conflict and patient knowledge. RESULTS: 13 articles, reporting on 11 studies (4 RCTs, 1 cluster RCT and 6 quasi-experimental) met the inclusion criteria. There were 2714 participants across all studies (2372 in RCTs), of which 26% were women and the mean age was 71 years. Socioeconomically disadvantaged groups were poorly represented in the included studies. Seven studies (n=2508) focused on non-valvular AF and the mean CHAD2DS2-VASc across studies was 3.2 and for HAS-BLED 1.9. All tools focused on decisions regarding thromboembolic stroke prevention and most enabled calculation of individualised stroke risk. Tools were heterogeneous in features and functions; four tools were patient decision aids. The readability of content was reported in one study. Meta-analyses showed a reduction in decisional conflict (4 RCTs (n=2167); standardised mean difference -0.19; 95% CI -0.30 to -0.08; p=0.001; I2=26.5%; moderate certainty evidence) corresponding to a decrease in 12.4 units on a scale of 0 to 100 (95% CI -19.5 to -5.2) and improvement in patient knowledge (2 RCTs (n=1057); risk difference 0.72, 95% CI 0.68, 0.76, p<0.001; I2=0%; low certainty evidence) favouring digital patient decision-support tools compared with usual care. Four of the 11 tools were publicly available and 3 had been implemented in healthcare delivery. CONCLUSIONS: In the context of stroke prevention in AF, digital patient decision-support tools likely reduce decisional conflict and may result in little to no change in patient knowledge, compared with usual care. Future studies should leverage digital capabilities for increased personalisation and interactivity of the tools, with better consideration of health literacy and equity aspects. Additional robust trials and implementation studies are warranted. PROSPERO REGISTRATION NUMBER: CRD42020218025.

Association of GRK5 variant rs10886471 with the therapeutic effect of repaglinide in patients of type 2 diabetes mellitus in Peshawar, Pakistan.

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder with a rising global prevalence. The primary objective of this study was to explore the relationship between the GRK5 variant (rs10886471) and the therapeutic effect of repaglinide in patients of T2DM in Peshawar, Pakistan. A quasi-experimental study was designed. The study group consisted of patients with Type 2 Diabetes Mellitus (T2DM) categorized into responders and non-responders based on their HbA1c level reduction in response to repaglinide treatment. After ethical approval, and consent from the participants, sociodemographic and clinical data was collected from 60 T2DM patients. Blood samples were collected followed by DNA extraction and quantification with UV-Vis Spectroscopy. Genotyping for the GRK5 variant rs10886471 was done using the PCR-based method. Among socio-demographic factors family history and BMI showed significant association (P<0.05) with the therapeutic response to repaglinide. The Statistical analyses, including chi-square tests and logistic regression of GRK5 variant rs10886471 exhibited a significant association with the therapeutic response. Variant allele exhibited significant association (OR: 1.2, p=0.049) with the therapeutic response to repaglinide. The study demonstrated a significant relationship between the GRK5 variant (rs10886471) and the therapeutic response to repaglinide in patients of T2DM of Peshawar, Pakistan.

Development of a new computer simulated environment to screen cognition: assessing the feasibility and acceptability of Leaf Café in younger and older adults.

BACKGROUND: Existing traditional cognitive screening tools for dementia have various limitations, including overreliance on tests assessing verbal memory and, to a lesser extent, on some aspects of executive functioning. Comprehensive neuropsychological assessment is sensitive to impairment but time-intensive and expensive. Virtual reality may provide a dynamic and unique understanding of cognitive performance and increase the ecological validity of cognitive assessment. The use of virtual reality in screening for cognitive function in older persons is promising, but evidence for its use remains sparse. OBJECTIVE: Our primary aim was to examine the feasibility and acceptability of a newly developed, virtual reality assessment module, 'Leaf Café', a computer-based program that assesses cognition in an engaging, efficient, and ecologically relevant way. The secondary aim was to assess the ability of the module to discriminate between performances of younger and older adults. METHODS: A cross-sectional study was carried out in Sydney, Australia, targeting adults aged 18 years and above. Participants completed a traditional cognitive screening tool (Telephone Interview for Cognitive Status-Modified, TICS-M) and Leaf Café, a low-immersive virtual reality module designed to evaluate learning and memory, perceptual-motor function, and executive functioning. The total performance score for each participant, ranging from 0 to 180, was correlated with their cognitive performance assessed by TICS-M, using Pearson's correlation coefficient. Following module completion, participants were presented with an open and closed-question survey to capture their perceptions, attitudes, and feedback on the module, encompassing practicality, acceptability, and enjoyment. Both descriptive and content analyses were employed to interpret the obtained data. RESULTS: A sample of 131 participants (mean age 54.9 years, SD = 20.8, range 20-85) took part. The majority were female (71.8%) and born in an English-speaking country (75.8%). The mean amount of time spent in the module was 32.8 min (SD = 13.3) with a mean module score of 107.6 (SD = 38.7). Most participants completed the highest level (5; 80.5%). There was a significant correlation between Leaf Café total scores with TICS-M cognitive scores overall, and for both younger (aged 18-64 years) and older adult (aged 65 + years) groups. No significant difference was found on performance between age groups on TICS-M performance, however, younger adults had significantly better performance on the Leaf Café module than older adults (M = 124.1 vs 95.9; p < .001). Participants had similar response proportions regarding user experience with most agreeing that the module was easy to use (84%) and to navigate (85%). Compared with younger adults, older adults had lower rates of agreement on the module's design (36.8% vs 64.3%; p = .020) and support experienced (20.5% vs 53.6%; p = .007). Participants highlighted the significance of practicality and the cognitive challenges presented by the module, in terms of memory strain and user interface concerns. Feedback encompassed different opinions on the usefulness of music, with suggestions for improvements centred around clearer instructions, varied game dynamics, and considerations for diverse user needs. CONCLUSIONS: Leaf Café is a feasible and acceptable tool to be used for screening for cognitive impairment in older adults and has real-world assessment value. Further verification on the game's utility in detecting cognitive impairment is required.

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis.

INTRODUCTION: Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes. METHODS: PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives. RESULTS: Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization. DISCUSSION: Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review.

BACKGROUND: Natural Language Processing (NLP) applications have developed over the past years in various fields including its application to clinical free text for named entity recognition and relation extraction. However, there has been rapid developments the last few years that there's currently no overview of it. Moreover, it is unclear how these models and tools have been translated into clinical practice. We aim to synthesize and review these developments. METHODS: We reviewed literature from 2010 to date, searching PubMed, Scopus, the Association of Computational Linguistics (ACL), and Association of Computer Machinery (ACM) libraries for studies of NLP systems performing general-purpose (i.e., not disease- or treatment-specific) information extraction and relation extraction tasks in unstructured clinical text (e.g., discharge summaries). RESULTS: We included in the review 94 studies with 30 studies published in the last three years. Machine learning methods were used in 68 studies, rule-based in 5 studies, and both in 22 studies. 63 studies focused on Named Entity Recognition, 13 on Relation Extraction and 18 performed both. The most frequently extracted entities were "problem", "test" and "treatment". 72 studies used public datasets and 22 studies used proprietary datasets alone. Only 14 studies defined clearly a clinical or information task to be addressed by the system and just three studies reported its use outside the experimental setting. Only 7 studies shared a pre-trained model and only 8 an available software tool. DISCUSSION: Machine learning-based methods have dominated the NLP field on information extraction tasks. More recently, Transformer-based language models are taking the lead and showing the strongest performance. However, these developments are mostly based on a few datasets and generic annotations, with very few real-world use cases. This may raise questions about the generalizability of findings, translation into practice and highlights the need for robust clinical evaluation.

Decoding type 2 diabetes mellitus genetic risk variants in Pakistani Pashtun ethnic population using the nascent whole exome sequencing and MassARRAY genotyping: A case-control association study.

Genome-wide association studies have greatly increased the number of T2DM associated risk variants but most of them have focused on populations of European origin. There is scarcity of such studies in developing countries including Pakistan. High prevalence of T2DM in Pakistani population prompted us to design this study. We have devised a two stage (the discovery stage and validation stage) case-control study in Pashtun ethnic population in which 500 T2DM cases and controls each have been recruited to investigate T2DM genetic risk variants. In discovery stage Whole Exome Sequencing (WES) was used to identify and suggest T2DM pathogenic SNPs, based on SIFT and Polyphen scores; whereas in validation stage the selected variants were confirmed for T2DM association using MassARRAY genotyping and appropriate statistical tests. Results of the study showed the target positive association of rs1801282/PPARG (OR = 1.24, 95%Cl = 1.20-1.46, P = 0.010), rs745975/HNF4A (OR = 1.30, 95%Cl = 1.06-1.38, P = 0.004), rs806052/GLIS3 (OR = 1.32, 95%Cl = 1.07-1.66, P = 0.016), rs8192552/MTNR1B (OR = 1.53, 95%Cl = 0.56-1.95, P = 0.012) and rs1805097/IRS-2 (OR = 1.27, 95%Cl = 1.36-1.92, P = 0.045), with T2DM; whereas rs6415788/GLIS3, rs61788900/NOTCH2, rs61788901/NOTCH2 and rs11810554/NOTCH2 (P>0.05) showed no significant association. Identification of genetic risk factors/variants can be used in defining high risk subjects assessment, and disease prevention.

Protocol for a pre-post, mixed-methods feasibility study of the Brain Bootcamp behaviour change intervention to promote healthy brain ageing in older adults.

INTRODUCTION: Behaviour change interventions represent key means for supporting healthy ageing and reducing dementia risk yet brief, scalable behaviour change interventions targeting dementia risk reduction in older adults is currently lacking. Here we describe the aims and design of the three-month Brain Bootcamp initiative that seeks to target multiple dementia risk and protective factors (healthy eating, physical, social and cognitive inactivity), through the use of multiple behaviour change techniques, including goal-setting for behaviour, information about health consequences and physical prompts to change behaviours that reduce dementia risk among older adults. Our secondary aim is to understand participants' views of dementia prevention and explore the acceptability and integration of this campaign into daily life. METHODS: Brain Bootcamp is a pre-post feasibility trial conducted in Sydney, Australia beginning in January 2021 until late August. Participants aged ≥65 years living independently in the community (n = 252), recruited through social media and flyers, will provide information about their demographics, medical history, alcohol consumption, smoking habits, mental health, physical activity, cognitive activity, and diet to generate a dementia risk profile at baseline and assess change therein at three-month follow-up. During the intervention, participants will receive a resource pack containing their individual risk profile, educational booklet on dementia risk factors and four physical items designed to prompt physical, social and mental activity, and better nutrition. Outcome measures include change in dementia risk scores, dementia awareness and motivation. A qualitative process evaluation will interview a sample of participants on the acceptability and feasibility of the intervention. DISCUSSION: This will be the first short-term multi-domain intervention targeting dementia risk reduction in older adults. Findings will generate a new evidence base on how to best support efforts targeting lifestyle changes and to identify ways to optimise acceptability and effectiveness towards brain health for older adults. TRIAL REGISTRATION NUMBER: ACTRN 381046 (registered 17/02/2021); Pre-results.

A personalized mobile app for physical activity: An experimental mixed-methods study.

Objectives: To investigate the feasibility of the be.well app and its personalization approach which regularly considers users' preferences, amongst university students. Methods: We conducted a mixed-methods, pre-post experiment, where participants used the app for 2 months. Eligibility criteria included: age 18-34 years; owning an iPhone with Internet access; and fluency in English. Usability was assessed by a validated questionnaire; engagement metrics were reported. Changes in physical activity were assessed by comparing the difference in daily step count between baseline and 2 months. Interviews were conducted to assess acceptability; thematic analysis was conducted. Results: Twenty-three participants were enrolled in the study (mean age = 21.9 years, 71.4% women). The mean usability score was 5.6 ± 0.8 out of 7. The median daily engagement time was 2 minutes. Eighteen out of 23 participants used the app in the last month of the study. Qualitative data revealed that people liked the personalized activity suggestion feature as it was actionable and promoted user autonomy. Some users also expressed privacy concerns if they had to provide a lot of personal data to receive highly personalized features. Daily step count increased after 2 months of the intervention (median difference = 1953 steps/day, p-value <.001, 95% CI 782 to 3112). Conclusions: Incorporating users' preferences in personalized advice provided by a physical activity app was considered feasible and acceptable, with preliminary support for its positive effects on daily step count. Future randomized studies with longer follow up are warranted to determine the effectiveness of personalized mobile apps in promoting physical activity.

Analyzing security issues of android mobile health and medical applications.

OBJECTIVE: We conduct a first large-scale analysis of mobile health (mHealth) apps available on Google Play with the goal of providing a comprehensive view of mHealth apps' security features and gauging the associated risks for mHealth users and their data. MATERIALS AND METHODS: We designed an app collection platform that discovered and downloaded more than 20 000 mHealth apps from the Medical and Health & Fitness categories on Google Play. We performed a suite of app code and traffic measurements to highlight a range of app security flaws: certificate security, sensitive or unnecessary permission requests, malware presence, communication security, and security-related concerns raised in user reviews. RESULTS: Compared to baseline non-mHealth apps, mHealth apps generally adopt more reliable signing mechanisms and request fewer dangerous permissions. However, significant fractions of mHealth apps expose users to serious security risks. Specifically, 1.8% of mHealth apps package suspicious codes (eg, trojans), 45.0% rely on unencrypted communication, and as much as 23.0% of personal data (eg, location information and passwords) is sent on unsecured traffic. An analysis of the app reviews reveals that mHealth app users are largely unaware of the surfaced security issues. CONCLUSION: Despite being better aligned with security best practices than non-mHealth apps, mHealth apps are still far from ensuring robust security guarantees. App users, clinicians, technology developers, and policy makers alike should be cognizant of the uncovered security issues and weigh them carefully against the benefits of mHealth apps.

Mobile health and privacy: cross sectional study.

OBJECTIVES: To investigate whether and what user data are collected by health related mobile applications (mHealth apps), to characterise the privacy conduct of all the available mHealth apps on Google Play, and to gauge the associated risks to privacy. DESIGN: Cross sectional study SETTING: Health related apps developed for the Android mobile platform, available in the Google Play store in Australia and belonging to the medical and health and fitness categories. PARTICIPANTS: Users of 20 991 mHealth apps (8074 medical and 12 917 health and fitness found in the Google Play store: in-depth analysis was done on 15 838 apps that did not require a download or subscription fee compared with 8468 baseline non-mHealth apps. MAIN OUTCOME MEASURES: Primary outcomes were characterisation of the data collection operations in the apps code and of the data transmissions in the apps traffic; analysis of the primary recipients for each type of user data; presence of adverts and trackers in the app traffic; audit of the app privacy policy and compliance of the privacy conduct with the policy; and analysis of complaints in negative app reviews. RESULTS: 88.0% (n=18 472) of mHealth apps included code that could potentially collect user data. 3.9% (n=616) of apps transmitted user information in their traffic. Most data collection operations in apps code and data transmissions in apps traffic involved external service providers (third parties). The top 50 third parties were responsible for most of the data collection operations in app code and data transmissions in app traffic (68.0% (2140), collectively). 23.0% (724) of user data transmissions occurred on insecure communication protocols. 28.1% (5903) of apps provided no privacy policies, whereas 47.0% (1479) of user data transmissions complied with the privacy policy. 1.3% (3609) of user reviews raised concerns about privacy. CONCLUSIONS: This analysis found serious problems with privacy and inconsistent privacy practices in mHealth apps. Clinicians should be aware of these and articulate them to patients when determining the benefits and risks of mHealth apps.

COVID-19 as 'Game Changer' for the Physical Activity and Mental Well-Being of Augmented Reality Game Players During the Pandemic: Mixed Methods Survey Study.

BACKGROUND: Location-based augmented reality (AR) games, such as Pokémon GO and Harry Potter: Wizards Unite, have been shown to have a beneficial impact on the physical activity, social connectedness, and mental health of their players. In March 2020, global social distancing measures related to the COVID-19 pandemic prompted the AR games developer Niantic Inc to implement several changes to ensure continued player engagement with Pokémon GO and Harry Potter: Wizards Unite. We sought to examine how the physical and mental well-being of players of these games were affected during the unprecedented COVID-19 restriction period as well as how their video game engagement was affected. OBJECTIVE: The aims of this study were to examine the impact of COVID-19-related social restrictions on the physical and mental well-being of AR game players; to examine the impact of COVID-19-related social restrictions on the use of video games and motivations for their use; and to explore the potential role of AR games (and video games in general) in supporting well-being during COVID-19-related social restrictions. METHODS: A mixed methods web-based self-reported survey was conducted in May 2020, during which COVID-19-related social restrictions were enforced in many countries. Participants were recruited on the web via four subreddits dedicated to Pokémon GO or Harry Potter: Wizards Unite. Data collected included quantitative data on demographics, time spent playing video games, physical activity, and mental health; qualitative data included motivations to play and the impact of video games on mental health during COVID-19 lockdown. RESULTS: We report results for 2004 participants (1153/1960 male, 58.8%, average age 30.5 years). Self-reported physical activity during COVID-19-related social restrictions significantly decreased from 7.50 hours per week on average (SD 11.12) to 6.50 hours (SD 7.81) (P<.001). More than half of the participants reported poor mental health (925/1766, 52.4%; raw World Health Organization-5 Well-Being Index score <13). Female gender, younger age, and reduced exercise were significant predictors of poor mental health. Participants reported a significant increase in video game play time from 16.38 hours per week on average (SD 19.12) to 20.82 hours (SD 17.49) (P<.001). Approximately three quarters of the participants (n=1102/1427, 77.2%) reported that playing video games had been beneficial to their mental health. The changes made to Pokémon GO and Harry Potter: Wizards Unite were very well received by players, and the players continued to use these games while exercising and to maintain social connection. In addition to seeking an escape during the pandemic and as a form of entertainment, participants reported that they used video games for emotional coping and to lower stress, relax, and alleviate mental health conditions. CONCLUSIONS: AR games have the potential to promote physical and mental health during the COVID-19 pandemic. Used by populations under isolation and distress, these games can improve physical and mental health by providing virtual socialization, sustained exercise, temporal routine, and mental structure. Further research is needed to explore the potential of AR games as digital behavioral interventions to maintain human well-being in the wider population.

Envisioning an artificial intelligence documentation assistant for future primary care consultations: A co-design study with general practitioners.

OBJECTIVE: The study sought to understand the potential roles of a future artificial intelligence (AI) documentation assistant in primary care consultations and to identify implications for doctors, patients, healthcare system, and technology design from the perspective of general practitioners. MATERIALS AND METHODS: Co-design workshops with general practitioners were conducted. The workshops focused on (1) understanding the current consultation context and identifying existing problems, (2) ideating future solutions to these problems, and (3) discussing future roles for AI in primary care. The workshop activities included affinity diagramming, brainwriting, and video prototyping methods. The workshops were audio-recorded and transcribed verbatim. Inductive thematic analysis of the transcripts of conversations was performed. RESULTS: Two researchers facilitated 3 co-design workshops with 16 general practitioners. Three main themes emerged: professional autonomy, human-AI collaboration, and new models of care. Major implications identified within these themes included (1) concerns with medico-legal aspects arising from constant recording and accessibility of full consultation records, (2) future consultations taking place out of the exam rooms in a distributed system involving empowered patients, (3) human conversation and empathy remaining the core tasks of doctors in any future AI-enabled consultations, and (4) questioning the current focus of AI initiatives on improved efficiency as opposed to patient care. CONCLUSIONS: AI documentation assistants will likely to be integral to the future primary care consultations. However, these technologies will still need to be supervised by a human until strong evidence for reliable autonomous performance is available. Therefore, different human-AI collaboration models will need to be designed and evaluated to ensure patient safety, quality of care, doctor safety, and doctor autonomy.

An Immersive Virtual Reality Platform for Assessing Spatial Navigation Memory in Predementia Screening: Feasibility and Usability Study.

BACKGROUND: Traditional methods for assessing memory are expensive and have high administrative costs. Memory assessment is important for establishing cognitive impairment in cases such as detecting dementia in older adults. Virtual reality (VR) technology can assist in establishing better quality outcome in such crucial screening by supporting the well-being of individuals and offering them an engaging, cognitively challenging task that is not stressful. However, unmet user needs can compromise the validity of the outcome. Therefore, screening technology for older adults must address their specific design and usability requirements. OBJECTIVE: This study aimed to design and evaluate the feasibility of an immersive VR platform to assess spatial navigation memory in older adults and establish its compatibility by comparing the outcome to a standard screening platform on a personal computer (PC). METHODS: VR-CogAssess is a platform integrating an Oculus Rift head-mounted display and immersive photorealistic imagery. In a pilot study with healthy older adults (N=42; mean age 73.22 years, SD 9.26), a landmark recall test was conducted, and assessment on the VR-CogAssess was compared against a standard PC (SPC) setup. RESULTS: Results showed that participants in VR were significantly more engaged (P=.003), achieved higher landmark recall scores (P=.004), made less navigational mistakes (P=.04), and reported a higher level of presence (P=.002) than those in SPC setup. In addition, participants in VR indicated no significantly higher stress than SPC setup (P=.87). CONCLUSIONS: The study findings suggest immersive VR is feasible and compatible with SPC counterpart for spatial navigation memory assessment. The study provides a set of design guidelines for creating similar platforms in the future.

A Virtual Reality Food Court to Study Meal Choices in Youth: Design and Assessment of Usability.

BACKGROUND: Regular consumption of take-out and fast foods with sugary drinks is associated with poor quality diets and higher prevalence of obesity. Among the settings where such food is consumed is the food court typically found in shopping malls prominent in many countries. OBJECTIVE: The objective of this research was to develop a virtual reality food court that could be used to test food environmental interventions, such as taxation, and ultimately to facilitate the selection of healthier food choices. METHODS: Fourteen food courts in Sydney, Australia were selected to include those in the city center and suburbs of high and low socioeconomic status. Researchers visited the courts to collect information on number and type of food outlets, all menu items for sale, cost of foods and beverages and sales promotions. This information was used to assemble 14 food outlets typically found in food courts, and representative menus were compiled. The UNITY gaming platform was used to design a virtual reality food court that could be used with HTC VIVE goggles. Participants navigated the virtual reality food court using the head-mounted display, keyboard, and mouse and selected a lunch meal, including food and beverage. A validated questionnaire on presence within the virtual reality food court and system usability was completed at the end of the session. The constructs for presence included a sense of control, sensory fidelity, realism, distraction, and involvement. Questions were rated on a scale from 1 (worst) through 7 (best) for each of 28 questions giving a maximum total score of 196. The systems usability scale (SUS) that gives a final score out of 100 was also assessed. RESULTS: One hundred and sixty-two participants with a mean age of 22.5 (SD 3.1) years completed the survey. The mean score for total presence was 144 (SE 1.4) consisting of control: 62.1 (SE 0.8), realism: 17.5 (SE 0.2), involvement: 9.6 (SE 0.2), sensory fidelity: 34.9 (SE 0.4), and distraction: 24.0 (SE 0.3). The mean SUS was 69 (SE 1.1). CONCLUSIONS: Virtual reality shows promise as a tool to study food choice for test interventions to inform practice and policy.