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Abstract Background The increasing use of erythropoietins with long half-lives and the tendency to lengthen the administration interval to monthly injections call for raising awareness on the pharmacokinetics and risks of new erythropoietin stimulating agents (ESA). Their pharmacodynamic complexity and individual variability limit the possibility of attaining comprehensive clinical experience. In order to help physicians acquiring prescription abilities, we have built a prescription computer model to be used both as a simulator and education tool. Methods The pharmacokinetic computer model was developed using Visual Basic on Excel and tested with 3 different ESA half-lives (24, 48 and 138 hours) and 2 administration intervals (weekly vs. monthly). Two groups of 25 nephrologists were exposed to the six randomised combinations of half-life and administration interval. They were asked to achieve and maintain, as precisely as possible, the haemoglobin target of 11-12 g/dL in a simulated naïve patient. Each simulation was repeated twice, with or without randomly generated bleeding episodes. Results The simulation using an ESA with a half-life of 138 hours, administered monthly, compared to the other combinations of half-lives and administration intervals, showed an overshooting tendency (percentages of Hb values > 13 g/dL 15.8 ± 18.3 vs. 6.9 ± 12.2; P < 0.01), which was quickly corrected with experience. The prescription ability appeared to be optimal with a 24 hour half-life and weekly administration (ability score indexing values in the target 1.52 ± 0.70 vs. 1.24 ± 0.37; P < 0.05). The monthly prescription interval, as suggested in the literature, was accompanied by less therapeutic adjustments (4.9 ± 2.2 vs. 8.2 ± 4.9; P < 0.001); a direct correlation between haemoglobin variability and number of therapy modifications was found (P < 0.01). Conclusions Computer-based simulations can be a useful tool for improving ESA prescription abilities among nephrologists by raising awareness about the pharmacokinetic characteristics of the various ESAs and recognizing the factors that influence haemoglobin variability.

Background: Assessment of health-related quality of life (HRQoL) in patients with allergy to the venom of the Jack Jumper Ant (JJA), Myrmecia pilosula - a Hymenoptera order species native and endemic to the South-Eastern quarter of Australia. This has not previously been studied, despite an estimated population prevalence of generalised allergic symptoms as high as 3% in some areas., Objective: To validate the VQLQ HRQoL instrument - previously validated in wasp and bee venom allergic patients - for use in this specific ant venom-allergic population., Methods: The 14-item VQLQ survey instrument was administered to patients with clinical allergy to JJA venom presenting at the state treatment centre for venom-immunotherapy. Surveys were performed at different time points of the progression through visits for venom immunotherapy treatment. Cross-sectional and longitudinal validation was performed against 'expectation of outcome'(EO) questionnaire by determining correlation and agreement., Results: 271 individuals contributed survey data, comprising a median age of 52 years (3-85) with a bimodal distribution, with 25% being < 18 years of age. Internal consistency was excellent, with a Cronbach of 0.95. Cross-sectional validity was demonstrated with a positive correlation VQLQ to EO of 0.44 (p < 0.001). Performance was nearly identical when stratified into adults and children(<18 yo). Longitudinal Validity was suggested as both VQLQ and EO improved over time in both adults and children, but this only had paired correlation at two time points in adults. Bland-Altman analysis demonstrated an acceptable agreement between VQLQ and EO and no evidence of systematic bias., Conclusion: The VQLQ appears to offer similar performance of HRQoL measurement in patients suffering from JJA venom allergy, as has previously been demonstrated in other Hymenoptera species. In addition, this is the first study to demonstrate cross-sectional validity specifically in a paediatric population 3-18 years of age., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: Implicit bias perpetuates health care inequities and manifests in patient-provider interactions, particularly nonverbal social cues like dominance. We investigated the use of artificial intelligence (AI) for automated communication assessment and feedback during primary care visits to raise clinician awareness of bias in patient interactions., Materials and Methods: (1) Assessed the technical performance of our AI models by building a machine-learning pipeline that automatically detects social signals in patient-provider interactions from 145 primary care visits. (2) Engaged 24 clinicians to design usable AI-generated communication feedback for their workflow. (3) Evaluated the impact of our AI-based approach in a prospective cohort of 108 primary care visits., Results: Findings demonstrate the feasibility of AI models to identify social signals, such as dominance, warmth, engagement, and interactivity, in nonverbal patient-provider communication. Although engaged clinicians preferred feedback delivered in personalized dashboards, they found nonverbal cues difficult to interpret, motivating social signals as an alternative feedback mechanism. Impact evaluation demonstrated fairness in all AI models with better generalizability of provider dominance, provider engagement, and patient warmth. Stronger clinician implicit race bias was associated with less provider dominance and warmth. Although clinicians expressed overall interest in our AI approach, they recommended improvements to enhance acceptability, feasibility, and implementation in telehealth and medical education contexts., Discussion and Conclusion: Findings demonstrate promise for AI-driven communication assessment and feedback systems focused on social signals. Future work should improve the performance of this approach, personalize models, and contextualize feedback, and investigate system implementation in educational workflows. This work exemplifies a systematic, multistage approach for evaluating AI tools designed to raise clinician awareness of implicit bias and promote patient-centered, equitable health care interactions., Competing Interests: The authors have no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Augmented reality enables the wearer to see both their physical environment and virtual objects. Holograms could allow 3D video of providers to be transmitted to distant sites, allowing patients to interact with virtual providers as if they are in the same physical space. Our aim was to determine if Tele-Stroke augmented with Holo-Stroke, compared with Tele-Stroke alone, could improve satisfaction and perception of immersion for the patient. Methods: Kinect cameras positioned at 90-degree intervals around the hub practitioner were used. Cameras streamed real-time optical video to a unity point-cloud program where the data were stitched together in a 360-degree view. The resultant hologram was positioned in 3D space and was visible through the head-mounted display by the patient. Radiology images were shared in Tele-Stroke and via hologram. Likert satisfaction questions were administered. Wilcoxon signed-rank testing was used. Results: Each of the 30 neurology clinic participants scored both Tele-Stroke and Holo-Stroke. Out of these, 29 patients completed the assessments (1 failure owing to computer reboot). Average age was 52 years, with 53.3% of the patients being female, 70.0% being White, and 13.3% being Hispanic. Likert scale score median "Overall" was 32 Tele-Stroke versus 48 Holo-Stroke ( p < 0.00001), "Immersion" was 5 versus 10 ( p < 0.00001), "Beneficial Technique" was 6 versus 10 ( p < 0.00001), and "Ability to See Images" was 5 versus 10 ( p < 0.00001). Discussion: Holo-Stroke 3D holographic Tele-Stroke exams resulted in feasibility, satisfaction, and high perception of immersion for the patient. Patients were enthusiastic for the more immersive, personal discussion with their provider and a robust way to experience radiology images. Though further assessments are needed, Holo-Stroke can help the provider "be there, not just see there!"

Inflammatory bowel disease (IBD) is characterized by chronic intestinal inflammation with no cure and limited treatment options that often have systemic side effects. In this study, we developed a target-specific system to potentially treat IBD by engineering the probiotic bacterium Escherichia coli Nissle 1917 (EcN). Our modular system comprises three components: a transcription factor-based sensor (NorR) capable of detecting the inflammation biomarker nitric oxide (NO), a type 1 hemolysin secretion system, and a therapeutic cargo consisting of a library of humanized anti-TNFα nanobodies. Despite a reduction in sensitivity, our system demonstrated a concentration-dependent response to NO, successfully secreting functional nanobodies with binding affinities comparable to the commonly used drug Adalimumab, as confirmed by enzyme-linked immunosorbent assay and in vitro assays. This newly validated nanobody library expands EcN therapeutic capabilities. The adopted secretion system, also characterized for the first time in EcN, can be further adapted as a platform for screening and purifying proteins of interest. Additionally, we provided a mathematical framework to assess critical parameters in engineering probiotic systems, including the production and diffusion of relevant molecules, bacterial colonization rates, and particle interactions. This integrated approach expands the synthetic biology toolbox for EcN-based therapies, providing novel parts, circuits, and a model for tunable responses at inflammatory hotspots.

Healthcare providers' implicit bias, based on patients' physical characteristics and perceived identities, negatively impacts healthcare access, care quality, and outcomes. Feedback tools are needed to help providers identify and learn from their biases. To incorporate providers' perspectives on the most effective ways to present such feedback, we conducted semi-structured design critique sessions with 24 primary care providers. We found that providers seek feedback designed with transparent metrics indicating the quality of their communication with a patient and trends in communication patterns across visits. Based on these metrics and trends, providers want this feedback presented in a dashboard paired with actionable, personalized tips about how to improve their communication behaviors. Our study provides new insights for interactive systems to help mitigate the impact of implicit biases in patient-provider communication. New systems that build upon these insights could support providers in making healthcare more equitable, particularly for patients from marginalized communities.

Patient-provider communication influences patient health outcomes, and analyzing such communication could help providers identify opportunities for improvement, leading to better care. Interpersonal communication can be assessed through "social-signals" expressed in non-verbal, vocal behaviors like interruptions, turn-taking, and pitch. To automate this assessment, we introduce a machine-learning pipeline that ingests audio-streams of conversations and tracks the magnitude of four social-signals: dominance, interactivity, engagement, and warmth. This pipeline is embedded into ConverSense, a web-application for providers to visualize their communication patterns, both within and across visits. Our user study with 5 clinicians and 10 patient visits demonstrates ConverSense's potential to provide feedback on communication challenges, as well as the need for this feedback to be contextualized within the specific underlying visit and patient interaction. Through this novel approach that uses data-driven self-reflection, ConverSense can help providers improve their communication with patients to deliver improved quality of care.

Implicit biases may negatively influence healthcare providers' behaviors toward patients from historically marginalized communities, impacting providers' communication style, clinical decision-making, and delivery of quality care. Existing interventions to mitigate negative experiences of implicit biases are primarily designed to increase recognition and management of stereotypes and prejudices through provider-facing tools and resources. However, there is a gap in understanding and designing interventions from patient perspectives. We conducted seven participatory co-design workshops with 32 Black, Indigenous, People of Color (BIPOC), Lesbian, Gay, Bisexual, Transgender, Queer/Questioning (LGBTQ+), and Queer, Transgender, Black, Indigenous, People of Color (QTBIPOC) individuals to design patient-centered interventions that help them address and recover from provider implicit biases in primary care. Participants designed four types of solutions: accountability measures, real-time correction, patient enablement tools, and provider resources. These informatics interventions extend the research on implicit biases in healthcare through inclusion of valuable, firsthand patient perspectives and experiences., (©2023 AMIA - All rights reserved.)

G-protein-coupled receptors (GPRs), including pro-inflammatory ovarian cancer GPR1 (OGR1/GPR68) and anti-inflammatory T cell death-associated gene 8 (TDAG8/GPR65), are involved in pH sensing and linked to inflammatory bowel disease (IBD). OGR1 and TDAG8 show opposite effects. To determine which effect is predominant or physiologically more relevant, we deleted both receptors in models of intestinal inflammation. Combined Ogr1 and Tdag8 deficiency was assessed in spontaneous and acute murine colitis models. Disease severity was assessed using clinical scores. Colon samples were analyzed using quantitative polymerase chain reaction (qPCR) and flow cytometry (FACS). In acute colitis, Ogr1 -deficient mice showed significantly decreased clinical scores compared with wildtype (WT) mice, while Tdag8 -deficient mice and double knockout (KO) mice presented similar scores to WT. In Il-10- spontaneous colitis, Ogr1 -deficient mice presented significantly decreased, and Tdag8 -deficient mice had increased inflammation. In the Il10 -/- × Ogr1 -/- × Tdag8 -/- triple KO mice, inflammation was significantly decreased compared with Tdag8 -/- . Absence of Ogr1 reduced pro-inflammatory cytokines in Tdag8 -deficient mice. Tdag8 -/- had significantly more IFNγ + T-lymphocytes and IL-23 T-helper cells in the colon compared with WT. The absence of OGR1 significantly alleviates the intestinal damage mediated by the lack of functional TDAG8. Both OGR1 and TDAG8 represent potential new targets for therapeutic intervention.

While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing structured requests and perceiving how such devices operate. Voice-first user interfaces have the potential to address these challenges by enabling multimodal interactions. Standalone voice + touchscreen Voice Assistants (VAs), such as Echo Show, are specific types of devices that adopt such interfaces and are gaining popularity. However, the affordances of the additional touchscreen for older adults are unknown. Through a 40-day real-world deployment with older adults living independently, we present a within-subjects study (N = 16; age M = 82.5, SD = 7.77, min . = 70, max . = 97) to understand how a built-in touchscreen might benefit older adults during device setup, conducting self-report diary survey, and general uses. We found that while participants appreciated the visual outputs, they still preferred to respond via speech instead of touch. We identified six design implications that can inform future innovations of senior-friendly VAs for managing healthcare and improving quality of life.

The Geriatrics 5Ms: Medications, Mind, Mobility, what Matters most and Multicomplexity is a framework to address the complex needs of older adults. Intelligent Voice Assistants (IVAs) are increasingly popular and have potential to support health-related needs of older adults. We utilized previously collected qualitative data on older adults' views of how an IVA may address their health-related needs and ascertained their fit into the Geriatrics 5Ms framework. The codes describing health challenges and potential IVA solutions fit the framework: (1) Medications: difficulty remembering medications., Solution: reminders. (2) Mind: isolation, anxiety, memory loss., Solution: companionship, memory aids. (3) Mobility: barriers to exercise., Solution: incentives, exercise ideas. (4) Matters most: eating healthy foods., Solution: suggest and order nutritious foods, (5) Multicomplexity; managing multimorbidity., Solution: symptom tracking and communicating with health care professionals. Incorporating the 5Ms framework into IVA design can aid in addressing health care priorities of older adults., Competing Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Michael Hogarth has an equity interest in LifeLink Inc. and also serves on the company’s Scientific Advisory Board. The terms of this arrangement have been reviewed and approved by the University of California, San Diego in accordance with its conflict of interest policies. UCSD IRB Protocol: 191134, (© The Author(s) 2023.)

While standalone Voice Assistants (VAs) are promising to support older adults' daily routine and wellbeing management, onboarding and setting up these devices can be challenging. Although some older adults choose to seek assistance from technicians and adult children, easy set up processes that facilitate independent use are still critical, especially for those who do not have access to external resources. We aim to understand the older adults' experience while setting up commercially available voice-only and voice-first screen-based VAs. Rooted in participants observations and semi-structured interviews, we designed a within-subject study with 10 older adults using Amazon Echo Dot and Echo Show. We identified the values of the built-in touchscreen and the instruction documents, as well as the impact of form factors, and outline important directions to support older adult independence with VAs.

Objective: People who experience marginalization, including Black, Indigenous, People of Color (BIPOC) and Lesbian, Gay, Bisexual, Transgender, Queer, Plus (ie, all other marginalized genders and sexual orientations) people (LGBTQ+) experience discrimination during healthcare interactions, which negatively impacts patient-provider communication and care. Yet, scarce research examines the lived experience of unfair treatment among patients from marginalized groups to guide patient-centered tools that improve healthcare equity., Materials and Methods: We interviewed 25 BIPOC and/or LGBTQ+ people about their experiences of unfair treatment and discrimination when visiting healthcare providers. Through thematic analysis, we describe participants' immediate reactions and longer-term consequences of those experiences., Results: We identified 4 ways that participants reacted to discrimination in the moment: Fighting, Fleeing, Excusing, and Working Around Bias. Long-term consequences reflect 6 ways they coped: Delaying or Avoiding Care, Changing Healthcare Providers, Self-prescribing, Covering Behaviors, Experiencing Health Complications, and Mistrusting Healthcare Institutions., Discussion: By describing how patients react to experiences of unfair treatment and discrimination, our findings enhance the understanding of health disparities as patients cope and struggle to speak out.To combat these problems, we identify 3 future directions for informatics interventions that improve provider behavior, support patient advocacy, and address power dynamics in healthcare., Conclusions: BIPOC and LGBTQ+ patients' perspectives on navigating unfair treatment and discrimination in healthcare offers critical insight into their experiences and long-term consequences of those experiences. Understanding the circumstances and consequences of unfair treatment, discrimination, and the impact of bias through this patient-centered lens is crucial to inform informatics technologies that promote health equity., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Most telemedicine modalities have limited ability to enhance procedural and operative care. We developed a novel system to provide synchronous bidirectional expert mixed reality-enabled virtual procedural mentoring. In this feasibility study, we evaluated mixed reality mentoring of combat casualty care related procedures in a re-perfused cadaver model., Methods: Novices received real-time holographic mentoring from experts using augmented reality via Hololens (Microsoft Inc, Redmond, WA). The experts maintained real-time awareness of the novice's operative environment using virtual reality via HTC-Vive (HTC Corp, Xindian District, Taiwan). Additional cameras (both environments) and novel software created the immersive, shared, 3-dimensional mixed reality environment in which the novice and expert collaborated. The novices were prospectively randomized to either mixed reality or audio-only mentoring. Blinded experts independently evaluated novice procedural videos using a 5-point Likert scale-based questionnaire. Nonparametric variables were evaluated using the Wilcoxon rank-sum test and comparisons using the χ 2 analysis; significance was defined at P < .05., Results: Surgeon and nonsurgeon novices (14) performed 69 combat casualty care-related procedures (38 mixed reality, 31 audio), including various vascular exposures, 4-compartment lower leg fasciotomy, and emergency neurosurgical procedures; 85% were performed correctly with no difference in either group. Upon video review, mixed reality-mentored novices showed no difference in procedural flow and forward planning (3.67 vs 3.28, P = .21) or the likelihood of performing individual procedural steps correctly (4.12 vs 3.59, P = .06)., Conclusion: In this initial feasibility study, our novel mixed reality-based mentoring system successfully facilitated the performance of a wide variety of combat casualty care relevant procedures using a high fidelity re-perfused cadaver model. The small sample size and limited variety of novice types likely impacted the ability of holographically mentored novices to demonstrate improvement over the audio-only control group. Despite this, using virtual, augmented, and mixed reality technologies for procedural mentoring demonstrated promise, and further study is needed., (Published by Elsevier Inc.)

Population aging is an increasingly important consideration for health care in the 21th century, and continuing to have access and interact with digital health information is a key challenge for aging populations. Voice-based Intelligent Virtual Assistants (IVAs) are promising to improve the Quality of Life (QoL) of older adults, and coupled with Ecological Momentary Assessments (EMA) they can be effective to collect important health information from older adults, especially when it comes to repeated time-based events. However, this same EMA data is hard to access for the older adult: although the newest IVAs are equipped with a display, the effectiveness of visualizing time-series based EMA data on standalone IVAs has not been explored. To investigate the potential opportunities for visualizing time-series based EMA data on standalone IVAs, we designed a prototype system, where older adults are able to query and examine the time-series EMA data on Amazon Echo Show - a widely used commercially available standalone screen-based IVA. We conducted a preliminary semi-structured interview with a geriatrician and an older adult, and identified three findings that should be carefully considered when designing such visualizations.

Although clinical training in implicit bias is essential for healthcare equity, major gaps remain both for effective educational strategies and for tools to help identify implicit bias. To understand the perspectives of clinicians on the design of these needed strategies and tools, we conducted 21 semi-structured interviews with primary care clinicians about their perspectives and design recommendations for tools to improve patient-centered communication and to help mitigate implicit bias. Participants generated three types of solutions to improve communication and raise awareness of implicit bias: digital nudges, guided reflection, and data-driven feedback. Given the nuance of implicit bias communication feedback, these findings illustrate innovative design directions for communication training strategies that clinicians may find acceptable. Improving communication skills through individual feedback designed by clinicians for clinicians has the potential to improve healthcare equity.

Bias toward historically marginalized patients affects patient-provider interactions and can lead to lower quality of care and poor health outcomes for patients who are Black, Indigenous, People of Color (BIPOC) and Lesbian, Gay, Bisexual, Transgender and Gender Diverse (LGBTQ+). We gathered experiences with biased healthcare interactions and suggested solutions from 25 BIPOC and LGBTQ+ people. Through qualitative thematic analysis of interviews, we identified ten themes. Eight themes reflect the experience of bias: Transactional Care, Power Inequity, Communication Casualties, Bias-Embedded Medicine, System-level problems, Bigotry in Disguise, Fight or Flight, and The Aftermath. The remaining two themes reflect strategies for improving those experiences: Solutions and Good Experiences. Characterizing these themes and their interconnections is crucial to design effective informatics solutions that can address biases operating in clinical interactions with BIPOC and LGBTQ+ patients, improve the quality of patient-provider interactions, and ultimately promote health equity., (©2021 AMIA - All rights reserved.)

Background: Excess weight gain in young adulthood is associated with future weight gain and increased risk of chronic disease. Although multimodal, technology-based weight-loss interventions have the potential to promote weight loss among young adults, many interventions have limited personalization, and few have been deployed and evaluated for longer than a year. We aim to assess the effects of a highly personalized, 2-year intervention that uses popular mobile and social technologies to promote weight loss among young adults., Methods: The Social Mobile Approaches to Reducing Weight (SMART) 2.0 Study is a 24-month parallel-group randomized controlled trial that will include 642 overweight or obese participants, aged 18-35 years, from universities and community colleges in San Diego, CA. All participants receive a wearable activity tracker, connected scale, and corresponding app. Participants randomized to one intervention group receive evidence-based information about weight loss and behavior change techniques via personalized daily text messaging (i.e., SMS/MMS), posts on social media platforms, and online groups. Participants in a second intervention group receive the aforementioned elements in addition to brief, technology-mediated health coaching. Participants in the control group receive a wearable activity tracker, connected scale, and corresponding app alone. The primary outcome is objectively measured weight in kilograms over 24 months. Secondary outcomes include anthropometric measurements; physiological measures; physical activity, diet, sleep, and psychosocial measures; and engagement with intervention modalities. Outcomes are assessed at baseline and 6, 12, 18, and 24 months. Differences between the randomized groups will be analyzed using a mixed model of repeated measures and will be based on the intent-to-treat principle., Discussion: We hypothesize that both SMART 2.0 intervention groups will significantly improve weight loss compared to the control group, and the group receiving health coaching will experience the greatest improvement. We further hypothesize that differences in secondary outcomes will favor the intervention groups. There is a critical need to advance understanding of the effectiveness of multimodal, technology-based weight-loss interventions that have the potential for long-term effects and widespread dissemination among young adults. Our findings should inform the implementation of low-cost and scalable interventions for weight loss and risk-reducing health behaviors., Trial Registration: ClinicalTrials.gov NCT03907462 . Registered on April 9, 2019., (© 2021. The Author(s).)

Voice-based Intelligent Virtual Assistants (IVAs) promise to improve healthcare management and Quality of Life (QOL) by introducing the paradigm of hands-free and eye-free interactions. However, there has been little understanding regarding the challenges for designing such systems for older adults, especially when it comes to healthcare related tasks. To tackle this, we consider the processes of care delivery and QOL enhancements for older adults as a collaborative task between patients and providers. By interviewing 16 older adults living independently or semi-independently and 5 providers, we identified 12 barriers that older adults might encounter during daily routine and while managing health. We ultimately highlighted key design challenges and opportunities that might be introduced when integrating voice-based IVAs into the life of older adults. Our work will benefit practitioners who study and attempt to create full-fledged IVA-powered smart devices to deliver better care and support an increased QOL for aging populations.

Ecological momentary assessment (EMA) is used to evaluate subjects' behaviors and moods in their natural environments, yet collecting real-time and self-report data with EMA is challenging due to user burden. Integrating voice into EMA data collection platforms through today's intelligent virtual assistants (IVAs) is promising due to hands-free and eye-free nature. However, efficiently managing conversations and EMAs is non-trivial and time consuming due to the ambiguity of the voice input. We approach this problem by rethinking the data modeling of EMA questions and what is needed to deploy them on voice-first user interfaces. We propose a unified metadata schema that models EMA questions and the necessary attributes to effectively and efficiently integrate voice as a new EMA modality. Our schema allows user experience researchers to write simple rules that can be rendered at run-time, instead of having to edit the source code. We showcase an example EMA survey implemented with our schema, which can run on multiple voice-only and voice-first devices. We believe that our work will accelerate the iterative prototyping and design process of real-world voice-based EMA data collection platforms.

Background: Technology has changed the way that men who have sex with men (MSM) seek sex. More than 60% of MSM in the United States use the internet and/or smartphone-based geospatial networking apps to find sex partners. We correlated use of the most popular app (Grindr) with sexual risk and prevention behavior among MSM., Methods: A nested cohort study was conducted between September 2018 and June 2019 among MSM receiving community-based human immunodeficiency virus (HIV) and sexually transmitted infection (STI) screening in central San Diego. During the testing encounter, participants were surveyed for demographics, substance use, risk behavior (previous 3 months), HIV pre-exposure prophylaxis (PrEP) use, and Grindr usage. Participants who tested negative for HIV and who were not on PrEP were offered immediate PrEP., Results: The study included 1256 MSM, 1090 of whom (86.8%) were not taking PrEP. Overall, 580 of 1256 (46%) participants indicated that they used Grindr in the previous 7 days. Grindr users reported significantly higher risk behavior (greater number of male partners and condomless sex) and were more likely to test positive for chlamydia or gonorrhea (8.6% vs 4.7% of nonusers; P = .005). Grindr users were also more likely to be on PrEP (18.7% vs 8.7% of nonusers; P < .001) and had fewer newly diagnosed HIV infections (9 vs 26 among nonusers; P = .014). Grindr users were also nearly twice as likely as nonusers to initiate PrEP (24.6% vs 14%; P < .001)., Conclusions: Given the higher risk behavior and greater acceptance of PrEP among MSM who used Grindr, Grindr may provide a useful platform to promote HIV and STI testing and increase PrEP uptake., (© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Mobile health (mHealth) research involving pervasive sensors, mobile apps and other novel data collection tools and methods present new ethical, legal, and social challenges specific to informed consent, data management and bystander rights. To address these challenges, a participatory design approach was deployed whereby stakeholders contributed to the development of a web-based commons to support the mHealth research community including researchers and ethics board members. The CORE (Connected and Open Research Ethics) platform now features a community forum, a resource library and a network of nearly 600 global members. The utility of the participatory design process was evaluated by analyzing activities carried out over an 8-month design phase consisting of 86 distinct events including iterative design deliberations and social media engagement. This article describes how participatory design yielded 55 new features directly mapped to community needs and discusses relationships to user engagement as demonstrated by a steady increase in CORE member activity and followers on Twitter.

A significant number of young Americans are vulnerable to excess weight gain, especially during the college years. While technology-based weight loss interventions have the potential to be very engaging, short-term approaches showed limited success. In our work we aim to better understand the impact of long-term, multimodal, technology-based weight loss interventions, and study their potential for greater effect among college students. In this paper we lay the basis for our approach towards a multimodal health intervention for young adults: we present formative work based on interviews and a design workshop with 26 young adults. We discuss our intervention at the intersection of user feedback, empirical evidence from previous work, and behavior change theory.

Data grouping is among the most frequently used operations in data visualization. It is the process through which relevant information is gathered, simplified, and expressed in summary form. Many popular visualization tools support automatic grouping of data (e.g., dividing up a numerical variable into bins). Although grouping plays a pivotal role in supporting data exploration, further adjustment and customization of auto-generated grouping criteria is non-trivial. Such adjustments are currently performed either programmatically or through menus and dialogues which require specific parameter adjustments over several steps. In response, we introduce Embedded Merge & Split (EMS), a new interaction technique for direct adjustment of data grouping criteria. We demonstrate how the EMS technique can be designed to directly manipulate width and position in bar charts and histograms, as a means for adjustment of data grouping criteria. We also offer a set of design guidelines for supporting EMS. Finally, we present the results of two user studies, providing initial evidence that EMS can significantly reduce interaction time compared to WIMP-based technique and was subjectively preferred by participants.

Background: Evidence is mixed regarding how physicians' use of the electronic health record (EHR) affects communication in medical encounters., Objective: To investigate whether the different ways physicians interact with the computer (mouse clicks, key strokes, and gaze) vary in their effects on patient participation in the consultation, physicians' efforts to facilitate patient involvement, and silence., Design: Cross-sectional, observational study of video and event recordings of primary care and specialty consultations., Participants: Thirty-two physicians and 217 patients., Main Measures: Predictor variables included measures of physician interaction with the EHR (mouse clicks, key strokes, gaze). Outcome measures included active patient participation (asking questions, stating preferences, expressing concerns), physician facilitation of patient involvement (partnership-building and supportive talk), and silence., Key Results: Patients were less active participants in consultations in which physicians engaged in more keyboard activity (b = -0.002, SE = 0.001, p = 0.02). More physician gaze at the computer was associated with more silence in the encounter (b = 0.21, SE = 0.09, p = 0.02). Physicians' facilitative communication, which predicted more active patient participation (b = 0.65, SE = 0.14, p < 0.001), was not related to EHR activity measures., Conclusions: Patients may be more reluctant to actively participate in medical encounters when physicians are more physically engaged with the computer (e.g., keyboard activity) than when their behavior is less demonstrative (e.g., gazing at EHR). Using easy to deploy communication tactics (e.g., asking about a patient's thoughts and concerns, social conversation) while working on the computer can help physicians engage patients as well as maintain conversational flow.

Mobile Imaging, pervasive Sensing, Social media and location Tracking (MISST) tools used in research are raising new ethical challenges for scientists and the Institutional Review Boards (IRBs) charged with protecting human participants. Yet, little guidance exists to inform the ethical design and the IRB's regulatory review of MISST research. MISST tools/methods produce personal health data that is voluminous and granular and, which may not be subject to policies like the Health Information Portability and Accessibility Act (HIPAA). The NIH Research Portfolio Online Reporting Tools (RePORTER) database was used to identify the number, nature and scope of MISST-related studies supported by the NIH at three time points: 2005, 2010 and 2015. The goal was to: 1-examine the extent to which the NIH is supporting this research and, 2-identify how these tools are being used in research. The number of funded MISST research projects increased 384% from 2005 to 2015. Results revealed that while funding of MISST research is growing, it only represented about 1% of the total NIH budget in 2015. However, the number of institutes, agencies, and centers supporting MISST research increased by roughly 50%. Additionally, the scope of MISST research is diverse ranging from use of social media to track disease transmission to personalized interventions delivered through mobile health applications. Given that MISST research represents about 1% of the NIH budget and is on an increasing upward trajectory, support for research that can inform the ethical, legal and social issues associated with this research is critical., Competing Interests: Competing interestsThe authors declare no competing financial interests.

Vast quantities of personal health information and private identifiable information are being created through mobile apps, wearable sensors, and social networks. While new strategies and tools for obtaining health data have expanded researchers' abilities to design and test personalized and adaptive health interventions, the deployment of pervasive sensing and computational techniques to gather research data is raising ethical challenges for Institutional Review Boards (IRBs) charged with protecting research participants. To explore experiences with, and perceptions about, technology-enabled research, and identify solutions for promoting responsible conduct of this research we conducted focus groups with human research protection program and IRB affiliates. Our findings outline the need for increased collaboration across stakeholders in terms of: (1) shared and dynamic resources that improve awareness of technologies and decrease potential threats to participant privacy and data confidentiality, and (2) development of appropriate and dynamic standards through collaboration with stakeholders in the research ethics community.