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1. Preventing Cardiovascular Disease Among Urban African Americans With a Mobile Health App (the MOYO App): Protocol for a Usability Study

   https://doi.org/10.2196/16699  

   Taylor Jr, Herman A ; Francis, Sherilyn ; Evans, Chad Ray ; Harvey, Marques ; Newton, Brittney A ; Jones, Camara P ; Akintobi, Tabia Henry ; Clifford, Gari ( January 2020 , JMIR Research Protocols)

   null (Ed.)

   Background Cardiovascular disease (CVD) disparities are a particularly devastating manifestation of health inequity. Despite advancements in prevention and treatment, CVD is still the leading cause of death in the United States. Additionally, research indicates that African American (AA) and other ethnic-minority populations are affected by CVD at earlier ages than white Americans. Given that AAs are the fastest-growing population of smartphone owners and users, mobile health (mHealth) technologies offer the unparalleled potential to prevent or improve self-management of chronic disease among this population. Objective To address the unmet need for culturally tailored primordial prevention CVD–focused mHealth interventions, the MOYO app was cocreated with the involvement of young people from this priority community. The overall project aims to develop and evaluate the effectiveness of a novel smartphone app designed to reduce CVD risk factors among urban-AAs, 18-29 years of age. Methods The theoretical underpinning will combine the principles of community-based participatory research and the agile software development framework. The primary outcome goals of the study will be to determine the usability, acceptability, and functionality of the MOYO app, and to build a cloud-based data collection infrastructure suitable for digital epidemiology in a disparity population. Changes in health-related parameters over a 24-week period as determined by both passive (eg, physical activity levels, sleep duration, social networking) and active (eg, use of mood measures, surveys, uploading pictures of meals and blood pressure readings) measures will be the secondary outcome. Participants will be recruited from a majority AA “large city” school district, 2 historically black colleges or universities, and 1 urban undergraduate college. Following baseline screening for inclusion (administered in person), participants will receive the beta version of the MOYO app. Participants will be monitored during a 24-week pilot period. Analyses of varying data including social network dynamics, standard metrics of activity, percentage of time away from a given radius of home, circadian rhythm metrics, and proxies for sleep will be performed. Together with external variables (eg, weather, pollution, and socioeconomic indicators such as food access), these metrics will be used to train machine-learning frameworks to regress them on the self-reported quality of life indicators. Results This 5-year study (2015-2020) is currently in the implementation phase. We believe that MOYO can build upon findings of classical epidemiology and longitudinal studies like the Jackson Heart Study by adding greater granularity to our knowledge of the exposures and behaviors that affect health and disease, and creating a channel for outreach capable of launching interventions, clinical trials, and enhancements of health literacy. Conclusions The results of this pilot will provide valuable information about community cocreation of mHealth programs, efficacious design features, and essential infrastructure for digital epidemiology among young AA adults. International Registered Report Identifier (IRRID) DERR1-10.2196/16699 

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2. WeRSort: Preliminary Results from a New Method of Remote Collaboration Facilitated by Fully Immersive Virtual Reality

   https://doi.org/10.1177/1541931218621470  

   Narasimha, Shraddhaa ; Scharett, Emma ; Madathil, Kapil Chalil ; Bertrand, Jeffrey ( September 2018 , Proceedings of the Human Factors and Ergonomics Society Annual Meeting)

   null (Ed.)

   Fully immersive virtual reality, with the unique ability to replicate the real world, could potentially aid in real-time communication. Geographically separated teams can collaborate using virtual reality. To test the viability of using virtual reality for remote collaboration, we designed a system called “WeRSort” where teams sorted cards in a virtual environment. Participants performed the task as a team of 2 in one of three conditions-controls-only condition, generic embodiment and full embodiment. Objective measures of performance, time and percentage match with master cards showed no significant difference. Subjective measures of presence and system usability also showed no statistical significance. However, overall work-load obtained from NASA-TLX showed that fully immersive virtual reality resulted in lower workload in comparison with the other two. Qualitative data was collected and analyzed to understand collaboration using the awareness evaluation model. 

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3. What I Wish My Instructor Knew: Navigating COVID-19 as an Underrepresented Student - Evidence Based Research

   Sealey, Zaniyah V. Lewis ( July 2021 , ASEE Virtual Annual Conference Content Access)

   In March 2020, the global COVID-19 pandemic forced universities across the United States to immediately stop face-to-face activities and transition to virtual instruction. While this transition was not easy for anyone, the shift to online learning was especially difficult for STEM courses, particularly engineering, which has a strong practical/laboratory component. Additionally, underrepresented students (URMs) in engineering experienced a range of difficulties during this transition. The purpose of this paper is to highlight underrepresented engineering students’ experiences as a result of COVID-19. In particular, we aim to highlight stories shared by participants who indicated a desire to share their experience with their instructor. In order to better understand these experiences, research participants were asked to share a story, using the novel data collection platform SenseMaker, based on the following prompt: Imagine you are chatting with a friend or family member about the evolving COVID-19 crisis. Tell them about something you have experienced recently as an engineering student. Conducting a SenseMaker study involves four iterative steps: 1) Initiation is the process of designing signifiers, testing, and deploying the instrument; 2) Story Collection is the process of collecting data through narratives; 3) Sense-making is the process of exploring and analyzing patterns of the collection of narratives; and 4) Response is the process of amplifying positive stories and dampening negative stories to nudge the system to an adjacent possible (Van der Merwe et al. 2019). Unlike traditional surveys or other qualitative data collection methods, SenseMaker encourages participants to think more critically about the stories they share by inviting them to make sense of their story using a series of triads and dyads. After completing their narrative, participants were asked a series of triadic, dyadic, and sentiment-based multiple-choice questions (MCQ) relevant to their story. For one MCQ, in particular, participants were required to answer was “If you could do so without fear of judgment or retaliation, who would you share this story with?” and were given the following options: 1) Family 2) Instructor 3) Peers 4) Prefer not to answer 5) Other. A third of the participants indicated that they would share their story with their instructor. Therefore, we further explored this particular question. Additionally, this paper aims to highlight this subset of students whose primary motivation for their actions were based on Necessity. High-level qualitative findings from the data show that students valued Grit and Perseverance, recent experiences influenced their Sense of Purpose, and their decisions were majorly made based on Intuition. Chi-squared tests showed that there were not any significant differences between race and the desire to share with their instructor, however, there were significant differences when factoring in gender suggesting that gender has a large impact on the complexity of navigating school during this time. Lastly, ~50% of participants reported feeling negative or extremely negative about their experiences, ~30% reported feeling neutral, and ~20% reported feeling positive or extremely positive about their experiences. In the study, a total of 500 micro-narratives from underrepresented engineering students were collected from June – July 2020. Undergraduate and graduate students were recruited for participation through the researchers’ personal networks, social media, and through organizations like NSBE. Participants had the option to indicate who is able to read their stories 1) Everyone 2) Researchers Only, or 3) No one. This work presents qualitative stories of those who granted permission for everyone to read. 

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4. Do Simulated Augmented Reality Overlays Influence Street-Crossing Decisions for Non-Mobility-Impaired Older and Younger Adult Pedestrians?

   https://doi.org/10.1177/00187208231151280  

   Malik, Jeehan ; Kim, Nam-Yoon ; Parr, Morgan D. N. ; Kearney, Joseph K. ; Plumert, Jodie M. ; Rector, Kyle ( January 2023 , Human Factors: The Journal of the Human Factors and Ergonomics Society)

   This study used a virtual environment to examine how older and younger pedestrians responded to simulated augmented reality (AR) overlays that indicated the crossability of gaps in a continuous stream of traffic.

   Older adults represent a vulnerable group of pedestrians. AR has the potential to make the task of street-crossing safer and easier for older adults.

   We used an immersive virtual environment to conduct a study with age group and condition as between-subjects factors. In the control condition, older and younger participants crossed a continuous stream of traffic without simulated AR overlays. In the AR condition, older and younger participants crossed with simulated AR overlays signaling whether gaps between vehicles were safe or unsafe to cross. Participants were subsequently interviewed about their experience.

   We found that participants were more selective in their crossing decisions and took safer gaps in the AR condition as compared to the control condition. Older adult participants also reported reduced mental and physical demand in the AR condition compared to the control condition.

   AR overlays that display the crossability of gaps between vehicles have the potential to make street-crossing safer and easier for older adults. Additional research is needed in more complex real-world scenarios to further examine how AR overlays impact pedestrian behavior.

   With rapid advances in autonomous vehicle and vehicle-to-pedestrian communication technologies, it is critical to study how pedestrians can be better supported. Our research provides key insights for ways to improve pedestrian safety applications using emerging technologies like AR.

    

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5. Career Interview Readiness in Virtual Reality (CIRVR): A Platform for Simulated Interview Training for Autistic Individuals and Their Employers

   https://doi.org/10.1145/3505560  

   Adiani, Deeksha ; Itzkovitz, Aaron ; Bian, Dayi ; Katz, Harrison ; Breen, Michael ; Hunt, Spencer ; Swanson, Amy ; Vogus, Timothy J. ; Wade, Joshua ; Sarkar, Nilanjan ( March 2022 , ACM Transactions on Accessible Computing)

   Employment outcomes for autistic 1 individuals are often poorer relative to their neurotypical (NT) peers, resulting in a greater need for other forms of financial and social support. While a great deal of work has focused on developing interventions for autistic children, relatively less attention has been paid to directly addressing the employment challenges faced by autistic adults. One key impediment to autistic individuals securing employment is the job interview. Autistic individuals often experience anxiety in interview situations, particularly with open-ended questions and unexpected interruptions. They also exhibit atypical gaze patterns that may be perceived as, but not necessarily indicative of, disinterest or inattention. In response, we developed a closed-loop adaptive virtual reality (VR)–based job interview training platform, which we have named Career Interview Readiness in VR (CIRVR). CIRVR is designed to provide an engaging, adaptive, and individualized experience to practice and refine interviewing skills in a less anxiety-inducing virtual context. CIRVR contains a real-time physiology-based stress detection module, as well as a real-time gaze detection module, to permit individualized adaptation. We also present the first prototype of the CIRVR Dashboard, which provides visualizations of data to help autistic individuals as well as potential employers and job coaches make sense of the data gathered from interview sessions. We conducted a feasibility study with 9 autistic and 8 NT individuals to assess the preliminary usability and feasibility of CIRVR. Results showed differences in perceived usability of the system between autistic and NT participants, and higher levels of stress in autistic individuals during interviews. Participants across both groups reported satisfaction with CIRVR and the structure of the interview. These findings and feedback will support future work in improving CIRVR’s features in hopes for it to be a valuable tool to support autistic job candidates as well as their potential employers. 

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