Decision-Making about COVID-19 Vaccines among Health Care Workers and Their Adolescent Children

Health care workers promote COVID-19 vaccination for adolescent patients, and as parents, may influence their own children to get vaccinated. We conducted virtual, semi-structured qualitative interviews with vaccinated health care workers and their adolescent children to explore their decision-making process for COVID-19 vaccination. In total, 21 health care workers (physicians, nurses, and medical staff) and their adolescent children (N = 17) participated in interviews. The following three themes described parent-adolescent decision-making for COVID-19 vaccination: (1) family anticipation and hesitation about COVID-19 vaccine approval; (2) parents’ or adolescents’ choice: the decision maker for adolescent COVID-19 vaccination; and (3) leveraging one’s vaccination status to encourage others to get vaccinated. Nurses encouraged adolescent autonomy in decisions for COVID-19 vaccination while physicians viewed vaccination as the parent’s decision. Health care workers and their adolescent children used role-modeling to motivate unvaccinated peers and may model their decision-making process for adolescent COVID-19 vaccination with their own children to support their patients’ and parents’ vaccine decisions

Community-based organization perspectives on participating in state-wide community canvassing program aimed to reduce COVID-19 vaccine disparities in California

Background: Inequities in COVID-19 vaccine accessibility and reliable COVID-related information disproportionately affected marginalized racial and ethnic communities in the U.S. The Get Out the Vaccine (GOTVax) program, an innovative statewide government-funded COVID-19 vaccine canvassing program in California, aimed to reduce structural barriers to COVID-19 vaccination in high-risk communities with low vaccination rates. GOTVax consisted of a community-academic-government partnership with 34 local trusted community-based organizations’ (CBOs) to conduct COVID-19 vaccine outreach, education, and vaccine registration. The purpose of this qualitative evaluation study was to explore the barriers and facilitators of using local CBOs to deploy a geographically, racially, and ethnically diverse state-wide COVID-19 vaccine outreach program. Methods: Semi-structured online interviews were conducted with participating GOTVax CBO leaders from November 2021 to January 2022. Transcripts were analyzed using reflexive thematic analysis. Results: Thirty-one of 34 CBOs participated (91% response rate). Identified themes encompassed both facilitators and barriers to program participation. Key facilitators included leveraging trust through recognized entities; promoting empathetic, tailored outreach; and flexibility of milestone-based CBO funding contracts for rapid program implementation. Barriers included navigating community sociopolitical, geographic, and cultural factors; managing canvassers’ safety; desiring metrics for self-evaluation of outreach success; mitigating canvassing technology challenges; and concerns of program infrastructure initially limiting outreach. CBOs problem-solved barriers with academic and government partners. Conclusions: Between May and December 2021, the GOTVax program reached over 2 million California residents and registered over 60,000 residents for COVID-19 vaccination. Public health campaigns may improve benefits from leveraging the expertise of community-trusted CBOs and universities by providing flexible infrastructure and funding, allowing CBOs to seamlessly tailor outreach most applicable to local minoritized communities

Creating Personalized Digital Human Models of Perception For Visual Analytics

Abstract. Our bodies shape our experience of the world, and our bodies influence what we design. How important are the physical differences between people? Can we model the physiological differences and use the models to adapt and personalize designs, user interfaces and artifacts? Within many disciplines Digital Human Models and Standard Observer Models are widely used and have proven to be very useful for modeling users and simulating humans. In this paper, we create personalized digital human models of perception (Individual Observer Models), particularly focused on how humans see. Individual Observer Models capture how our bodies shape our perceptions. Individual Observer Models are useful for adapting and personalizing user interfaces and artifacts to suit individual users ’ bodies and perceptions. We introduce and demonstrate an Individual Observer Model of human eyesight, which we use to simulate 3600 biologically valid human eyes. An evaluation of the simulated eyes finds that they see eye charts the same as humans. Also demonstrated is the Individual Observer Model successfully making predictions about how easy or hard it is to see visual information and visual designs. The ability to predict and adapt visual information to maximize how effective it is is an important problem in visual design and analytics