Students' preferences for returning to colleges and universities during the COVID-19 pandemic: A discrete choice experiment.

Importance: When an emerging infectious disease outbreak occurs, such as COVID-19, institutions of higher education (IHEs) must weigh decisions about how to operate their campuses. These decisions entail whether campuses should remain open, how courses should be delivered (in-person, online, or a mixture of the two), and what safety plans should be enacted for those on campus. These issues have weighed heavily on campus administrators during the on-going COVID-19 pandemic. However, there is still limited knowledge about how such decisions affect students' enrollment decisions and campus safety in practice when considering compliance. Objectives: To assess 1) students' willingness to comply with health protocols and contrast their perception of their classmates' compliance, 2) whether students prefer in-person or online learning during a pandemic, and 3) the importance weights of different aspects of campus operations (i.e., modes of course delivery and safety plans) for students when they decide to enroll or defer. Design setting and participants: An internet-based survey of college students took place from June 25, 2020 to July 10, 2020. Participants included 398 industrial engineering students at the Georgia Institute of Technology, a medium-size public university in Atlanta, Georgia. The survey included a discrete choice experiment with questions that asked students to choose whether to enroll or defer when presented with hypothetical scenarios related to Fall 2020 modes of course delivery and aspects of campus safety. The survey also asked students about expected compliance with health protocols, whether they preferred in-person or online courses, and sociodemographic information. Main outcomes and measures: We examine students' willingness to comply with potential health protocols. We estimated logistic regression models to infer significant factors that lead to a student's choice between in-person and online learning. Additionally, we estimated discrete choice models to infer the importance of different modes of course delivery and safety measures to students when deciding to enroll or defer. Results: The survey response rate was 20.8%. A latent class model showed three classes of students: those who were "low-concern" (comprising a 29% expected share of the sample), those who were "moderate-concern" (54%) and those who were "high-concern" (17%). We found that scenarios that offered an on-campus experience with large classes delivered online and small classes delivered in-person, strict safety protocols in terms of mask-wearing, testing, and residence halls, and lenient safety protocols in terms of social gatherings were broadly the scenarios with the highest expected enrollment probabilities. The decision to enroll or defer for all students was largely determined by the mode of delivery for courses and the safety measures on campus around COVID-19 testing and mask-wearing. A logistic regression model showed that a higher perceived risk of infection of COVID-19, a more suitable home environment, being older, and being less risk-seeking were significant factors for a person to choose online learning. Students stated for themselves and their classmates that they would comply with some but not all health protocols against COVID-19, especially those limiting social gatherings. Conclusions and relevance: The majority of students indicated a preference to enroll during the COVID-19 pandemic so long as sufficient safety measures were put in place and all classes were not entirely in-person. As IHEs consider different options for campus operations during pandemics, they should consider the heterogeneous preferences among their students. Offering flexibility in course modes may be a way to appeal to many students who vary in terms of their concern about the pandemic. At the same time, since students overall preferred some safety measures placed around mask-wearing and COVID-19 testing on campus, IHEs may want to recommend or require wearing masks and doing some surveillance tests for all students, faculty, and staff. Students were expecting themselves and their fellow classmates to comply with some but not all health protocols, which may help IHEs identify protocols that need more education and awareness, like limits on social gatherings and the practice of social distancing at social gatherings.

Precursory elements of safety culture: Exploratory analyses of engineering students' safety attitudes.

INTRODUCTION: Safety culture as a concept has been well-researched in the literature. There is less work, however, on how individuals entering the workforce acquire and partake in safety culture over time and how they might be primed to partake in the positive elements of safety culture. METHOD: We begin this exploration by surveying engineering students' attitudes toward safety and experiences with safety education at the Georgia Institute of Technology (n = 316). RESULTS: We find disparities among engineering disciplines, where some majors have more negative views toward safety than others. This may point to the need for more [effective] safety education to prevent negative attitudes toward safety in the workplace. In addition to describing trends among engineering students' attitudes, this study also uses factor analysis to characterize the latent constructs of precursory safety culture: the safety-related attitudes that may direct how people engage with safety culture as early-career engineers. PRACTICAL APPLICATIONS: The analysis provides a conceptual construction of precursor safety culture attitudes, which can serve as a guide to future measurement efforts.

The causal influence of neighborhood design on physical activity within the neighborhood: evidence from Northern California.

PURPOSE: Test for a causal relationship between neighborhood design and physical activity within the neighborhood by controlling for self-selection. DESIGN: Cross-sectional and quasi-longitudinal analyses of residents of selected neighborhoods. SETTING: Eight Northern California neighborhoods. SUBJECTS: Random sample of 1682 adults stratified by movers (moved within 1 year) and nonmovers (moved > 1 year ago) responding to self-administered mail surveys (24.7% response rate). MEASURES: Self-reported number of days in last 7 days of moderate to vigorous physical activity somewhere in the neighborhood and self-reported change in physical activity in the neighborhood from prior to moving (for movers) or from 1 year ago (for nonmovers). ANALYSIS: Zero-inflated Poisson regression for cross-sectional analysis (n = 1497); ordered probit model for quasi-longitudinal analysis (n = 1352). RESULTS: After we controlled for physical activity attitudes and neighborhood preferences, selected neighborhood design characteristics were associated with physical activity within the neighborhood and changes in selected neighborhood design characteristics were associated with changes in physical activity within the neighborhood. CONCLUSIONS: Both cross-sectional and quasi-longitudinal analyses provided evidence of a causal impact of neighborhood design. Improving physical activity options, aesthetic qualities, and social environment may increase physical activity. Critical limitations included self-report measures of physical activity, lack of measures of duration and intensity of neighborhood physical activity, lack of measures of total physical activity, and limited measures of preferences related to physical activity.

Using Travel Diary Data to Estimate the Emissions Impacts of Transportation Strategies: The Puget Sound Telecommuting Demonstration Project.

Transportation control measures are often implemented for their environmental benefits, but there is a need to quantify what benefits actually occur. Telecommuting has the potential to reduce the number of daily trips and miles traveled with personal vehicles and, consequently, the overall emissions resulting from vehicle activity. This search studies the emissions impacts of telecommuting for the participants of the Puget Sound Telecommuting Demonstration Project (PSTDP). The California Air Resources Board's emissions models, EMFAC7F and BURDEN7F, are used to estimate the emissions on telecommuting days and non-telecommuting days, based on travel diaries completed by program participants. This study, among the first of its kind, represents the most sophisticated application of emissions models to travel diary data. Analysis of the travel diary data and the emissions model output supports the hypothesis that telecommuting has beneficial transportation and air quality impacts. The most important results are that telecommuting decreases the number of daily trips (by 30%), the vehicle-miles traveled (VMT) (by 63%), and the number of cold starts (by 44%), especially those taking place in early morning. These reductions are shown to have a large effect on daily emissions, with a 50% to 60% decrease in pollutants generated by a telecommuter's personal vehicle use on a telecommuting day. These net savings are almost entirely due to the elimination of commute trips, as non-commute trips increased by 0.33 trips per person-day (9% of the total trips), and the non-commute VMT increased by 2.2 miles. Overall reduc- tions in travel and emissions of this magnitude are observed because the telecommuters in this sample are long-distance commuters, with commutes twice as long as the regional average. However, even as telecommuting adoption moves into the mainstream, its net impacts are still expected to be beneficial- a reduction in VMT and in emissions. It is important to note that when the level of telecommuting is considered (that is, the percentage of work days that employees actually telecommute), the weekly savings are a much smaller proportion of total weekday travel. Also, these findings represent average per-capita reductions; the aggregate (or overall, regionwide) impacts are determined by scaling these reductions by the number of program participants. Thus, the aggregate effectiveness of telecommuting must take into account the number of people likely to participate as telecommuters and how often they telecommute, not just the per-capita, peroccasion impacts.