Dataset Information

Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

ABSTRACT: Electric scooters (e-scooters) are an increasingly popular form of transportation in urban areas. While research on this topic has focused primarily on injuries, there are multiple mechanisms by which e-scooter share programs may impact health. The aim of this study is to explore the health-related behaviors of e-scooter users and to discuss their implications for public health. Data were collected using an online survey emailed to registered e-scooter users. A total of 1070 users completed the survey. Descriptive variable statistics and chi-squared analysis were performed to determine variable dependent relationships and equality of proportions. The most common destinations reported were "just riding around for fun", home, and dining/shopping. The two most common modes of transportation that would have been used if e-scooters were not available were walking (43.5%) and using a personal vehicle (28.5%). Riding behavior was equally mixed between on the street, on the sidewalk, and equal amounts of both. e-Scooters in Provo are likely having both positive (e.g., air pollution) and negative impacts on health (e.g., injuries, physical inactivity). Future research should further explore patterns of e-scooter use and explicitly examine the linkages between e-scooters and areas of health beyond just injuries.

SUBMITTER: Glenn J

PROVIDER: S-EPMC7503491 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

Glenn Jeffrey J Bluth Madeline M Christianson Mannon M Pressley Jaymie J Taylor Austin A Macfarlane Gregory S GS Chaney Robert A RA

International journal of environmental research and public health 20200831 17

Electric scooters (e-scooters) are an increasingly popular form of transportation in urban areas. While research on this topic has focused primarily on injuries, there are multiple mechanisms by which e-scooter share programs may impact health. The aim of this study is to explore the health-related behaviors of e-scooter users and to discuss their implications for public health. Data were collected using an online survey emailed to registered e-scooter users. A total of 1070 users completed the ...[more]

PMID: 32878295

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Project description:BackgroundOnline health communities (OHCs) have increasingly gained traction with patients, caregivers, and supporters globally. Chinese OHCs are no exception. However, user-generated content (UGC) and the associated user behaviors in Chinese OHCs are largely underexplored and rarely analyzed systematically, forfeiting valuable opportunities for optimizing treatment design and care delivery with insights gained from OHCs.ObjectiveThis study aimed to reveal both the shared and distinct characteristics of 2 popular OHCs in China by systematically and comprehensively analyzing their UGC and the associated user behaviors.MethodsWe concentrated on studying the lung cancer forum (LCF) and breast cancer forum (BCF) on Mijian, and the diabetes consultation forum (DCF) on Sweet Home, because of the importance of the 3 diseases among Chinese patients and their prevalence on Chinese OHCs in general. Our analysis explored the key user activities, small-world effect, and scale-free characteristics of each social network. We examined the UGC of these forums comprehensively and adopted the weighted knowledge network technique to discover salient topics and latent relations among these topics on each forum. Finally, we discussed the public health implications of our analysis findings.ResultsOur analysis showed that the number of reads per thread on each forum followed gamma distribution (HL=0, HB=0, and HD=0); the number of replies on each forum followed exponential distribution (adjusted RL2=0.946, adjusted RB2=0.958, and adjusted RD2=0.971); and the number of threads a user is involved with (adjusted RL2=0.978, adjusted RB2=0.964, and adjusted RD2=0.970), the number of followers of a user (adjusted RL2=0.989, adjusted RB2=0.962, and adjusted RD2=0.990), and a user's degrees (adjusted RL2=0.997, adjusted RB2=0.994, and adjusted RD2=0.968) all followed power-law distribution. The study further revealed that users are generally more active during weekdays, as commonly witnessed in all 3 forums. In particular, the LCF and DCF exhibited high temporal similarity (ρ=0.927; P<.001) in terms of the relative thread posting frequencies during each hour of the day. Besides, the study showed that all 3 forums exhibited the small-world effect (mean σL=517.15, mean σB=275.23, and mean σD=525.18) and scale-free characteristics, while the global clustering coefficients were lower than those of counterpart international OHCs. The study also discovered several hot topics commonly shared among the 3 disease forums, such as disease treatment, disease examination, and diagnosis. In particular, the study found that after the outbreak of COVID-19, users on the LCF and BCF were much more likely to bring up COVID-19-related issues while discussing their medical issues.ConclusionsUGC and related online user behaviors in Chinese OHCs can be leveraged as important sources of information to gain insights regarding individual and population health conditions. Effective and timely mining and utilization of such content can continuously provide valuable firsthand clues for enhancing the situational awareness of health providers and policymakers.

Project description:Background Measures to protect against the spread of COVID-19 include guidance on personal and environmental hygiene. Some guidelines related to COVID-19 directly align with or have similarity to evidence-based food safety practices (FSP) taught in nutrition education classes, including handwashing and washing produce before eating. Objective To understand the impacts of the COVID-19 pandemic on youth handwashing and washing produce before eating behaviors. Study Design, Setting, Participants Data were collected from youth (N = 1,098) in grades 3-5 who participated in SNAP-Education (SNAP-Ed) and the Expanded Food and Nutrition Education Program (EFNEP) in Florida. Utilizing common self-report survey measures, baseline measures from 3 years prior to the pandemic and 3 months during the pandemic were compared for handwashing before eating and washing produce before eating. Due to incomplete data collection during the first 8 months of the pandemic, only behaviors from October 20-January 31 intervals (October 2018- January 2021) were compared to control for seasonal differences. Measurable Outcomes/Analysis Behavioral measures are based on a frequency scale from 1 to 4 (4 being the most frequent). An independent samples t test was used to compare baseline FSP scores from intervals before and during the pandemic. Results No significant difference was found in the frequency of handwashing before and during COVID-19 (3.16 vs 3.18, respectively; P = 0.76). A significant increase was found in the frequency of washing produce before eating before and during COVID-19 (3.14 vs 3.31, respectively; P = 0.008). Conclusion This study did not find any significant changes in handwashing frequency during COVID-19, however, a significant increase in washing produce prior to eating was found. Handwashing prior to eating is a current CDC guideline for COVID-19 mitigation while washing produce prior to eating is not (CDC 2021). Changes in lifestyle and/or eating arrangements during the pandemic might explain these findings.

Project description:BackgroundFor robots to be effectively used in health applications, they need to display appropriate social behaviors. A fundamental requirement in all social interactions is the ability to engage, maintain, and demonstrate attention. Attentional behaviors include leaning forward, self-disclosure, and changes in voice pitch.ObjectiveThis study aimed to examine the effect of robot attentional behaviors on user perceptions and behaviors in a simulated health care interaction.MethodsA parallel randomized controlled trial with a 1:1:1:1 allocation ratio was conducted. We randomized participants to 1 of 4 experimental conditions before engaging in a scripted face-to-face interaction with a fully automated medical receptionist robot. Experimental conditions included a self-disclosure condition, voice pitch change condition, forward lean condition, and neutral condition. Participants completed paper-based postinteraction measures relating to engagement, perceived robot attention, and perceived robot empathy. We video recorded interactions and coded for participant attentional behaviors.ResultsA total of 181 participants were recruited from the University of Auckland. Participants who interacted with the robot in the forward lean and self-disclosure conditions found the robot to be significantly more stimulating than those who interacted with the robot in the voice pitch or neutral conditions (P=.03). Participants in the forward lean, self-disclosure, and neutral conditions found the robot to be significantly more interesting than those in the voice pitch condition (P<.001). Participants in the forward lean and self-disclosure conditions spent significantly more time looking at the robot than participants in the neutral condition (P<.001). Significantly, more participants in the self-disclosure condition laughed during the interaction (P=.01), whereas significantly more participants in the forward lean condition leant toward the robot during the interaction (P<.001).ConclusionsThe use of self-disclosure and forward lean by a health care robot can increase human engagement and attentional behaviors. Voice pitch changes did not increase attention or engagement. The small effects with regard to participant perceptions are potentially because of the limitations in self-report measures or a lack of comparison for most participants who had never interacted with a robot before. Further research could explore the use of self-disclosure and forward lean using a within-subjects design and in real health care settings.

Project description:BackgroundHealth behaviors and cardiometabolic disease risk factors may differ between military and civilian populations; therefore, in U.S. active duty military personnel, we assessed relationships between demographic characteristics, self-reported health behaviors, and doctor-informed medical conditions.MethodsData were self-reported by 27,034 active duty military and Coast Guard personnel who responded to the 2011 Department of Defense Health Related Behaviors Survey. Multivariate linear and logistic regressions were used to estimate cross-sectional associations between (1) demographic characteristics (age, sex, service branch, marital status, children, race/ethnicity, pay grade) and self-reported behaviors (exercise, diet, smoking, alcohol, sleep); (2) demographic characteristics and doctor-informed medical conditions (hypertension, hypercholesterolemia, low high density lipoprotein (HDL) cholesterol, hyperglycemia) and overweight/obesity; and (3) behaviors and doctor-informed medical conditions.ResultsAmong respondents (age 29.9?±?0.1 years, 14.7% female), females reported higher intake than men of fruit, vegetables, and dairy; those with higher education reported higher intakes of whole grains; those currently married and/or residing with children reported higher intake of starches. Older age and female sex were associated with higher odds (ORs 1.25 to 12.54 versus the youngest age group) of overweight/obesity. Older age and female sex were also associated with lower odds (ORs 0.29 to 0.65 versus male sex) of doctor-informed medical conditions, except for blood glucose, for which females had higher odds. Those currently married had higher odds of high cholesterol and overweight/obesity, and separated/divorced/widowed respondents had higher odds of high blood pressure and high cholesterol. Short sleep duration (<?5 versus 7-8 h/night) was associated with higher odds (ORs 1.36to 2.22) of any given doctor-informed medical condition. Strength training was associated with lower probability of high cholesterol, high triglycerides, and low HDL, and higher probability of overweight/obesity. Dietary factors were variably associated with doctor-informed medical conditions and overweight/obesity.ConclusionsThis study observed pronounced associations between health behaviors-especially sleep-and medical conditions, thus adding to evidence that sleep is a critical, potentially modifiable behavior within this population. When possible, adequate sleep should continue to be promoted as an important part of overall health and wellness throughout the military community.

Dataset Information

Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

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Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

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