Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.
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ABSTRACT:
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]
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Project description:ObjectiveTo analyse injuries related to manual and electric scooter use from January 2016 up to and including July 2019.SettingElectric scooter rental services were launched in Denmark in January 2019. The services were provided by private companies. Although rules for handling and riding scooters have been established, no reports either before or after introduction of electric scooters anticipated the full extent of use, and injuries to riders and pedestrians.ParticipantsAll patient records mentioning manual or electric scooters. Records were reviewed, and data were stratified according to two groups: manual and electric scooters.InterventionsA predefined survey was completed in all cases where 'scooter' was present. This contained variables such as type of scooter, type of participant, mechanism of injury, acuity, intoxication, referral to treatment facility.Outcome measuresAmong incidents involving scooters, summary statistics on continuous and categorical variables of interest were reported.Results468 scooter-related injuries were recorded. We found that manual scooter riders were more likely to be children under the age of 15; fall alone-involving no other party; sustain contusions, sprains and lacerations; and bruise either their fingers or toes. Riders of electric scooters were likely to be 18-25 years, sustain facial bruising and lacerations requiring sutures, and be under the influence of alcohol or drugs. Non-riders of electric scooters were mostly elderly people who tripped over scooters, consequently sustaining moderate to severe injuries.ConclusionThere were two different types of population sustaining injuries from manual and electric scooters, respectively. The proportion of non-riders injured by electric scooters were surprisingly large (17%), and while electric scooters are here to stay, several apparently preventable injuries occur as a result of reckless driving and discarded electric scooters. Current rules for usage might not prevent unnecessary accidents and secure traffic safety and the lives of older individuals.
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Project description:IntroductionElectric scooter (e-scooter) rental usage has increased exponentially around the country, expanding to more than 120 cities by the end of 2018. Early attempts to capture the safety effects of widespread adoption of this technology have been hampered by lack of accurate ridership data. Here we describe a 17-month evolution of ridership characteristics in St. Louis, Missouri, and the frequency of e-scooter rental-related injuries serious enough to require an emergency department (ED) visit over this time frame; we also provide estimates of incidence rates of injuries based on company ridership data.MethodsWe performed a combination retrospective chart review and prospective questionnaire-based analysis of adult e-scooter rental-related ED visits in both downtown St. Louis Level 1 trauma centers during the first 17 months of e-scooter rental usage (August 2018-December 2019). The retrospective portion focused on demographics, alcohol use, helmet use, disposition, operative repair, and temporal and severity markers. The prospective portion focused on more detailed crash and rider data. Finally, we used ridership data from both e-scooter rental companies in St. Louis to estimate incidence and temporal trends.ResultsA total of 221 patients had e-scooter rental-related ED visits. The median age of our population was 31 years with 58.8% male and 53.8% White. There were no deaths. Ninety-two patients were found to have fractures with 38% requiring surgery. Of the 21 patients diagnosed with head injury, five had an intracranial bleed. Overall incidence of ED visits related to e-scooters was 2.1 per 10,000 trips and 2.2 per 10,000 miles with the number of ED visits by month closely correlated with the number of rides per month (Pearson correlation coefficient = 0.95).ConclusionThe number of e-scooter rental-related injuries seen in St. Louis trauma centers was relatively low and correlated closely with overall number of rides. The number of injuries decreased and were less severe from 2018 to 2019 with infrequent intracranial injuries and a large percentage of fractures requiring operative repair.
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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.
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Project description:ImportanceElectric scooter (e-scooter) use is increasing in France and in many urban environments worldwide. Yet little is known about injuries associated with use of e-scooters.ObjectiveTo describe characteristics and outcomes of major trauma involving e-scooters.Design, setting, and participantsA multicenter cohort study was conducted in France using the national major trauma registry between January 1, 2019, and December 20, 2022. All patients admitted to a participating major trauma center following a road traffic crash (RTC) involving an e-scooter, a bicycle, or a motorbike were included.ExposureIncluded patients were compared according to the 3 mechanisms.Main outcomes and measuresThe primary outcome was trauma severity as defined by the Injury Severity Score (ISS). Secondary outcomes included the trends of the number of patients per year, a comparison of the RTC epidemiologic factors, injury severity, resources used, and in-hospital outcomes.ResultsA total of 5233 patients involved in RTCs were admitted (median age, 33 [IQR, 24-48] years; 4629 [88.5%] men; median ISS, 13 [IQR, 8-22]). The population included 229 e-scooter RTCs (4.4%), 4094 motorbike RTCs (78.2%), and 910 bicycle RTCs (17.4%). The number of patients treated following e-scooter RTCs increased by 2.8-fold in 4 years (from 31 in 2019 to 88 in 2022), while bicycle RTCs increased by 1.2-fold and motorbike RTCs decreased by 0.9-fold. At admission, 36.7% of e-scooter users had a blood alcohol content higher than the legal threshold (n = 84) and 22.5% wore a protective helmet (n = 32). Among e-scooter RTCs, 102 patients (45.5%) had an ISS of 16 or higher. This proportion was similar for patients with motorbike RTCs (1557 [39.7%]; P = .10) and bicycle RTCs (411 [47.3%]; P = .69). With a proportion of 25.9% (n = 50), patients with e-scooter RTCs had twice as many severe traumatic brain injuries (Glasgow Coma Scale ≤8) as motorbike RTCs (445 [11.8%]) and a proportion comparable to bicycle RTCs (174 [22.1%]). The mortality of e-scooter RTCs was 9.2% (n = 20), compared with 5.2% (n = 196) (P = .02) for motorbikes and 10.0% (n = 84) (P = .82) for bicycles.Conclusions and relevanceThe findings of this study suggest that trauma involving e-scooters in France has significantly increased over the past 4 years. These patients presented with injury profiles as severe as those of individuals who experienced bicycle or motorbike RTCs, with a higher proportion of severe traumatic brain injury.
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Project description:A parking sharing strategy is proposed to solve the problems of parking difficulty caused by the imbalance between parking spaces and parking demand. The vacant parking spaces of residential area can be efficiently utilized to meet the parking demands of those who are working at nearby or come for other activities based on the parking sharing strategy. The paper analyzes the distribution of vehicle arrival numbers and parking durations, then establishes a shared parking allocation model aiming to maximize the parking benefit considering the overtime-parking behavior of the parking users. Simulation methods are used to the analyze the relationship among the parking benefit, proportion of reserved parking, numbers of parking demand, acceptance rate of parking demand and utilization of shared parking spaces. Then, based on the principle of maximum parking benefit, we can determine the optimal proportion of reserved parking, number of shared parking spaces that should be purchased from the residents. Taking the utilization of shared parking spaces as an indicator, the validity of the static allocation principle is proved to be effective. Some allocation rules for parking demand are proposed to guarantees the maximum parking revenue and minimum impact on residents simultaneously.
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Project description:PurposeThe 2016-2020 Utah Comprehensive Cancer Prevention and Control Plan prioritized strategies to address cancer survivorship experiences. In this paper we present estimates for nine indicators evaluating these priorities, trends over time, and assess disparities in survivorship experiences across demographic subgroups.MethodsWe surveyed a representative sample of Utah cancer survivors diagnosed between 2012 and 2019 with any reportable cancer diagnosis. We calculated weighted percentages and 95% confidence intervals (CI) for each indicator. We assessed change over time using a test for trend across survey years in a logistic regression model and used Rao-Scott F-adjusted chi-square tests to test the association between demographic characteristics and each survivorship indicator.ResultsMost of the 1,793 respondents (93.5%) reported their pain was under control, 85.7% rated their overall health as good, very good, or excellent, but 46.5% experienced physical, mental, or emotional limitations. Only 1.7% of survivors aged 75 or older were current smokers, compared to 5.8% of 65-74-year-olds and 7.9% of survivors aged 55-74 (p < 0.006). No regular physical activity was reported by 20.6% and varied by survivor age and education level. The proportion who received a survivorship care plan increased from 34.6% in 2018 to 43.0% in 2021 (p = 0.025). However, survivors under age 55 were significantly less likely to receive a care plan than older survivors.ConclusionThis representative survey of cancer survivors fills a gap in understanding of the cancer survivorship experience in Utah. Results can be used to evaluate and plan additional interventions to improve survivorship quality of life.
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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.
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