Neighborhoods, Daily Activities, and Measuring Health Risks Experienced in Urban Environments.

Studies of place and health often classify a subject\u27s exposure status according to that which is present in their neighborhood of residence. One\u27s neighborhood is often proxied by designating it to be an administratively defined unit such as census tract, to make analysis feasible. Although it is understood that residential space and actual lived space may not correspond and therefore exposure misclassification may result, few studies have the opportunity to investigate the implications of this issue concretely. A population-based case-control study that is currently underway provides one such opportunity. Adolescent victims of assault in Philadelphia, Pennsylvania, USA, and a control sample of adolescents drawn randomly from the community are being enrolled to study how alcohol consumption and time spent nearby alcohol outlets - individual-level and environmental-level risk factors for violence, respectively - over the course of daily activities relate to the likelihood of being assaulted. Data from a rapport-building exercise consist of hand-drawn sketches that subjects drew on street maps when asked to indicate the area considered their neighborhood. The main data consist of self-reported, detailed paths of the routes adolescents traveled from one location to the next over the course of one full day. Having noticed interesting patterns as the data collection phase proceeds, we present here an analysis conducted with the data of 55 control subjects between 15 and 19 years old. We found that hand-drawn neighborhoods and activity paths did not correspond to census tract boundaries, and time subjects spent in close proximity to alcohol outlets during their daily activities was not correlated with the prevalence of alcohol outlets in the census tract of their residence. This served as a useful example demonstrating how classifying subjects as exposed based solely on the prevalence of the exposure in the geographic area of their residence may misrepresent the exposure that is etiologically meaningful

Building capacity for dissemination and implementation research: One university’s experience

Abstract Background While dissemination and implementation (D&I) science has grown rapidly, there is an ongoing need to understand how to build and sustain capacity in individuals and institutions conducting research. There are three inter-related domains for capacity building: people, settings, and activities. Since 2008, Washington University in St. Louis has dedicated significant attention and resources toward building D&I research capacity. This paper describes our process, challenges, and lessons with the goal of informing others who may have similar aims at their own institution. Activities An informal collaborative, the Washington University Network for Dissemination and Implementation Research (WUNDIR), began with a small group and now has 49 regular members. Attendees represent a wide variety of settings and content areas and meet every 6 weeks for half-day sessions. A logic model organizes WUNDIR inputs, activities, and outcomes. A mixed-methods evaluation showed that the network has led to new professional connections and enhanced skills (e.g., grant and publication development). As one of four, ongoing, formal programs, the Dissemination and Implementation Research Core (DIRC) was our first major component of D&I infrastructure. DIRC’s mission is to accelerate the public health impact of clinical and health services research by increasing the engagement of investigators in later stages of translational research. The aims of DIRC are to advance D&I science and to develop and equip researchers with tools for D&I research. As a second formal component, the Washington University Institute for Public Health has provided significant support for D&I research through pilot projects and a small grants program. In a third set of formal programs, two R25 training grants (one in mental health and one in cancer) support post-doctoral scholars for intensive training and mentoring in D&I science. Finally, our team coordinates closely with D&I functions within research centers across the university. We share a series of challenges and potential solutions. Conclusion Our experience in developing D&I research at Washington University in St. Louis shows how significant capacity can be built in a relatively short period of time. Many of our ideas and ingredients for success can be replicated, tailored, and improved upon by others

Academic cross-pollination: The role of disciplinary affiliation in research collaboration

Academic collaboration is critical to knowledge production, especially as teams dominate scientific endeavors. Typical predictors of collaboration include individual characteristics such as academic rank or institution, and network characteristics such as a central position in a publication network. The role of disciplinary affiliation in the initiation of an academic collaboration between two investigators deserves more attention. Here, we examine the influence of disciplinary patterns on collaboration formation with control of known predictors using an inferential network model. The study group included all researchers in the Institute of Clinical and Translational Sciences (ICTS) at Washington University in St. Louis. Longitudinal data were collected on co-authorships in grants and publications before and after ICTS establishment. Exponential-family random graph models were used to build the network models. The results show that disciplinary affiliation independently predicted collaboration in grant and publication networks, particularly in the later years. Overall collaboration increased in the post-ICTS networks, with cross-discipline ties occurring more often than within-discipline ties in grants, but not publications. This research may inform better evaluation models of university-based collaboration, and offer a roadmap to improve cross-disciplinary collaboration with discipline-informed network interventions

Characterization of Motorcycle Encroachments in the US

In 2020, there were 5,579 motorcyclist fatalities in the U.S., which is the highest on record. Despite accounting for only 3% of registered vehicles, motorcycles are involved in 42% of fatal guardrail impacts. Roadside safety hardware testing guidelines are outlined in the Manual for Assessing Safety Hardware (MASH) for passenger vehicles and large trucks but these procedures do not include any motorcycle impacts. Although international test procedures for roadside hardware prescribe motorcycle crash tests, it is not known if the prescribed test conditions reflect the conditions at which motorcycles depart the roadway in the U.S. A better understanding of the characteristics of motorcycles departing the roadway in the U.S. is needed before the development of motorcycle crash tests. This study used the National Cooperative Highway Research Program (NCHRP) 17-88 database to compare the encroachment and impact characteristics of motorcycles, passenger vehicles, single-unit trucks, and tractor-trailer trucks. Motorcycles were found to have a similar distribution of impact angles to passenger vehicles, with an 85th percentile of 24 degrees. The median and 85th percentile impact angle was found to be shallower for tractor-trailer trucks compared with motorcycles and passenger vehicles. Additionally, large trucks and motorcycles were found to roll over at a higher frequency than passenger vehicles. During the first event, almost 80% of motorcycles were upright. By the second event, almost 50% of motorcyclists were separated from the motorcycle. This indicates that a large percentage of riders lose contact with the motorcycle during the first event and are separated during any subsequent events. Based on these results, future motorcycle-barrier tests should consider an upright configuration and an impact angle of 24 degrees

Utility of Facebook\u27s social connectedness index in modeling COVID-19 spread: Exponential random graph modeling study

BACKGROUND: The COVID-19 (the disease caused by the SARS-CoV-2 virus) pandemic has underscored the need for additional data, tools, and methods that can be used to combat emerging and existing public health concerns. Since March 2020, there has been substantial interest in using social media data to both understand and intervene in the pandemic. Researchers from many disciplines have recently found a relationship between COVID-19 and a new data set from Facebook called the Social Connectedness Index (SCI). OBJECTIVE: Building off this work, we seek to use the SCI to examine how social similarity of Missouri counties could explain similarities of COVID-19 cases over time. Additionally, we aim to add to the body of literature on the utility of the SCI by using a novel modeling technique. METHODS: In September 2020, we conducted this cross-sectional study using publicly available data to test the association between the SCI and COVID-19 spread in Missouri using exponential random graph models, which model relational data, and the outcome variable must be binary, representing the presence or absence of a relationship. In our model, this was the presence or absence of a highly correlated COVID-19 case count trajectory between two given counties in Missouri. Covariates included each county\u27s total population, percent rurality, and distance between each county pair. RESULTS: We found that all covariates were significantly associated with two counties having highly correlated COVID-19 case count trajectories. As the log of a county\u27s total population increased, the odds of two counties having highly correlated COVID-19 case count trajectories increased by 66% (odds ratio [OR] 1.66, 95% CI 1.43-1.92). As the percent of a county classified as rural increased, the odds of two counties having highly correlated COVID-19 case count trajectories increased by 1% (OR 1.01, 95% CI 1.00-1.01). As the distance (in miles) between two counties increased, the odds of two counties having highly correlated COVID-19 case count trajectories decreased by 43% (OR 0.57, 95% CI 0.43-0.77). Lastly, as the log of the SCI between two Missouri counties increased, the odds of those two counties having highly correlated COVID-19 case count trajectories significantly increased by 17% (OR 1.17, 95% CI 1.09-1.26). CONCLUSIONS: These results could suggest that two counties with a greater likelihood of sharing Facebook friendships means residents of those counties have a higher likelihood of sharing similar belief systems, in particular as they relate to COVID-19 and public health practices. Another possibility is that the SCI is picking up travel or movement data among county residents. This suggests the SCI is capturing a unique phenomenon relevant to COVID-19 and that it may be worth adding to other COVID-19 models. Additional research is needed to better understand what the SCI is capturing practically and what it means for public health policies and prevention practices

A new measure for multi-professional medical team communication: Design and methodology for multilingual measurement development

BACKGROUND: As implementation science in global health continues to evolve, there is a need for valid and reliable measures that consider diverse linguistic and cultural contexts. A standardized, reproducible process for multilingual measure development may improve accessibility and validity by participants in global health settings. To address this need, we propose a rigorous methodology for multilingual measurement development. We use the example of a novel measure of multi-professional team communication quality, a determinant of implementation efforts. METHODS: The development and translation of this novel bilingual measure is comprised of seven steps. In this paper, we describe a measure developed in English and Spanish, however, this approach is not language specific. Participants are engaged throughout the process: first, an interprofessional panel of experts and second, through cognitive interviewing for measure refinement. The steps of measure development included: (1) literature review to identify previous measures of team communication; (2) development of an initial measure by the expert panel; (3) cognitive interviewing in a phased approach with the first language (English); (4): formal, forward-backward translation process with attention to colloquialisms and regional differences in languages; (5) cognitive interviewing repeated in the second language (Spanish); (6) language synthesis to refine both instruments and unify feedback; and (7) final review of the refined measure by the expert panel. RESULTS: A draft measure to assess quality of multi-professional team communication was developed in Spanish and English, consisting of 52 questions in 7 domains. This measure is now ready for psychometric testing. CONCLUSIONS: This seven-step, rigorous process of multilingual measure development can be used in a variety of linguistic and resource settings. This method ensures development of valid and reliable tools to collect data from a wide range of participants, including those who have historically been excluded due to language barriers. Use of this method will increase both rigor and accessibility of measurement in implementation science and advance equity in research and practice

Comparing projected impacts of cigarette floor price and excise tax policies on socioeconomic disparities in smoking

About half of all US states have cigarette minimum price laws (MPLs) that require a per cent mark-up on prices, but research suggests they may not be very effective in raising prices. An alternative type of MPL sets a floor price below which packs cannot be sold, and may be more promising. This new type of MPL policy has only been implemented in 1 city, therefore its benefits relative to excise taxes is difficult to assess