Factors Associated with Arkansans’ First Use of Telehealth during the COVID-19 Pandemic

Objective. To examine the factors associated with the first use of telehealth during the COVID-19 pandemic using Andersen’s Model of Healthcare Utilization. Andersen’s Model of Healthcare Utilization allowed the categorization of the independent variables into the following: (1) predisposing factors, including sociodemographic variables and health beliefs; (2) enabling factors, including socioeconomic status and access to care; and (3) need for care, including preexisting or newly diagnosed conditions and reasons to seek out care or to utilize a new mode of care. Methods. Potential respondents (n = 4,077) were identified for recruitment from a volunteer registry in Arkansas. Recruitment emails provided a study description, the opportunity to verify meeting the study’s inclusion criteria and to consent for participation, and a link to follow to complete the survey online. The online survey responses were collected between July and August of 2020 (n = 1,137). Results. Telehealth utilization included two categories: (1) utilizers reported the first use of telehealth services during the pandemic, and (2) nonutilizers reported they had never used telehealth. Lower odds of reporting telehealth utilization during the pandemic were associated with race (Black; OR = 0:57, CI [0.33, 0.96]) and education (high School or less; OR = 0:45, CI [0.25, 0.83]). Higher odds of reporting telehealth utilization included having more than one provider (OR = 2:33, CI [1.30, 4.18]), more physical (OR = 1:12, CI [1.00, 1.25]) and mental (OR 1.53, CI [1.24, 1.88]) health conditions, and changes in healthcare delivery during the pandemic (OR = 3:49, CI [2.78, 4.38]). Conclusions. The results illustrate that disparities exist in Arkansans’ utilization of telehealth services during the pandemic. Future research should explore the disparities in telehealth utilization and how telehealth may be used to address disparities in care for Black Arkansans and those with low socioeconomic status

Population-based incidence and 5-year survival for hospital-admitted traumatic brain and spinal cord injury, Western Australia, 2003-2008

This study aimed at analysing first-time hospitalisations for traumatic brain injury (TBI) and spinal cord injury (SCI) in Western Australia (WA), in terms of socio-demographic profile, cause of injury, relative risks and survival, using tabular and regression analyses of linked hospital discharge and mortality census files and comparing results with published standardised mortality rates (SMRs) for TBI. Participants were all 9,114 first hospital admissions for TBI or SCI from 7/2003 to 6/2008, linked to mortality census data through 12/2008, and the main outcome measures were number of cases by cause, SMRs in hospital and post-discharge by year through year 5. Road crashes accounted for 34 % of hospitalised TBI and 52 % of hospitalised SCI. 8,460 live TBI discharges experienced 580 deaths during 24,494 person-years of follow-up. The life-table expectation of deaths in the cohort was 164. Post-discharge SMRs were 7.66 in year 1, 3.86 in year 2 and averaged 2.31 in years 3 through 5. 317 live SCI discharges experienced 18 deaths during 929 years of follow-up. Post-discharge SMRs were 7.36 in year 1 and a fluctuating average of 2.13 in years 2 through 5. Use of data from model systems does not appear to yield biased SMRs. Similarly no systematic variation was observed between all-age studies and the more numerous studies that focused on those aged 14 to 16 and older. Based on two studies, SMRs for TBI, however, may be higher in year 2 post-discharge in Australia than elsewhere. That possibility and its cause warrant exploration. Expanding public TBI/SCI compensation in WA from road crash to all causes might triple TBI compensation and double SCI compensation

A Non-equilibrium Approach to Rangeland Riparian Management: A Study at Tejon Ranch, California

Riparian areas in arid rangelands provide a wide range of ecosystem services and are critical areas for conservation of landscape and regional biological diversity. Creeks and their associated riparian habitats also provide unique resources for livestock management, however these systems have proven to be sensitive to disturbance from livestock. Ecological site concepts and associated state-and-transition models are useful tools for understanding rangeland plant succession and the relative influence of management actions. These models have been widely developed for upland rangeland systems; however, extension of these models to rangeland riparian systems is still in its infancy. In this study I classified two ecological sites along four streams on the Tejon Ranch in the southern San Joaquin Valley, California. Using vegetation data gathered over four years at fifteen study reaches I identified three distinct vegetation states and plausible conditions precipitating transitions between states. I monitored large mammal and herpetofauna activity at each of the study reaches and compared the predictive power of the categorical ecological site and state-and-transition models in predicting wildlife activity to models based on continuous environmental variables. Finally I investigated the role of cattle and feral pig management on riparian vegetation and wildlife. Ecological sites proved to be a good predictor of observed wildlife community assemblages and was included in top models predicting activity of three of five mammal species: bobcat (Lynx rufus) deer (Odocoileus hemionus) and feral pig (Sus scrofa); and two of three reptile species: western fence lizard (Sceloporus occidentalis) and Gilbert’s skink (Plestiodon gilberti). In contrast, vegetation states proved to be a poor predictor compared to continuous variables. Cattle and feral pigs appear to have played a role in the one observed vegetation transition, and cattle and feral pig activity was correlated with increased cover of hydrophyllic vegetation and bare soil, and decreased cover of upland vegetation and forbs. Summer cattle activity and spring pig activity were the most strongly correlated with changes in vegetation attributes. Results from this study illustrate the utility of ecological sites to model riparian vegetation change and provide a framework for understanding the effect of rangeland management on riparian vegetation and wildlife

Environmental Data_for ESD

This file contains the environmental attributes of each plot that did not change between the years of sampling. It was used in the Ecological Site cluster analysis to create the Ecological Site classification

Environmental Data_Plot_Years

This file contains environmental attributes data for each of the study reaches. It contains attributes that do not change between years (geology, elevation, etc.) and also attributes that change between years (Cattle Exclosure and Annual Precipitation). Columns are the environmental criteria, rows are the individual plot_years

Applying ecological site concepts and state-and-transition models to a grazed riparian rangeland

Ecological sites and state‐and‐transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively, little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state‐and‐transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches × 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well‐suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state‐and‐transition models to aid decision making for conservation and management of rangeland riparian areas

Data from: Applying ecological site concepts and state-and-transition models to a grazed riparian rangeland

Ecological sites and state-and-transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state-and-transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well-suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state-and-transition models to aid decision making for conservation and management of rangeland riparian areas

Relationship between Sociodemographic Factors, Perceived COVID-19 Risk, and Engagement with Health Protective Behaviors

Objectives: This study describes the relationship between sociodemographic factors, chronic conditions, coronavirus disease 2019 (COVID-19) fears and stressors, and the perception of risk from COVID-19 and the use of health protective behaviors among Arkansans during the COVID-19 pandemic. Methods: Data collected from an online survey, administered in Arkansas between July and August 2020 (n = 1205), were used to estimate regressions. The data analysis was completed in April 2021. Results:Wearing a face mask was the most commonly reported behavior (97.4%), followed by handwashing (97.2%). Protective behaviors increased with higher levels of fear (β = 0.030, P \u3c 0.001), more stressors (β = 0.057, P = 0.002), and age (β = 0.006, P = 0.030). Female (β = 0.510, P \u3c 0.001) and Black (β = 0.268, P = 0.039) respondents reported engaging in more protective behaviors than males or other races/ethnicities. Conclusions: In future pandemic planning, there will be a need to create messaging and interventions to increase health protective behaviors directed at young adults, men, and those with lower education levels. Providers will need to address fears related to COVID-19 and help their patients to manage those fears and anxieties

Supporting Information

This supporting information document links all the plant species codes used in the analysis with the full species names. It also includes attribute information for each of the species in the analysis (family, wetland status, etc.)