20 research outputs found

    A Collaborative In Situ Simulation-based Pediatric Readiness Improvement Program for Community Emergency Departments

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    Background More than 30 million children are cared for across 5,000 U.S. emergency departments (EDs) each year. Most of these EDs are not facilities designed and operated solely for children. A Web-based survey provided a national and state-by-state assessment of pediatric readiness and noted a national average score was 69 on a 100-point scale. This survey noted wide variations in ED readiness with scores ranging from 61 in low-pediatric-volume EDs to 90 in the high-pediatric-volume EDs. Additionally, the mean score at the state level ranged from 57 (Wyoming) to 83 (Florida) and for individual EDs ranged from 22 to 100. The majority of prior efforts made to improve pediatric readiness have involved providing Web-based resources and online toolkits. This article reports on the first year of a program that aimed to improve pediatric readiness across community hospitals in our state through in situ simulation-based assessment facilitated by our academic medical center. The primary aim was to improve the pediatric readiness scores in the 10 participating hospitals. The secondary aim was to explore the correlation of simulation-based performance of hospital teams with pediatric readiness scores. Methods This interventional study measured the Pediatric Readiness Survey (PRS) prior to and after implementation of an improvement program. This program consisted of three components: 1) in situ simulations, 2) report-outs, and 3) access to online pediatric readiness resources and content experts. The simulations were conducted in situ (in the ED resuscitation bay) by multiprofessional teams of doctors, nurses, respiratory therapists, and technicians. Simulations and debriefings were facilitated by an expert team from a pediatric academic medical center. Three scenarios were conducted for all teams and include: a 6-month-old with respiratory failure, an 8-year-old with diabetic ketoacidosis (DKA), and a 6-month-old with supraventricular tachycardia (SVT). A performance score was calculated for each scenario. The improvement of PRS was compared before and after the simulation program. The correlation of the simulation performance of each hospital and the PRS was calculated. Results Forty-one multiprofessional teams from 10 EDs in Indiana participated in the study, five were of medium pediatric volume and five were medium- to high-volume EDs. The PRS significantly improved from the first to the second on-site verification assessment (58.4 ± 4.8 to 74.7 ± 2.9, p = 0.009). Total adherence scores to scenario guidelines were 54.7, 56.4, and 62.4% in the respiratory failure, DKA, and SVT scenarios, respectively. We found no correlation between simulation performance and PRS scores. Medium ED pediatric volume significantly predicted higher PRS scores compared to medium-high pediatric ED volume (β = 8.7; confidence interval = 0.72–16.8, p = 0.034). Conclusions Our collaborative improvement program that involved simulation was associated with improvement in pediatric readiness scores in 10 EDs participating statewide. Future work will focus on further expanding of the network and establishing a national model for pediatric readiness improvement

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    Development and validation of a social cognitive theory-based instrument to predict physical activity among people with spinal cord injury

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    Background: There are over 200,000 people with spinal cord injury in the U.S. alone and each year another 15,000 to 20,000 incidents occur. Massive trauma to the spine can result in a SCI leaving behind devastation to the body including paralyzed muscle and loss of sensation. People with SCI are more susceptible to sedentary lifestyles because of the displacement of physical functioning caused by the spinal cord injury and the overwhelming majority are physically inactive. Benefits of physical activity for people with SCI include physical fitness, functional capacity, social integration and psychological well-being. Theoretical constructs have been operationalized to measure social cognitions towards physical activity for this population; however a valid and reliable instrument is lacking. Purpose: Therefore, the purpose of this study was to develop and validate a social cognitive theory-based instrument to predict physical activity among people with SCI. Methods: An instrument was drafted utilizing previous items from the literature. To examine content validity of the instrument, an expert panel of six people reviewed it, and the instrument was modified based on feedback. Cognitive interviewing with five people with SCI was conducted to assess readability, comprehensibility, and time. The final 64-item version of the instrument was used to collect data from participants via an online survey in order to test the validity and reliability. Results: One-hundred twenty-six people with SCI completed the survey with the majority being male (64.3%), white (79.4%), married (39.7%), with a mean age of 42.8 (± 13.7). The most prevalent level of SCI was complete paraplegia (34.9%) and the mean years from time since injury was 14.0 (±11.6). The physical activity outcome variable was significantly and positively correlated with self-regulatory efficacy (r = 0.575), task self-efficacy (r = 0.491), self-regulation (r = 0.432), social support (r= 0.284), and outcome expectations (r = 0.247). A prediction model for the physical activity outcome consisted of self-regulatory efficacy (B = 4.883; p < .001) and social support (B = 1.389; p = .050). Discussion: Multivariate analysis revealed that self-regulatory efficacy and social support were the strongest predictors of physical activity among people with SCI. Based on findings from the study, physical activity interventions targeted at people with spinal cord injury should focus on improving self-regulatory behaviors and providing social support to increase physical activity. A strategy for increasing self-regulatory efficacy within an intervention may involve the development of an action plan by each participant. The action planning would include setting goals and objectives, scheduling times for physical activity, and identifying barriers and a plan for coping with each barrier. Social support is the perceived support from others concerning the behavior and may include family, friends, or online communities. Targeting social support in an intervention may include peer modeling, peer support, health messages from participant doctor, and family involvement. (Published By University of Alabama Libraries
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