Publications by authors named "Shawn M Bergman"

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the "big" data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed.

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Introduction: Using crew scheduling and injury incident data from a Fortune 500 manufacturing company, this study analyzed the effect of consecutive shifts and shifts near holidays on near misses and incidents.

Methods: Logistic regressions were conducted with consecutive workdays, days near holidays, and time of shift as predictors of incident and near miss outcomes.

Results: The logistic regression analysis indicated that working consecutive day shifts increases the probability of an incident occurring, with the fourth consecutive shift resulting in the most risk.

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Research indicates that promoting time spent in the outdoors and outdoor physical activity increases children's daily physical activity and improves health. One method showing promise is doctor prescriptions for outdoor physical activity for children; however, no empirical evidence currently exists on prescriptions for children's outdoor physical activity. A pilot study was conducted at one pediatric practice in western North Carolina during 2015 to test the feasibility and potential effectiveness of conducting an outdoor physical activity prescription program for children aged 5-13 years.

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Objective: To determine feasibility and estimate the effect of a 10-week tai chi chuan (TCC) intervention on anxiety and sleep quality in young adults.

Participants: Seventy-five adults (18-40 years) from a predominately undergraduate midsized university.

Methods: This was an assessor blinded, randomized feasibility trial, and participants were randomized into one of three groups: 10 weeks of TCC meeting 2 times per week, 10 weeks of TCC with a DVD of the curriculum, and control group receiving a handout on anxiety management.

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The current research examined the relationships among exercise goal contents, behavioral regulation, physical activity, and aerobic fitness within the context of eight-week university physical education courses. Participants were undergraduate students (M age = 20.2 year, SD = 2.

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This study examined relationships between exercise motives, exercise behavioral regulations, and physical fitness in college students. It was hypothesized that more intrinsic motives and more self-determined regulations would be associated with better fitness. Exercise motives of students participating in physical activity classes (N = 194) were assessed using the Motives for Physical Activity Measure-Revised (MPAM-R) and behavioral regulations were assessed with the Behavioral Regulation in Exercise Questionnaire 2 (BREQ-2).

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The present study examined the process of shared leadership in 45 ad hoc decision-making teams. Each team member's leadership behavior (n = 180) was assessed by behaviorally coding videotapes of the teams' discussions. The within-team patterns of leadership behavior were examined using cluster analysis.

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Article Synopsis
  • This study evaluated the effectiveness of the iPedometer app for iPhone in measuring physical activity among college students.
  • Twenty students wore both the iPedometer and a StepWatch 3 Step Activity Monitor while walking on a treadmill at various speeds to compare step counts.
  • The results showed that the iPedometer app was significantly less accurate than the other devices, indicating it is not a reliable tool for tracking physical activity.
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Worry has been described as a core feature of several disorders, particularly generalized anxiety disorder (GAD). The present study examined the latent structure of worry by applying 3 taxometric procedures (MAXEIG, MAMBAC, and L-Mode) to data collected from 2 large samples. Worry in the first sample (Study 1) of community participants (n=1,355) was operationalized by worry engagement, absence of worry, and the worry feature of trait anxiety.

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