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This study reports the development and validation of the Online Learning Self-efficacy Scale (OLSS) for online students. The original 73 OLSS items, developed through a comprehensive review of literature and a content and validity review process by a panel of education graduate students and faculty members, were sent out through a survey to the online students in a university in the southern region of the United States. The data from 366 online students who responded to the survey were analyzed using exploratory and confirmatory factory analyses with a structural equation modeling approach. The final validated OLSS consists of 31 items loading on four factors: Technology use self-efficacy (TU); Online learning task self-efficacy (OLT), Instructor and peer interaction and communication self-efficacy (IPIC), and Self-regulation and motivation efficacy (SRM). Cronbach's α ranged between 0.866 and 0.948 indicating high internal consistency reliability for the OLSS. [ABSTRACT FROM AUTHOR]

Recent amendments to design ground snow load requirements in current US standards have reduced the size of case-study regions by 91% from what they were in previous standards, primarily in western states. This reduction is made possible through the development of highly accurate regional generalized additive models (RGAMs), stitched together with a novel smoothing scheme implemented in the R software package remap, to produce the continental-scale maps of reliability-targeted design ground snow loads available in current standards. This approach allows for better characterizations of the changing relationship between temperature, elevation, and ground snow loads across the conterminous US (CONUS). RGAMs are shown to have 10% or better improvement in mean absolute mapping error in two independently created data sets when compared with traditional mapping techniques. Structures must be able to withstand environmental stresses without collapsing, including snow. Design ground snow loads are estimated using snow measurements taken at weather stations throughout the US. Mapping techniques allow design ground snow loads to be estimated at regions between weather stations. This paper describes a regional approach for mapping design ground snow loads in CONUS and demonstrates the improved accuracy of the approach, relative to previous methods, on two independently created national data sets. [ABSTRACT FROM AUTHOR]

The Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN) study aims to delineate the independent and interaction effects of genomic (genetic and epigenetic) and psychological–environmental (maternally perceived racial discrimination, mental health, and parenting behavior) factors on blood pressure (BP) among African American mother–child dyads over time. The purpose of this article is to describe the two-step genetic and epigenetic approach that will be executed to explore Gene × Environment interactions on BP using a longitudinal cohort design. Procedure for the single collection of DNA at Time 1 includes the use of the Oragene 500-format saliva sample collection tube, which provides enough DNA for both the Illumina Multi-Ethnic Genotyping and 850K EPIC methylation analyses. BP readings, height, weight, percentage of body fat, and percentage of body water will be measured on all participants every 6 months for 2 years for a total of 4 time points. Genomic data analyses to be completed include multivariate modeling, assessment of population admixture and structure, and extended analyses including Bonferroni correction, false discovery rate methods, Monte Carlo approach, EIGENSTRAT methods, and so on, to determine relationships among both main and interaction effects of genetic, epigenetic, and psychological environmental factors on BP. [ABSTRACT FROM AUTHOR]