scispace - formally typeset
Search or ask a question
Institution

Bowling Green State University

EducationBowling Green, Ohio, United States
About: Bowling Green State University is a education organization based out in Bowling Green, Ohio, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 8315 authors who have published 16042 publications receiving 482564 citations. The organization is also known as: BGSU.


Papers
More filters
Journal ArticleDOI
TL;DR: This article found that religion is a unique: form of motivation, source of value and significance, contributor to mortality and health; source of coping; and source of distress, which points to the need for: theory and research on the sacred, attention to the pluralization of religious beliefs and practices; evaluation of individual and social interventions that address spiritual problems and apply spiritual resources to their resolution; and collaboration between psychological and religious groups that draws on their unique identities and strengths.
Abstract: Although many social scientists have assumed that religion can be reduced to more basic processes, there may be something unique about religion. By definition, religion has a distinctively meaningful point of reference, the sacred. Empirically, studies also suggest that religion may be a unique: form of motivation; source of value and significance; contributor to mortality and health; source of coping; and source of distress. These findings point to the need for: theory and research on the sacred; attention to the pluralization of religious beliefs and practices; evaluation of individual and social interventions that address spiritual problems and apply spiritual resources to their resolution; and collaboration between psychological and religious groups that draws on their unique identities and strengths.

320 citations

Journal ArticleDOI
TL;DR: Findings indicate that segmenting work and nonwork roles can help employees detach and recover from work demands and show that the segmentation norm within a work group is associated with employee experiences outside of work.
Abstract: Employees can have difficulty mentally distancing themselves from work during off-job time due to increasing use of communication technologies (e.g., e-mail, cell phone, etc.). However, psychological detachment from work during nonwork time is important for employee recovery and health. This study examined several antecedents of psychological detachment: work-home segmentation preference, perceived segmentation norm, and the use of communication technology at home. Results indicate that segmentation preference and segmentation norm were positively associated with psychological detachment. Further, technology use at home partially mediated these relationships. Findings indicate that segmenting work and nonwork roles can help employees detach and recover from work demands. In addition, findings show that the segmentation norm within a work group is associated with employee experiences outside of work. (PsycINFO Database Record (c) 2011 APA, all rights reserved).

317 citations

Journal ArticleDOI
TL;DR: Data analysis indicated that when controlling for the quality of the initial projects, there was a significant relationship between thequality of peer feedback students provided for others and the qualityOf the students' own final projects, but no significant relationship was found between the quality and active engagement in reviewing peers' projects.
Abstract: This study investigated the relationship between the quality of peer assessment and the quality of student projects in a technology application course for teacher education students. Forty-three undergraduate student participants completed the assigned projects. During the peer assessment process, students first anonymously rated and commented on two randomly assigned peers' projects, and they were then asked to improve their projects based on the feedback they received. Two independent raters blindly evaluated student initial and final projects. Data analysis indicated that when controlling for the quality of the initial projects, there was a significant relationship between the quality of peer feedback students provided for others and the quality of the students' own final projects. However, no significant relationship was found between the quality of peer feedback students received and the quality of their own final projects. This finding supported a prior research claim that active engagement in reviewing peers' projects may facilitate student learning. [ABSTRACT FROM AUTHOR]

315 citations

Journal ArticleDOI
01 Oct 2015-Heredity
TL;DR: It is demonstrated that using more phenotypic variables can increase effect sizes, and allow for stronger inferences, as well as eliminating variables potentially reduces effect sizes for comparative analyses, yet test statistics require more observations than variables.
Abstract: The analysis of phenotypic change is important for several evolutionary biology disciplines, including phenotypic plasticity, evolutionary developmental biology, morphological evolution, physiological evolution, evolutionary ecology and behavioral evolution. It is common for researchers in these disciplines to work with multivariate phenotypic data. When phenotypic variables exceed the number of research subjects--data called 'high-dimensional data'--researchers are confronted with analytical challenges. Parametric tests that require high observation to variable ratios present a paradox for researchers, as eliminating variables potentially reduces effect sizes for comparative analyses, yet test statistics require more observations than variables. This problem is exacerbated with data that describe 'multidimensional' phenotypes, whereby a description of phenotype requires high-dimensional data. For example, landmark-based geometric morphometric data use the Cartesian coordinates of (potentially) many anatomical landmarks to describe organismal shape. Collectively such shape variables describe organism shape, although the analysis of each variable, independently, offers little benefit for addressing biological questions. Here we present a nonparametric method of evaluating effect size that is not constrained by the number of phenotypic variables, and motivate its use with example analyses of phenotypic change using geometric morphometric data. Our examples contrast different characterizations of body shape for a desert fish species, associated with measuring and comparing sexual dimorphism between two populations. We demonstrate that using more phenotypic variables can increase effect sizes, and allow for stronger inferences.

314 citations

Journal ArticleDOI
TL;DR: Increases over time in social support and social problem-solving skills were significantly related to improvement in behavioral and academic adjustment, whereas stressful life events were not predictive of adjustment.
Abstract: We investigated the contributions of stressful life events and resources (social support and social problem-solving skills) to predicting changes in children's adjustment. At Time 1, 361 third through fifth graders completed measures of social support and social problem-solving skills. Their parents completed a stressful life events scale and a child behavior rating measure. The children's teachers provided ratings of behavioral and academic adjustment. 2-year follow-up data (Time 2) were obtained for approximately half of the sample on the same measures. Time 1 stressful life events and resources showed some significant but modest zero-order correlations with the Time 2 adjustment indices. Hierarchical multiple regressions revealed prospective effects for Time 1 social support on later teacher-rated competencies and grade-point average. In addition, increases over time in social support and social problem-solving skills (a composite score) were significantly related to improvement in behavioral and academic adjustment, whereas stressful life events were not predictive of adjustment.

313 citations


Authors

Showing all 8365 results

NameH-indexPapersCitations
Eduardo Salas12971162259
Russell A. Barkley11935560109
Hong Liu100190557561
Jaak Panksepp9944640748
Kenneth I. Pargament9637241752
Robert C. Green9152640414
Robert W. Motl8571227961
Evert Jan Baerends8531852440
Hugh Garavan8441928773
Janet Shibley Hyde8322738440
Michael L. Gross8270127140
Jerry Silver7820125837
Michael E. Robinson7436619990
Abraham Clearfield7451319006
Kirk S. Schanze7351219118
Network Information
Related Institutions (5)
University of South Carolina
59.9K papers, 2.2M citations

90% related

City University of New York
56.5K papers, 1.7M citations

90% related

University of Oregon
40.8K papers, 2.1M citations

89% related

Texas Tech University
39.2K papers, 1.1M citations

89% related

Arizona State University
109.6K papers, 4.4M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
202321
202274
2021485
2020511
2019497