Studies of the dimensionality of the Life Orientation Test-Revised (LOT-R), considered as the gold standard in the measurement of dispositional optimism, yield controversial results due to the various factorial solutions found. Consequently, the factorial structure of the test has not yet been fully established. The aim of this study is to determine the factorial structure of the LOT-R by comparing seven previous models and their empirical evidence. The test was administered to 906 Spanish participants, ages 18 to 61 (mean age: 23; 56% males). Confirmatory factor analyses were conducted using polychoric correlations. Considering the theoretical background and the best model fit indices (RMSEA=.038; CFI=.98), we conclude that the test presents a factorial structure of a second-order factor (life orientation) composed of two factors (optimism and pessimism). Thus, we recommend using a single global score that could be referred to as life orientation but which ultimately represents the level of dispositional optimism.
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http://dx.doi.org/10.1016/j.ijchp.2015.01.003 | DOI Listing |
Nat Commun
December 2024
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, 100871, Beijing, China.
Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines.
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December 2024
Institute of Psychology, University of Debrecen, Debrecen, Hungary.
Introduction: The positive impact of youth sport on physical, mental and social health has been highlighted in several research which reinforces further investigations concerning the reasons for dropout of athletes. As one of the most emergent difficulties in youth sports is to prevent athletes from dropping out, it is important to explore what factors play important part in this process. The purpose of this study was to identify barriers and challenges related to sport persistence and dropout.
View Article and Find Full Text PDFBMC Med Educ
December 2024
Center for Chung-Ang Medical Education Resource Allocation (CAMERA), College of Medicine, Chung-Ang University, Dongjak-gu, Seoul, Republic of Korea.
Background: Physicians' job satisfaction and their relationships with patients are critical factors in modern healthcare. Understanding medical students' perceptions of these aspects is crucial for enhancing the quality of healthcare. Hence, this study examined medical students' perspectives on improving physician job satisfaction and the essential patient-oriented attitudes required for developing into skilled physicians.
View Article and Find Full Text PDFACS Appl Electron Mater
December 2024
James Watt School of Engineering, University of Glasgow, G12 8QQ Glasgow, Scotland, U.K.
Electronics based on natural or degradable materials are a key requirement for next-generation devices, where sustainability, biodegradability, and resource efficiency are essential. In this context, optimizing the molecular chemical structure of organic semiconductor compounds (OSCs) used as active layers is crucial for enhancing the efficiency of these devices, making them competitive with conventional electronics. In this work, honey-gated organic field-effect transistors (HGOFETs) were fabricated using four different perylene derivative films as OSCs, and the impact of the chemical structure of these perylene derivatives on the performance of HGOFETs was investigated.
View Article and Find Full Text PDFFront Big Data
December 2024
Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, VA, United States.
Introduction: Self-efficacy is a critical determinant of students' academic success and overall life outcomes. Despite its recognized importance, research on predictors of self-efficacy using machine learning models remains limited, particularly within Muslim societies. This study addresses this gap by leveraging advanced machine learning techniques to analyze key factors influencing students' self-efficacy.
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