Drawing on social identity theory and social-cognitive theory, we hypothesize that organizational identification predicts unethical pro-organizational behavior (UPB) through the mediation of moral disengagement. We further propose that competitive interorganizational relations enhance the hypothesized relationships. Three studies conducted in China and the United States using both survey and vignette methodologies provided convergent support for our model. Study 1 revealed that higher organizational identifiers engaged in more UPB, and that this effect was mediated by moral disengagement. Study 2 found that organizational identification once again predicted UPB through the mediation of moral disengagement, and that the mediation relationship was stronger when employees perceived a higher level of industry competition. Finally, Study 3 replicated the above findings using a vignette experiment to provide stronger evidence of causality. Theoretical and practical implications are discussed. (PsycINFO Database Record
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http://dx.doi.org/10.1037/apl0000111 | DOI Listing |
Mol Neurobiol
January 2025
Department of Molecular Pharmacology, Albert Einstein College of Medicine Forchheimer 209, 1300 Morris Park Avenue, Bronx, NY, 10461, USA.
Epidemiological evidence has shown that the regular ingestion of vegetables and fruits is associated with reduced risk of developing chronic diseases. The introduction of the 3Rs (replacement, reduction, and refinement) principle into animal experiments has led to the use of valid, cost-effective, and efficient alternative and complementary invertebrate animal models which are simpler and lower in the phylogenetic hierarchy. Caenorhabditis elegans (C.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, Grote Kruisstraat 2/1, 9712TS, Groningen, The Netherlands.
Recruits are exposed to high levels of psychological and physical stress during the special forces selection period, resulting in dropout rates of up to 80%. To identify who likely drops out, we assessed a group of 249 recruits, every week of the selection program, on their self-efficacy, motivation, experienced psychological and physical stress, and recovery. Using linear regression as well as state-of-the-art machine learning techniques, we aimed to build a model that could meaningfully predict dropout while remaining interpretable.
View Article and Find Full Text PDFInt J Med Inform
January 2025
World Health Organization Headquarters Switzerland.
Background: This paper addresses the importance of timely and robust information systems that underpin emergency response decision-making, as evidenced during the COVID-19 pandemic in the WHO European Region. Recognizing the relevance of these systems, we propose the strengthening of national emergency response information management systems (ERIMS) within the broader digital health information system (HIS) framework. We aim to develop and present an innovative assessment tool designed to evaluate and assist in the strengthening of ERIMS, contributing to a more resilient and effective emergency response.
View Article and Find Full Text PDFIn the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.
View Article and Find Full Text PDFBackground/aims: Certain sociodemographic groups are routinely underrepresented in clinical trials, limiting generalisability. Here, we describe the extent to which enriched enrolment approaches yielded a diverse trial population enriched for older age in a randomised controlled trial of a blood-based multi-cancer early detection test (NCT05611632).
Methods: Participants aged 50-77 years were recruited from eight Cancer Alliance regions in England.
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