Objective: Research into post-traumatic growth (PTG) finds individuals report positive changes in their identity, relationships, and worldviews after trauma. In a pre-registered 16-week longitudinal study, we examined trait change after recent trauma exposure to test an operationalization of PTG as positive personality change. We examined the influence of intrapersonal and social factors including motivation to change traits, perceived social support, and event centrality.
Method: Participants (n = 1004) reported on trauma exposure in past 1-month, centrality of each traumatic event, and social support. Participants with trauma exposure (n = 146) and a matched control group reported on their traits in 8 waves at 2-week intervals, and motivation to change traits in 3 waves.
Results: Although some trait change was observed, it was not consistent with PTG. We found agreeableness declined in the trauma relative to the control group among participants who did not want to change in this trait. Conscientiousness declined for individuals with highly central traumas. Social support predicted increases in emotional stability, conscientiousness, and openness but only for individuals in the control group.
Conclusions: We discuss the value of defining PTG as positive trait change and suggest future directions including assessment of facet-level changes and ideographic methods.
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http://dx.doi.org/10.1111/jopy.12759 | DOI Listing |
J Agromedicine
January 2025
Department of Mechanical Engineering, George Mason University, Fairfax, VA, USA.
Objectives: Commercial fishing is one of the most dangerous industries in the United States, and although injuries have been a prominent focus for research, some health and safety risk factors such as sleep are understudied. In this paper, data from a multi-modal research study of sleep patterns, lifestyle factors, occupational exposures, medical histories, and health assessments in four U.S.
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Orthopedic and Traumatology Unit, Arnaldo Pugliese Hospital, Azienda Ospedaliero-Universitaria "Renato Dulbecco" di Catanzaro, Viale Pio X, 88100 Catanzaro, Italy.
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Zayed Center for Health Sciences, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates.
While the pulmonary effects of regular waterpipe smoking (R-WPS) are well-defined, the impact of occasional waterpipe smoking (O-WPS) on the lungs remains less established. This study investigated the pulmonary toxicity and underlying mechanisms of O-WPS versus R-WPS following 6 months of exposure, focusing on histopathology, inflammation in the lung, bronchoalveolar lavage fluid (BALF), and plasma, as well as oxidative stress, genotoxicity, mitochondrial dysfunction, and the expression of mitogen-activated protein kinases (MAPKs) in lung homogenates. Exposure to both O-WPS and R-WPS resulted in significant histological changes, including increased numbers of alveolar macrophages and lymphocytes, as well as interstitial fibrosis.
View Article and Find Full Text PDFDiagnostics (Basel)
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University Center for Orthopedics, Trauma Surgery and Plastic Surgery, University Hospital Carl Gustav Carus Dresden, 01307 Dresden, Germany.
The aim of this study was to compare the technique of navigation-assisted biopsy based on fused PET and MRI datasets to CT-guided biopsies in terms of the duration of the procedure, radiation dose, complication rate, and accuracy of the biopsy, particularly in anatomically complex regions. Between 2019 and 2022, retrospectively collected data included all navigated biopsies and CT-guided biopsies of suspected primary bone tumors or solitary metastases. Navigation was based on preoperative CT, PET-CT/-MRI, and MRI datasets, and tumor biopsies were performed using intraoperative 3D imaging combined with a navigation system.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Orthopaedic Surgery and Traumatology, Bern University Hospital, Inselspital, University of Bern, Bern, Switzerland.
Scapular morphological attributes show promise as prognostic indicators of retear following rotator cuff repair. Current evaluation techniques using single-slice magnetic-resonance imaging (MRI) are, however, prone to error, while more accurate computed tomography (CT)-based three-dimensional techniques, are limited by cost and radiation exposure. In this study we propose deep learning-based methods that enable automatic scapular morphological analysis from diagnostic MRI despite the anisotropic resolution and reduced field of view, compared to CT.
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