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The current study aimed to validate the Japanese version of the Burnout Assessment Tool (BAT-J), a new burnout measure. We conducted an Internet survey to confirm the validity and reliability of the BAT-J, using registered monitors from a Japanese survey company. The first-wave survey was conducted in May 2018, with 1,032 monitors. Of these, 498 participated in the second-wave survey in June 2018 to confirm 1-month test-retest reliability. We examined the factorial validity of the BAT-J core symptoms (BAT-JC) and BAT-J secondary symptoms (BAT-JS), as well as their reliability (internal consistency and test-retest reliability) and construct validity. Factorial validity was examined using confirmatory factor analyses and exploratory structural equation modeling bifactor analyses. Convergent and discriminant validity were examined using multitrait-multimethod frameworks well as the average variance explained. Exploratory structural equation modeling bifactor solutions for the BAT-JC, BAT-JS, and BAT-J demonstrated the best fit to the data. They also indicated that the general factor accounted for over two-thirds of the common variance explained. Internal consistency and test-retest reliability were confirmed. Convergent and internal discriminant validity of the BAT-JC were confirmed vis-ȧ-vis burnout, as assessed with the Maslach Burnout Inventory - General Survey. Moreover, external discriminant validity of the BAT-J was demonstrated for work engagement and workaholism. Finally, both BAT scales showed significant positive relationships with job demands and turnover intention. All validity results were in line with the job demands-resources model. The results of the current study provide the first evidence for the BAT-J's reliability and factorial and construct validity.
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http://dx.doi.org/10.3389/fpsyg.2020.01819 | DOI Listing |
Neurosci Biobehav Rev
September 2025
Psychiatry and Clinical Psychobiology, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy; University Vita-Salute San Raffaele, Milano, Italy.
Machine learning (ML) could be useful in identifying reliable predictors of treatment response in affective and not affective psychoses, potentially helping to propose personalized interventions. In this systematic review and meta-analysis, we evaluated studies exploiting ML algorithms to predict the improvement of psychotic symptoms, cognition and quality of life in psychoses related to different treatments. We searched MEDLINE (PubMed), Web of Science, and PsycINFO databases updated until February 2024, identifying 64 articles published in English in peer-reviewed journals.
View Article and Find Full Text PDFPhotodiagnosis Photodyn Ther
September 2025
Department of Ophthalmology, People's Hospital of Feng Jie, Chongqing, 404600, China. Electronic address:
Objective: This study aims to develop a robust, multi-task deep learning framework that integrates vessel segmentation and radiomic analysis for the automated classification of four retinal conditions- diabetic retinopathy (DR), hypertensive retinopathy (HR), papilledema, and normal fundus-using fundus images.
Materials: AND.
Methods: A total of 2,165 patients from eight medical centers were enrolled.
Biosens Bioelectron
September 2025
Cancer Research Institute, The First Affiliated Hospital, University of South China, Hengyang, 421001, PR China; State Key Laboratory of Chemo/Biosensing and Chemometrics, School of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, PR China. Electronic address:
A highly sensitive, selective, and simple method for detecting uranyl ions (UO) is crucial for human health and environmental safety. Amidoxime-based nanomaterials have been widely employed for UO detection, but their higher affinity for vanadium than UO limits their practical applications. Herein, a novel covalent organic polymer fluorescent probe (TT-COP) for UO detection was innovatively developed by a one-step Schiff-base condensation reaction between 3,3',5,5'-tetramethylbenzidine (TMB) and 2,4,6-triformylphloroglucinol (Tp).
View Article and Find Full Text PDFNeuroradiology
September 2025
Universitair Ziekenhuis Leuven, Leuven, Belgium.
Aim: Volumetric analysis of orbital soft tissues using magnetic resonance imaging (MRI) offers valuable diagnostic and pathophysiological insights into orbital inflammation, trauma, and tumors. However, the optimal MRI protocols and post-processing methods for specific conditions remain unclear.
Methods: A systematic search was performed in PubMed/MEDLINE, Web of Science, and Cochrane Library for all studies published before November 2024.
Am J Hum Biol
September 2025
University of California, San Francisco, San Francisco, California, USA.
Background: Telomere length (TL) is a valuable marker of aging and stress that reflects both genetic and environmental influences. Quantitative PCR (qPCR) TL measurement is a powerful and cost-effective assay, especially in population studies with limited quantities of source material. Nevertheless, collecting and transporting high-quality blood samples can be logistically challenging, and research suggests that several preanalytical and analytical factors can influence the reliability and precision of the qPCR assay.
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