Background: Work-related quality of life (WRQoL) is a multidimensional concept related to life satisfaction. Evaluating WRQoL is essential in healthcare settings since employee satisfaction affects patient service quality. Only a few studies have focused on the quality of life of rehabilitation health workers. We aimed to validate the Italian version of the WRQoL scale on a population of rehabilitation health professionals; the secondary objective was to investigate the work-related quality of life of professionals concerning the work settings in which they operate.
Methods: Participants were recruited from January 2022 to December 2023 according to specific inclusion criteria. Questionnaires were administered through an online survey requiring also personal employment data, and together with the SF-12 questionnaire, a test-retest was performed on 30 therapists. Reliability was assessed with Cronbach's alpha, test-retest stability through intraclass correlation coefficient (ICC), and concurrent validity was calculated using Pearson's correlation.
Results: We enrolled 284 individuals. Internal consistency analysis showed statistically significant results: Cronbach's alpha was > 0.70; construct validity analyses revealed statistically significant data for total scores and subscales, compared to SF-12 scores.
Conclusion: The WRQoL scale is a valid and reliable tool to assess the quality of working life of rehabilitation professionals.
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http://dx.doi.org/10.23749/mdl.v115i4.15644 | DOI Listing |
Glob Health Res Policy
January 2025
Center for Public Health and Epidemic Preparedness and Response, Peking University, Haidian District, 38Th Xueyuan Road, Beijing, 100191, China.
Background: As population aging intensifies, it becomes increasingly important to elucidate the casual relationship between aging and changes in population health. Therefore, our study proposed to develop a systematic attribution framework to comprehensively evaluate the health impacts of population aging.
Methods: We used health-adjusted life expectancy (HALE) to measure quality of life and disability-adjusted life years (DALY) to quantify the burden of disease for the population of Guangzhou.
Pilot Feasibility Stud
January 2025
Department of Internal Medicine - Cardiology, Virginia Commonwealth University, West Hospital 8th Floor, North Wing, Richmond, VA, 23298, USA.
Background: To determine the feasibility, acceptability, and preliminary efficacy of a 6-month tailored non-linear progressive physical activity intervention (PAI) for lymphoma patients undergoing chemotherapy.
Methods: Patients newly diagnosed with lymphoma (non-Hodgkin (NHL) or Hodgkin (HL)) were randomized into the PAI or healthy living intervention (HLI) control (2:1). Feasibility was assessed by examining accrual, adherence, and retention rates.
Inj Epidemiol
January 2025
Injury Prevention Research Center, University of Iowa, 145 N Riverside Dr., Iowa City, IA, 52242, USA.
Background: Motor vehicle crashes are the second leading cause of injury death among adults aged 65 and older in the U.S., second only to falls.
View Article and Find Full Text PDFBMC Med Genomics
January 2025
Department of Otolaryngology, First Affiliated Hospital of Kunming Medical University, 295 Xichang Road, WuHua District, Kunming City, Yunnan Province, China.
Hearing loss is a prevalent condition with a significant impact on individuals' quality of life. However, comprehensive studies investigating the differential gene expression and regulatory mechanisms associated with hearing loss are lacking, particularly in the context of diverse patient samples. In this study, we integrated data from 10 patients across different regions, age groups, and genders, with their data retrieved from a public transcriptome database, to explore the molecular basis of hearing loss.
View Article and Find Full Text PDFJ Transl Med
January 2025
School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, 116024, Dalian, China.
Background: Parkinson's Disease (PD) is a neurodegenerative disorder, and eye movement abnormalities are a significant symptom of its diagnosis. In this paper, we developed a multi-task driven by eye movement in a virtual reality (VR) environment to elicit PD-specific eye movement abnormalities. The abnormal features were subsequently modeled by using the proposed deep learning algorithm to achieve an auxiliary diagnosis of PD.
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