Background: Musculoskeletal disorders are important health problems due to their high incidence as well as their effects on the society and individuals.
Objective: The aim of this study was to determine the musculoskeletal disorders experienced by teachers, and to evaluate their relationship with certain factors causing musculoskeletal disorders.
Methods: The cross-sectional study was carried out on 416 teachers working in a provincial center using the face-to-face interview method.
Results: Per this 64.9% of the teachers had musculoskeletal disorders, and the pain was mostly localized in the neck region with 55.5%. The work stress scores of the teachers were found to have a positive and significant correlation with musculoskeletal disorder scores and a negative significant correlation with the satisfaction with life scores (p≤0.001). In multiple regression analysis, the time spent sitting at a desk, time spent working in a standing position, time devoted to housework, shoe preference, work stress and life satisfaction were determined as effective predictors on musculoskeletal complaints. The model that was developed explained 22.5% of the variance (R2 = 22.5; p≤0.001).
Conclusions: Due to the prevalence of musculoskeletal disorders among teachers, health-promoting actions are needed in order to raise the awareness of both administrators and teachers in improving working conditions as well as preventing musculoskeletal disorders.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.3233/WOR-210070 | DOI Listing |
Rheumatology (Oxford)
January 2025
Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Objectives: The 2022 European Society of Cardiology and European Respiratory Society (ESC/ERS) Guidelines for pulmonary arterial hypertension (PAH) recommend risk stratification to optimize management. However, the performance of generic PAH risk stratification tools in patients with systemic sclerosis (SSc)-associated PAH remains unclear. Our objective was to identify the most accurate approach for risk stratification at SSc-PAH diagnosis.
View Article and Find Full Text PDFJ Patient Rep Outcomes
January 2025
EuroQol Research Foundation, Rotterdam, The Netherlands.
Background: Multiple diseases, such as Adolescent Idiopathic Scoliosis (AIS), present at adolescent age and the impact on quality of life (QoL) prolongs into adulthood. For the EQ-5D, a commonly used instrument to measure QoL, the current guideline is ambiguous whether the youth or adult version is to be preferred at adolescent age. To assess which is most suitable, this study tested for equivalence along predefined criteria of the youth (EQ-5D-5L) and adult (EQ-5D-Y-5L) version in an adolescent population receiving bracing therapy for AIS.
View Article and Find Full Text PDFR I Med J (2013)
February 2025
Department of Orthopedics, Brown University, Providence, RI.
Objectives: Knee Osteoarthritis (OA) is one of the most frequently encountered conditions in orthopedic practice. This study aimed to validate the Knee Intake Patient Survey (KIPS), a short-form questionnaire designed to assist in the initial diagnosis and treatment stratification for knee OA.
Methods: Patient intake survey results from a single adult reconstruction clinic were retrospectively analyzed alongside clinical diagnoses and treatment recommendations.
R I Med J (2013)
February 2025
Professor of Medicine, Clinician Educator, Warren Alpert Medical School, Brown University; Associate Chief, Cardiology, Brown University Health Cardiovascular Institute, Providence, Rhode Island.
Chest pain is one of the most common chief complaints seen in both the emergency department (ED) and primary care settings.1,2 It is estimated that 20-40% of the general population will suffer from chest pain at some point throughout their lives.3 Interestingly although obstructive coronary artery disease (CAD) prevalence has declined, chest pain as a presenting symptom has become increasingly common over the last decade.
View Article and Find Full Text PDFPhysiol Rep
February 2025
Motion and Exercise Science, University of Stuttgart, Stuttgart, Germany.
The maintenance of an appropriate ratio of body fat to muscle mass is essential for the preservation of health and performance, as excessive body fat is associated with an increased risk of various diseases. Accurate body composition assessment requires precise segmentation of structures. In this study we developed a novel automatic machine learning approach for volumetric segmentation and quantitative assessment of MRI volumes and investigated the efficacy of using a machine learning algorithm to assess muscle, subcutaneous adipose tissue (SAT), and bone volume of the thigh before and after a strength training.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!