Introduction: Sickness presenteeism is a phenomenon where "workers go to work when ill." The objective of this study was to determine the prevalence of and work-related factors associated with presenteeism among nursing care providers in selected tertiary hospitals in Bangalore city.
Methodology: Participants were selected using stratified sampling followed by simple random sampling. A questionnaire was designed to capture socio-demographic information, sickness-related behavior, performance-based self-esteem (PBSE), and selected work-related characteristics.
Results: A total of 357 participants were enrolled in the study, 274 were staff nurses (S/N) and 83 were nursing assistants (N/A). About 75% of the participants reported presenteeism at least once in the last year, two-fifths did so in the last 4 weeks and nearly 15% were sick on the day of the interview. The mean Stanford Sickness Presenteeism Scale-6 score was 18.49 ± 3.84. The most frequent reason for presenteeism was "perceived mildness of the disease." In bivariate analysis, those who were younger, male, had children, higher qualifications, chronic ailment/s, financial commitments, lesser work experience, and higher PBSE had higher presenteeism scores. When introduced into a linear regression model, those S/N who had children [Standardized coefficient = 0.23 (0.40-1.97)], higher PBSE scores [Standardized coefficient = 0.385 (0.15-2.55)], and reported sickness absenteeism in the preceding 4 weeks [Standardized coefficient = 0.136 (0.12-1.01)] were significantly associated with higher presenteeism scores. Those N/A who had lesser work experience had higher presenteeism scores [Standardized coefficient = -0.33 (-0.02--0.004)].
Conclusion: Presenteeism is a common phenomenon among nursing care providers. It is imperative that both employers and employees be educated about its ill effects on the individual, fellow staff, and patients, followed by the adoption of preventive measures.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434814 | PMC |
| http://dx.doi.org/10.4103/ijoem.ijoem_240_22 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Standardization of the Arabic Version of the Adult ADHD Self-Report Screening Scale for DSM-5 (ASRS-5) Among Adults in Saudi Arabia: Variability of ADHD Screening According to Sociodemographic Variables.
J Atten Disord
January 2025
Johns Hopkins Aramco Healthcare, Clinical Psychology and Counseling Services Unit, Saudi Arabia.
Objective: This study investigated the psychometric properties of the Arabic version of the Adult Self-Report Scale-5 (the ASRS-5-AR) within a large sample of adults residing in Saudi Arabia.
Methods: This cross-sectional study applied the ASRS-5-AR to a random sample of 4,299 Saudi and non-Saudi adults, aged 19 to 66 years (31.16 ± 9.
Cephalomedullary nail is the gold standard treatment for intertrochanteric fracture in geriatric population. The aim of the study was to investigate the differences of the reamed versus the unreamed short proximal femoral nailing (PFN), in terms of the duration of surgery and the outcome. The impact of patients and fracture characteristics to the outcome was also evaluated.
View Article and Find Full Text PDFFully automated coronary artery calcium score and risk categorization from chest CT using deep learning and multiorgan segmentation: A validation study from National Lung Screening Trial (NLST).
Int J Cardiol Heart Vasc
February 2025
Department of Radiology, Frimley Park Hospital NHS Foundation Trust, Camberley, Surrey, UK.
Background: The National Lung Screening Trial (NLST) has shown that screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. These patients are also at high risk of coronary artery disease, and we used deep learning model to automatically detect, quantify and perform risk categorisation of coronary artery calcification score (CACS) from non-ECG gated Chest CT scans.
Materials And Methods: Automated calcium quantification was performed using a neural network based on Mask regions with convolutional neural networks (R-CNN) for multiorgan segmentation.
Development of a vegetation canopy reflectance sensor and its diurnal applicability under clear sky conditions.
Front Plant Sci
January 2025
Jiangsu Collaborative Innovation Center of Regional Modern Agriculture & Environmental Protection, Huaiyin Normal University, Huai'an, China.
The spectral reflectance provides valuable information regarding vegetation growth and plays an important role in agriculture, forestry, and grassland management. In this study, a small, portable vegetation canopy reflectance (VCR) sensor that can operate throughout the day was developed. The sensor includes two optical bands at 710 nm and 870 nm, with the light separated by filters, and has a field of view of 28°.
View Article and Find Full Text PDFEffect of nutrition warning, brand, and claims on the perception of product healthiness by Brazilian consumers.
Food Res Int
February 2025
Embrapa Food Technology, Av. das Américas, 29501, CEP 23.020-470 Rio de Janeiro, RJ, Brazil.
In response to the rise of Non-communicable Diseases, public policies, such as Front-of-package (FOP) nutrition labeling, have been implemented to clarify information on food labels and promote healthier eating habits. Brazil adopted black magnifier warning label in 2020, which consists of a black rectangle with a magnifier glass followed by the expression "High in" for three critical nutrients: added sugar, saturated fat and/or sodium. This study aims to evaluate the effect of black magnifier warning label, brand, and claims on Brazilian consumers' perceived healthiness.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!