Factors leading to work absenteeism in Tunisian ankylosing spondylitis patients

Saidane, O.; Mahmoud, I.; Gafsi, Leila; Houda, Ajleni; Tekaya, R.; Abdelmoula, L.

doi:10.1016/j.ejr.2017.06.009

Cited by 11 publications

(5 citation statements)

References 20 publications

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“…Zhang et al 35 assessed the construct validity of the WPAI questionnaire among patients with rheumatoid arthritis and found absenteeism to correlate the least with health-related outcomes compared with other WPAI domains. 35 Saidane et al 36 also demonstrated that disease severity and disease activity were not associated with absenteeism among people with AS in a cohort study. 36 We have shown in a previous analysis from BSRBR-AS that presenteeism predicts future absenteeism, which predicts future work loss.…”

Section: Discussionmentioning

confidence: 93%

“… 35 Saidane et al 36 also demonstrated that disease severity and disease activity were not associated with absenteeism among people with AS in a cohort study. 36 We have shown in a previous analysis from BSRBR-AS that presenteeism predicts future absenteeism, which predicts future work loss. Taken together, these results emphasise that biological therapy may be less effective at improving work outcome when given late in the natural history of the condition.…”

Section: Discussionmentioning

confidence: 93%

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Impact of biological therapy on work outcomes in patients with axial spondyloarthritis: results from the British Society for Rheumatology Biologics Register (BSRBR-AS) and meta-analysis

et al. 2018

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ObjectivesTo quantify, among patients with axial spondyloarthritis (axSpA), the benefit on work outcomes associated with commencing biologic therapy.MethodsThe British Society for Rheumatology Biologics Register in Axial Spondyloarthritis (BSRBRAS) recruited patients meeting Assessment of SpondyloArthritis International Society criteria for axSpA naïve to biological therapy across 83 centres in Great Britain. Work outcomes (measured using the Work Productivity and Activity Impairment Index) were compared between those starting biological therapy at the time of recruitment and those not. Differences between treatment groups were adjusted using propensity score matching. Results from BSRBR-AS were combined with other studies in a meta-analysis to calculate pooled estimates.ResultsOf the 577 participants in this analysis who were in employment, 27.9% were starting biological therapy at the time of recruitment. After propensity score adjustment, patients undergoing biological therapy, at 12-month follow-up, experienced significantly greater improvements (relative to non-biological therapy) in presenteeism (−9.4%, 95% CI −15.3% to –3.5%), overall work impairment (−13.9%, 95% CI −21.1% to –6.7%) and overall activity impairment (−19.2%, 95% CI −26.3% to –12.2%). There was no difference in absenteeism (−1.5%, 95% CI −8.0 to 4.9). Despite these improvements, impact on work was still greater in the biological treated cohort at follow-up. In the meta-analysis including 1109 subjects across observational studies and trials, treatment with biological therapy was associated with significantly greater improvements in presenteeism, work impairment and activity impairment, but there was no difference in absenteeism.ConclusionsThere is consistent evidence that treatment with biological therapy significantly improves work productivity and activity impairment in people with axSpA. However, there remain substantial unmet needs in relation to work.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 93%

Impact of biological therapy on work outcomes in patients with axial spondyloarthritis: results from the British Society for Rheumatology Biologics Register (BSRBR-AS) and meta-analysis

et al. 2018

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“…To develop an appropriate model, companies should consult with experts in the relevant field and choose the appropriate attributes based on their experience and geographic location. Saidene et al, for instance, investigated the factors leading to work absenteeism in Tunisia and concluded that excessive work hours, poor posture, workplace stress, and insufficient rest time are significant attributes leading to absenteeism [43].…”

Section: Results and Model Comparisonmentioning

confidence: 99%

Incorporating a Machine Learning Model into a Web-Based Administrative Decision Support Tool for Predicting Workplace Absenteeism

et al. 2022

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Productivity losses caused by absenteeism at work cost U.S. employers billions of dollars each year. In addition, employers typically spend a considerable amount of time managing employees who perform poorly. By using predictive analytics and machine learning algorithms, organizations can make better decisions, thereby increasing organizational productivity, reducing costs, and improving efficiency. Thus, in this paper we propose hybrid optimization methods in order to find the most parsimonious model for absenteeism classification. We utilized data from a Brazilian courier company. In order to categorize absenteeism classes, we preprocessed the data, selected the attributes via multiple methods, balanced the dataset using the synthetic minority over-sampling method, and then employed four methods of machine learning classification: Support Vector Machine (SVM), Multinomial Logistic Regression (MLR), Artificial Neural Network (ANN), and Random Forest (RF). We selected the best model based on several validation scores, and compared its performance against the existing model. Furthermore, project managers may lack experience in machine learning, or may not have the time to spend developing machine learning algorithms. Thus, we propose a web-based interactive tool supported by cognitive analytics management (CAM) theory. The web-based decision tool enables managers to make more informed decisions, and can be used without any prior knowledge of machine learning. Understanding absenteeism patterns can assist managers in revising policies or creating new arrangements to reduce absences in the workplace, financial losses, and the probability of economic insolvency.

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“…Por su parte, Saidane (2018), resalta que el ausentismo en el trabajo también puede ser ocasionado por otra serie de enfermedades o factores relacionados como: depresión, dolor, fatiga, turnos rotativos seguidos, postura, horas de trabajo, distancia al lugar de trabajo y duración del tiempo de descanso. Puntualmente, la fatiga física y antigüedad laboral en el servicio clínico representaron un factor de riesgo significativo para presentar ausentismo laboral pues aumenta en 1,05 veces más el riesgo de ausentarse en el trabajo, relación que no se ha evidenciado en cuadros de fatiga cognitiva (Martínez, 2020).…”

Section: Introductionunclassified

Ausentismo de trabajadores, repercusión en cumplimiento de objetivos institucionales, centro de salud 3 – Loja, Ecuador

Paredes Quezada,

Garate Aguirre

2023

RUNAS

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El presente trabajo tiene como objetivo determinar los factores de ausentismo de los trabajadores y su influencia en el cumplimiento de los objetivos Institucionales del Centro de Salud No 3 de la Ciudad de Loja Ecuador. La metodología aplicada es de tipo correlacional pues existe un grado de relación entre las variables de investigación (Factores de Ausentismo y Objetivos Institucionales) y explicativa en virtud de que esta investigación responderá a las causas de los eventos, centrándose en el por qué y en qué condiciones ocurren, o la relación entre ellas. Estos factores fueron evaluados entre 40 servidores/trabajadores del Centro de Salud No. 3 de la ciudad de Loja, Ecuador. Se concluyó que el ausentismo en los trabajadores del Centro de salud No 3 de la ciudad de Loja, influye en el cumplimiento de los objetivos institucionales planteados en el Programa Operativo Local de Salud del año 2022, siendo las principales causas la ausencia por enfermedad, vacaciones y permisos por asuntos personales.

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Factors leading to work absenteeism in Tunisian ankylosing spondylitis patients

Cited by 11 publications

References 20 publications

Impact of biological therapy on work outcomes in patients with axial spondyloarthritis: results from the British Society for Rheumatology Biologics Register (BSRBR-AS) and meta-analysis

Impact of biological therapy on work outcomes in patients with axial spondyloarthritis: results from the British Society for Rheumatology Biologics Register (BSRBR-AS) and meta-analysis

Incorporating a Machine Learning Model into a Web-Based Administrative Decision Support Tool for Predicting Workplace Absenteeism

Ausentismo de trabajadores, repercusión en cumplimiento de objetivos institucionales, centro de salud 3 – Loja, Ecuador

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