Background: Accidental exposure to blood (AEB) poses a risk of bloodborne infections for healthcare workers (HCWs) during hospital activities. In this study, we identified individual behavioral and organizational predictors of AEB among HCWs.
Methods: The study was a prospective, 1-year follow-up cohort study conducted in university hospitals in Paris, France.
Objectives: To quantify the burden of COVID-19-related sick leave during the first pandemic wave in France, accounting for sick leaves due to symptomatic COVID-19 ('symptomatic sick leaves') and those due to close contact with COVID-19 cases ('contact sick leaves').
Methods: We combined data from a national demographic database, an occupational health survey, a social behaviour survey and a dynamic SARS-CoV-2 transmission model. Sick leave incidence from 1 March 2020 to 31 May 2020 was estimated by summing daily probabilities of symptomatic and contact sick leaves, stratified by age and administrative region.
Objectives: In modern professional life, mental health prevention and promotion have become a major challenge for decision-makers. Devising appropriate actions requires better understanding the role played by each work-related psychosocial factor (WPSF). The objective of this study was to present a relevant tool to hierarchise WPSFs that jointly takes into account their (impact on mental health) and their (the proportion of the population exposed to WPSF).
View Article and Find Full Text PDFObjective: Healthcare workers (HCWs) are at high risk of experiencing stress and fatigue due to the demands of their work within hospitals. Improving their physical and mental health and, in turn, the quality and safety of care requires considering factors at both individual and organisational/ward levels. Using a multicentre prospective cohort, this study aims to identify the individual and organisational predictors of stress and fatigue of HCWs in several wards from university hospitals.
View Article and Find Full Text PDFBackground: High turnover among healthcare workers is an increasingly common phenomenon in hospitals worldwide, especially in intensive care units (ICUs). In addition to the serious financial consequences, this is a major concern for patient care (disrupted continuity of care, decreased quality and safety of care, increased rates of medication errors, …).
Objective: The goal of this article was to understand how the ICU-level nurse turnover rate may be explained from multiple covariates at individual and ICU-level, using data from 526 French registered and auxiliary nurses (RANs).
Background: Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods.
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