How to prioritize work-related psychosocial factors impacting mental health? Regression and random forest approaches

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Determinants of healthcare worker turnover in intensive care units: A micro-macro multilevel analysis.

BackgroundHigh 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, …).ObjectiveThe 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).MethodsA cross-sectional study was conducted in ICUs of Paris-area hospitals in 2013. First, we developed a small extension of a multi-level modeling method proposed in 2007 by Croon and van Veldhoven and validated its properties using a comprehensive simulation study. Second, we applied this approach to explain RAN turnover in French ICUs.ResultsBased on the simulation study, the approach we proposed allows to estimate the regression coefficients with a relative bias below 7% for group-level factors and below 12% for individual-level factors. In our data, the mean observed RAN turnover rate was 0.19 per year (SD = 0.09). Based on our results, social support from colleagues and supervisors as well as long durations of experience in the profession were negatively associated with turnover. Conversely, number of children and impossibility to skip a break due to workload were significantly associated with higher rates of turnover. At ICU-level, number of beds, presence of intermediate care beds (continuous care unit) in the ICU and staff-to-patient ratio emerged as significant predictors.ConclusionsThe findings of this research may help decision makers within hospitals by highlighting major determinants of turnover among RANs. In addition, the new approach proposed here could prove useful to researchers faced with similar micro-macro data

Impact des facteurs de risque psychosociaux liés au travail sur la santé mentale : étude transversale sur la population active française

International audienceIntroduction Au cours des dernières décennies, le monde du travail a connu de profond changement (organisation du travail, charge de travail. La précarisation croissante des emplois ou encore l’augmentation actuelle des pressions au travail ne sont pas sans conséquences sur l’aggravation des problèmes de santé mentale au travail. Ces troubles mentaux peuvent être la source d'une productivité limitée, des congés maladie souvent longs et multiples, des retraites anticipées, de dépression ou même de suicides. Cependant, les facteurs de risques psychosociaux (FRPS) liés aux troubles mentaux sont mal connus chez les employés. Comprendre les facteurs qui contribuent à une altération de la santé mentale peut aider à élaborer des stratégies de prévention et d’intervention efficaces afin de lutter contre ces troubles sur le lieu de travail. L’objectif de cette étude est d’identifier les facteurs environnementaux et organisationnels ayant un impact sur la santé mentale des employés.Méthodes Le présent travail est basé sur une étude transversale réalisée en mars 2018 sur un échantillon de 3200 actifs représentatifs de la population active française. Le niveau de santé mentale est mesuré avec le questionnaire GHQ-28. Quarante-quatre FRPS liés à l'environnement et à l'organisation du lieu de travail ont été documentés. Cinquante facteurs individuels liés aux caractéristiques sociodémographiques, à l'hygiène de vie et aux conditions médicales ont également été recueillies. Une régression logistique sur les 44 FRPS a été effectué afin d'identifier ceux ayant un impact important sur la santé mentale. La régression est ajustée sur le sexe, l'âge, la durée du travail par semaine, le travail en week-end, le travail de nuit, le travail en heures décalées, la durée du trajet professionnel, les antécédents de chômage et de maladies chroniques. Résultats L’échantillon de l’étude est constitué de 49% de femmes, avec un âge moyen de 41,4 ans (écart-type de 11.1 ans). En se basant sur la littérature et sur la distribution du score GHQ-28 de l'échantillon, nous avons choisi un seuil de 24 pour identifier les cas psychiatriques potentiels. Plus d’une personne active sur cinq (22.2%, Intervalle de Confiance [IC95%] 20.6-24.0) souffre de détresse conduisant à un trouble mental au moment de l'étude. Les résultats ont montré la difficulté de concilier vie privée et vie professionnelle comme étant le facteur le plus associé aux troubles mentaux (OR = 1.97, IC95% 1.52-2.54, Exposition [E] 15%). Ensuite, le manque de support entre collègues (OR = 1.63, IC95% 1.29-2.06, E = 28%) et les exigences émotionnelles au travail (OR = 1.43, IC95% 1.13-1.79, E = 42%) sont également associés à une mauvaise santé mentale. Être effrayé dans l'exercice de son travail, craindre pour son avenir professionnel, ne pas être satisfait de la communication et des échanges au travail et faire un travail nécessitant de longues périodes de concentration intenses sont aussi des facteurs associés aux troubles mentaux. Conclusion Cette étude propose un premier regard sur les troubles de santé mentale des salariés français et confirme l'urgence de s’emparer de la question de la santé mentale sur le lieu de travail. Étant donné que corrélation n'implique pas causalité, une analyse de causalité devrait également être effectuée afin de déterminer les facteurs sur lesquels agir en priorité pour d'améliorer la santé mentale des employés

Impact of work-related psychosocial factors on mental health: A cross-sectional study in the French working population

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Impact of work-related psychosocial factors on mental health: A cross-sectional study in the French working population

International audienceBACKGROUND. According to Organization for Economic Cooperation and Development, mental health problems, such as depression and anxiety disorders, affect more than one in six people across the European Union in any given year. In the past few decades, mental health problems have increasingly contributed to sickness absence and long-term disability, and return to work is often complicated even if re-employment programs have a modest effect on the quality of life. Mental disorders lead to higher rates of absenteeism and constitute a leading cause of early retirement in Europe and have a direct impact on workplaces through reducing productivity, and increasing healthcare costs. A better understanding of work-related psychosocial factors (PSF) associated with employee’s mental health is important to help decision-makers and public authority to consider specific actions.AIMS. The aim of this study at first, is to determine the exposure of the French work population to work-related PSF and second, to measure the impact of PSF on mental health.DATA. The present work is based on a cross-sectional study conducted in march 2018 on a sample of 3200 workers, representative of the French working population. The sample has been randomly drawn from the French database “Ipsos Access Panel” and data were collected within a questionnaire administered during a computer assisted web interview (CAWI). To measure the level of mental health for each individual, the validated General Health Questionnaire (GHQ-28 items), constructed by Goldberg is used. GHQ-28 items, which is surely the most internationally used, is a self-administered screening questionnaire designed to detect probable psychiatric disorder in primary care settings. The questionnaire doesn’t give any information on the basic health status of the subject. It allows to know if the interviewee is better or worse than usual at the time of the questionnaire. The French version of the questionnaire, used in our study, has been validated. In order to measure psychosocial factors (PSF) at work, 44-item questionnaire is developed. These factors were inspired by major theoretical works from Karasek, Siegrist and Greenberg, and the French report by Michel Gollac. In addition, fifty individual covariates about socio-demographic situation, health and life hygiene conditions, job characteristics and work environment were measured. In our study, we focused only on some of them. Indeed, only nine variables were extracted in the database that could be important in the prediction of mental health. These variables are: gender, age, work duration per week, working on the week-end, working at night, work on staggered hours, commuting duration, previous experience of unemployment and chronic medical condition.METHODS. A multiple logistic regression is used to estimate the impact of each work-related PSF on employee’s mental health, adjusted on the nine confounders. RESULTS. This study analyzed French 2803 employees, among them 48.6% women, with a mean age of 41.4 (11.13). According to the literature and to the distribution of GHQ-28 score in the sample, we choose a threshold of 24 to identify potential psychiatric cases. This was 22.2%, IC95[20,6; 24.0]. Ten PSF remains significantly associated with mental health. “Having problems to handle professional and personal responsibilities” was reported by 15% of the population and has the strongest association with mental health (Odd Ratio OR=1.97, Confidence Interval 95% [1.52; 2.54]). Among people exposed, 45% were potential psychiatric cases whereas 18% among unexposed. 52% of the sample reported having an unsatisfactory job compensation (OR=1.42 [1.15, 1.77]). Job insecurity (OR=1.44 [1.15; 1.78], 42% exposed), lack of social support (OR=1.63 [1.29; 2.06], 27% exposed) were also identified, as well as the emotional burden of the job (OR=1.43 [1.13; 1.79], 43% exposed), and the absence of symbolic compensation of the job in terms of self- esteem (OR=1.32 [1.03;1.69], 22% exposed). The other PSF were unsatisfactory communication at work (OR=1.39 [1.11; 1.75], 43% exposed), feeling afraid when doing the job (OR=1.53, [1.21; 1.93], 28% exposed), doing repetitive tasks (OR=1.29 [1.04; 1.60], 38% exposed) and having a highly cognitive demanding job in term of concentration (OR=1.35 [1.08; 1.70], 32% exposed). In addition, four individual covariates were associated to mental health: having a bad medical condition, being woman, being over 45 years old and work more than 50 hours per week.CONCLUSION. Our study identified 10 PSF associated with mental health with an important exposition rate among employees. The study provided an initial look at the mental health disorders for French employees and the urgency to address mental health at workplace. As correlation does not imply causality, a causal analysis should also be performed before generating recommendations for work conditions

Work-related psychosocial risk factors and psychiatric disorders: A cross-sectional study in the French working population.

PURPOSE:The study estimates the prevalence of probable psychiatric disorder in the working population, determines the proportion of people presenting a probable psychiatric disorder among people exposed to work-related psychosocial risk factors (PSRFs), and identifies which PSRF has the strongest association with having a probable psychiatric disorder. METHODS:A cross-sectional study conducted in March 2018 involved a representative sample of the French working population. The General Health Questionnaire 28 (GHQ-28) was used to estimate the prevalence of probable psychiatric disorder and 44 items were gathered from theoretical models of PSRFs. We used multiple logistic regression to estimate the association of each PSRF with having a probable psychiatric disorder, adjusted on individual, health, and job confounders. RESULTS:This study involved 3200 French participants. The proportion of probable psychiatric disorder was 22.2% [20.6; 24.0]. Ten PSRFs were significantly associated with it. The strongest association was for having problems handling professional and personal responsibilities (reported by 15% of the study population) (OR = 1.97 [1.52; 2.54]), with 45% pathological GHQ-28 scores (potential psychiatric cases) for people exposed to this PSRF versus 18% non-exposed. The next strongest association was lack of support of colleagues (reported by 28%) (OR = 1.63 [1.29; 2.06]). The third strongest association was feeling sometimes afraid when doing the job (reported by 63%) (OR = 1.53, [1.21; 1.93]). CONCLUSIONS:Our study identified 10 PSRFs associated with psychiatric disorder, with substantial exposure rate among the population. The results of our research could help develop recommendations to improve work environment

Multilevel approach to individual and organisational predictors of stress and fatigue among healthcare workers of a university hospital: a longitudinal study

International audienceObjective 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. Methods Our cohort consists of 695 HCWs from 32 hospital wards drawn at random within four volunteer hospital centres in Paris-area. Three-level longitudinal analyses, accounting for repeated measures (level 1) across participants (level 2) nested within wards (level 3) and adjusted for relevant fixed and time-varying confounders, were performed. Results At baseline, the sample was composed by 384 registered nurses, 300 auxiliary nurses and 11 midwives. According to the three-level longitudinal models, some predictors were found in common for both stress and fatigue (low social support from supervisors, work overcommitment, sickness presenteeism and number of beds per ward). However, specific predictors for high level of stress (negative life events, low social support from colleagues and breaks frequently cancelled due to work overload) and fatigue (longer commuting duration, frequent use of interim staff in the ward) were also found. Conclusion Our results may help identify at-risk HCWs and wards, where interventions to reduce stress and fatigue should be focused. These interventions could include manager training to favour better staff support and overall safety culture of HCWs

Identifying individual and organizational predictors of accidental exposure to blood (AEB) among hospital healthcare workers: A longitudinal study

International audienceBackground: 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. Data were collected from the Stress at Work and Infectious Risk in Patients and Caregivers (STRIPPS) study. Eligible participants included nurses, nursing assistants, midwives, and physicians from 32 randomly selected wards in 4 hospitals. AEB occurrences were reported at baseline, 4 months, 8 months, and 12 months, and descriptive statistical and multilevel risk-factor analyses were performed. Results: The study included 730 HCWs from 32 wards, predominantly nurses (52.6%), nursing assistants (41.1%), physicians (4.8%), and midwives (1.5%). The incidence rate of AEB remained stable across the 4 visits. The multilevel longitudinal analysis identified several significant predictors of AEB occurrence. Individual-level predictors included younger age, occupation as nurses or midwives, irregular work schedule, rotating shifts, and lack of support from supervisors. The use of external nurses was the most significant ward-level predictor associated with AEB occurrence. Conclusions: AEBs among HCWs are strongly associated with organizational predictors, highlighting the importance of complementing infection control policies with improved staff management and targeted training. This approach can help reduce AEB occurrences and enhance workplace safety for HCWs

A multilevel approach to individual and organizational predictors of stress and fatigue among healthcare workers of a university hospital: A longitudinal study

This article is a preprint and has not been peer-reviewed. It reports new medical research that has yet to be evaluated and so should not be used to guide clinical practice.Objective Healthcare workers 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 organizational levels. Using a multi-center prospective cohort, this study aims to identify the individual and organizational predictors of stress and fatigue of healthcare workers in several wards from university hospitals. Methods Our cohort consist of 695 healthcare workers from 32 hospital wards drawn at random within four volunteer hospital centers in Paris-area. Three-level longitudinal analyses, accounting for repeated measures (level 1) across participants (level 2) nested within wards (level 3) and adjusted for relevant fixed and time varying confounders were performed. Results At baseline, the sample was composed by 384 registered nurses, 300 auxiliary nurses and 11 midwives. According to the 3-level longitudinal models, some predictors were found in common for both stress and fatigue (low support from the hierarchy, low safety culture, overcommitment at work, presenteeism while sick…). However, specific predictors for high level of stress (negative life events, low support from the colleagues and high frequency of break cancellation) and fatigue (commuting duration, frequent use of interim staff in the ward…) were also found. Conclusion Our results may help identify at-risk healthcare workers and wards, where interventions to reduce stress and fatigue should be focused. These interventions could include manager training to favor better staff support and overall safety culture of healthcare workers. 1. What is already known about this subject? Healthcare workers have high levels of perceived stress and fatigue, particularly in medical fields highly exposed to infectious risks. High occupational stress and fatigue can negatively affect healthcare workers behaviors in terms of absenteeism, and ultimately intention to leave as well as quality of care. Individual and organizational differences contribute to different perceptions and consequences of occupational stress and fatigue in healthcare workers. 2. What are the new findings? The ward-level environment significantly influences the stress and fatigue of healthcare workers, in addition to individual factors and time variations. Hierarchy providing low support and with low safety culture, work overinvestment, presenteeism while sick, and working in smaller wards were identified as predictors of both high stress and fatigue of healthcare workers. Negative life events (whether personal or professional), low support from the colleagues and high frequency of break cancellation are specific predictors of high level of stress. While commuting duration, frequent use of interim staff and working in a medical ward were associated with high level of fatigue. 3. How might this impact on policy or clinical practice in the foreseeable future? In this study, we can identify some areas for improvement to better prevent stress and fatigue for healthcare workers. High stress and fatigue can be reduced through mutual and specific organizational intervention strategies

Monitoring sick leave data for early detection of influenza outbreaks

Posté sur MedRxiv le 30 mai 2020Background - 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. Aim - To study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks Methods - Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells from 2010 to 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. Results - Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and specificity (86%), and detected outbreaks on average 2.5 weeks earlier. Conclusion - Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks