scholarly journals Work-Related Psychosocial Risk Factors for Long-Term Sick Leave

2014 ◽  
Vol 56 (8) ◽  
pp. 787-793 ◽  
Author(s):  
Cecilie Aagestad ◽  
Håkon A. Johannessen ◽  
Tore Tynes ◽  
Hans Magne Gravseth ◽  
Tom Sterud
Author(s):  
Sandra D. M. Bot ◽  
Caroline B. Terwee ◽  
Daniëlle A. W. M. van der Windt ◽  
Allard J. van der Beek ◽  
Lex M. Bouter ◽  
...  

2020 ◽  
Vol 70 (3) ◽  
pp. 203-206
Author(s):  
L Uronen ◽  
H Moen ◽  
S Teperi ◽  
K-P Martimo ◽  
J Hartiala ◽  
...  

Abstract Background Psychosocial risk factors influence early retirement and absence from work. Health checks by occupational health nurses (OHNs) may prevent deterioration of work ability. Health checks are documented electronically mostly as free text, and therefore the effect of psychological risk factors on working capacity is difficult to detect. Aims To evaluate the potential of text mining for automated early detection of psychosocial risk factors by examining health check free-text documentation, which may indicate medical statements recommending early retirement, prolonged sick leave or rehabilitation. Psychosocial risk factors were extracted from OHN documentation in a nationwide occupational health care registry. Methods Analysis of health check documentation and medical statements regarding pension, sick leave and rehabilitation. Annotations of 13 psychosocial factors based on the Prima-EF standard (PAS 1010) were used with a combination of unsupervised machine learning, a document search engine and manual filtering. Results Health check documentation was analysed for 7078 employees. In 83% of their health checks, psychosocial risk factors were mentioned. All of these occurred more frequently in the group that received medical statements for pension, rehabilitation or sick leave than the group that did not receive medical statement. Documentation of career development and work control indicated future loss of work ability. Conclusions This study showed that it was possible to detect risk factors for sick leave, rehabilitation and pension from free-text documentation of health checks. It is suggested to develop a text mining tool to automate the detection of psychosocial risk factors at an early stage.


PLoS ONE ◽  
2020 ◽  
Vol 15 (5) ◽  
pp. e0233472
Author(s):  
Astrid M. Chevance ◽  
Oumou S. Daouda ◽  
Alexandre Salvador ◽  
Patrick Légeron ◽  
Yannick Morvan ◽  
...  

Author(s):  
Valerio Ghezzi ◽  
Tahira M. Probst ◽  
Laura Petitta ◽  
Valeria Ciampa ◽  
Matteo Ronchetti ◽  
...  

While the role of individual differences in shaping primary appraisals of psychosocial working conditions has been well investigated, less is known about how objective characteristics of the employee profile (e.g., age) are associated with different perceptions of psychosocial risk factors. Moreover, previous research on the link between employment status (i.e., work contract) and such perceptions has provided mixed results, leading to contradictory conclusions. The present study was conducted on a nationally representative sample of theItalian employed workforce surveyed with computer-assisted telephone interviewing (CATI) methodology. The principal aim of the study is to bridge this gap in the extant literature by investigating the interplay between two key characteristics of the employee profile (i.e., age and work contract) in shaping employees’ perceptions of psychosocial risk factors. Given the disparate literature scenario on the interplay between age and employment status in shaping primary appraisals of psychosocial stressors, we formulated and compared multiple competitive informative hypotheses. Consistent with the principles of the conservation of resources (COR) theory, we found that older contingent employees reported a higher level of psychosocial risk than their permanent peers who, in turn, were more vulnerable than middle-aged and younger workers (regardless of their employment status). These results highlight the importance of simultaneously assessing multipleobjective variables of the employee profile (i.e., age and employment status) which may act to shape subjective perceptions of psychosocial risk factors for work-related stress. Given our findings, employers and policy makers should consider older contingent employees as one of the workforce sub-populationsmost vulnerable to negative work environments.


2017 ◽  
Vol 1 (S1) ◽  
pp. 27-27
Author(s):  
Kelly M. Bower ◽  
Deborah Gross ◽  
Margaret Ensminger ◽  
Jana Goins ◽  
Phyllis Sharps

OBJECTIVES/SPECIFIC AIMS: The purpose of this study is to understand factors that are associated with identifying which eligible pregnant women in Baltimore City accept a referral for HV services. Taking into account demographic and obstetrical variables, we will examine the extent to which 13 medical and 14 psychosocial risk factors differentiate pregnant women who (1) accepted a HV referral, (2) could not be located, or (3) refused a HV referral. METHODS/STUDY POPULATION: In this observational study, we will use secondary data on 8172 pregnant women collected by Health Care Access Maryland (HCAM) between 2014 and 2016. HCAM is the single point of entry for all pregnant women in Baltimore City into HV. HV eligibility includes being a pregnant woman, residing in Baltimore City, being uninsured or receiving Medicaid, and being identified by a prenatal care provider who completed an assessment profile of the woman’s medical and psychosocial risk (prenatal risk assessment). The outcome variable, HV engagement status (ie, accepted referral, could not be located, refused referral), will be based on HCAM discharge codes. Medical risk factors include BMI, hypertension, anemia, asthma, sickle cell, diabetes, vaginal bleeding, genetic risk, sexually transmitted disease, last dental visit >1 year ago, and taking prescription medications. Psychosocial risk factors include current pregnancy unintended; <1 year since last delivery; late entry to prenatal care (>20 wk gestation); mental, physical, or developmental disability; history of abuse or violence within past 6 months; tobacco use; alcohol use; illegal substance use within the past 6 months; resides in home built before 1978; homelessness; lack of social/emotional support; exposure to long-term stress; lack of transportation; and history of depression or mental illness. All risk factor variables are categorical (yes/no). Control variables will include demographics (eg, age, race, ethnicity, marital status, educational level) and OB history (eg, history of preterm labor, history of fetal or infant death). We will conduct descriptive statistics to characterize the sample and look for interrelatedness among the risk factors. Where there is a high level of inter-relatedness we will consider combining or omitting variables to reduce redundancy. We will use multinomial regression to examine which medical and psychological factors are associated with referral category. RESULTS/ANTICIPATED RESULTS: We hypothesize that (a) women with more medical risk factors will be more likely to accept a referral for HV services, (b) women with more psychosocial risk factors will be more likely to refuse HV or not be located, and (c) certain risk factors, such as depression/mental illness, history of abuse/violence, illegal substance use, homelessness, and exposure to long-term stress will be the strongest predictors of not accepting HV referral and/or not being located. DISCUSSION/SIGNIFICANCE OF IMPACT: The translation of effective randomized control trials (RCTs) to successful implementation in community-based programs can be challenging. Community-based programs serving low-income communities typically lack the same resources available to recruit and retain participants in RCTs. And, exclusion criteria applied in RCTs are often not applied in real world implementation which can open program to participants with more complex social and medical characteristics. Findings from this study will inform the translation of evidence-based HV programs into real world settings through an enhanced understanding of the characteristics of women who are not engaged by HV programs. This will inform development of improved outreach methods that may more effectively engage at-risk women for prenatal HV services.


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