Literature DB >> 28207074

Prediction of long-term and frequent sickness absence using company data.

C R L Boot, A van Drongelen, I Wolbers, H Hlobil, A J van der Beek, T Smid.   

Abstract

Year:  2017        PMID： 28207074     DOI： 10.1093/occmed/kqx014

Source DB:  PubMed          Journal:  Occup Med (Lond)        ISSN： 0962-7480            Impact factor:   1.611


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  3 in total

1.  Patterns and predictors of sick leave among Swedish non-hospitalized healthcare and residential care workers with Covid-19 during the early phase of the pandemic.

Authors:  Marta A Kisiel; Tobias Nordqvist; Gabriel Westman; Magnus Svartengren; Andrei Malinovschi; Helena Janols
Journal:  PLoS One       Date:  2021-12-09       Impact factor: 3.240

2.  Quantifying the impact of environment factors on the risk of medical responders' stress-related absenteeism.

Authors:  Mario P Brito; Zhiyin Chen; James Wise; Simon Mortimore
Journal:  Risk Anal       Date:  2022-03-14       Impact factor: 4.302

3.  Long-term sickness absence in a working population: development and validation of a risk prediction model in a large Dutch prospective cohort.

Authors:  Lennart R A van der Burg; Sander M J van Kuijk; Marieke M Ter Wee; Martijn W Heymans; Angelique E de Rijk; Goedele A Geuskens; Ramon P G Ottenheijm; Geert-Jan Dinant; Annelies Boonen
Journal:  BMC Public Health       Date:  2020-05-15       Impact factor: 3.295
  3 in total

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