Journal article

Employment predictors of exit from work among workers with disabilities: A survival analysis from the household income labour dynamics in Australia survey

Allison Milner, Yamna Taouk, George Disney, Zoe Aitken, Jerome Rachele, Anne Kavanagh

PLOS ONE | PUBLIC LIBRARY SCIENCE | Published : 2018

Abstract

OBJECTIVES: Across high-income countries, unemployment rates among workers with disabilities are disproportionately high. The aim of this study was to identify characteristics of employment associated with dropping out of work and assess whether these were different for workers with versus without disabilities. METHODS: Using a longitudinal panel study of working Australians (2001 to 2015), the current study estimated Kaplan-Meier curves and Cox proportional hazard regression models to identify predictors of leaving employment, including psychosocial job quality, employment arrangement, and occupational skill level. Effect modification by disability status of the relationship between employm..

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Grants

Awarded by Australian Research Council


Awarded by NHMRC Partnership Project


Funding Acknowledgements

[ "AM received funding from the Victorian Health and Medical Research Fellowship, Department of Health, State Government of Victoria (AU); AK and AM received funding from the Australian Research Council Linkage Project (LP150100077); AM and AK received funding from the NHMRC Partnership Project (APP1151843). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript", "This paper uses unit record data from the Household, Income and Labour Dynamics in Australia HILDA) Survey. The HILDA Project was initiated and is funded by the Australian Government Department of Social Services DSS) and is managed by the Melbourne Institute of Applied Economic and Social Research Melbourne Institute). The findings and views reported in this paper, however, are those of the author and should not be attributed to either DSS or the Melbourne Institute. The data used in this paper was extracted using the Add-On Package PanelWhiz for Stata. PanelWhiz (http://www.PanelWhiz.eu) was written by Dr. John P. Haisken-DeNew (john@PanelWhiz.eu)." ]