Barriers and enablers to returning to work from long-term sickness absence: Part I-A quantitative perspective.
BACKGROUND
Long-term sickness absence (LTSA) in the United Kingdom labor market has become a major health issue in recent years. In contrast to short-term sickness absence, rates for LTSA have been on the increase. This paper, part 1 of a two-part paper, identifies individual domain barriers to returning to work (RTW) from LTSA across the work disability timeline in the UK labor market.


METHODS
This is a retrospective cohort study of 6,246 workers from an occupationally diverse Police Force within the UK using a large administrative database. A series of chi-squared analyses were conducted to analyze the between and within group associations. Next, multiple logistic regression analyses using the Enter method were performed to develop a predictive model for RTW and Absence Phase.


RESULTS
Findings substantiated the presence of individual domain barriers to RTW and predictors of RTW outcome and established the absence phase specificity of a number of risk factors of prolonged work disability. In particular, injury/illness especially mental ill health (MIH), physical job demands, sex, and number of episodes of LTSA are significant individual domain barriers to RTW and represent important risk factors for prolonged work disability.


CONCLUSIONS
Duration of work disability is associated with medical diagnosis, especially MIH, physical job demands, sex, and number of LTSA episodes. Findings also support the importance of using the outcome measure of absence phase of risk factors in addition to RTW outcome.
Board
Belinda J
BJ
Department of Psychology, University of Surrey, UK. belinda@peoplewise.co.uk
Brown
Jennifer
J
D000041:Absenteeism; D000367:Age Factors; D016009:Chi-Square Distribution; D002908:Chronic Disease / Q000453:epidemiology; D015331:Cohort Studies; D004185:Disability Evaluation; D004651:Employment / Q000706:statistics & numerical data*; D005069:Evaluation Studies as Topic; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009784:Occupational Diseases / Q000175:diagnosis / Q000453:epidemiology*; D016495:Police; D012189:Retrospective Studies; D012307:Risk Factors; D012737:Sex Factors; D018582:Sick Leave / Q000706:statistics & numerical data*; D018434:Sickness Impact Profile; D013997:Time Factors; D006113:United Kingdom; D014937:Work / Q000523:psychology / Q000706:statistics & numerical data*