Predictors of employees' early retirement intentions: an 11-year longitudinal study.
BACKGROUND
Adjusting work life and encouraging older employees to continue at work has become a common challenge as the workforce ages. Gender differences in retirement decisions have largely been overlooked in previous studies, despite the fact that retirement as a life course event and the experience of retirement can be gender dependent.


OBJECTIVE
To explore which personal and work-related psychological factors predict early retirement intentions among older women and men and to investigate the stability of these predictors through use of longitudinal data.


METHODS
This research is based on an 11-year follow-up study of ageing Finnish municipal employees. Data on 1101 employees' early retirement intentions were analysed with binary logistic regression analysis in separate longitudinal and cross-sectional models.


RESULTS
Gender differences in early retirement intentions were detected both at baseline and at follow-up. Negative perceptions about work and low work and general life satisfaction were associated with early retirement intentions among women. For men, good self-rated work ability and perceived good health were negatively associated with early retirement intentions. In addition, negative perceptions about work predicted early retirement intentions among men.


CONCLUSIONS
Adverse work- or health-related factors detected in middle age predicted subsequent early retirement intentions.
von Bonsdorff
Monika E
ME
The Finnish Institute of Occupational Health, Topeliuksenkatu 41 a A, FIN-00250 Helsinki, Finland. monika.bonsdorff@ttl.fi
Huuhtanen
Pekka
P
Tuomi
Kaija
K
Seitsamo
Jorma
J
D000368:Aged; D000375:Aging / Q000523:psychology; D004651:Employment / Q000523:psychology* / Q000706:statistics & numerical data; D004812:Epidemiologic Methods; D005260:Female; D005387:Finland / Q000453:epidemiology; D006304:Health Status; D006801:Humans; D033182:Intention; D008297:Male; D008875:Middle Aged; D009790:Occupations / Q000706:statistics & numerical data; D010415:Pensions; D010549:Personal Satisfaction; D012179:Retirement / Q000523:psychology / Q000706:statistics & numerical data*; D012737:Sex Factors