Unwanted sexual advances at work: variations by employment arrangement in a sample of working Australians.
OBJECTIVE
We tested the hypothesis that the risk of experiencing unwanted sexual advances at work (UWSA) is greater for precariously-employed workers in comparison to those in permanent or continuing employment.


METHODS
A cross-sectional population-based telephone survey was conducted in Victoria (66% response rate, N=1,101). Employment arrangements were analysed using eight differentiated categories, as well as a four-category collapsed measure to address small cell sizes. Self-report of unwanted sexual advances at work was modelled using multiple logistic regression in relation to employment arrangement, controlling for gender, age, and occupational skill level.


RESULTS
Forty-seven respondents reported UWSA in our sample (4.3%), mainly among women (37 of 47). Risk of UWSA was higher for younger respondents, but did not vary significantly by occupational skill level or education. In comparison to Permanent Full-Time, three employment arrangements were strongly associated with UWSA after adjustment for age, gender, and occupational skill level: Casual Full-Time OR = 7.2 (95% Confidence Interval 1.7-30.2); Fixed-Term Contract OR = 11.4 (95% CI 3.4-38.8); and Own-Account Self-Employed OR = 3.8 (95% CI 1.2-11.7). In analyses of females only, the magnitude of these associations was further increased.


CONCLUSIONS
Respondents employed in precarious arrangements were more likely to report being exposed to UWSA, even after adjustment for age and gender.


CONCLUSIONS
Greater protections from UWSA are likely needed for precariously employed workers.
Melbourne School of Population Health, University of Melbourne, Victoria, Australia. alamonta@unimelb.edu.au
Anthony D
AD
Lamontagne
Peter M
PM
Smith
Amber M
AM
Louie
Michael
M
Quinlan
Jean
J
Shoveller
Aleck S
AS
Ostry
D000293:Adolescent; D000328:Adult; D001315:Australia; D003430:Cross-Sectional Studies; D004651:Employment / Q000523:psychology / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009790:Occupations / Q000145:classification / Q000706:statistics & numerical data*; D017678:Sex Distribution; D017406:Sexual Harassment / Q000523:psychology / Q000706:statistics & numerical data*; D017132:Workplace / Q000523:psychology*; D055815:Young Adult