Research Design The Women at Work Study (WAW) targeted women aged 40 years and over, in academic, administrative and executive level roles at three Australian Universities. Data were collected via an online survey over a two-month period, between November 2013 and January 2014. The study was promoted through the Universities’ communication channels, including all-staff emails and advertisements on staff intranet homepages. A click through link to the online survey was provided. The online survey included questions relating to health and lifestyle; well-being; menstrual status and menopause-related symptoms; employment conditions; job characteristics and work outcomes. The survey included widely used and well-validated scales to assess women’s health (e.g. SF-12v2, Maruish, 2012) and women’s enjoyment and engagement at work (e.g. work engagement, Schaufeli et al., 2006; and job satisfaction, Cammann et al., 1983). The project was approved by the ethics committees of all institutions involved.
Sample The Women at Work survey was completed by 839 female university employees aged 40 years and over, who were employed as academic, administrative or executive level staff:
Uni A (421) 18.9% of the known population of female staff aged 40+;
Uni B (259) 6.7% of the known population of female staff aged 40+; and
Uni C (159) 17.2% of the known population of female staff aged 40+.
The percentage of participants in each position type from each participating University is presented below in Table 1.
Table 1 – Percentage of sample in each position type by participating University
Uni A (N=421)
Uni B (N=259)
Uni C (N=159)
The percentage of participants by position title is presented separately for academic and administrative staff in Table 2. Note: in this table, administrative staff includes executive level staff.
Table 2 – Percentage of academic and administrative staff by position title*
Academic Staff (N=328)
Administrative Staff (N=511)
Coordinator or Supervisor
Senior Research Fellow
Principal Research Fellow
*Tallies do not add to total N because of missing data.
Data Analysis Responses from the three participating Universities were combined for the analyses presented in this report (N=839). Regressions, T-tests, ANOVAs and Chi-Square statistical tests were used to test for significant differences between age groups (40 to 49 year olds; 50 to 59 year olds; and 60+ year olds), menstrual status groups (pre-menopausal; peri-menopausal; and post-menopausal) and position types (academic; and administrative/executive level). Differences in mean scale scores and differences in percentages are only reported in text if they are statistically significant at p<.05.