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. 2023 Feb 21:11:1125496.
doi: 10.3389/fpubh.2023.1125496. eCollection 2023.

Gender equality in the Italian academic context. Results from the IGEA project

Affiliations

Gender equality in the Italian academic context. Results from the IGEA project

Giovanna Deiana et al. Front Public Health. .

Abstract

The Innovation for Gender Equality in Academia (IGEA) project is focused on the analysis of the gender composition in academia, on the identification of the health needs of the academic population and on the assessment of their organizational wellbeing, in order to promote equal working conditions and opportunities. The study, focused on the identification of health needs, involved the construction of an ad hoc questionnaire in order to collect the socio-demographic characteristics and the perception of working environment of the participants. Differences between males and females were evaluated by the Mann-Whitney test, and Pearson Chi-Square or Fisher exact tests as appropriate, highlighting significant differences between genders regarding the occurrence of anxiety, panic, irritation and annoyance related to work activities. A multivariate logistic regression analysis was performed to identify factors associated with the perception of work-related anxiety/panic, showing a direct association with the difficulty in work performance and the work-related stress during the pandemic period, whereas, an indirect association was found with job satisfaction and the feeling of being appreciated by colleagues. Occupational stress can increase the risk of developing physical and mental conditions, also affecting work performance and absenteeism. It is therefore fundamental to plan targeted interventions, implement policies and specific actions, in order to avoid and reduce any differences related to gender.

Keywords: academic staff; gender equality; occupational stress; university; workplace.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Forest plot of multivariate logistic regression results (OR, 95% CI).

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