RESISTIRE Survey analysis
As part of quantitative research activities in the RESISTIRÉ project, a free web and mobile application (app) survey - available in both Android and iOS mobile operating systems - has been designed to address the knowledge gaps identified through RESISTIRÉ’s research agenda. Quantitative data availability was identified as a key challenge in understanding how COVID-19-related policies impacted inequalities across Europe. While European and national-level RAS have been successful in mitigating some of these gaps, there remains a need for more granular and comparable data, especially with regard to intersectional minoritised groups. The RESISTIRÉ Study App and web survey was developed to meet these challenges and collect data through an intersectional lens and demonstrate how a gender+ perspective can be embedded within a research survey from the very beginning. The demographic questions captured various inequality grounds (age, gender, country of residence, sexual orientation, being a member of a minority ethnic group, living with a disability or chronic illness, trans identity, and educational level) to allow for an intersectional data collection. Substantial effort was also undertaken to translate the content of the survey into fourteen languages to maximise responses from participants.
This section provides a short analysis and visualisations of the survey data collected up to the closure of the survey on the 30th of July 2023, gathering 263 responses. It starts with sociodemographic data, followed by an analysis of the responses gathered in the five survey modules (employment, pay, care, working from home, and community and safety). The aim is to showcase how quantitative cross-country analysis can be performed through an intersectional lens. To do so, we employed statistical regression, simultaneously considering different inequality grounds while focusing on the questions with the highest response rates. We used the data gathered from both mandatory survey questions and questions that were utilised to generate instant visualisations on the mobile app as well as the web survey, specifically focusing on those with statistically significant results. Furthermore, we incorporated non-mandatory questions that revealed statistically significant findings, which are presented below for each module.