All time references are in CEST
Surveying Ukrainian Refugees in Europe: Implementation, Methods, Challenges, and Exchange of Experiences 1 |
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| Session Organisers |
Dr Jean Philippe Décieux (Federal Institure for Population Research) Mrs Silvia Schwanhäuser (Institute for Employment Research) |
| Time | Thursday 20 July, 09:00 - 10:30 |
| Room | U6-01a |
Since the start of the war in the Ukraine, many Ukrainians became internally displaced people or sought refuge in the surrounding European countries. So far, nearly 10 million border crossings from Ukraine have been registered and more than 6 million individual refugees from Ukraine were recorded across Europe (27 July 2022). This massive displacement and inflow of refugees within a short period of time generally poses a significant challenge for local and national politics, administration and society of the refuge giving countries. Hence, there is a need for appropriate empirical evidence, in order to take efficient actions, grant needed support, and helping effective social integration.
In response to this growing demand, a large number of survey projects have been initiated in Europe. These projects all face special circumstances and conditions: On the one hand, Ukrainian refugees constitute a hard-to-reach survey population that is only insufficiently represented within common sampling frames, as they are allowed for a visa-free entry within the EU states and temporary admission without asylum procedures. Moreover, they are often accommodated by friends or family in the destination country and are highly mobile within their first months of arrival. On the other hand, they form a highly-digitalized group and mostly own a (mobile-)device to proceed web surveys.
We would like to bring projects surveying Ukrainian refugees together for an exchange of their experiences and to discuss survey methodological and practical challenges. We particularly encourage submissions that offer a perspective on the following dimensions of survey research:
• Different sampling strategies and approaches
• Approaches to reach the target population
• Different survey Designs and Modes
• Questionnaire design and translation
• Fieldwork organization and monitoring
• Attrition, follow-up rules, and experiences in tracing respondents’ return or onward migration
• Innovative tracking techniques for longitudinal designs
Keywords: hard-to-reach; refugee survey; sampling; probaility vs. non-probability sampling
Dr Hans Walter Steinhauer (German Institute for Economic Research) - Presenting Author
Dr Jean Philippe Décieux (Federal Institute for Population Research)
Dr Andreas Ette (Federal Institute for Population Research)
Dr Manuel Siegert (Federal Office for Migration and Refugees)
Professor Sabine Zinn (German Institute for Economic Research)
After Russia’s invasion of Ukraine in early 2022 millions of Ukrainians fled their country. By now more than one million of these have found refuge in Germany. Integrating such a large number of refugees is challenging. Although having learned from the refugee crisis in 2015 and after, this influx of Ukrainian refugees differs in many aspects concerning demographics, perceived acceptance, allocation, and migration flows. In order to learn about the recently arriving refugees, their needs, and resources, as well as challenges ahead, a survey allowing for generalization to this population was urgently needed. To ease this need quickly, we developed a novel sampling strategy to create a random sample for the population of Ukrainian refugees using of two different registers; namely the central register for foreigners (AZR) and the local residents register (EMR). Being able to access both registers allows for profiting from each registers’ advantages, while compensating their disadvantages. Having access to both registers, we were able to show that both consistently cover the population of Ukrainian refugees. Using information from the AZR allowed us to sample 100 municipalities at the first stage based on the number of Ukrainian refuges. Within each sampled municipality all refugees aged 18 to 70 were listed with their address from the corresponding EMR at the second stage. This resulted in a list consisting of addresses to sample from at the second stage. To minimize the risk of sampling multiple refugees from the same household we sorted the list by address and family name and implemented a systematic random sampling at the second stage. This sampling design results in an initial sample of 48,000 individuals in regions with a high density of Ukrainian refuges while also mapping the characteristics of the population.
Mr Thomas Hinz (University of Konstanz) - Presenting Author
Ms Valeriia Sazonova (KNU Kyiv)
Mr Taras Tsymbal (KNU Kyiv)
In this paper, we describe how the total population of Ukrainians living in a small town in Germany was approached to take part in a survey study on living conditions, choice of location, legal status, and other issues. The survey was fielded in December 2022, size of total population was N=966 (registered addresses). All members of the total population received an invitation in Ukrainian (and German) language to participate in the survey – either by returning a paper questionnaire by regular mail or scanning a QR code to start an online survey on mobile devices. In addition, we made use of local telegram chat channels of refugees to reach out for (further) potential participants. Since there is precise information about the composition of the total population, analyses first focus on selective mode choice (PAPI vs. online) and on potential selection bias of network recruiting as well. A side-effect of the research is that the administrative register as a source to connect to refugees can be evaluated. Besides basic socio-economic information, we addressed a variety of political and at least partly sensitive issues (e.g. a trauma short scale). The paper analyses if these topics trigger distinct reactions by survey mode and recruiting mode. In general, the paper contributes to the discussion how refugee population can be surveyed – without substantial biases.
Dr Oksana Senyk (Ukrainian Catholic University)
Dr Anastasiia Shyroka (Ukrainian Catholic University) - Presenting Author
Dr Tetiana Zavada (Ukrainian Catholic University)
Ms Olena Vons (Ukrainian Catholic University)
Professor Anna Kornadt (University of Luxembourg)
Data were collected online from May until September 2022 and participants were contacted both personally and electronically. Research materials were distributed at places of residence for displaced persons such as governmental shelters for Ukrainian refugees and different institutions organized by Ukrainian refugees abroad (e.g., Ukrainian cultural centers, summer camps for Ukrainian children). Potential participants were contacted personally with the help of flyers distributed at the abovementioned places or electronically by the authorities of the listed organizations after they approved the study. Contact was also made through different communities of Ukrainians in social networks like Facebook or Telegram. Overall, participants’ response rate in the social networks was very low: only 2-3 persons out of 1000 participated in the study. Personal contact and invitation to participate were more successful: among those displaced abroad about 1 in 40 contacted persons eventually filled in the survey, while for internally displaced persons contacted via social workers the response rate was about 60-80%. The final study sample consists of N = 340 Ukrainian adults (97% females) aged 18-55, who fled the war from 23 different regions of Ukraine to the other safer Ukrainian regions (N=100) or abroad (N=240). The majority of our participants had their basic needs satisfied at average to high levels (from 58% reporting to have a place to live during the nearest months, to 90-98% having access to food, hygiene products and medical care). Our findings show difficulties to reach participants online, and also an under representation of those with severe life conditions. Response rate was higher with personal contact, thus, a more personal approach seems most promising to collect data in vulnerable populations.