Statistical Characteristics of the Integration Process of Ukrainian Refugees in Germany (Based on a Pilot Survey)

The phenomenon of forced migration of Ukrainians because of the war in Ukraine remains highly relevant and calls for sociological surveys to provide a statistical assessment of the intentions of Ukrainians granted temporary protection in Europe between 2022 and 2024, considering their psycho-emotional state and living conditions. Temporary protection is an exceptional status established to provide immediate and temporary protection to displaced persons from non-EU countries who are unable to return to their country of origin. This status was first activated on March 4, 2022, in response to the full-scale invasion of Russia into the territory of Ukraine, to offer quick and effective assistance to people fleeing the war in Ukraine. This article, based on a survey of Ukrainian refugees who received temporary protection during the full-scale war in Ukraine, analyses the key factors influencing their integration into a new socio-cultural environment and their willingness to remain abroad. The data for this study was collected in 2024 through a survey of Ukrainian refugees living in Germany. The sample included 145 participants, selected via snowball sampling and self-selection methods, with stratification by gender, age, and employment status. The article explores the theoretical and methodological foundations of this pilot sociological survey and provides a critical review of prior studies on Ukrainian refugees abroad. The socio-demographic profile of the survey participants, who have received temporary protection in Germany, is presented, along with a statistical description of factors affecting their psycho-emotional state, living conditions, and future intentions. A statistical evaluation was conducted to assess the factors influencing the adaptation of Ukrainian refugees to the new socio-cultural environment. Additionally, the analysis identifies the significant factors affecting the refugees’ willingness to remain in Germany on a permanent basis after the war. The study also developed several binary regression models (probit models) to estimate the likelihood of Ukrainians not returning to their homeland after the war. Based on these binary classification models, a final model was constructed, which may be used to estimate potential losses in the working-age population, the decline in natural population growth, and the overall impact on the demographic situation in Ukraine.