| Popis: |
We aim to re-analyse longitudinal data from 2016 to 2019 of the IAB-BAMF-SOEP survey using Growth Mixture Models. Previous cross-sectional variable-centered research with the IAB-BAMF-SOEP data has shown that the mental health and life satisfaction of refugees in Germany are highly correlated and below the national average (Metzing et al., 2020; Paiva Lareiro et al., 2020). Ambrosetti et al. (2021) found that receiving a secure asylum status is associated with increasing life satisfaction, while an insecure asylum status is associated with lower life satisfaction. Additionally, post-migration stressors such as insecure asylum status, unemployment, crowded housing, and seeking family reunification have been identified as risk factors for depression and low life satisfaction (Nutsch & Bozorgmehr, 2020; Walther et al., 2020). Based on these findings, we will investigate the development of the psychosocial well-being of refugees in Germany. In particular, we will analyze differences in anxiety and depression symptom scores depending on the legal asylum status between 2016 and 2019. We aim to gain a nuanced understanding of the refugee population and add a new perspective to existing variable-centered research by taking a person-centered longitudinal approach. We will identify subgroups (latent classes) with varying life satisfaction levels and explore the longitudinal development. Furthermore, our analysis will explore how various factors of the asylum process, such as legal asylum status, housing, employment status, whether the official hearing has taken place, whether a spouse lives outside of Germany, and whether children live outside of Germany, are related to the likelihood of belonging to specific subgroups. Thus, our longitudinal analysis can provide insights into potential psychosocial risk factors, identify subgroups with distinct needs, and guide targeted clinical and political interventions for different subgroups and the refugee population as a whole. |
