Investigating the aftermath of the Türkiye 2023 earthquake: exploring post-disaster uncertainty among Syrian migrants using social network analysis with public health approach.

Objectives: On February 6th, 2023, a doublet earthquake struck Türkiye, impacting more than 15 million people including migrants, and resulting in over 50,000 deaths. The Syrian migrants experience multiple uncertainties in their daily lives which are further compounded by multifaceted challenges of the post-disaster environment. Social media was used intensively and with impunity in this environment and thereby provides a window into the explicit and implicit dynamics of daily life after a disaster. We aimed to explore how a post-disaster environment potentially generates new uncertainties or exacerbating pre-existing ones for migrants through social media analysis with an indirect perspective, in the context of 2023-Earthquake in Türkiye and Syrian migrants. Methods: Social network analysis was used to analyze Twitter-data with the hashtags 'Syrian' and 'earthquake' during a 10-day period beginning on March 22nd, 2023. We calculated network metrics, including degree-values and betweenness-centrality and clustered the network to understand groups. We analyzed a combination of 27 tweets with summative content analysis using a text analysis tool, to identify the most frequently used words. We identified the main points of each tweet and assessed these as possible contributors to post-disaster uncertainty among migrants by using inductive reasoning. Results: There were 1918 Twitter users, 274 tweets, 124 replies and 1726 mentions. Discussions about Syrian migrants and earthquakes were established across various groups (ngroups(edges > 15) = 16). Certain users had a greater influence on the overall network. The nine most frequently used words were included under uncertainty-related category (nmost_frequently_used_words = 20); 'aid, vote, house, citizen, Afghan, illegal, children, border, and leave'. Nine main points were identified as possible post-disaster uncertainties among migrants. Conclusion: The post-disaster environment has the potential to exacerbate existing uncertainties, such as being an undocumented migrant, concerns about deportation and housing, being or having a child, inequality of rights between being a citizen and non-citizen, being in minority within minority, political climate of the host nation and access to education or to generate new ones such equitable distribution of aid, which can lead to poor health outcomes. Recognizing the possible post-disaster uncertainties among migrants and addressing probable underlying factors might help to build more resilient and healthy communities.

The adaptation of Turkish health literacy scale for literate Syrian adult refugees living in Turkey: a reliability-validity study.

BACKGROUND: Turkey hosts the world's largest refugee population of whom 3.5 million are Syrians and this population has been continuously growing since the year 2011. This situation causes various problems, mainly while receiving health-care services. In planning the migrant health-care services, for the policy makers of host countries, health literacy level of migrants is an important measure. Determination of health literacy level of Syrian refugees in Turkey would be supportive for planning some interventions to increase health-care service utilization, as well as health education and health communication programs. An "original health literacy scale" for 18-60 years of age Turkish literate adults (Hacettepe University Health Literacy Scale-HLS) was developed to be used as a reference scale in 2018. Since it would be useful to compare the health literacy levels of Turkish adults with Syrian adult refugees living in Turkey with an originally developed scale, in this study, it was aimed to adapt the HLS-Short Form for Syrian refugees. METHODS: This methodological study was carried out between the years 2019-2020 in three provinces of Turkey where the majority of Syrians reside. The data was collected by pre-trained, Arabic speaking 12 interviewers and three supervisors via a questionnaire on household basis. At first, the original Scale and questionnaire were translated into Arabic and back translated into the original language. The questionnaire and the Scale were pre-tested among 30 Syrian refugees in Ankara province. A total of 1254 refugees were participated into the main part of the study; 47 health-worker participants were excluded from the validity-reliability analysis. Confirmatory factor analysis (CFA) was performed. Cronbach's alpha and Spearman-Brown coefficients were calculated. RESULTS: Of the participants, 52.9% was male; 26.1% had secondary education level or less; almost half of them had moderate economic level; 27.5% could not speak Turkish. The Cronbach's Alpha was 0.75, Spearman-Brown Coefficient was 0.76; RMSEA = 0.073, CFI = 0.93, TLI = 0.92 and GFI = 0.95 for the Scale. The Cronbach's Alpha was 0.76, Spearman-Brown Coefficient was 0.77; RMSEA = 0.085, CFI = 0.93, TLI = 0.91 and GFI = 0.95 for self-efficacy part. CONCLUSION: In conclusion, the adapted HLS would be a reliable instrument to evaluate the health-literacy level of Syrian refugees living in Turkey and could allow for a comparison of the host country's health literacy level to that of the refugees using the same scale.

Global overview of refugees: comparison of 2005 and 2015 data for the 10 most affected countries.

BACKGROUND: The refugee problem has become a global concern with multidimensional characteristics. Monitoring migration flows over time and comparing the situation with a number of indicators can give clues on how to manage the problem. AIMS: In this study, the global refugee issue was discussed by focusing on such data including the potential factors causing crises in the most affected countries. METHODS: In this ecological study, the analysis was completed for the countries that either "host" or "source" refugees between 2005 and 2015. Excel-dataset was formed for United Nations Development Programme (UNDP), World Bank and United Nations High Commissioner for Refugees (UNHCR) datasets and were converted to SPSS-23.0. Mapping was done via pixelmap. RESULTS: In 2005, Pakistan, Islamic Republic of Iran, and the United States of America were the first three on the hosting country list, while Germany ranked 8th and China 9th. In 2015, Turkey ranked first as hosting country while previously it was not even in the top 10 countries. Geographical proximity plays a crucial role during displacement. Countries differ from each other according to the values of selected indices. CONCLUSIONS: Global solutions integrated with local precautions to reduce the worldwide burden of migration are required.