Program at a glance 2021
Investigations upon various (social) political inquiries
|Session Organiser|| Dr Brita Dorer (gesis)
|Time||Friday 16 July, 15:00 - 16:30|
How Many Older Informal Caregivers Are There in Europe? Comparison of Estimates of Their Prevalence from Three European Surveys
Professor Aviad Tur-Sinai (The Max Stern Yezreel Valley College) - Presenting Author
Professor Andrea Teti (University of Vechta)
Professor Alexander Rommel (Robert Koch-Institute)
Professor Valentina Hlebec (University of Ljubljana)
Dr Giovanni Lamura (INRCA IRCCS—National Institute of Health and Science on Ageing)
Informal caregivers are people providing some type of unpaid, ongoing assistance to a person with a chronic illness or disability. Long-term care measures and policies cannot take place without taking into account the quantitatively crucial role played by informal caregivers. We use the European Health Interview Survey (EHIS), the European Quality of Life Survey (EQLS), and the Study on Health and Ageing in Europe (SHARE) to measure the prevalence of informal caregivers in the European population, and analyze associated socio-demographic factors. These surveys represent the only surveys delivering regular data on the investigated topic at a European level.
This rate ranges between about 13 percent in Portugal and Spain, and more than 22 percent in Luxembourg, Belgium, and Denmark. It declines in older age groups and, on average, is lower in men than in women in all countries studied, and lower among the poorly educated compared to those with higher levels of education. However, large variance was observed in the average share of informal caregivers for most countries between the three surveys. Our findings, estimated through the three surveys, reveal common trends, but also a series of disparities.
The main take-home message of this study is: given the large differences in the prevalence rates of informal caregiving reported for some countries by major studies in this field, data users should use current evidence deriving from these sources with caution. Data producers, on the other hand, should increase efforts to better understand why this divergence exists, and take action to possibly remove it, or more clearly explain the reasons behind such partly discording results. Additional research will be needed to enable policy makers to access a richer and more harmonized body of data, allowing them to adopt truly evidence-based and targeted policies and interventions in this field.
Using Mixed Method Research to Explore Organizations Supporting Migrants
Dr Stefania Kalogeraki (University of Crete) - Presenting Author
Organizations supporting migrants have become increasingly important specifically in countries hosting a significant number of migrants. Such organisations play a key role in immigrants’ lives and their socio-economic, cultural and political integration. Organizations supporting migrants may act as social service providers for newcomers restricted from access to health care and other social services. Moreover, these organizations act as community centres where immigrants can meet members of their own or other ethnic groups as well as learn important things in order to achieve economic stability and self-sufficiency as well as participate in social and political life. Organizations supporting migrants are particularly important in host countries that are not so welcoming for newcomers. By studying organisations in such contexts we collect valuable information about the settlement process of immigrants. Although numerous studies focus on the specific organizations, the majority of them are based on mono-method approaches, either quantitative or qualitative ones. The paper based on a mixed method approach and using data collected during the recent ‘refugee crisis’ in the context of the EU-funded TransSOL project provides some evidence on the distinct features of informal and formal migrant organizations uncovering their diverse roles in meeting migrants’ needs in Greece. Greece is an interesting case study to examine organizations supporting migrants as it hosts a significant number of migrants and during the recent ‘refugee crisis’ it became one of the major entry points by sea since a high number of refugees entered its territory en route to wealthier European countries. In addition, several studies demonstrate that Greeks report relatively higher rates of xenophobic stances and concerns about the potential negative impacts of migrants on the country compared to their European counterparts.
The paper applies a mixed method approach with the rationale of complementarity. The quantitative findings portray some key aspects (such as organizational structure, activities, ultimate aims and means to achieve them, etc.) of formal and informal migrant organizations operating in the country. The qualitative study investigates how representatives of migrant entities frame their solidarity initiatives uncovering an additional facet that complements specific quantitative findings. Specifically, informal organizations frame their solidarity initiatives in relation to migrants’ mobilization as the only means to claim their rights whereas formal organizations frame their solidarity initiatives in relation to the implementation of adequate policies. The paper contributes to the discussion on the value of mixed method designs in providing an enriched understanding of specific facets of the research theme under study.
Assessing the relationship between survey data and Twitter data as measures of public opinion - A methodological pilot study
Dr Johannes Breuer (GESIS - Leibniz Institute for the Social Sciences) - Presenting Author
Mr Felix Bensmann (GESIS - Leibniz Institute for the Social Sciences)
Professor Stefan Dietze (GESIS - Leibniz Institute for the Social Sciences)
Dr Ran Yu (GESIS - Leibniz Institute for the Social Sciences)
Ms Katarina Boland (GESIS - Leibniz Institute for the Social Sciences)
Large national and international survey programs, such as the Eurobarometer, the European Social Survey, or the World Values Survey provide rich and representative data on public opinions about a wide variety of subjects. While data from these survey programs are highly valuable and can be used to gain important insights, they have certain attributes that limit the ways in which they can be used for measuring public opinion. Most importantly, conducting these surveys is a costly and time-intensive effort, meaning that these data cannot be collected with a high frequency. A data source that provides data with much higher frequency and at a much lower cost is social media. While social media data cannot be sampled as purposively and contain much more noise than survey data, they can be used to capture changes in public opinion with high temporal granularity as well as direct reactions to events of societal relevance, including unforeseen events, such as the spread of the current COVID-19 pandemic. Despite the obvious differences between survey data and data from social media, they can both be used for assessing public opinion about different topics.
The aim of our study was to assess how trends in public opinion as measured by surveys and Twitter data correlate and which factors affect this relationship. To do this, we used Twitter data from the continuous TweetsKB data collection together with survey data from two studies. Our use cases were attitudes towards migration into the EU and willingness to get vaccinated against COVID-19. For the topic of migration, we used data from the Eurobarometer from the years 2014 to 2019. For the second use case, we used survey data from the German study COVID-19 Snapshot Monitoring (COSMO) from 2020. Using these two examples allowed us to compare correlations in trends in the two data sources for two different topics and different time spans. Specifically, we looked at the relationship over time between the sentiment of tweets about the two use case topics and the average opinions of survey respondents. A key challenge was to collect relevant tweets. To avoid biases in the selection, we used automated procedures for generating the seedlists for filter terms. Our approach automatically identifies relevant tweets for a given variable and computes a time series of sentiments corresponding to the respective survey variable trends. Overall, our results for the two topics show medium-strong correlations between the Twitter and survey data trends, whose size depends on the chosen parameters, such as the considered time window and sentiment type. Based on the findings from our methodological pilot study, we will present recommendations for research that wants to use Twitter data to measure public opinion or seeks to relate it to or combine it with survey data.
To survey or not to survey - A comparison of survey and micro simulation pension data for the very old
Mr Marvin Kraemer (Kantar) - Presenting Author
Dr Thorsten Heien (Kantar)
When collecting survey data of very old people, the question arises whether the interviewees are still able to give valid and reliable answers considering the higher risk of physical and mental restrictions. From a total survey error (TSE) perspective, this implies bigger measurement and representation problems for a given survey statistic. Therefore and in view of the rather stable living conditions of older people, in the survey on “Old-age security in Germany” (Alterssicherung in Deutschland; ASID) run for the Federal Ministry of Labour and Social Affairs, data for people aged 80+ is gathered by a micro simulation of older ASID survey data. The simulation model includes a) a demographic ageing including mortality processes, b) the calculation of survivor’s pensions and c) the projection of other incomes. With respect to the considerable improvement of older people’s health statuses in the last decades as part of the demographic change, for the ASID 2019 people aged 80 to 84 were interviewed for the very first time next to the ongoing simulation of data for people aged 80+. The paper analyses survey and simulation ASID data for people aged 80 to 84 and compares the results to external statistics (e.g. administrative data of the Statutory Pension Insurance) to validate both data sources.