Abstract

The European Social Survey (ESS) is an academically-driven multi-country survey, which has been administered in over 30 countries to date. Its three aims are, firstly - to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe's changing institutions, secondly - to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond, and thirdly - to develop a series of European social indicators, including attitudinal indicators.

In the seventh round, the survey covers 22 countries and employs the most rigorous methodologies. From Round 7 it is funded by the Members, Observers and Guests of ESS European Research Infrastructure Consortium (ESS ERIC) who represent national governments. Participating countries directly fund the central coordination costs of the ESS ERIC, as well the costs of fieldwork and national coordination in their own country.

The survey involves strict random probability sampling, a minimum target response rate of 70% and rigorous translation protocols. The hour-long face-to-face interview includes questions on a variety of core topics repeated from previous rounds of the survey and also two modules developed for Round 7 covering Social Inequalities in Health and their Determinants and Attitudes towards Immigration and their Antecedents (the latter is a partial repeat of a module from round 1).

Geographic coverage

1) European Union countries - Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Latvia, Lithuania, Netherlands, Poland, Portugal, Slovenia, Spain, Sweden, United Kingdom. 2) Non-European Union countries: Israel, Norway, Switzerland.

Analysis unit

Individuals

Universe

All persons aged 15 and over, residing within private households, regardless of their nationality, citizenship, language or legal status, in participating countries.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling procedure varied by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on how sampling was conducted in each of the 22 countries.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Austria - structured questionnaires in German Belgium - structured questionnaires in Dutch , French Czech Republic - structured questionnaires in Czech, Slovak (from the respondent's side - exceptional) Denmark - structured questionnaires in Danish Estonia - structured questionnaires in Estonian, Russian Finland - structured questionnaires in Finnish, Swedish, English France - structured questionnaires in French Germany - structured questionnaires in German Hungary - structured questionnaires in Hungarian Ireland - structured questionnaires in English Israel - structured questionnaires in Hebrew, Arabic and Russian Lithuania - structured questionnaires in Lithuanian and Russian Netherlands - structured questionnaires in Dutch Norway - structured questionnaires in Norwegian and English Poland - structured questionnaires in Polish Portugal - structured questionnaires in Portuguese Slovenia - structured questionnaires in Slovenian Spain - structured questionnaires in Spanish and Catalan Sweden - structured questionnaires in Swedish Switzerland - structured questionnaires in German/Swiss-German, French, Italian United Kingdom - structured questionnaires in English

Cleaning operations

Sampling procedure varied slightly by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on how data entry and editing was conducted in each of the 22 countries.

Response rate

Response rate varied by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on the response rate in each of the 22 countries.

Abstract

The European Social Survey (ESS) is an academically-driven multi-country survey, which has been administered in over 30 countries to date. Its three aims are, firstly - to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe's changing institutions, secondly - to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond, and thirdly - to develop a series of European social indicators, including attitudinal indicators.

In the sixth round, the survey covers 29 countries and employs the most rigorous methodologies. It is funded via the European Commission's 7th Framework Programme, the European Science Foundation and national funding bodies in each country.

The survey involves strict random probability sampling, a minimum target response rate of 70% and rigorous translation protocols. The hour-long face-to-face interview includes questions on a variety of core topics repeated from previous rounds of the survey and also two modules developed for Round Six covering Europeans' Understandings and Evaluations of Democracy and Personal and Social Wellbeing (the latter is a partial repeat of a module from round 3).

Geographic coverage

1) European Union countries - Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Italy, Lithuania, Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, United Kingdom. 2) Non-European Union countries: Albania, Iceland, Israel, Kosovo, Norway, Switzerland, Russian Federation, Ukraine.

Analysis unit

Individuals

Universe

All persons aged 15 and over, resident within private households, regardless of their nationality, citizenship, language or legal status, in participating countries.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling procedure varied by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on how sampling was conducted in each of the 29 countries.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Albania - structured questionnaires in Albanian and Greek (5 interviews). Belgium - structured questionnaires in Dutch, French Bulgaria - structured questionnaires in Bulgarian Cyprus - structured questionnaires in Greek Czech Republic - structured questionnaires in Czech, 2 interviews in Slovak, respondent induced. Denmark - structured questionnaires in Danish Estonia - structured questionnaires in Estonian, Russian Finland - structured questionnaires in Finnish, Swedish, English France - structured questionnaires in French Germany - structured questionnaires in German Hungary - structured questionnaires in Hungarian Iceland - structured questionnaires in Icelandic Ireland - structured questionnaires in English Israel - structured questionnaires in Hebrew, Arabic, Russian Italy - structured questionnaires in Italian Kosovo - structured questionnaires in Albanian, Serbian Lithuania - structured questionnaires in Lithuanian and Russian Netherlands - structured questionnaires in Dutch Norway - structured questionnaires in Norwegian, English (28 interviews), Arabic (1 interview). One interview in Arabic conducted with an interpreter present. Poland - structured questionnaires in Polish Portugal - structured questionnaires in Portuguese Russian Federation - structured questionnaires in Russian Slovakia - structured questionnaires in Slovak, Hungarian Slovenia - structured questionnaires in Slovenian Spain - structured questionnaires in Spanish and Catalan Sweden - structured questionnaires in Swedish Switzerland - structured questionnaires in German/Swiss-German, French, Italian Ukraine - structured questionnaires in Ukrainian, Russian United Kingdom - structured questionnaires in English

Cleaning operations

Sampling procedure varied slightly by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on how data entry and editing was conducted in each of the 29 countries.

Response rate

Response rate varied by country. Please see the "Documentation Report" available in the 'Documentation' section for detailed information on the response rate in each of the 29 countries.

Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

The survey studied several themes, including the use of media, social trust, political participation and interest, political trust, political orientation and commitment, satisfaction with own circumstances and certain public services, perceptions of own well-being, religious views, experiences of discrimination, and national and ethnic identity. These themes are recurring in different ESS rounds. Themes for the rotating modules in this collection round included timing of life events and pensions. The survey also charted participation in voluntary work and charity, subjective well-being, and satisfaction in job and wages. The self-administered follow-up questionnaire included the Schwartz Human Values Scale as well as test questions controlling the main questionnaire. Questions about income and income disparity were also asked. The respondents' socio-demographics were widely charted, including, among others, household composition, gender, age, type of neighbourhood, education, occupation, background information on spouse and parents, trade union membership, household income, and marital status.

Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

The Survey of Health, Ageing and Retirement in Europe (SHARE), is a longitudinal micro-data infrastructure created in response to a communication by the European Commission (2000) to the Council and the European Parliament, which identified population ageing and its social and economic challenges to growth and prosperity to be among the most pressing challenges of the 21st century in Europe. SHARE has also become one of the most prestigious social science infrastructures and was in 2011 the first to be appointed a European Research Infrastructure Consortium (ERIC) by the European Council.The overarching objective of SHARE is to better understand the interactions between bio-medical factors, the socio-economic environment and policy interventions in the ageing European populations. SHARE aims to achieve this objective by providing a research infrastructure for fundamental science as well as a tool for policy evaluation and design. Initiated in 2002, SHARE is scheduled to launch, all in all, 10 data collection waves. At present eight waves have been fulfilled and seven waves are available to the research community.

Please also cite the following publications in addition to the SHARE acknowledgement:

Malter, F. and A. Börsch-Supan (Eds.) (2017). SHARE Wave 6: Panel innovations and collecting Dried Blood Spots. Munich: Munich Center for the Economics of Aging (MEA). Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S. and Zuber, S. (2013). Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology DOI: 10.1093/ije/dyt088.

SHARE - Survey of Health, Ageing and Retirement in Europe - is a multidisciplinary and cross-national panel database. It provides micro data on health, socio-economic status and social and family networks of thousands individuals aged 50 or over and their (younger) partners. The Survey of Health, Ageing and Retirement in Europe seeks to analyse the process of population ageing in depth.

Copyright © Survey of Health, Ageing and Retirement in Europe (SHARE) 2012

When using data from this dataset, please cite the dataset as follows: Börsch-Supan, A. (2022). Survey of Health, Ageing and Retirement in Europe (SHARE) Wave 4. Release version: 8.0.0. SHARE-ERIC. Data set. DOI: 10.6103/SHARE.w4.800

Please also cite the following publications in addition to the SHARE acknowledgement: - Börsch-Supan A., M. Brandt , H. Litwin and G. Weber (Eds). (2013). Active ageing and solidarity between generations in Europe: First results from SHARE after the economic crisis. Berlin: De Gruyter. - Malter, F., Börsch-Supan, A.(Eds.) (2013). SHARE Wave 4: Innovations & Methodology. Munich: MEA, Max Planck Institute for Social Law and Social Policy. - Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan, B., Stuck, S., Zuber, S. (2013). Data Resource Profile: The Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology DOI: 10.1093/ije/dyt088.

Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

Average (mean) rating for 'Worthwhile' in the First ONS Annual Experimental Subjective Wellbeing survey.

The Office for National Statistics has included the four subjective well-being questions below on the Annual Population Survey (APS), the largest of their household surveys.

• Overall, how satisfied are you with your life nowadays?
• Overall, to what extent do you feel the things you do in your life are worthwhile?
• Overall, how happy did you feel yesterday?
• Overall, how anxious did you feel yesterday?

This dataset presents results from the second of these questions, "Overall, to what extent do you feel the things you do in your life are worthwhile?". Respondents answer these questions on an 11 point scale from 0 to 10 where 0 is ‘not at all’ and 10 is ‘completely’. The well-being questions were asked of adults aged 16 and older.

Well-being estimates for each unitary authority or county are derived using data from those respondents who live in that place. Responses are weighted to the estimated population of adults (aged 16 and older) as at end of September 2011.

This dataset contains the mean responses: the average reported value for respondents resident in each area. It also contains the standard error, the sample size and lower and upper confidence limits at the 95% level.

The data cabinet also makes available the proportion of people in each county and unitary authority that answer with ‘low wellbeing’ values. For the ‘worthwhile’ question answers in the range 0-6 are taken to be low wellbeing.

The ONS survey covers the whole of the UK, but this dataset only includes results for counties and unitary authorities in England, for consistency with other statistics available at this website.

At this stage the estimates are considered ‘experimental statistics’, published at an early stage to involve users in their development and to allow feedback. Feedback can be provided to the ONS via this email address.

The APS is a continuous household survey administered by the Office for National Statistics. It covers the UK, with the chief aim of providing between-census estimates of key social and labour market variables at a local area level. Apart from employment and unemployment, the topics covered in the survey include housing, ethnicity, religion, health and education. When a household is surveyed all adults (aged 16+) are asked the four subjective well-being questions.

The 12 month Subjective Well-being APS dataset is a sub-set of the general APS as the well-being questions are only asked of persons aged 16 and above, who gave a personal interview and proxy answers are not accepted. This reduces the size of the achieved sample to approximately 120,000 adult respondents in England.

The original data is available from the ONS website.

Detailed information on the APS and the Subjective Wellbeing dataset is available here.

As well as collecting data on well-being, the Office for National Statistics has published widely on the topic of wellbeing. Papers and further information can be found here.

A poll released to mark World Mental Health Day reveals that during the 12 months preceding the survey, 15% of respondents across EU Member States sought professional help for psychological or emotional problems and 7% took antidepressants, mostly for depression or anxiety. According to the results, there is still stigma attached to mental disorders, with 22% of those surveyed saying they would find it difficult to speak to a person with a "significant mental disorder". This issue and the other results will be discussed during the next thematic conference under the European Pact for Mental Health and Well-being. The main themes addressed in this report are: • The state of mental well-being – how well people feel mentally and physically, and what impact has this had on their lives• Level of comfort at work – how secure people feel in their current jobs, whether they feel their skills match their current role and whether they feel they receive adequate recognition/respect for what they do • Care and treatment – what help and treatment people have sought to ameliorate any mental health conditions they have experienced • Perceptions of people with mental illness – how comfortable people feel about interacting with those with a mental health problem

The results by volumes are distributed as follows:

• Volume A: Countries
• Volume AA: Groups of countries
• Volume A' (AP): Trends
• Volume AA' (AAP): Trends of groups of countries
• Volume B: EU/socio-demographics
• Volume B' (BP) : Trends of EU/ socio-demographics
• Volume C: Country/socio-demographics ---- Researchers may also contact GESIS - Leibniz Institute for the Social Sciences: https://www.gesis.org/eurobarometer

The Survey of Health, Ageing and Retirement in Europe (SHARE) is a multidisciplinary and cross-national database of micro data on health, socio-economic status and social and family networks of individuals aged 50 or over which was designed after the role models of the United States Health and Retirement Study (HRS) and the English Longitudinal Study of Ageing (ELSA). SHARE-Israel was added to the collection during 2005 and 2006 and required a complex adaptation of the SHARE survey instruments for implementation in Israel. In order to access the three major population groups that make up Israeli society, veteran Jewish-Israelis, Arab-Israelis and new immigrants from the former Soviet Union after 1989, it was necessary to translate the CAPI questionnaire and the drop off questionnaire into Hebrew, Arabic and Russian. Data collected include health variables (e.g., self-reported health, physical functioning, cognitive functioning, health behavior, use of health care facilities), psychological variables (e.g., psychological health, well-being, life satisfaction), economic variables such as (current work activity, job characteristics, opportunities to work past retirement age, sources and composition of current income, wealth and consumption, housing, education), and social support variables (e.g., assistance within families, transfers of income and assets, social networks, volunteer activities). Two physical performance measures were also employed. The first was grip strength, the respondent's maximum handgrip strength measured by means of a dynamometer. The second physical performance measure was walking speed, which was asked only of persons aged 75 and older. This physical measurement involved asking the respondent to walk a certain distance and measuring the time it took for the respondent to complete the task. Unique to SHARE-Israel were questions in the drop-off questionnaire regarding trauma. Respondents were asked about difficult life events that they had experienced and the degree to which they were affected by them. The events were drawn from the following areas (1) having personally suffered injury in war, in a terrorist attack, a grave illness or accident, (2) having witnessed injury or death in war, in a terrorist attack, and/or in an accident or crime, (3) having been a victim of crime, abuse, sexual harassment and/or severe economic adversity, (4) having had a close person injured or lost due to war, a terrorist attack, accident or grave illness, (5) loss of spouse and/or offspring, and (6) having provided or received long term care due to functional disability. A separate inventory chronicled respondents' exposure to the Holocaust. Also included in the drop-off questionnaire were questions regarding pension reform: which addressed respondents' awareness of the legislated delay in the age of eligibility for retirement pension in Israel, (for men, age 67 and for women, age 64). It also inquired about implications of the change in pension age, information regarding personal plans for employment or retirement in light of the change, and sources of income that would be used to bridge the period between retirement and receipt of pension, if early retirement was contemplated. Full details regarding SHARE can be located at the SHARE Web site.

Replication code and data for the research note "Does Health Vulnerability Predict Voting for Right-Wing Populist Parties in Europe?" in APSR. Data sources: European Social Survey, V-Dem Institute, and World Bank.

Using micro-data on six surveys–the Gallup World Poll 2005–2023, the U.S. Behavioral Risk Factor Surveillance System, 1993–2022, Eurobarometer 1991–2022, the UK Covid Social Survey Panel, 2020–2022, the European Social Survey 2002–2020 and the IPSOS Happiness Survey 2018–2023 –we show individuals’ reports of subjective wellbeing in Europe declined in the Great Recession of 2008/9 and during the Covid pandemic of 2020–2021 on most measures. They also declined in four countries bordering Ukraine after the Russian invasion in 2022. However, the movements are not large and are not apparent everywhere. We also used data from the European Commission’s Business and Consumer Surveys on people’s expectations of life in general, their financial situation and the economic and employment situation in the country. All of these dropped markedly in the Great Recession and during Covid, but bounced back quickly, as did firms’ expectations of the economy and the labor market. Neither the annual data from the United Nation’s Human Development Index (HDI) nor data used in the World Happiness Report from the Gallup World Poll shifted much in response to negative shocks. The HDI has been rising in the last decade reflecting overall improvements in economic and social wellbeing, captured in part by real earnings growth, although it fell slightly after 2020 as life expectancy dipped. This secular improvement is mirrored in life satisfaction which has been rising in the last decade. However, so too have negative affect in Europe and despair in the United States.

Statistics Norway has a long tradition of conducting “Level of Living”-surveys, and the surveys elucidate the living condition components like the economy, housing conditions, leisure activities, social networks, exposedness and fear of crime, health, education, care, employment and working conditions. The Survey on Income and Living Conditions (EU-SILC) is a European sampling survey concerning income, social inclusiveness and living conditions that is coordinated though the EUs statistical organ, Eurostat, and rooted in the European Statistical System (ESS). The primary purpose of EU-SILC is to produce a data foundation for the EUs indicators for welfare and social inclusiveness. The living condition survey EU-SILC will, jointly with the surveys on working conditions and data on health, care and social contact from the European Health Interview Survey (EHIS), cover all of the mentioned components of level of living surveys over a three-year period. The theme of the 2015 EU-SILC survey on living conditions was housing, exposedness and fear of crime, material shortages, and social and cultural participation.

The Survey of Health, Ageing and Retirement in Europe (SHARE) is a multidisciplinary and cross-national panel database of micro data on health, socio-economic status and social and family networks of more than 30,000 individuals aged 50 or over. Eleven countries have contributed data to the 2004 SHARE baseline study. They are a balanced representation of the various regions in Europe, ranging from Scandinavia (Denmark and Sweden) through Central Europe (Austria, France, Germany, Switzerland, Belgium, and the Netherlands) to the Mediterranean (Spain, Italy and Greece). Further data have been collected in 2005-06 in Israel. Two 'new' EU member states - the Czech Republic and Poland - as well as Ireland have joined SHARE in 2006 and participated in the second wave of data collection in 2006-07. The survey’s third wave of data collection, SHARELIFE in 2008-09, will collect detailed retrospective life-histories in sixteen countries, with Slovenia joining in as a new member.The data are available to the entire research community for no costs via de SHARE website.

The European Health Interview Survey (EHIS) is a major European Union reference source for comparative statistics on health status, health determinants and use of health care services. It was planned that EHIS would be conducted once every five years.

The first wave of EHIS was launched under an informal agreement and implemented in 17 EU Member States and in Switzerland and Turkey between 2006 and 2009. The second wave of EHIS was completed under a European Parliament and Council regulation in all 28 EU Member States, Iceland, Norway and Turkey between 2013 and 2015. The third wave of EHIS took place in 2019 and 2020 and was completed by all member sates in accordance with the European Parliament and Council regulation. The UK was required to complete EHIS Wave 3 as the UK was a member state in 2019. Users should note that the United Kingdom opted out of the first wave and did not take part, so UK EHIS data exists only from Wave 2 and Wave 3. This dataset contains only the UK responses.

Further information about the survey may be found on the European Commission "http://ec.europa.eu/eurostat/web/microdata/european-health-interview-survey" title="European Health Interview Survey" style="background-color: rgb(255, 255, 255);"> European Health Interview Survey webpage.

Latest edition information
For the second edition (March 2022), data and documentation for Wave 3 were added to the study.

Full edition for scientific use. PUMA Surveys consist of separate modules designed and prepared by different principle investigators. This PUMA Survey consists of three modules: MODULE 1 "Non-Health Influences on Generic Health Ratings: Comparing the Susceptibility of Self-Rated Health (SRH) and the Minimum European Health Module (MEHM) to Biases Due to Optimism, Hypochondriasis, and Social Desirability", MODULE 2 "Online completion versus face-to-face completion. Testing mixing modes of data collection for Austrian social surveys", MODULE 3 "Concerns of Smartphone Owners When Using their Device for Research". Fieldwork was conducted by Statistics Austria. MODULE 1: Non-Health Influences on Generic Health Ratings: Comparing the Susceptibility of Self-Rated Health (SRH) and the Minimum European Health Module (MEHM) to Biases Due to Optimism, Hypochondriasis, and Social Desirability (Patrick Lazarevič, Martina Brandt, Marc Luy, Caroline Berghammer) Self-rated health (SRH) is the most widely used single-indicator of health in many scientific disciplines (Jylhä 2009). Even though more comprehensive approaches to measure generic health exist, they are often too time consuming for survey interviews, especially in multi-thematic surveys, due to time limitations. Research in this regard has shown that, even when controlling for comprehensive health information, SRH is noticeably and independently influenced by non-health factors like satisfaction with life or social participation (e.g., Lazarevič 2018). While these results illustrate that health ratings are influenced by non-health factors, the personality traits that are assumed to bias SRH (e.g., optimism, social desirability, or hypochondriasis) are typically not directly measured. The Minimum European Health Module (MEHM), as proposed by Robine & Jagger (2003), complements SRH with the questions whether the respondent suffers from a chronic disease and whether and to what extent they are limited in their usual activities due to a health problem. Thus, MEHM can be seen as a compromise between using SRH as a single-indicator and a comprehensive scale while covering the two most relevant factors for health ratings, i.e., chronic diseases and the functional status (Lazarevič 2018). While MEHM is obviously less time- and cost-intensive than more comprehensive approaches to measure health and there was some research done on its components separately (e.g., Berger et al. 2015), hardly anything is known about its usefulness as a short-scale of generic health, its overall psychometric properties, and its susceptibility to non-health factors potentially biasing the health measurement. This module tested the feasibility and utility of using the Minimum European Health Module (MEHM) as a short scale for measuring generic health. We demonstrate the feasibility of extracting a factor score from MEHM utilizing confirmatory factor analyses based on polychoric correlations. Further analyses suggest that this factor score might be useful in reducing bias in generic health measurement due to optimism and social desirability. MODULE 2: Online completion versus face-to-face completion. Testing mixing modes of data collection for Austrian social surveys (Markus Hadler, Franz Höllinger, Anja Eder) Collecting data online is a promising tool, given the problems survey research faces in terms of lowering response rates and increasing costs. Yet, the results on the comparability of online and face-to-face surveys are ambiguous (see Roberts et al. 2016). Therefore, the aim of our research is to test differences in responses when completing surveys online compared to collecting the same data face-to-face. Our PUMA-module collects some of the core ISSP questions online, which were asked face-to-face (CAPI) in the same time-period. The topics of the ISSP questionnaires 2017 and 2018 are “Social Networks” and “Religion.” At face value, we expect that these two areas may attract different respondents when conducted online as compared to face-to-face. Online networking should be more prevalent and traditional religious activities less common among the online respondents. If there are no significant differences between these two samples, our study will be a strong indicator that online tools are valid instruments. Therefore, the mixed modes design aims to break new ground in understanding the advantages and limitations, the costs and benefits of combining online and face-to-face interviews in Austria on the basis of two prominent survey modules from the International Social Survey Programme. MODULE 3: Concerns of Smartphone Owners When Using their Device for Research (Florian Keusch, Martin Weichbold) Smartphone use is on the rise worldwide (Pew Research Center 2017). Survey researchers are aware that smartphone users increasingly complete online surveys on their mobile devices and have investigated the quality of survey data provided via smartphones (e.g., Couper et al. 2017; Keusch &...

Note: ‘Left’ = 0–3 on the left-right self-placement scale, ‘Middle’ = 4–6, and ‘Right’ = 7–10. Frequencies with political regime indicate the number of countries instead of individuals.

This statistic displays the results of a survey amongst German citizens in April 2016, regarding their opinion on the desirability of the EU strengthening its health and social security policy. ** percent of respondents reported they believed the EU should strengthen its health and social security policy more than at present.

Abstract

In 2013, the EU-SILC instrument covered all EU Member States plus Iceland, Turkey, Norway, Switzerland and Croatia. EU-SILC has become the EU reference source for comparative statistics on income distribution and social exclusion at European level, particularly in the context of the "Program of Community action to encourage cooperation between Member States to combat social exclusion" and for producing structural indicators on social cohesion for the annual spring report to the European Council. The first priority is to be given to the delivery of comparable, timely and high quality cross-sectional data.

There are two types of datasets: 1) Cross-sectional data pertaining to fixed time periods, with variables on income, poverty, social exclusion and living conditions. 2) Longitudinal data pertaining to individual-level changes over time, observed periodically - usually over four years.

Social exclusion and housing-condition information is collected at household level. Income at a detailed component level is collected at personal level, with some components included in the "Household" section. Labor, education and health observations only apply to persons aged 16 and over. EU-SILC was established to provide data on structural indicators of social cohesion (at-risk-of-poverty rate, S80/S20 and gender pay gap) and to provide relevant data for the two 'open methods of coordination' in the field of social inclusion and pensions in Europe.

This is the 1st version of the 2013 Cross-Sectional User Database as released in July 2015.

Geographic coverage

The survey covers following countries: Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Spain; Ireland; Italy; Latvia; Lithuania; Luxembourg; Hungary; Malta; Netherlands; Poland; Portugal; Romania; Slovenia; Slovakia; Serbia; Sweden; United Kingdom; Iceland; Norway; Turkey; Switzerland

Small parts of the national territory amounting to no more than 2% of the national population and the national territories listed below may be excluded from EU-SILC: France - French Overseas Departments and territories; Netherlands - The West Frisian Islands with the exception of Texel; Ireland - All offshore islands with the exception of Achill, Bull, Cruit, Gorumna, Inishnee, Lettermore, Lettermullan and Valentia; United Kingdom - Scotland north of the Caledonian Canal, the Scilly Islands.

Analysis unit

• Households;
• Individuals 16 years and older.

Universe

The survey covered all household members over 16 years old. Persons living in collective households and in institutions are generally excluded from the target population.

Kind of data

Sample survey data [ssd]

Sampling procedure

On the basis of various statistical and practical considerations and the precision requirements for the most critical variables, the minimum effective sample sizes to be achieved were defined. Sample size for the longitudinal component refers, for any pair of consecutive years, to the number of households successfully interviewed in the first year in which all or at least a majority of the household members aged 16 or over are successfully interviewed in both the years.

For the cross-sectional component, the plans are to achieve the minimum effective sample size of around 131.000 households in the EU as a whole (137.000 including Iceland and Norway). The allocation of the EU sample among countries represents a compromise between two objectives: the production of results at the level of individual countries, and production for the EU as a whole. Requirements for the longitudinal data will be less important. For this component, an effective sample size of around 98.000 households (103.000 including Iceland and Norway) is planned.

Member States using registers for income and other data may use a sample of persons (selected respondents) rather than a sample of complete households in the interview survey. The minimum effective sample size in terms of the number of persons aged 16 or over to be interviewed in detail is in this case taken as 75 % of the figures shown in columns 3 and 4 of the table I, for the cross-sectional and longitudinal components respectively.

The reference is to the effective sample size, which is the size required if the survey were based on simple random sampling (design effect in relation to the 'risk of poverty rate' variable = 1.0). The actual sample sizes will have to be larger to the extent that the design effects exceed 1.0 and to compensate for all kinds of non-response. Furthermore, the sample size refers to the number of valid households which are households for which, and for all members of which, all or nearly all the required information has been obtained. For countries with a sample of persons design, information on income and other data shall be collected for the household of each selected respondent and for all its members.

At the beginning, a cross-sectional representative sample of households is selected. It is divided into say 4 sub-samples, each by itself representative of the whole population and similar in structure to the whole sample. One sub-sample is purely cross-sectional and is not followed up after the first round. Respondents in the second sub-sample are requested to participate in the panel for 2 years, in the third sub-sample for 3 years, and in the fourth for 4 years. From year 2 onwards, one new panel is introduced each year, with request for participation for 4 years. In any one year, the sample consists of 4 sub-samples, which together constitute the cross-sectional sample. In year 1 they are all new samples; in all subsequent years, only one is new sample. In year 2, three are panels in the second year; in year 3, one is a panel in the second year and two in the third year; in subsequent years, one is a panel for the second year, one for the third year, and one for the fourth (final) year.

According to the Commission Regulation on sampling and tracing rules, the selection of the sample will be drawn according to the following requirements:

1. For all components of EU-SILC (whether survey or register based), the crosssectional and longitudinal (initial sample) data shall be based on a nationally representative probability sample of the population residing in private households within the country, irrespective of language, nationality or legal residence status. All private households and all persons aged 16 and over within the household are eligible for the operation.
2. Representative probability samples shall be achieved both for households, which form the basic units of sampling, data collection and data analysis, and for individual persons in the target population.
3. The sampling frame and methods of sample selection shall ensure that every individual and household in the target population is assigned a known and non-zero probability of selection.
4. By way of exception, paragraphs 1 to 3 shall apply in Germany exclusively to the part of the sample based on probability sampling according to Article 8 of the Regulation of the European Parliament and of the Council (EC) No 1177/2003 concerning

Community Statistics on Income and Living Conditions. Article 8 of the EU-SILC Regulation of the European Parliament and of the Council mentions: 1. The cross-sectional and longitudinal data shall be based on nationally representative probability samples. 2. By way of exception to paragraph 1, Germany shall supply cross-sectional data based on a nationally representative probability sample for the first time for the year 2008. For the year 2005, Germany shall supply data for one fourth based on probability sampling and for three fourths based on quota samples, the latter to be progressively replaced by random selection so as to achieve fully representative probability sampling by 2008. For the longitudinal component, Germany shall supply for the year 2006 one third of longitudinal data (data for year 2005 and 2006) based on probability sampling and two thirds based on quota samples. For the year 2007, half of the longitudinal data relating to years 2005, 2006 and 2007 shall be based on probability sampling and half on quota sample. After 2007 all of the longitudinal data shall be based on probability sampling.

Detailed information about sampling is available in Quality Reports in Related Materials.

Mode of data collection

Mixed