Joint Programming Initiative

More Years, Better Lives

The Potential and Challenges of Demographic Change

ESS – European Social Survey
ESS – European Social Survey

Topic
Wellbeing
Health and Performance
Public Attitudes towards Older Age
Intergenerational Relationships
Relevance for this Topic
Country Europe
URL
More Topics

Governance

Contact information

ESS Data Archive
Norwegian Social Science Data Services (NSD)
Harald Hårfagresgt. 29
N-5007 Bergen
Norway
Phone: +47-555-82117
Fax: +47-555-89650
Email: essdatasupport(at)nsd.uib.no
Url: http://www.europeansocialsurvey.org/

Timeliness, transparency

Wave 1: data collected in 2002 and first version released in September 2003. Wave 2: data collected in 2004 and first version released in September 2005. Wave 3: data collected in 2006 and first version released in September 2007. Wave 4: data collected in 2008 and first version released in September 2009. Wave 5: data collected in 2010 and first version released in October 2011.

Type of data


Survey

Type of Study

Longitude survey: long-term study of random or different samples

Data gathering method

Face-to-face interview (CAPI, PAPI)

Type of data


Survey

Type of Study

Longitude survey: long-term study of random or different samples

Data gathering method

Face-to-face interview (CAPI, PAPI)

Type of data


Survey

Type of Study

Longitude survey: long-term study of random or different samples

Data gathering method

Face-to-face interview (CAPI, PAPI)

Type of data


Survey

Type of Study

Longitude survey: long-term study of random or different samples

Data gathering method

Face-to-face interview (CAPI, PAPI)


Access to data


Data for each round and country can be downloaded (SAS, SPSS) after registration. Online analyses via Nesstar are possible. The ESS Cumulative Data Wizard gives access to cumulative data from countries that have been included in the integrated ESS files in two or more rounds. Data is downloadable free of charge.

Conditions of access


Registration necessary to access data files; data is available free of charge and without restrictions for non-profit purposes


Anonymised data


SAS and SPSS


Data and documentation are available in English.

Access to data


Data for each round and country can be downloaded (SAS, SPSS) after registration. Online analyses via Nesstar are possible. The ESS Cumulative Data Wizard gives access to cumulative data from countries that have been included in the integrated ESS files in two or more rounds. Data is downloadable free of charge.

Conditions of access


Registration necessary to access data files; data is available free of charge and without restrictions for non-profit purposes


Anonymised data


SAS and SPSS


Data and documentation are available in English.

Access to data


Data for each round and country can be downloaded (SAS, SPSS) after registration. Online analyses via Nesstar are possible. The ESS Cumulative Data Wizard gives access to cumulative data from countries that have been included in the integrated ESS files in two or more rounds. Data is downloadable free of charge.

Conditions of access


Registration necessary to access data files; data is available free of charge and without restrictions for non-profit purposes


Anonymised data


SAS and SPSS


Data and documentation are available in English.

Access to data


Data for each round and country can be downloaded (SAS, SPSS) after registration. Online analyses via Nesstar are possible. The ESS Cumulative Data Wizard gives access to cumulative data from countries that have been included in the integrated ESS files in two or more rounds. Data is downloadable free of charge.

Conditions of access


Registration necessary to access data files; data is available free of charge and without restrictions for non-profit purposes


Anonymised data


SAS and SPSS


Data and documentation are available in English.


Coverage


ESS1(2002): 254 total variables ESS2 (2004): 332 total variables ESS3 (2006): 269 total variables ESS4 (2008): 264 total variables ESS5 (2010): 289 total variables The minimum effective sample size is 1,500 (or 800 for countries with less than 2 million inhabitants).


2002


Based on population size of districts/provinces (Note that there are some differences regarding stratification between countries covered; i.e. in Finland, stratification is additionally based on age and sex; in the Czech Republic, stratification is additionally based on urbanisation)


Random


ESS1: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom ESS2: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom. ESS3: Austria, Belgium, Bulgaria, Cyprus, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Latvia, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom. ESS4: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and United Kingdom. ESS5: Austria, Belgium, Bulgaria, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Estonia, Spain, Finland, France, Greece, Croatia, Hungary, Ireland, Israel, Iceland, Italy, Luxembourg, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Sweden, Slovenia, Slovakia, Turkey, Ukraine and the United Kingdom


15+


The survey consists of two sections, both of which consist of about 120 items: a core module that includes questions and topics covered in all questionnaires and two rotating modules that are repeated at intervals. Generally, the survey aims to collect data about social life and attitudes in Europe. With regard to ageing, the survey covers the themes of age discrimination, intergenerational relations, health and performance and wellbeing. The core module of ESS provides information regarding people's perceptions of being discriminated and the grounds of that discrimination. It also looks at perceptions about how important it is to care for others’ wellbeing. Furthermore, in round two, special attention was devoted to opinions on health and care seeking. The 30-item rotating module addresses issues, such as what does (good) health mean to people, when a symptom is considered an illness, and attitudes towards treatment and perceptions of the doctor-patient relationship.


• Abrams, D. Vauclair, C., & Swift. H. “Predictors of attitudes to age across Europe.” Research Report No 735, Department for Work and Pensions (2011). ISBN 978 1 84712 961 1. • Abrams, D., et al. “Ageism in Europe. Findings from European Social Survey.” EURAGE Report (2011). ISBN 978-0-9568731-0-1. • Emery, T. “Intergenerational conflict: Evidence from Europe.” Population Ageing 5 (2012): 7-22. • Huppert, F. A., et al. “Measuring Well-being Across Europe: Description of the ESS Well-being Module and Preliminary Findings.” Social Indicators Research 91 (2009): 301-315. • Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. “Can differences in medical drug compliance between European countries be explained by social factors: analyses based on data from the European Social Survey, round 2.” BMC Public Health 9(145) (2009). DOI:10.1186/1471-2458-9-145. • McKey, S. “Chapter 8: Never too old? Attitudes towards longer working lives.” British Social Attitudes: The 26th Report (2010). Online ISBN: 9781446212073. • Van den Heuvel, J., Wim, A., & van Santvoort, M. M. “Experienced discrimination amongst European old citizens.” European Journal of Ageing 8 (2011): 291-299.

Coverage


ESS1(2002): 254 total variables ESS2 (2004): 332 total variables ESS3 (2006): 269 total variables ESS4 (2008): 264 total variables ESS5 (2010): 289 total variables The minimum effective sample size is 1,500 (or 800 for countries with less than 2 million inhabitants).


2002


Based on population size of districts/provinces (Note that there are some differences regarding stratification between countries covered; i.e. in Finland, stratification is additionally based on age and sex; in the Czech Republic, stratification is additionally based on urbanisation)


Random


ESS1: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom ESS2: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom. ESS3: Austria, Belgium, Bulgaria, Cyprus, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Latvia, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom. ESS4: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and United Kingdom. ESS5: Austria, Belgium, Bulgaria, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Estonia, Spain, Finland, France, Greece, Croatia, Hungary, Ireland, Israel, Iceland, Italy, Luxembourg, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Sweden, Slovenia, Slovakia, Turkey, Ukraine and the United Kingdom


15+


The survey consists of two sections, both of which consist of about 120 items: a core module that includes questions and topics covered in all questionnaires and two rotating modules that are repeated at intervals. Generally, the survey aims to collect data about social life and attitudes in Europe. With regard to ageing, the survey covers the themes of age discrimination, intergenerational relations, health and performance and wellbeing. The core module of ESS provides information regarding people's perceptions of being discriminated and the grounds of that discrimination. It also looks at perceptions about how important it is to care for others’ wellbeing. Furthermore, in round two, special attention was devoted to opinions on health and care seeking. The 30-item rotating module addresses issues, such as what does (good) health mean to people, when a symptom is considered an illness, and attitudes towards treatment and perceptions of the doctor-patient relationship.


• Abrams, D. Vauclair, C., & Swift. H. “Predictors of attitudes to age across Europe.” Research Report No 735, Department for Work and Pensions (2011). ISBN 978 1 84712 961 1. • Abrams, D., et al. “Ageism in Europe. Findings from European Social Survey.” EURAGE Report (2011). ISBN 978-0-9568731-0-1. • Emery, T. “Intergenerational conflict: Evidence from Europe.” Population Ageing 5 (2012): 7-22. • Huppert, F. A., et al. “Measuring Well-being Across Europe: Description of the ESS Well-being Module and Preliminary Findings.” Social Indicators Research 91 (2009): 301-315. • Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. “Can differences in medical drug compliance between European countries be explained by social factors: analyses based on data from the European Social Survey, round 2.” BMC Public Health 9(145) (2009). DOI:10.1186/1471-2458-9-145. • McKey, S. “Chapter 8: Never too old? Attitudes towards longer working lives.” British Social Attitudes: The 26th Report (2010). Online ISBN: 9781446212073. • Van den Heuvel, J., Wim, A., & van Santvoort, M. M. “Experienced discrimination amongst European old citizens.” European Journal of Ageing 8 (2011): 291-299.

Coverage


ESS1(2002): 254 total variables ESS2 (2004): 332 total variables ESS3 (2006): 269 total variables ESS4 (2008): 264 total variables ESS5 (2010): 289 total variables The minimum effective sample size is 1,500 (or 800 for countries with less than 2 million inhabitants).


2002


Based on population size of districts/provinces (Note that there are some differences regarding stratification between countries covered; i.e. in Finland, stratification is additionally based on age and sex; in the Czech Republic, stratification is additionally based on urbanisation)


Random


ESS1: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom ESS2: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom. ESS3: Austria, Belgium, Bulgaria, Cyprus, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Latvia, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom. ESS4: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and United Kingdom. ESS5: Austria, Belgium, Bulgaria, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Estonia, Spain, Finland, France, Greece, Croatia, Hungary, Ireland, Israel, Iceland, Italy, Luxembourg, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Sweden, Slovenia, Slovakia, Turkey, Ukraine and the United Kingdom


15+


The survey consists of two sections, both of which consist of about 120 items: a core module that includes questions and topics covered in all questionnaires and two rotating modules that are repeated at intervals. Generally, the survey aims to collect data about social life and attitudes in Europe. With regard to ageing, the survey covers the themes of age discrimination, intergenerational relations, health and performance and wellbeing. The core module of ESS provides information regarding people's perceptions of being discriminated and the grounds of that discrimination. It also looks at perceptions about how important it is to care for others’ wellbeing. Furthermore, in round two, special attention was devoted to opinions on health and care seeking. The 30-item rotating module addresses issues, such as what does (good) health mean to people, when a symptom is considered an illness, and attitudes towards treatment and perceptions of the doctor-patient relationship.


• Abrams, D. Vauclair, C., & Swift. H. “Predictors of attitudes to age across Europe.” Research Report No 735, Department for Work and Pensions (2011). ISBN 978 1 84712 961 1. • Abrams, D., et al. “Ageism in Europe. Findings from European Social Survey.” EURAGE Report (2011). ISBN 978-0-9568731-0-1. • Emery, T. “Intergenerational conflict: Evidence from Europe.” Population Ageing 5 (2012): 7-22. • Huppert, F. A., et al. “Measuring Well-being Across Europe: Description of the ESS Well-being Module and Preliminary Findings.” Social Indicators Research 91 (2009): 301-315. • Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. “Can differences in medical drug compliance between European countries be explained by social factors: analyses based on data from the European Social Survey, round 2.” BMC Public Health 9(145) (2009). DOI:10.1186/1471-2458-9-145. • McKey, S. “Chapter 8: Never too old? Attitudes towards longer working lives.” British Social Attitudes: The 26th Report (2010). Online ISBN: 9781446212073. • Van den Heuvel, J., Wim, A., & van Santvoort, M. M. “Experienced discrimination amongst European old citizens.” European Journal of Ageing 8 (2011): 291-299.

Coverage


ESS1 (2002): 254 total variables ESS2 (2004): 332 total variables ESS3 (2006): 269 total variables ESS4 (2008): 264 total variables ESS5 (2010): 289 total variables The minimum effective sample size is 1,500 (or 800 for countries with less than 2 million inhabitants).


2002


Based on population size of districts/provinces (Note that there are some differences regarding stratification between countries covered; i.e. in Finland, stratification is additionally based on age and sex; in the Czech Republic, stratification is additionally based on urbanisation)


Random


ESS1: Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, United Kingdom ESS2: Austria, Belgium, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom. ESS3: Austria, Belgium, Bulgaria, Cyprus, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Latvia, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Ukraine, United Kingdom. ESS4: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, and United Kingdom. ESS5: Austria, Belgium, Bulgaria, Switzerland, Cyprus, Czech Republic, Germany, Denmark, Estonia, Spain, Finland, France, Greece, Croatia, Hungary, Ireland, Israel, Iceland, Italy, Luxembourg, Latvia, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Russian Federation, Sweden, Slovenia, Slovakia, Turkey, Ukraine and the United Kingdom


15+


The survey consists of two sections, both of which consist of about 120 items: a core module that includes questions and topics covered in all questionnaires and two rotating modules that are repeated at intervals. Generally, the survey aims to collect data about social life and attitudes in Europe. With regard to ageing, the survey covers the themes of age discrimination, intergenerational relations, health and performance and wellbeing. The core module of ESS provides information regarding people's perceptions of being discriminated and the grounds of that discrimination. It also looks at perceptions about how important it is to care for others’ wellbeing. Furthermore, in round two, special attention was devoted to opinions on health and care seeking. The 30-item rotating module addresses issues, such as what does (good) health mean to people, when a symptom is considered an illness, and attitudes towards treatment and perceptions of the doctor-patient relationship.


• Abrams, D. Vauclair, C., & Swift. H. “Predictors of attitudes to age across Europe.” Research Report No 735, Department for Work and Pensions (2011). ISBN 978 1 84712 961 1. • Abrams, D., et al. “Ageism in Europe. Findings from European Social Survey.” EURAGE Report (2011). ISBN 978-0-9568731-0-1. • Emery, T. “Intergenerational conflict: Evidence from Europe.” Population Ageing 5 (2012): 7-22. • Huppert, F. A., et al. “Measuring Well-being Across Europe: Description of the ESS Well-being Module and Preliminary Findings.” Social Indicators Research 91 (2009): 301-315. • Larsen, J., Stovring, H., Kragstrup, J., & Hansen, D. G. “Can differences in medical drug compliance between European countries be explained by social factors: analyses based on data from the European Social Survey, round 2.” BMC Public Health 9(145) (2009). DOI:10.1186/1471-2458-9-145. • McKey, S. “Chapter 8: Never too old? Attitudes towards longer working lives.” British Social Attitudes: The 26th Report (2010). Online ISBN: 9781446212073. • Van den Heuvel, J., Wim, A., & van Santvoort, M. M. “Experienced discrimination amongst European old citizens.” European Journal of Ageing 8 (2011): 291-299.


Linkage


The questionnaire is designed to be identical in all countries except in regard to language, education and religion, which are country specific. A post-hoc harmonisation is applied.


No

Linkage


The questionnaire is designed to be identical in all countries except in regard to language, education and religion, which are country specific. A post-hoc harmonisation is applied.


No

Linkage


The questionnaire is designed to be identical in all countries except in regard to language, education and religion, which are country specific. A post-hoc harmonisation is applied.


No

Linkage


The questionnaire is designed to be identical in all countries except in regard to language, education and religion, which are country specific. A post-hoc harmonisation is applied.


No


Data quality


The data is regularly checked for completeness, missing and duplicated records, for illegal codes, and any other potential errors in the data. The data are then corrected and documented. A specific coding error occurred in the ESS 2 database for Slovenia: All respondents who answered that they do not belong to a group that is discriminated have been coded as belonging to a group which is discriminated against in the following question ‘On what grounds is your group discriminated against?’.


Possible due to usage of data from several sources and their selected variables.


Consistent within the project due to centralised strategy.

Data quality


The data is regularly checked for completeness, missing and duplicated records, for illegal codes, and any other potential errors in the data. The data are then corrected and documented. A specific coding error occurred in the ESS 2 database for Slovenia: All respondents who answered that they do not belong to a group that is discriminated have been coded as belonging to a group which is discriminated against in the following question ‘On what grounds is your group discriminated against?’.


Possible due to usage of data from several sources and their selected variables.


Consistent within the project due to centralised strategy.

Data quality


The data is regularly checked for completeness, missing and duplicated records, for illegal codes, and any other potential errors in the data. The data are then corrected and documented. A specific coding error occurred in the ESS 2 database for Slovenia: All respondents who answered that they do not belong to a group that is discriminated have been coded as belonging to a group which is discriminated against in the following question ‘On what grounds is your group discriminated against?’.


Possible due to usage of data from several sources and their selected variables.


Consistent within the project due to centralised strategy.

Data quality


The data is regularly checked for completeness, missing and duplicated records, for illegal codes, and any other potential errors in the data. The data are then corrected and documented. A specific coding error occurred in the ESS 2 database for Slovenia: All respondents who answered that they do not belong to a group that is discriminated have been coded as belonging to a group which is discriminated against in the following question ‘On what grounds is your group discriminated against?’.


Possible due to usage of data from several sources and their selected variables.


Consistent within the project due to centralised strategy.


Applicability


The ESS provides researchers with the possibility to conduct comparative research on age discrimination, health, intergenerational solidarity and wellbeing across Europe and over time. More specifically, the data from the round two rotating module on health offers the possibility to study perceptions on health and health seeking behaviour. Statistical weighting made it possible to adjust for national differences in sampling mechanisms. Additionally, the dataset provides socio-economic background characteristics of the participants, such as educational level, household income, marital status and profession, and therefore, the dataset is very suitable for cross-country comparison. The round three module on wellbeing is particularly valuable because it allows for the study of not only individualistic aspects of wellbeing, but also social and interpersonal wellbeing. It includes measures of interpersonal experience and functioning in the social domain. The module also incorporates a substantial number of items covering important aspects of daily life. The data from the round four module on intergenerational relations and ageism provide a unique possibility to study attitudes towards old-age and the interaction between old and young from a comparative perspective with a comprehensive set of variables. Experts in the field of ageism claimed that there are no panel or time series datasets of such views/attitudes that have such a comprehensive coverage of intergenerational relations. A great effort has been made to ensure comparability and the methods of sampling, data collection and use of common instruments all guarantee high quality data. The core modules include the same questions on discrimination and intergenerational relations and therefore, changes over time could be studied. Although the countries participating in each round differ somewhat, the survey has great geographical coverage. However, researchers also reported some comparability problems in the round two data, which were used to study and compare human values. The metric invariance has not been supported across the 25 countries in the dataset, suggesting that comparison between the first and second round is only possible between 14 countries. Some comparability and validity shortcomings were also reported with regard to round three data, which were used to study social capital across Europe.

Applicability


The ESS provides researchers with the possibility to conduct comparative research on age discrimination, health, intergenerational solidarity and wellbeing across Europe and over time. More specifically, the data from the round two rotating module on health offers the possibility to study perceptions on health and health seeking behaviour. Statistical weighting made it possible to adjust for national differences in sampling mechanisms. Additionally, the dataset provides socio-economic background characteristics of the participants, such as educational level, household income, marital status and profession, and therefore, the dataset is very suitable for cross-country comparison. The round three module on wellbeing is particularly valuable because it allows for the study of not only individualistic aspects of wellbeing, but also social and interpersonal wellbeing. It includes measures of interpersonal experience and functioning in the social domain. The module also incorporates a substantial number of items covering important aspects of daily life. The data from the round four module on intergenerational relations and ageism provide a unique possibility to study attitudes towards old-age and the interaction between old and young from a comparative perspective with a comprehensive set of variables. Experts in the field of ageism claimed that there are no panel or time series datasets of such views/attitudes that have such a comprehensive coverage of intergenerational relations. A great effort has been made to ensure comparability and the methods of sampling, data collection and use of common instruments all guarantee high quality data. The core modules include the same questions on discrimination and intergenerational relations and therefore, changes over time could be studied. Although the countries participating in each round differ somewhat, the survey has great geographical coverage. However, researchers also reported some comparability problems in the round two data, which were used to study and compare human values. The metric invariance has not been supported across the 25 countries in the dataset, suggesting that comparison between the first and second round is only possible between 14 countries. Some comparability and validity shortcomings were also reported with regard to round three data, which were used to study social capital across Europe.

Applicability


The ESS provides researchers with the possibility to conduct comparative research on age discrimination, health, intergenerational solidarity and wellbeing across Europe and over time. More specifically, the data from the round two rotating module on health offers the possibility to study perceptions on health and health seeking behaviour. Statistical weighting made it possible to adjust for national differences in sampling mechanisms. Additionally, the dataset provides socio-economic background characteristics of the participants, such as educational level, household income, marital status and profession, and therefore, the dataset is very suitable for cross-country comparison. The round three module on wellbeing is particularly valuable because it allows for the study of not only individualistic aspects of wellbeing, but also social and interpersonal wellbeing. It includes measures of interpersonal experience and functioning in the social domain. The module also incorporates a substantial number of items covering important aspects of daily life. The data from the round four module on intergenerational relations and ageism provide a unique possibility to study attitudes towards old-age and the interaction between old and young from a comparative perspective with a comprehensive set of variables. Experts in the field of ageism claimed that there are no panel or time series datasets of such views/attitudes that have such a comprehensive coverage of intergenerational relations. A great effort has been made to ensure comparability and the methods of sampling, data collection and use of common instruments all guarantee high quality data. The core modules include the same questions on discrimination and intergenerational relations and therefore, changes over time could be studied. Although the countries participating in each round differ somewhat, the survey has great geographical coverage. However, researchers also reported some comparability problems in the round two data, which were used to study and compare human values. The metric invariance has not been supported across the 25 countries in the dataset, suggesting that comparison between the first and second round is only possible between 14 countries. Some comparability and validity shortcomings were also reported with regard to round three data, which were used to study social capital across Europe.

Applicability


The ESS provides researchers with the possibility to conduct comparative research on age discrimination, health, intergenerational solidarity and wellbeing across Europe and over time. More specifically, the data from the round two rotating module on health offers the possibility to study perceptions on health and health seeking behaviour. Statistical weighting made it possible to adjust for national differences in sampling mechanisms. Additionally, the dataset provides socio-economic background characteristics of the participants, such as educational level, household income, marital status and profession, and therefore, the dataset is very suitable for cross-country comparison. The round three module on wellbeing is particularly valuable because it allows for the study of not only individualistic aspects of wellbeing, but also social and interpersonal wellbeing. It includes measures of interpersonal experience and functioning in the social domain. The module also incorporates a substantial number of items covering important aspects of daily life. The data from the round four module on intergenerational relations and ageism provide a unique possibility to study attitudes towards old-age and the interaction between old and young from a comparative perspective with a comprehensive set of variables. Experts in the field of ageism claimed that there are no panel or time series datasets of such views/attitudes that have such a comprehensive coverage of intergenerational relations. A great effort has been made to ensure comparability and the methods of sampling, data collection and use of common instruments all guarantee high quality data. The core modules include the same questions on discrimination and intergenerational relations and therefore, changes over time could be studied. Although the countries participating in each round differ somewhat, the survey has great geographical coverage. However, researchers also reported some comparability problems in the round two data, which were used to study and compare human values. The metric invariance has not been supported across the 25 countries in the dataset, suggesting that comparison between the first and second round is only possible between 14 countries. Some comparability and validity shortcomings were also reported with regard to round three data, which were used to study social capital across Europe.


  • The information about this dataset was compiled by the author:
  • Diana Lopez-Falcon
  • (see Partners)