All time references are in CEST
Poster Session 1
|Session Organiser|| Mrs Vera Lomazzi (University of Bergamo, Italy)
|Time||Wednesday 19 July, 15:00 - 16:00|
Dr Lydia Repke (GESIS - Leibniz Institute for the Social Sciences)
Dr Cornelia Neuert (GESIS - Leibniz Institute for the Social Sciences) - Presenting Author
Dr Wiebke Weber (Ludwig-Maximilians-Universität München)
This poster presents the Survey Quality Predictor (SQP) 3.0. This tool is an open-access software developed to predict the measurement quality of survey questions for continuous latent variables based on the characteristics of the questions (such as the topic, the properties of the answer scale, and the mode of administration). It is freely available at sqp.gesis.org and can be used: 1) to make informed decisions about the proper formulation of a survey question before data collection takes place; 2) to compare translations of survey items across countries and languages in cross-national research; and 3) to correct for measurement error in substantive analyses of the relationships between variables.
The prediction algorithm of SQP 3.0 is based on a meta-analysis of more than 600 multitrait-multimethod (MTMM) experiments in 28 languages and 33 countries. SQP 3.0 is a very powerful tool both at the stage of questionnaire design, that is, before data collection to improve survey questions, and at the stage of data analysis, that is, after data collection to correct for measurement errors. The poster explains what is behind SQP 3.0, what researchers can use this program for, and how to apply it.
Mr Peter Cornick (The National Centre for Social Research)
Dr Eva Aizpurua (The National Centre for Social Research) - Presenting Author
Any change in survey mode, or modes, involves complex trade-offs regarding representation, measurement, respondent experience, environmental impact, time and cost. The direction and extent of these trade-offs will differ for each survey. It is important to consider the impact any of change in mode thoroughly before making an informed decision about the long-term design of a survey.
To this end, the Centre for Social Survey Transformation at the National Centre for Social Research has developed the REMoDEL approach. This provides a clear, systematic process for transforming social surveys and generating robust evidence around the trade-offs involved.
By using well-established techniques based on a deep understanding of the research literature, and placing emphasis on empirical evidence, the REMoDEL approach is methodologically neutral. It aims only to identify the optimal solution to any specified research needs.
Our poster will explain the REMoDEL approach and how it has been used to adapt major UK surveys.
Dr Giulia Maria Dotti-Sani (University of Milano) - Presenting Author
Dr Marta Moroni (University of Milano)
Ms Francesca Mosca (University of Genova)
Professor Katia Perini (University of Genova)
Dense urban areas, the reduction of green spaces and pressure coming from anthropic activities have severe effects and impacts on global ecosystems, causing the decline of biodiversity and habitat fragmentation worldwide. Limited biological diversity of urban areas is causing the reduction of ecosystem resilience with negative consequences on human wellbeing. Therefore, strategies for biodiversity loss reduction and biodiversity conservation are extremely important to improve local livability and reduce environmental negative effects.
Despite the urgency of the issue, individual concern toward reduced local biological diversity has received scant attention in the literature. Similarly, little is known about citizens’ interest and reactions to environmental policies aimed at containing the damage of declining biodiversity.
From a sociological perspective, given the topic's salience for present and future human well-being, a deeper understanding of citizens’ attitudes towards biodiversity in general and policies and strategies aimed at improving local livability in particular is needed.
From a design perspective, the success of certain strategies, such as the introduction of different species of animals in urban environments, largely depends on the willingness of the people living in the affected areas to accept them. Yet, little is known about citizens’ perceptions of different animal species (e.g., spiders, wasps) and their willingness to accept their introduction in the areas where they live.
Against this background, this study relies on the fifth wave of the ResPOnsE COVID-19 dataset, an ad-hoc online survey carried out in Italy between November and December 2022, to investigate a) respondents’ attitudes towards biodiversity; b) their beliefs about the relationship between the improvement of local livability and well-being; c) their preferences in terms of the introduction of different animal species in the urban environment.
Dr Anna-Carolina Haensch (Ludwig Maximilians University Munich) - Presenting Author
Dr Christoph Kern (LMU Munich)
Mr Jacob Beck (LMU Munich)
New data sources and nonprobability samples play an increasingly important role in monitoring public opinion, particularly in the context of disruptive events such as the COVID-19 pandemic. At the same time, issues such as nonresponse bias and coverage error question the fitness of such data sources to inform policy decisions. Against this background, a broad range of
adjustment methods have been proposed in the recent survey research literature to correct for biases of non-random samples. This includes approaches such as propensity-adjusted probability prediction (PAPP; Rafei et al. 2020) and machine
learning-based kernel weighting (KW-ML; Kern et al. 2020) that draw on flexible prediction methods.
In this study, we set out to assess and systematically compare the ability of adjustment techniques in reducing non-response bias in the COVID-19 Trends and Impact Survey (CTIS). CTIS was the largest ever cross-sectional survey conducted on a daily basis globally and was designed to track COVID-19 health behaviors and prevalence. In our comparison, we vary the adjustment method – including pseudo-weighting, prediction modeling, and doubly robust approaches – and the auxiliary information used for the adjustment across multiple target variables. Given the time scale of CTIS data, we are able to compile estimates on a weekly basis and asses how they track estimates from benchmark data sources. Our comparison shows how recently proposed adjustment methods perform under challenging real-world conditions when timely data was in high demand.
Dr Johann Carstensen (German Centre for Higher Education Research and Science Studies (DZHW))
Dr Sebastian Lang (German Centre for Higher Education Research and Science Studies (DZHW)) - Presenting Author
Mr Heiko Quast (German Centre for Higher Education Research and Science Studies (DZHW))
Although the issue is of utmost importance for panel studies, there is not much evidence on how survey frequency affects the stability of a panel (see most recently Zabel 1998 for very short wave intervals). From a theoretical point of view, a higher contact frequency might lead to a lower rate of unsuccessful contact attempts through increased bonding with the respondents and address maintenance. The latter is of particular relevance for highly mobile respondent groups such as students or university graduates. Moreover, a higher survey frequency also offers the advantage of shorter periods of time for the retrospective collection of life history data (Haunberger 2010). This should reduce recall errors and the cognitive burden for respondents. At the same time, however, more frequent interviews also increase the response burden and could thus lead to a reduced willingness to participate (Haunberger 2010; Schnauber and Daschmann 2016; Stocké and Langfeldt 2003; Nederhof 1986).
To examine the effect of the survey frequency we implemented an experiment in a panel of secondary school graduates that usually surveys respondents every two years. To vary the survey frequency, an additional wave was conducted one year after the second wave for a random sample of participants of the second wave. Both, control and treatment group, were then interviewed again two years after the second wave.
We find a minimally higher response rate with a biennial survey–but this difference is not statistically significant. Thus, with a higher expected data quality, no (significant) losses in terms of response seem to be expected if the survey interval is halved from biennial to annual.
Ms Madeleine Siegel (DeZIM- Institute) - Presenting Author
Ms Almuth Lietz (DeZIM-Institute)
Mr Jonas Koehler (DeZIM-Institute)
Ms Ida Li (DeZIM-Institute)
Dr Jörg Dollmann (DeZIM-Institute/MZES)
Dr Jannes Jacobsen (DeZIM Institute)
Professor Sabrina Mayer (University of Bamberg)
Incentives in surveys are a frequently used instrument to increase response rates and have been widely researched. In our paper we are interested in the effectiveness of prepaid incentives compared to post-paid incentives. The existing research on payment type is clear: prepaid incentives are more effective than post-paid incentives, especially when cash is offered. However, we assume that the survey mode, i.e., postal, or online, determines the outcome and has a moderating effect. Further, we investigate whether the results differ when vouchers are offered instead of cash.
To investigate our assumptions, we included two experimental designs to the recruitment wave and the first wave of the German DeZIM.panel: In the first experiment, that was included in the recruitment wave, we tested the value of the cash incentive (€5 vs. €10) as well as the payment type (unconditional pre-paid vs. conditional post-paid). In this experiment, people could participate both by postal mail and online. In the second experiment, that was included in the first wave, we examined voucher incentives (€10) as well as the payment type (unconditional pre-paid vs. conditional post-paid). Here participants could only participate online. To evaluate the results of the experiments, we consider several measures of data quality: response rates (initial response and completion rates), willingness to participate again (or panel consent), and item non-response.
Our data base - the DeZIM.panel - is a randomized, offline recruited online access panel with oversampling of specific groups with migration history. Since 2022, regular panel operation has taken place with four waves per year, supplemented by quick surveys on current topics.
Ms Honja Hama (Statistics Austria) - Presenting Author
Ms Katrin Schöber (Statistics Austria)
The Microcensus Housing Survey in Austria is a private household survey. The sample is stratified by provinces and covers about 20,000 households per quarter. It is based on the Central Population Register and collects up-to-date information on housing conditions and housing costs. At the beginning of 2021, the new Microcensus regulation came into force, in which Computer Assisted Web Interview (CAWI) was introduced as an additional survey mode to Computer Assisted Personal Interview (CAPI) and Computer Assisted Telephone Interview (CATI). On that account, the survey was adapted to an online-compatible questionnaire.
The questions needed to be easy to understand without assistance and short enough to read on a mobile device. In the beginning, the existing questionnaire was analysed through cognitive pretesting. The problems mostly occurred within the same questions and mainly concerned these about housing costs (rent, running costs, energy costs). In general, questions regarding the costs were easier to answer with documents (advance payment notice, rental agreement, utility bill, etc.).
With the results of the pretesting, the questionnaire was further improved. First, an introduction to the housing costs was implemented. The instruction prompts the respondents to prepare documents on housing costs. Afterwards, the respondents are asked which of them are available. Depending on the documents, the routing of the questionnaire is different and always refers to the said documents. The rent question is built like an invoice, so that the respondents can easily transfer the information from the invoice to the question without much calculation. The questionnaire was also tested in the Microcensus pilot survey and is used since 2021. The results show that the respond burden was reduced by the new format. Furthermore, the quality of the given information can now be analysed based on the used documents.
Dr Meredith Winn Lombard (French Institute of Demographic Studies)
Dr Arianna Caporali (French Institute of Demographic Studies) - Presenting Author
This presentation discusses the improvements to the data documentation process in Round 2 of the Generations and Gender Survey (GGS; https://www.ggp-i.org/) to better account for variable information across time and space and improve the efficiency and the quality of data documentation processes.
The GGS is a cross-national longitudinal survey covering countries in Europe and beyond. It provides in-depth life histories including detailed information on partnerships, fertility, work-life balance, transition to adulthood and later life. Round 1 began in 2002 and consists of one to three waves across nineteen countries. In 2020, we began a new round with a new sample and updated questionnaire.
At the same time, experiences in documenting GGS Round 1 demonstrated a need for data documentation processes better suited to documenting adaptations to the national contexts of the core questionnaire as well as the presence of specific variables across time and space. It was also necessary to involve less manual documentation in order to accommodate the growing scope of the survey.
To address these problems, we have changed the documentation process to include more automation of the variable-level documentation as well as systemic checks for inconsistencies with the core questionnaire. This has allowed us to document surveys more quickly with better accuracy. Further, data documentation is now compliant with the standard Data Documentation Initiative (DDI)-Lifecycle. This standard is specifically suited to document variables information across countries and waves, and allows us to better represent conceptual information in the GGS online data browsing portal. These changes represent important improvements in the quality of the metadata and are a significant added value for data users.
Dr Corinna Frodermann (Institute for Employment Research) - Presenting Author
Dr Mareike Bünning (German Centre of Gerontology)
Professor Lena Hipp (WZB Berlin Social Science Center)
Gender role attitudes are frequently asked in surveys because they have been found to be related to actual (labor market) behavior. To measure gender role attitudes, respondents are typically asked how they assess the consequences of mothers’ full-time employment on (pre-)school aged children (i.e. ISSP, BHPS, EVS). Yet, the development of these measures dates back to the late 1970s, consequently, the wording is criticized as being outdated and reflecting the social roles that were dominant at that time. Furthermore, these items disregard that attitudes may depend on the specific context and that the interplay of the various factors, as they may occur in real decision-making situations, cannot be considered when evaluating single statements. To overcome these limitations, we conducted a factorial survey experiment within the 15th wave of the German Panel Study "Labor Market and Social Security" (PASS), where 3,660 respondents evaluated short descriptions of fictive mothers who received a job offer. This design allows us to investigate the conditions under which people recommend different groups of mothers to accept different types of jobs in different family constellations.
The module was initially designed as a self-completing module for CAPI interviews. However, due to the COVID-19 pandemic and the aim to minimize personal contact, the factorial survey was therefore conducted with an online follow-up questionnaire after completing the personal interview. We use this data in two ways: 1) to conduct selectivity analyses and ask whether there are differences in the general willingness to participate, response rates, and dropouts with respect to sociodemographic characteristics 2) for a comparison of the vignette module with the classic items on gender role attitudes that were asked in wave 11 in terms of attitudes towards maternal employment.
Dr Melanie Revilla (IBEI) - Presenting Author
Mr Carlos Ochoa (RECSM-UPF)
Miss Patricia Iglesias (RECSM-UPF)
The expansion of the Internet and the development of new active and passive measurement tools, particularly on mobile devices, present exciting opportunities for survey researchers, such as visual or audio data capture. Using these new measurement opportunities could reduce respondents' burden, improve data quality, and extend measurement into new domains.
To collect such data in the frame of web surveys, researchers must implement special features on the programming of their web surveys. In this poster, we will present three tools created within the context of the WEB DATA OPP project: 1) WebdataVisual, a tool to gather visual data (e.g., images, screenshots) within the frame of web surveys, 2) WebdataVoice, a tool for dictation or recording of voice answers in the frame of web surveys, and 3) WebdataNow, a tool to implement in-the-moment surveys sent to participants just after an event of interest occurred and is detected using two types of passive data: the geographical coordinates of the participants and the online behaviours gathered using a meter installed by the participants on at least one of the devices they use to go online.
All the codes and documentation are currently available to the research community through the Open Science Framework (https://osf.io/bxuy6/).
Mrs Louisa Köppen (German Centre for Higher Education Research and Science Studies (DZHW))
Dr Kai Mühleck (German Centre for Higher Education Research and Science Studies (DZHW)) - Presenting Author
EUROGRADUATE 2022 is the 2nd European pilot survey of higher education graduates. Higher education graduates are seen by decision makers as being crucial for managing todays societal challenges, such as the digital and green transitions, innovative economies and societal cohesion. At this backdrop, EUROGRADUATE is an initiative to map the impact that experiences of European graduates during their time as students have had on their professional lives and their lives as European citizens. Survey topics are: the education experience and education history, the work history and characteristics of employment, international mobility, social outcomes of higher education (such as social trust, health, happiness, political participation and political attitudes), a well as socio-demographic characteristics of graduates. The survey was fielded in Autumn 2022 and closed in Spring 2023. All participating countries applied online surveys based on a centrally designed master questionnaire and methodology.
EUROGRADUATE 2022 covers 17 European countries (Austria, Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Germany, Greece, Hungary, Italy, Latvia, Malta, Norway, Portugal, Romania, Slovakia and Slovenia). The survey targets graduates of higher education one and five years after graduation to monitor the short-term and the mid-term development of graduates. Thus, for EUROGRADUATE 2022 the target groups are all graduates of the academic years 2020/21 and 2016/17 on ISCED-2011 levels 6 (Bachelor level) and 7 (Master level).
The survey is funded by the European Commission. It is part of a larger initiative, the European graduate tracking initiative, which aims at establishing regular, comprehensive, comparable and longitudinal data on higher education graduates in Europe.
The poster will present the EUROGRADUATE 2022 project with a focus on the survey methods applied, measures to ensure international comparability, differences in methods between countries, and methodological conclusions to be drawn from the field phase.
Mrs Laure Barbot (DARIAH-ERIC)
Mrs Irena Vipavc Brvar (Slovene Social Science Data Archives / CESSDA) - Presenting Author
The Social Sciences and Humanities Open Marketplace (SSH Open Marketplace) - marketplace.sshopencloud.eu - is a discovery portal which pools and contextualises resources for Social Sciences and Humanities research communities: tools, services, training materials, datasets, publications and workflows. The SSH Open Marketplace showcases solutions and research practices for every step of the research data life cycle. In doing so, it facilitates discoverability and findability of research services and products that are essential to enable sharing and re-use of workflows and methodologies.
Acting as a thematic entry door into the European Open Science Cloud (EOSC) - eosc.eu/about-eosc - , the SSH Open Marketplace was built as part of the SSHOC project - cordis.europa.eu/project/id/823782 - and is now funded and maintained by three European Research Infrastructure Consortia (ERIC) - DARIAH, CLARIN and CESSDA - as part of the SSH Open Cluster. The collaboration between the SSH Open Marketplace stakeholders (funders, providers, moderators or contributors) ensures that the cataloguing and contextualising efforts are meaningful and undertaken by and serve social sciences and humanities researchers.
With a population of ~6000 items, aggregated from 15+ trusted sources, as well as those provided by research communities and researchers themselves, the SSH Open Marketplace relies on community curation to ensure the catalogue entries remain up-to-date and useful for SSH researchers. Furthermore, curation routines performed by an Editorial Board, mixing automatic and manual tasks are set up to ensure and continuously improve (meta)data quality.
This poster presents how the SSH Open Marketplace can provide insights into the use of tools, methods and standards in the European Survey Research communities. Participants of the ESRA Conference 2023 are invited to contribute to the creation of new or enrichment of existing records for the benefit of the research community.
Ms Patricia A. Iglesias (Research and Expertise Centre for Survey Methodology, Pompeu Fabra University) - Presenting Author
Mr Carlos Ochoa (Research and Expertise Centre for Survey Methodology, Pompeu Fabra University)
Ms Melanie Revilla (IBEI)
Proposing web survey respondents to answer questions by sharing images is a practice that has gained notoriety during the last years. Indeed, images are expected to help getting more accurate and/or new insights, while also reducing the respondents' burden. Although this new collecting strategy may offer many advantages, it requires researchers to know how to operationalize, collect, process, and analyze this type of data, which is not yet an extended expertise among survey practitioners. This poster aims to guide researchers inexperienced in image analysis by presenting the main steps involved in the process of using images as a new data source: 1) operationalization, 2) definition of the labels, 3) choice of the most suitable classification method(s), 4) collection and 5) classification of the images, 6) verification of the classification outcomes, and 7) data analysis. Following this seven-step process can help practitioners assess whether image collection is appropriate for their research problem and, if so, plan their image-based research by providing them with the key considerations and decisions to address throughout their implementation.
Dr Ina Nepstad (Sikt - Norwegian Agency for Shared Services in Education and Research) - Presenting Author
Ms Mathilde Steinsvåg Hansen (Sikt - Norwegian Agency for Shared Services in Education and Research)
Ms Inga Brautaset (Sikt - Norwegian Agency for Shared Services in Education and Research)
Ms Lisa Lie Bjordal (Sikt - Norwegian Agency for Shared Services in Education and Research)
Mr Njaal Neckelmann (Sikt - Norwegian Agency for Shared Services in Education and Research)
Ms Marianne Høgetveit Myhren (Sikt - Norwegian Agency for Shared Services in Education and Research)
Ms Vigdis Namtvedt Kvalheim (Sikt - Norwegian Agency for Shared Services in Education and Research)
In the last two years, the pandemic has impacted both the way we live and the way we conduct research. The scenarios where our consent to multiple forms of opaque and unwarranted data processing and sharing has multiplied, thereby heightening the risks that our digital identity be relied upon to make decisions contrary to our interests. In Europe, the GDPR regulates the processing of personal data, including data of value to researchers. Research requires a legal basis for the processing of personal data, and a basis for any transfer of data outside Europe. In this context, the pandemic has stress-tested the soundness of the GDPR. The general rules of the GDPR are complex and can be difficult to apply to the field of research, and the digital changes in research, as a result of the pandemic, further contribute to this. Each Member State may supplement the regulation with national rules, making it even more complicated to understand how research data can be lawfully collected, stored, and used. This can easily lead to uncertainty and different interpretations within a community, causing both underuse and unlawful use of personal data for research and archive purposes. As a remedy, the GDPR and EU Commission calls for the creation and use of sector specific Codes of Conduct.
In collaboration with Social Sciences & Humanities Open Cloud (SSHOC), we have created a report that elaborates on the legal terms that must be met, identifies which terms should be addressed first, and provide general recommendations for how a GDPR Code of Conduct can be created. Valuable input from partners and a supervisory authority led to an analysis of legal terms, suggested scope, stakeholder analysis and framework for the establishment of an GDPR Code of conduct.
Mrs Rachael Phadnis (CDC Foundation/CDC) - Presenting Author
Dr Stacy Davlin (CDC Foundation/CDC)
Mr Casey Siesel (CDC)
Mrs Juliette Lee (CDC)
Mrs Veronica Lea (CDC)
Background: The increasing use of mobile phones provides opportunities to produce timely and accurate data to monitor trends and augment traditional health surveys. The COVID-19 pandemic created demand for real-time data, leading to a surge in mobile phone surveys for tracking the impacts of the pandemic We are reporting on mobile phone surveys conducted using Surveda a data collection platform developed for the Noncommunicable Disease Mobile Phone Survey, a component of the Bloomberg Philanthropies Data for Health Initiative.
Objectives: The goal of the surveys was to provide nationally representative estimates of knowledge, attitudes and practices (KAPs) and access and barriers to testing to improve and enhance the COVID-19 pandemic response in Ecuador. Methods: Two population-based, cross-sectional mobile phone surveys were conducted with Ecuadorian residents during the COVID-19 pandemic in June 2020 and November 2020. Weighted datasets were used to calculate the proportion of responses for categorical and binary variables. To compare the responses of the surveys, independent two-sample t-tests were conducted. In addition, response rates were calculated.
Results: For the first survey, n=1,172, the overall response rate was 13.7% and the completion rate was 89.0%. For the second survey, n=1,200, the overall response rate was 15.9% and the completion rate was 96.6%. Ecuadorians from the second survey were more likely to report trying to get tested for COVID-19 as well as receiving a COVID-19 test (19.7% vs. 39.4%, p-value=.0004). Lastly, respondents of the second survey were statistically significantly more likely than the respondents of the first survey to report that they were practicing social distancing (79.0% vs. 83.3%, p-value=.0414).
Conclusion: Findings from this survey help provide national estimates on select COVID-19 KAPs.
Mr Arturo Bertero (University of Milan) - Presenting Author
The link between attitudes and behaviour is a traditional query of social science research. Given the recent Italian general elections, this traditional research question can be declined in: how did political attitudes impact on Italian voting behaviours?
This contribution seeks to conceptualise political attitudes as a network, in order to understand the intricate infra-attitudes dynamics. Following the insights of network psychometric, RESPONSE data (https://dataverse.unimi.it/dataset.xhtml?persistentId=doi:10.13130/RD_UNIMI/FF0ABQ) will be analysed with a Mixed Graphical Model (https://arxiv.org/abs/1510.06871). In this model, survey variables are represented as network's nodes; their interconnections reflect statistical association instead. This poster will build a network of the following political attitudes:
- Propensity to vote for the main Italian party
- Identification with Italian party
- Position issues
- Valence issues
- Actual voting behaviour
The analysis will test the following hypotheses:
H1: the most central attitude will be the best predictor of voting behaviour
H2: Variables related to party identification will be the most central in the political attitudes network
This contribution will deepen the scientific knowledge of voting studies, being the first contribution applying network methods to Propensity to Vote items.
Miss Emmanuelle Duwez (CDSP (Sciences Po/CNRS)) - Presenting Author
ELIPSS (Étude Longitudinale par Internet Pour les Sciences Sociales) is a French, probability-based, web panel for social sciences research surveys.
Set up in 2012, thanks to fundings granted by the French National Research Agency (ANR), ELIPSS provided participants, to mitigate well-known coverage biases, with an Internet connection and a tablet to complete surveys. In 2020, after a pilot study and the following large-scale roll-out, ELIPSS transformed itself into a “lighter”, self-financing, research infrastructure. As a consequence of this latter significant evolution, now the panel members have to use their own devices.
In a retrospective fashion, this poster presents the ELIPSS infrastructure, its scope, the survey design and, eventually, the data produced and available to the wider research community.
Dr Michael Weinhardt (German Centre of Gerontology) - Presenting Author
We investigate how the topic of a survey, as it is emphasized in social media ads to recruit respondents, may influence and even bias survey results, such as the willingness to participate in online surveys and response behavior during the interview. Not everyone is likely to be attracted equally by specific social media ads. Instead, we assume that people are more drawn to media content that reflects their attitudes and political orientations. However, this may be problematic for survey research as this is likely to bias the sample and skew results on attitudes and orientations related to the survey topic presented during the advertising. For a short web survey covering attitudes towards supply chain legislation ("Lieferkettengesetz") and possible factors for explaining these attitudes (such as nationalism/cosmopolitanism, political orientation, generalized trust, justice principles, as well as a range of sociodemographic variables), we recruited participants on the social networking site Facebook using paid-for advertisements to people 18 years and older in Germany in January 2021. To investigate the effect of social media ad content on survey behavior, we ran an experiment with two different ads emphasizing different aspects of the topic, which was debated in the political arena at the time of the survey. In total, about 500 people responded and completed the survey. We analyze potential differences between the experimental groups in several ways. We look at the success of the different ads in triggering survey participation as well as differences in the distributions of key variables and political attitudes between the experimental groups. Results will be discussed in light of the trade-off of competing goals: on the one hand, attracting attention with social media ads to facilitate recruitment; on the other hand, neutrally presenting the survey topic to avoid bias.
Mrs Almuth Lietz (DeZIM-Institut) - Presenting Author
Dr Jörg Dollmann (DeZIM-Institut)
Dr Jannes Jacobsen (DeZIM-Institut)
Mr Jonas Köhler (DeZIM-Institut)
Professor Sabrina J. Mayer (DeZIM-Institut)
Mrs Madeleine Siegel (DeZIM-Institut)
In recent years, most Western European societies have become increasingly diverse due to ongoing immigration processes. Even though politics and society now mostly acknowledge the reality of post-migrant states in which immigration is an inevitable feature, data collection infrastructures still must catch up. Multi-wave access panels that allow researchers to analyse current trends in society, while still allowing for specific subgroup analyses, are still scarce.
To close this gap, the DeZIM.panel has been set up as such a data collection infrastructure that explicitly takes today’s post-migrant society into account. It was initiated by the German Center for Integration and Migration Research (DeZIM), which is funded by the German Federal Ministry. It started at the end of 2021, building on a large-scale offline-recruited first wave earlier in 2021 with more than 9,000 participants, oversampling specific immigrant-origin groups: people from Turkey and from other majority Muslim countries, from states with guest worker agreements and re-settlers from the East. The DeZIM.panel sample was the result of a two-stage stratified approach.
The DeZIM.panel is a multi-thematic survey that includes topics relevant to sociology, political science, psychology, educational sciences, economics, and other disciplines. It runs four regular waves per year. Each wave includes one of four core modules. The four core modules focus on political institutions, attitudes, and behaviour in wave 1; on societal values and societal norms in wave 2; on health and well-being in wave 3; and on labour, education, and discrimination experiences in wave 4. In addition, we ask questions about current topics, such as the Covid-19 pandemic and the war in Ukraine.
Our poster will provide an overview of the general setup of the DeZIM.panel and we intend to share best practices.