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Abstract In the social and behavioral sciences, surveys are frequently used to collect data. During the COVID-19 pandemic, surveys provided political actors and public health professionals with timely insights on the attitudes and behaviors of the general population. These insights were key in guiding actions to fight the pandemic. However, the data quality of these surveys remains unclear because systematic knowledge about how the survey data were collected during the COVID-19 pandemic is lacking. This is unfortunate, since decades of survey research have shown that survey design impacts data. Our Survey Data Collection and the COVID-19 Pandemic (SDCCP) project deals with this research gap. We collected rich metadata on survey design for 717 social and behavioral science surveys carried out in Germany during the first two years of the COVID-19 pandemic. In this data descriptor, we present a unique resource for a systematic assessment of the survey data collection practices and quality of surveys conducted in Germany during the COVID-19 pandemic.

Dyadic surveys aim to interview pairs of respondents, such as partners in a relationship. In dyadic surveys, it is often necessary to obtain the anchors’ consent to contact their partners and invite them to a survey. If the survey is operated in self-administered modes, no interviewer is present to improve the consent rate, for example, by providing convincing arguments and additional information. To overcome the challenges posed by self-administered modes for dyadic surveys and to improve consent rates, it is important to identify aspects that positively influence the likelihood of anchors giving consent to contact their partners. Ideally, these aspects are in the hands of the researchers, such as the survey design and aspects of the questionnaire. Thus, in this study, we analyzed the relationship between anchors’ survey experience and their willingness to consent to surveying their partners in self-administered modes. Based on data from the German Family Demography Panel Study (FReDA), we found that the anchors’ perceptions of the questionnaire as “interesting” or “too personal” were related to consent rates. These relationships were consistent across different survey modes and devices. Effects of other aspects of the questionnaire, such as “important for science” and “diverse” varied between modes and devices. We concluded with practical recommendations for survey research and an outlook for future research. * This article belongs to a special issue on “Family Research and Demographic Analysis – New Insights from the German Family Demography Panel Study (FReDA)”.

With the rising popularity of web surveys and the increasing use of paradata by survey methodologists, assessing information stored in user agent strings becomes inevitable. These data contain meaningful information about the browser, operating system, and device that a survey respondent uses. This article provides an overview of user agent strings, their specific structure and history, how they can be obtained when conducting a web survey, as well as what kind of information can be extracted from the strings. Further, the user written command parseuas is introduced as an efficient means to gather detailed information from user agent strings. The application of parseuas is illustrated by an example that draws on a pooled data set consisting of 29 web surveys.

This article introduces the evolution, framework, objectives, and design of the new data infrastructure “FReDA – The German Family Demography Panel Study”, which has been funded by the German Federal Ministry of Education and Research (BMBF) since 2020. FReDA is rooted in the Generation and Gender Survey (GGS) and the German Family Panel (pairfam). FReDA was initiated to facilitate research on family and demography by providing a comprehensive panel study allowing for international comparisons as well as dyadic analyses through a multi-actor design. The survey covers major fields of family research, such as fertility behaviour, reproductive health, work-family conflict, dyadic division of work, gender roles, intimate relations, separation and divorce, parenting and intergenerational relations, social inequalities, family attitudes, and well-being. FReDA interviews are conducted in a self-administered web-based (CAWI) or paper-based (PAPI) manner. The infrastructure consists of two different samples. First, the new FReDA-GGS survey started in early 2021, with a wave 1 study population of individuals aged 18 to 49 years and their partners. Second, the FReDA-pairfam survey will continue the 14-wave pairfam sample from 2022 onwards. The questionnaires of both samples will be harmonised as FReDA evolves. Data accessibility, organisation, and future perspectives of the data infrastructure are described and discussed in the paper’s conclusions.

Response probabilities are used in adaptive and responsive survey designs to guide data collection efforts, often with the goal of diversifying the sample composition. However, if response probabilities are also correlated with measurement error, this approach could introduce bias into survey data. This study analyzes the relationship between response probabilities and data quality in grid questions. Drawing on data from the probability-based GESIS panel, we found low propensity cases to more frequently produce item nonresponse and nondifferentiated answers than high propensity cases. However, this effect was observed only among long-time respondents, not among those who joined more recently. We caution that using adaptive or responsive techniques may increase measurement error while reducing the risk of nonresponse bias.

The worldwide spread of the COVID-19 pandemic has disrupted the fieldwork of surveys. The data collection efforts via the face-to-face mode have been affected especially, including the ongoing surveys that were in the field during the COVID-19 outbreak and the planned surveys scheduled for fieldwork later in 2020. We provide an account of how COVID-19 has impacted two family studies in Germany: “The German Family Panel” (pairfam) and the “Generations and Gender Survey” (GGS) both of which will be part of the “Family Research and Demographic Analysis” (FReDA) infrastructure. Based on pairfam, we illustrate the effects of the pandemic on ongoing data collection and the measures taken to proceed with fieldwork, and we report on a special COVID-19 survey. Based on FReDA-GGS, we outline how COVID-19 has affected our planned survey schedules, what future challenges are expected when fieldwork becomes possible again, and how we have adapted our plans accordingly.

Across waves of a panel survey, panel members are repeatedly exposed to the same or very similar survey questions, which might lead to learning effects. We used data from 24 waves of online interviews in a probability-based panel survey to investigate the positive and negative effects of becoming more familiar with the survey questions. We found that respondents became increasingly faster when answering the same questions across waves. Our analyses revealed that this effect could be attributed only partly to satisficing response behaviors associated with negative learning effects (i.e. speeding). In fact, positive learning effects (i.e. answering faster because of greater familiarity with the response tasks) appear to be the primary driver of change in response times. In summary, our research suggests that learning across waves of a panel survey has a positive effect on response behavior, which researchers should consider in survey planning and operations.