Relevance & Research Question

The wealth of survey data amassed over the last century represents an invaluable tool for understanding human beliefs, attitudes, and behaviors and how these have evolved. But although thousands of datasets are available to researchers, scholars are often unable to use more than a handful for any given project. One challenge is that many questions, even those asking about similar topics, employ different wordings and response options. Hence, it is often difficult to tell whether differences between responses to questions are indicative of items that track subtly different topics, methodological choices, or changes over time. Instead, scholars examining trends often limit analyses to the subset questions asked identically at multiple time points. The current study proposes a novel solution to identifying common questions across data collections.

Methods & Data

Using microdata from over 2000 distinct probability US surveys of abortion attitudes, we produce a vector of means for each abortion measure at the intersections of age, gender, race, religion, and location. These can then be correlated across surveys (with appropriate weighting) to determine how similar the measures are and to identify measures that appear to capture similar underlying constructs (through clustering and other dimension reduction). We then parameterize how estimates of that similarity shift depending on the data collection methods, survey firms, and the temporal distance between surveys.
Results

We show that this technique allows us to (1) identify the different types of historical questions that exist to measure views on abortion, (2) discern the similarity of those different types of questions, and (3) estimate how attitudes toward different types of questions have trended over time both overall and within population subgroups. We also find that stability of measures is relatively consistent for relations between items asked within 100 days of one-another, whereas it drops notably with longer time differences between measures.
Added Value

The study opens up novel methods for analysis of historical survey data.

Relevance & Research Question
In standardized surveys, the quality of responses is essential. Numerous studies discuss how respondents’ care and effort in answering survey questions is linked to personality, cognitive ability and socio-demographic variables such as age, education, and income, but only few researchers have studied the effect of political attitudes on response quality. Voogt & van Kempen (2002) find that differences between survey respondents and non-respondents in terms of political attitudes and behaviour exceed socio-demographic differences, and Barth & Schmitz (2016) argue that response quality systematically varies with ideological positions. Therefore, in this study we ask whether political attitudes are related to response quality in a standardized survey of the general population in Germany.
Methods & Data

German General Social Survey (ALLBUS/GGGS 2021), https://doi.org/10.4232/1.14002. The GGGS is a biennial survey based on a random sample of the German population. In 2021, due to the Covid-19 pandemic, it was fielded as a mail / web survey for the first time. The questionnaire was distributed in three randomized split versions. In the first step, indicators for response quality are constructed separately for each split version. These include non-substantial “response styles”, such as extreme responding and non-differentiation, as well as the proportion of item non-response. Subsequently, we conduct regression analyses with political attitudes (e.g. political interest, positions towards cultural and economic issues, intention to vote in upcoming election) as explanatory factors of response quality while controlling for socio-demographic variables, survey mode and number of contact attempts.
Results

The analyses show that differences in response quality in the GGGS 2021 are systematically related to age, education and political interest as well as other political attitudes.
Added Value
Research on the nexus between response quality and political attitudes is highly relevant, as systematic relationships between response quality and substantive variables of interest may seriously compromise surveys’ ability to capture “public opinion”. Whereas the GGGS is an offline-recruited population survey, effects of political attitudes on response quality are likely to be even more pronounced in (non-probability) online panels.

Relevance & Research Question
Understanding citizens’ architectural style preferences are important for aesthetically pleasing and sustainable urban environments. However, the opinions of the people are seldom considered in contemporary urban planning. In recent years, an intense debate has unfolded in Sweden about the role of politicians versus architects versus urban planners on how future urban landscapes should be built and, specifically, in what architectural style tradition. Thus, we explore architectural style preferences (classic vs modernist) of Swedish citizens. We model how preferences are predicted by sociodemographic and political factors.
Methods & Data
Data consisted of a non-probability sample (N=3119) and a probability sample (N=2125) from the online Swedish Citizen Panel at the University of Gothenburg. Participants were asked to state their preference for classic or modernist architecture and to associate design elements (building materials, level of details in facades and costs) with each tradition. Trust in various professional groups involved in urban planning, including architects, were also assessed.
Results
Findings demonstrate a general preference for classic over modernist architecture in the non-probability and probability-based sample (p <.001). Notably, no differences among different party supporters where observed, indicating low political polarization on architectural preferences. Further, a logit regression model underscored the negative association between classic architectural preferences and social and political trust, as well as trust in architects (p <.001).
Added Value
We show that Swedish citizens have a clear preference towards classical architecture and that this support is stable across sociodemographic groups and party preference. The results provide insights for policy makers in urban planning. Replication and extension of these findings is currently being collected in a large population representative mixed-mode survey on Swedish citizens. Results from the additional data collection will be presented at the conference.

Relevance & Research Question
With the increasing prevalence of digital work environments, understanding the impact of online interruptions on work efficiency becomes crucial. This study probes into how online interruptions' frequency and information richness affect the pace of work. It specifically examines two hypotheses: whether slow-frequency interruptions lead to a more efficient work pace compared to fast-frequency ones and how the nature of interruption information (lean: text-only vs. rich: image + text) influences the speed of work-related tasks.
Methods & Data
A 2 × 2 factorial experimental design was implemented, involving 250 participants in a simulated online trading game in which participants had to gain profits. The experiment manipulated two main variables: interruption frequency (slow vs. fast) and information richness (lean vs. rich). Participants' task completion times were recorded to measure work pace. Statistical analyses, including ANOVA and post hoc tests, were conducted to determine the effects of these variables on work efficiency.
Results
The ANOVA revealed significant main effects for interruption frequency on work pace, F(1, 246) = 8.97, p < .01, and for information richness, F(1, 246) = 6.54, p < .05. Participants dealing with slow-frequency interruptions had a mean work pace of 12.29 tasks per hour (SD = 4.21) compared to 13.87 tasks per hour (SD = 4.02) for those with fast-frequency interruptions. Surprisingly, lean information interruptions resulted in a faster work pace (M = 12.68, SD = 3.82) than rich information (M = 13.48, SD = 4.50). The interaction effect was significant, F(1, 246) = 9.33, p < .01, indicating that the most efficient work pace occurred under slow-frequency and lean information interruptions.
Added Value
This research sheds light on the nuanced effects of online interruptions in digital workplaces, challenging prevailing notions in media richness theory. By demonstrating that not only the frequency but also the type of information in interruptions can significantly influence work pace, it provides actionable insights for designing more productive digital work environments. These findings have implications for human-computer interaction designers, organizational psychologists, and workplace strategists aiming to optimize productivity in multi-tasking settings.