Consent to Data Linkage for Different Data Domains – The Role of Question Order, Question Wording, and Incentives

As our modern world has become increasingly digitalized, various types of data from different data domains are available that can enrich survey data. To link survey data to other sources, consent from the survey respondents is required. This article compares consent to data linkage requests for seven data domains: administrative data, smartphone usage data, bank data, biomarkers, Facebook data, health insurance data, and sensor data. We experimentally explore three factors of interest to survey designers seeking to maximize consent rates: consent question order, consent question wording, and incentives. The results of the study using a German online sample (n = 3,374) show that survey respondents have a relatively high probability of consent to share smartphone usage data, Facebook data, and biomarkers, while they are least likely to share their bank data in a survey. Of the three experimental factors, only the consent question order affected consent rates significantly. Additionally, the study investigated the interactions between the three experimental manipulations and the seven data domains, of which only the interaction between the data domains and the consent question order showed a consistent significant effect.

What’s in a Word? Just vs. Fair vs. Appropriate Earnings for Self and Others

Despite Rawls’ famous call to distinguish between justice and fairness, these and other justice-related words often seem to be used interchangeably by both ordinary people and justice researchers. Based on a survey-embedded question wording experiment (N = 4534) fielded in Germany as part of the GESIS Panel, we explore the effects of three justice words— “just,” “fair,” and “appropriate”—on the sense of justice about earnings for self and others. We observe differences in the just reward, justice evaluation, and justice consequences by justice word. For example, justice evaluations of one’s own earnings are more negative, i.e., deeper in the underreward territory, signaling larger just rewards, when using “just” instead of “fair” or “appropriate” in the question wording. No such clear pattern emerges for justice evaluations of others’ earnings. Our analyses show the decreasing effect of an underreward situation on psychosocial health to be significantly stronger in the “just” condition compared to the “fair” condition but do not reveal differential consequences by justice word for measures of satisfaction and trust. Overall, the observed differences by justice words are moderate in size. Nonetheless, our findings suggest caution for justice researchers in communicating with peers and respondents and warrant further inquiry extending research on the role of “justice language” to other language–country contexts.

Survey Methods in Crisis Management

Crisis management research has expanded to include a wide variety of research tools. Survey research has proven to be a useful tool for investigating key questions ranging from risk perception to the consequences of hazards. The context of crisis management presents particular demands on research tools including the deeply disruptive consequences of crises and the importance of place. Careful attention to question wording, sampling, the choice of survey mode, and ethical considerations should shape the design of survey research in crisis management.

The COVID States Project #59: What Americans think about people who are not vaccinated

In this report, we evaluate how people feel about those who are vaccinated and those who are not. A common way of measuring these feelings is through feeling thermometers – special survey items aimed at capturing a respondent’s overall level of warmth towards a particular person, group, or idea. Two of the thermometer questions we asked measured feelings towards “People who are vaccinated against COVID-19” and “People who are NOT vaccinated against COVID-19”, with response options ranging from 0 to 100 degrees. These are the two key outcome variables for this report (see the appendix for full question wording). To evaluate the gap between feelings towards those who are vaccinated against COVID-19 and those who are not, we take the difference in scores between the two corresponding thermometer questions. That tells us how much more favorably respondents view one group compared to the other. Our analyses examine how feelings expressed by the respondents are linked to factors such as partisanship, education, gender, age, income, place of residence and personal vaccination status, among others.

Persistent Misperceptions about Nicotine among US Physicians: Results from a Randomized Survey Experiment

We conducted a survey experiment among US physicians to evaluate whether question wording impacted perceptions about the health effects of nicotine. 926 physicians were randomized to receive one of two versions of a question matrix that asked about the “extent to which they agree or disagree that ‘nicotine’ (Version 1) or ‘nicotine, on its own,’ (Version 2) directly contributes to” birth defects, cardiovascular disease (CVD), cancer, depression, and chronic obstructive pulmonary disease (COPD). We evaluated whether question condition predicted strong agreement and/or agreement with each statement, and assessed demographic correlates of each outcome while adjusting for question version. Physicians who received Version 2 were less likely to “strongly agree” that nicotine directly caused birth defects (Prevalence Ratio (PR) 0.84, 95% CI 0.72–0.98), CVD (PR 0.89, 95% CI 0.84–0.95), cancer (PR 0.81, 95% CI 0.75–0.87), and COPD (PR 0.78, 95% CI 0.72–0.84). Females were more likely to “strongly agree” that nicotine directly contributes to birth defects and cancer, and family physicians were most likely to “strongly agree” that nicotine directly contributes to CVD, cancer, and COPD. Question wording is important when measuring physicians’ beliefs about nicotine; however, even after accounting for question version, misperceptions about the direct health effects of nicotine were common and varied by sex and specialty.

Adopting standard variable labels solves many of the problems with sharing and reusing data

Datasets and analysis scripts are becoming more available online, but most datasets are still unclear and difficult to use due to poor meta-data. Adopting standard variable label solves most of these problems and is easily implemented if we set the labels at the time of publication, that is, for authors to also establish standard variable labels when they establish for example, question wording. This simple step involves little effort but facilitates the sharing of datasets and analysis scripts enormously. Current initiatives to improve meta-data rely on users spending much time creating new meta-data for each variable, which is time consuming, unenjoyable, and hinders adoption. Some suggestions are made on how brief, unique, and clear variable labels can be developed, especially using the last two digits of the year the scale was published in. Standards for dataset and analysis script etiquette are the future, and the final section of the manuscript examines other easy places simple standards can save time and frustration for (re)users.