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Background The coronavirus nonstructural protein 5 (Nsp5) is a cysteine protease required for processing the viral polyprotein and is therefore crucial for viral replication. Nsp5 from several coronaviruses have also been found to cleave host proteins, disrupting molecular pathways involved in innate immunity. Nsp5 from the recently emerged SARS-CoV-2 virus interacts with and can cleave human proteins, which may be relevant to the pathogenesis of COVID-19. Based on the continuing global pandemic, and emerging understanding of coronavirus Nsp5-human protein interactions, we set out to predict what human proteins are cleaved by the coronavirus Nsp5 protease using a bioinformatics approach. Results Using a previously developed neural network trained on coronavirus Nsp5 cleavage sites (NetCorona), we made predictions of Nsp5 cleavage sites in all human proteins. Structures of human proteins in the Protein Data Bank containing a predicted Nsp5 cleavage site were then examined, generating a list of 92 human proteins with a highly predicted and accessible cleavage site. Of those, 48 are expected to be found in the same cellular compartment as Nsp5. Analysis of this targeted list of proteins revealed molecular pathways susceptible to Nsp5 cleavage and therefore relevant to coronavirus infection, including pathways involved in mRNA processing, cytokine response, cytoskeleton organization, and apoptosis. Conclusions This study combines predictions of Nsp5 cleavage sites in human proteins with protein structure information and protein network analysis. We predicted cleavage sites in proteins recently shown to be cleaved in vitro by SARS-CoV-2 Nsp5, and we discuss how other potentially cleaved proteins may be relevant to coronavirus mediated immune dysregulation. The data presented here will assist in the design of more targeted experiments, to determine the role of coronavirus Nsp5 cleavage of host proteins, which is relevant to understanding the molecular pathology of coronavirus infection.

In the context of the current “replication crisis” across the sciences, failures to reproduce a finding are often viewed as discrediting it. This paper shows how such a conclusion can be incorrect. In 1981, Schuman and Presser showed that including the word “freedom” in a survey question significantly increased approval of allowing a speech against religion in the USA. New experiments in probability sample surveys (n = 23,370) in the USA and 10 other countries showed that the wording effect replicated in the USA and appeared in four other countries (Canada, Germany, Taiwan, and the Netherlands) but not in the remaining countries. The effect appeared only in countries in which the value of freedom is especially salient and endorsed. Thus, public support for a proposition was enhanced by portraying it as embodying a salient principle of a nation’s culture. Instead of questioning initial findings, inconsistent results across countries signal limits on generalizability and identify an important moderator.

Despite its importance in terms of survey participation, the literature is sparse on how face-to-face interviewers differentially affect specific groups of sample units. This paper demonstrates how an alternative parametrization of the random components in multilevel models, so-called separate coding, delivers valuable insights into differential interviewer effects for specific groups of sample members. In the example of a face-to-face recruitment interview for a probability-based online panel, we detect small interviewer effects regarding survey participation for non-Internet households, whereas we find sizable interviewer effects for Internet households. We derive practical guidance for survey practitioners to address differential interviewer effects based on the proposed variance decomposition.

This paper provides a timely evaluation of whether the main COVID-19 lockdown policies – remote work, short-time work and closure of schools and childcare – have an immediate effect on the German p...

Recent years have seen a growing number of studies investigating the accuracy of nonprobability online panels; however, response quality in nonprobability online panels has not yet received much attention. To fill this gap, we investigate response quality in a comprehensive study of seven nonprobability online panels and three probability-based online panels with identical fieldwork periods and questionnaires in Germany. Three response quality indicators typically associated with survey satisficing are assessed: straight-lining in grid questions, item nonresponse, and midpoint selection in visual design experiments. Our results show that there is significantly more straight-lining in the nonprobability online panels than in the probability-based online panels. However, contrary to our expectations, there is no generalizable difference between nonprobability online panels and probability-based online panels with respect to item nonresponse. Finally, neither respondents in nonprobability online panels nor respondents in probability-based online panels are significantly affected by the visual design of the midpoint of the answer scale.

The outbreak of the COVID-19 pandemic has led to a vast increase in the demand for fast, frequent, and multi-faceted data to study the impact of the pandemic on people’s lives. Existing data collection infrastructures had to be adapted quickly during the early phase of the pandemic to meet this data demand. Our research group contributed to this by conducting the Mannheim Corona Study (MCS), a longitudinal probability-based online survey, in a daily rotating panel design that took place from March 20 through July 10, 2020. The fast-and-frequent panel data collection design of the MCS had numerous consequences for designing its questionnaires and choosing its measurement instruments. This included designing new instruments on the fly in the ever-changing pandemic environment, making efficient use of limited questionnaire space, and deciding on measurement frequencies in a structured manner under uncertain external conditions. In this report, we document the MCS approach to choosing measurement instruments fit for the purpose of fast and frequent data collection during the early phase of COVID-19 in Germany. We particularly highlight three examples of measurement instruments in the MCS and reflect on their measurement properties.

The rapid increase in smartphone surveys and technological developments open novel opportunities for collecting survey answers. One of these opportunities is the use of open-ended questions with requests for oral instead of written answers, which may facilitate the answer process and result in more in-depth and unfiltered information. Whereas it is now possible to collect oral answers on smartphones, we still lack studies on the impact of this novel answer format on the characteristics of respondents' answers. In this study, we compare the linguistic and content characteristics of written versus oral answers to political attitude questions. For this purpose, we conducted an experiment in a smartphone survey (N = 2402) and randomly assigned respondents to an answer format (written or oral). Oral answers were collected via the open source ‘SurveyVoice (SVoice)’ tool, whereas written answers were typed in via the smartphone keypad. Applying length analysis, lexical structure analysis, sentiment analysis and structural topic models, our results reveal that written and oral answers differ substantially from each other in terms of lengths, structures, sentiments and topics. We find evidence that written answers are characterized by an intentional and conscious answering, whereas oral answers are characterized by an intuitive and spontaneous answering.

Nonprobability online panels are commonly used in the social sciences as a fast and inexpensive way of collecting data in contrast to more expensive probability-based panels. Given their ubiquitous use in social science research, a great deal of research is being undertaken to assess the properties of nonprobability panels relative to probability ones. Much of this research focuses on selection bias, however, there is considerably less research assessing the comparability (or equivalence) of measurements collected from respondents in nonprobability and probability panels. This article contributes to addressing this research gap by testing whether measurement equivalence holds between multiple probability and nonprobability online panels in Australia and Germany. Using equivalence testing in the Confirmatory Factor Analysis framework, we assessed measurement equivalence in six multi-item scales (three in each country). We found significant measurement differences between probability and nonprobability panels and within them, even after weighting by demographic variables. These results suggest that combining or comparing multi-item scale data from different sources should be done with caution. We conclude with a discussion of the possible causes of these findings, their implications for survey research, and some guidance for data users.

Established face-to-face surveys encounter increasing pressures to move online. Such a mode switch is accompanied with methodological challenges, including the need to shorten the questionnaire that each respondent receives. Split Questionnaire Designs (SQDs) randomly assign respondents to different fractions of the full questionnaire (modules) and, subsequently, impute the data that are missing by design. Thereby, SQDs reduce the questionnaire length for each respondent. Although some researchers have studied the theoretical implications of SQDs, we still know little about their performance with real data, especially regarding potential approaches to constructing questionnaire modules. In a Monte Carlo study with real survey data, we simulate SQDs in three module-building approaches: random, same topic, and diverse topics. We find that SQDs introduce bias and variability in univariate and especially in bivariate distributions, particularly when modules are constructed with items of the same topic. However, single topic modules yield better estimates for correlations between variables of the same topic. Etablierte Face-to-Face-Erhebungen stehen zunehmend unter dem Druck, online durchgeführt zu werden. Ein solcher Wechsel des Erhebungsmodus ist mit methodischen Herausforderungen verbunden, unter anderem mit der Notwendigkeit, den Fragebogen, den jede/r Befragte erhält, zu kürzen. Bei geteilten Fragebögen (Split Questionnaire Designs, SQDs) werden den Befragten nach dem Zufallsprinzip verschiedene Teile des vollständigen Fragebogens (Module) zugewiesen, und anschließend werden die fehlenden Daten durch Imputation ermittelt. Auf diese Weise reduzieren SQDs die Länge des Fragebogens für jede/n Befragte/n. Obwohl einige Forschende die theoretischen Implikationen von SQDs untersucht haben, wissen wir immer noch wenig über ihre Leistung mit realen Daten, insbesondere im Hinblick auf mögliche Ansätze zur Konstruktion von Fragebogenmodulen. In einer Monte-Carlo-Studie mit realen Umfragedaten simulieren die Autor*innen SQDs in drei Ansätzen zur Modulerstellung: zufällig, gleiches Thema und verschiedene Themen. Sie stellen fest, dass SQDs Verzerrungen und Schwankungen in univariaten und vor allem in bivariaten Verteilungen verursachen, insbesondere wenn Module mit Items desselben Themas konstruiert werden. Einzelne Themenmodule liefern jedoch bessere Schätzungen für Korrelationen zwischen Variablen desselben Themas.

The ease at which online paradata can be captured in web surveys seems to increase social researchers’ desire to collect such data. Yet little attention is paid to whether respondents actually approve of their collection. This article, therefore, studies online survey respondents’ acceptance of automatically collecting their geographical locations. In wave 4 of the German Internet Panel, we asked respondents for their consent to automatically track their location using a JavaScript. Respondents were also asked to report their location in a set of traditional survey questions. About 62 percent of respondents consented to the automated collection of their location whereas 97 percent provided their location manually. With respect to consent biases, we find evidence that the composition of the achieved sample of geo-located respondents is biased and that the personal characteristics associated with respondents’ willingness to be geo-located differ between the automated tracking and manual provision of geo-information.

Once recruited, probability-based online panels have proven to enable high-quality and high-frequency data collection. In ever faster-paced societies and, recently, in times of pandemic lockdowns, such online survey infrastructures are invaluable to social research. In absence of email sampling frames, one way of recruiting such a panel is via postal mail. However, few studies have examined how to best approach and then transition sample members from the initial postal mail contact to the online panel registration. To fill this gap, we implemented a large-scale experiment in the recruitment of the 2018 sample of the German Internet Panel (GIP) varying panel recruitment designs in four experimental conditions: online-only, concurrent mode, online-first, and paper-first. Our results show that the online-only design delivers higher online panel registration rates than the other recruitment designs. In addition, all experimental conditions led to similarly representative samples on key socio-demographic characteristics.

Although the manifestation of borderline personality disorder (BPD) is situated in adolescence and young adulthood, in clinical practice the diagnosis and treatment often get delayed until adulthood. Preliminary research shows good results for structured treatments in young people with BPD. Early intervention programs for BPD show promising results in improvement of the level of functioning. This case study of a fourteen-year-old girl with BPD illustrates early intervention within the program Helping Young People Early (HYPE). This case illustrates the understanding, recognition and revision of relational patterns in emotional and relational problems. In addition, the case highlights the multidisciplinary integration of psychotherapeutic, systemic theoretical and psychosocial ingredients within a multidisciplinary early intervention program for BPD.

This paper evaluates the inequalities in employment trajectories during the first COVID-19 pandemic lockdown in Germany. We assess individual-level panel data collected weekly between 20 March and 25 June (N=2,297), which allows us to examine the risks of short-time work, furlough, and job loss, as well as changes between working on-site and from home. Using sequence analysis, we detect typical patterns of employment trajectories and analyse how these vary between socio-demographic groups. Finally, we relate the types of employment trajectories to changes in income, subjective job security (compared to values in January and February 2020), and COVID-19 infection risks. Our results show clear gradients in employment risks: low-wage workers were severely affected by furlough and job loss, while highly qualified employees were able to work from home. Furthermore, in contrast to previous crises, service sector and female employees were more affected by short-time work; however, its timing and duration differs compared to male workers in manufacturing. Income loss was pronounced among those who became unemployed and those continuously in short-term work, while everybody—including employees continuously working from home—experienced a significant reduction in subjective job security compared to employees whose employment hours or location have not changed. The infection risk was only increased for individuals who changed from furlough to working on-site.

Objective To understand the mental health response to repeated and prolonged stress during the COVID-19 related lockdown and the role of specific health behaviors to buffer against this stress. Methods In a longitudinal study with several measurement points covering three months during the COVID-19 pandemic, about 3500 randomly selected participants representative of the German population reported on their mental health (anxiety, depression, loneliness) and health behaviors (screen time, snack consumption, physical activity). Results Symptoms of anxiety, depression, and loneliness were highest shortly after the lockdown came into effect. Over time, the symptoms were stable or went down slightly, corresponding to patterns of habituation. Among people with higher vulnerability to poor mental health during the lockdown (e.g., women), the proportion with high levels of anxiety, depression, and loneliness was considerably larger. These groups also reported fewer health-promoting behaviors. More screen time, more snacking, and less physical activity were related to higher symptoms of anxiety, depression, and loneliness across all time points. Changes in health behaviors over time mostly did not predict changes in mental health symptoms. Conclusions Mental health and engagement in protective health behaviors was lowest at the start of the lockdown. Health behaviors mostly returned to pre-lockdown levels within three months. Engaging in healthier behaviors was associated with better mental health. Policy implications of these findings are discussed. This study provides important insights into (unintended) side effects of an international crisis and can contribute to a better understanding of how to preserve mental health.

The outbreak of COVID-19 has sparked a sudden demand for fast, frequent and accurate data on the societal impact of the pandemic. This demand has highlighted a divide in survey data collection: Most probability-based social surveys, which can deliver the necessary data quality to allow valid inference to the general population, are slow, infrequent and ill-equipped to survey people during a lockdown. Most non-probability online surveys, which can deliver large amounts of data fast, frequently and without interviewer contact, however, cannot provide the data quality needed for population inference. Well aware of this chasm in the data landscape, at the onset of the pandemic, we set up the Mannheim Corona Study (MCS), a rotating panel survey with daily data collection on the basis of the long-standing probability-based online panel infrastructure of the German Internet Panel (GIP). The MCS has provided academics and political decision makers with key information to understand the social and economic developments during the early phase of the pandemic. This paper describes the panel adaptation process, demonstrates the power of the MCS data on its own and when linked to other data sources, and evaluates the data quality achieved by the MCS fast-response methodology. © 2021 The Authors. Journal of the Royal Statistical Society: Series A (Statistics in Society) published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.

The literature on the effects of incentives in survey research is vast and covers a diversity of survey modes. The mode of probability-based online panels, however, is still young and so is research into how to best recruit sample units into the panel. This paper sheds light on the effectiveness of a specific type of incentive in this context: a monetary incentive that is paid conditionally upon panel registration within two weeks of receiving the initial postal mail invitation. We tested early bird cash incentives in a large-scale recruitment experiment for the German Internet Panel (GIP) in 2018. We find that panel response rates are significantly higher when offering early bird cash incentives and that fieldwork progresses considerably faster, leading to fewer reminders and greater cost-effectiveness. Furthermore, sample representativeness is similarly high with or without early bird incentives. Die Literatur über die Auswirkungen von Anreizen in der Umfrageforschung ist umfangreich und umfasst eine Vielzahl von Erhebungsmodi. Der Modus der "probability-based online panels" ist jedoch noch jung und damit auch die Forschung darüber, wie man am besten Stichprobeneinheiten für das Panel rekrutiert. Die vorliegende Arbeit beleuchtet die Wirksamkeit einer bestimmten Art von Anreiz in diesem Zusammenhang: ein monetärer Anreiz, der unter der Bedingung gezahlt wird, dass sich die Panelteilnehmer*innen innerhalb von zwei Wochen nach Erhalt der ersten postalischen Einladung registrieren. Die Autor*innen haben Frühbucheranreize in einem groß angelegten Rekrutierungsexperiment für das Deutsche Internetpanel (GIP) im Jahr 2018 getestet. Sie stellen fest, dass die Panel-Response-Raten signifikant höher sind, wenn Frühbucher-Boni angeboten werden, und dass die Feldarbeit deutlich schneller voranschreitet, was zu weniger Erinnerungsschreiben und einer höheren Kosteneffizienz führt. Außerdem ist die Repräsentativität der Stichprobe mit und ohne Frühbucherprämie ähnlich hoch.

Background: Health behaviors such as physical activity and a balanced diet are essential to promote and maintain health. Especially during a crisis, such as the COVID-19 pandemic, they have the potential to buffer against stress and protect mental health. Method: In a longitudinal study with four measurement points over 3 months during the COVID-19 pandemic, about 3,500 randomly selected participants representative of the German population reported their mental health (i.e., anxiety, depression, loneliness), screen time, snack consumption, and physical activity. Results: Symptoms of anxiety, depression, and loneliness were highest during the first month of the pandemic-related lockdown, particularly in women and people in poor health, and decreased over time. Screen time and snacking increased and physical activity decreased compared to pre-lockdown. Snacking and physical activity went back to pre-lockdown levels within 2 months; screen time increased further over time. Snack increase and physical activity decrease was stronger in women than men throughout the lockdown. Generally, more screen time, more snacking, and less physical activity were related to higher symptoms of anxiety, depression, and loneliness across all time points. Changes in health behaviors over time did not predict changes in mental health symptoms. Conclusions: Mental health and health behaviors worsened as an immediate response to stress but mostly returned to pre-crisis levels within 2 to 3 months. Engaging in healthier behaviors is associated with better mental health. This study provides important descriptions of (unintended) side effects of a national crisis and contributes to our understanding of how to preserve mental health.

Many policy analyses on COVID‐19 have been focusing on what kind of policies are implemented to contain the spread of COVID‐19. What seems equally important to explore are the social and political consequences of the confinement policies. Does the public support strict confinement policies? What are the social, political, and psychological consequences of the confinement policies? The question of how legitimate a policy is among the public is at the core of democratic theory. Its relevance also stems from the expected consequences of public support on behavior: The more someone supports a policy, the more someone is likely to follow the policy even if the policy is not strictly enforced. In this paper, we will focus on Germany, briefly summarize the main policies during the first 6 weeks of confinement and then explore political attitudes, risk perceptions, and the social consequences of the lockdown.

Background During the COVID-19 pandemic, one way to reduce further transmissions of SARS-CoV-2 is the widespread use of contact tracing apps. Such apps keep track of proximity contacts and warn contacts of persons who tested positive for an infection. Objective In this study, we analyzed potential barriers to the large-scale adoption of the official contact tracing app that was introduced in Germany on June 16, 2020. Methods Survey data were collected from 3276 adults during the week the app was introduced using an offline-recruited, probability-based online panel of the general adult population in Germany. Results We estimate that 81% of the population aged 18 to 77 years possess the devices and ability to install the official app and that 35% are also willing to install and use it. Potential spreaders show high access to devices required to install the app (92%) and high ability to install the app (91%) but low willingness (31%) to correctly adopt the app, whereas for vulnerable groups, the main barrier is access (62%). Conclusions The findings suggest a pessimistic view on the effectiveness of app-based contact tracing to contain the COVID-19 pandemic. We recommend targeting information campaigns at groups with a high potential to spread the virus but who are unwilling to install and correctly use the app, in particular men and those aged between 30 and 59 years. In addition, vulnerable groups, in particular older individuals and those in lower-income households, may be provided with equipment and support to overcome their barriers to app adoption.

Survey data collection costs have risen to a point where many survey researchers are abandoning large, expensive probability-based samples in favor of less expensive nonprobability samples. The empirical literature suggests this strategy may be unwise for many reasons, among them probability samples tend to outperform nonprobability samples on accuracy when assessed against population benchmarks. Nevertheless, the attractive cost properties and convenience of nonprobability samples suggest they are here to stay. But instead of forgoing probability sampling entirely, we consider a method of combining both probability and nonprobability samples in a way that exploits their strengths to overcome their weaknesses. Using Bayesian inference, we evaluate the use of nonprobability data as a supplement to probability-based estimations based on small probability samples. In a case study involving actual survey data, we show that specifying prior distributions using nonprobability data reduces variances and mean-squared errors considerably for estimates of two commonly used health variables, height and weight, compared to the probability-only sample estimates. We further show that these gains in efficiency yield expected cost savings up to 66% based on actual cost data from eight nonprobability surveys conducted by different commercial vendors and assumed cost data for a probability-based Internet panel. We conclude with a discussion of these findings, their implications for survey practice, and possible research extensions.

BACKGROUND During the COVID-19 pandemic, one way to reduce further transmissions of SARS-CoV-2 is the widespread use of contact tracing apps. Such apps keep track of proximity contacts and warn contacts of persons who tested positive for an infection. OBJECTIVE In this study, we analyzed potential barriers to the large-scale adoption of the official contact tracing app that was introduced in Germany on June 16, 2020. METHODS Survey data were collected from 3276 adults during the week the app was introduced using an offline-recruited, probability-based online panel of the general adult population in Germany. RESULTS We estimate that 81% of the population aged 18 to 77 years possess the devices and ability to install the official app and that 35% are also willing to install and use it. Potential spreaders show high access to devices required to install the app (92%) and high ability to install the app (91%) but low willingness (31%) to correctly adopt the app, whereas for vulnerable groups, the main barrier is access (62%). CONCLUSIONS The findings suggest a pessimistic view on the effectiveness of app-based contact tracing to contain the COVID-19 pandemic. We recommend targeting information campaigns at groups with a high potential to spread the virus but who are unwilling to install and correctly use the app, in particular men and those aged between 30 and 59 years. In addition, vulnerable groups, in particular older individuals and those in lower-income households, may be provided with equipment and support to overcome their barriers to app adoption.

Political knowledge can affect measures obtained in public opinion research and political science. When asked political knowledge questions, some respondents look up the answers online, inflating political knowledge scores. This response behavior is detectable in web surveys using paradata. This study investigates whether and to what extent respondents switch away from the survey to search for answers online using JavaScript OnBlur functions. Respondents were randomly assigned to device types (PC or smartphone) and response formats (open or closed) and answered a self-report question. The results reveal that about 30 percent of the respondents look up answers, depending on the device type and response format. They also reveal that switching away and correct answers are significantly associated with the response format. These findings provide new insights on looking up answers online and show that paradata are a promising new method to detect response behavior that may lead to incorrect inferences about respondents’ political knowledge. The findings also show that paradata and self-reports complement each other and that both measures should be combined in future web surveys measuring political knowledge.

The use of web surveys is a common and popular data collection method in behavioral and social research. Compared to other established survey modes, web surveys are frequently cheaper and less time consuming, because they are commonly self-administered. They also allow respondents to take part with few time and location restrictions. However, research has shown that web surveys are frequently associated with multitasking, which may negatively affect response behavior and response quality. In this study, we use paradata detecting switching away from the web survey to explore on-device media multitasking. We conducted a web survey in an opt-in access panel in Germany and randomly assigned respondents to a PC or smartphone condition. The results reveal that on-device media multitasking is more common on PCs than on smartphones. We also find evidence that engaging in on-device media multitasking affects response quality. Respondents who switch away are more likely to select the middle response category. In addition, the results show that the question presentation format, the device type, and respondents’ age and education are associated with the occurrence of on-device media multitasking. These findings point to the importance of controlling for on-device media multitasking in web surveys.

The EURAMET.M.FF-S10 comparison, also registered as EURAMET project 1325, was organized to compare the results of low gas flow facilities at twelve European laboratories. The following laboratories took part in the comparison: MIKES (Finland), INRIM (Italy), PTB (Germany), FORCE (Denmark), METAS (Switzerland), VSL (Netherlands), EIM (Greece), UL (Slovenia), CMI (Czech Republic), LNE (France), GUM (Poland), LEI (Lithuania). Due to the high amount of participants, the comparison was carried out in two parallel loops with one circulating transfer standard in each loop. MIKES acted as the pilot laboratory and INRIM and PTB were the linking laboratories. High-accuracy piston provers (MesaLabs DryCal 800) provided by Mesa Laboratories Inc. were used as transfer standards. Each transfer standard package consisted of three flow cells in order to cover the flow range of the comparison from 5 ml/min to 30 l/min. Generally, a good agreement between participating laboratories was found; 85% of the results agree with the comparison reference value and only 8% were found inconsistent. The remaining 7% of results were classified as inconclusive, because the participating laboratory stated uncertainty was lower than the standard uncertainty of the transfer standard. The comparison provided valuable experience of using piston provers as high precision transfer standards. Such an extensive inter-comparison using piston provers has not been done before. As such, it gives a good overview on the capabilities of European laboratories of calibrating such instruments that are commonly used in industrial calibration laboratories worldwide. Main text To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/. The final report has been peer-reviewed and approved for publication by the CCM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Research has shown that the non-Internet population is hesitant to respond to online survey requests. However, also subgroups in the Internet population with low digital affinity may hesitate to respond to online surveys. This latter issue has not yet received much attention by scholars despite its potentially detrimental effects on the external validity of online survey data. In this article, we explore the extent to which a person’s digital affinity contributes to nonresponse bias in the German Internet Panel, a probability-based online panel of the general population. With a multidimensional classification of digital affinity, we predict response to the first online panel wave and participation across panel waves. We find that persons who belong to different classes of digital affinity have systematically different sociodemographic characteristics and show different voting behavior. In addition, we find that initial response propensities vary by classes of digital affinity, as do attrition patterns over time. Our results demonstrate the importance of digital affinity for the reduction in nonresponse bias during fieldwork and for postsurvey adjustments.

At the turn of the decade, this special issue is a symbol of transformation in the survey world that slowly started in the 2000s and that is likely to continue into the future. At the heart of this transformation lies an age-old academic debate on the merits and costs of probability sampling methods for survey research. While a century ago, probability sampling was hailed as a way of saving costs when depicting social phenomena that were previously described by censuses only, it is becoming increasing expensive. At the same time, society is experiencing a great hunger for ever more and “bigger” data that may explain the increasingly complex world around us. A workshop on “Probability-Based and Nonprobability Survey Research” funded by the German Research Foundation (DFG) and organized by the Collaborative Research Center “Political Economy of Reforms” (SFB 884) at the University of Mannheim in June 2018 brought together expertise on the challenges and pitfalls of probability and nonprobability sampling and planted the seed for this special issue.

New measurements of ongoing subsidence of land proximal to the city of New Orleans, Louisiana, and including areas around the communities of Norco and Lutcher upriver along the Mississippi are reported. The rates of vertical motion are derived from interferometric synthetic aperture radar (InSAR) applied to Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired on 16 June 2009 and 2 July 2012. The subsidence trends are similar to those reported for 2002–2004 in parts of New Orleans where observations overlap, in particular in Michoud, the 9th Ward, and Chalmette, but are measured at much higher spatial resolution (6 m). The spatial associations of cumulative surface movements suggest that the most likely drivers of subsidence are groundwater withdrawal and surficial drainage/dewatering activities. High subsidence rates are observed localized around some major industrial facilities and can affect nearby flood control infrastructure. Substantial subsidence is observed to occur rapidly from shallow compaction in highly localized areas, which is why it could be missed in subsidence surveys relying on point measurements at limited locations.

© 2017, © The Author(s) 2017. Because research on the impact of web survey incentives has exclusively focused on Western settings, it is unclear to what extent current insights translate and generalize to non-Western societies, which are usually characterized by very different economic conditions, cultural traditions, and survey climates. The current article presents the results of a web survey incentives experiment among almost 4,440 Ghanaian university students who were offered conditional and unconditional incentives of different values (in the form of telephone credit). Our analyses partly replicate Western findings: Higher value incentives produce higher participation rates and unconditional incentives outperform conditional ones in the lower value conditions. In the case of relatively high incentives, however, conditional outperforms unconditional incentives. No differential effects of incentives on response quality were found. ispartof: SOCIAL SCIENCE COMPUTER REVIEW vol:36 issue:2 pages:231-250 status: published

Aim: To explore the clinical presentation, course, treatment and impact of early treatment in patients with remethylation disorders from the European Network and Registry for Homocystinurias and Methylation Defects (E-HOD) international web-based registry. Results: This review comprises 238 patients (cobalamin C defect n = 161; methylenetetrahydrofolate reductase deficiency n = 50; cobalamin G defect n = 11; cobalamin E defect n = 10; cobalamin D defect n = 5; and cobalamin J defect n = 1) from 47 centres for whom the E-HOD registry includes, as a minimum, data on medical history and enrolment visit. The duration of observation was 127 patient years. In 181 clinically diagnosed patients, the median age at presentation was 30 days (range 1 day to 42 years) and the median age at diagnosis was 3.7 months (range 3 days to 56 years). Seventy-five percent of pre-clinically diagnosed patients with cobalamin C disease became symptomatic within the first 15 days of life. Total homocysteine (tHcy), amino acids and urinary methylmalonic acid (MMA) were the most frequently assessed disease markers; confirmatory diagnostics were mainly molecular genetic studies. Remethylation disorders are multisystem diseases dominated by neurological and eye disease and failure to thrive. In this cohort, mortality, thromboembolic, psychiatric and renal disease were rarer than reported elsewhere. Early treatment correlates with lower overall morbidity but is less effective in preventing eye disease and cognitive impairment. The wide variation in treatment hampers the evaluation of particular therapeutic modalities. Conclusion: Treatment improves the clinical course of remethylation disorders and reduces morbidity, especially if started early, but neurocognitive and eye symptoms are less responsive. Current treatment is highly variable. This study has the inevitable limitations of a retrospective, registry-based design. © 2018 SSIEM

This article looks into the processes and outcomes of setting up and maintaining a probability-based longitudinal online survey, which is recruited face-to-face and representative of both the online and the offline population aged 16–75 in Germany. This German Internet Panel studies political and economic attitudes and reform preferences through bimonthly longitudinal online interviews of individuals. The results presented here demonstrate that a carefully designed and implemented online panel can produce high-quality data at lower marginal costs than existing panels that operate solely in a face-to-face mode. Analyses into the representativeness of the online sample showed no major coverage or nonresponse biases. Finally, including offline households in the panel is important as it improves the representation of the older and female segments of the population.

Linking survey data to external databases that contain records pertaining to the same respondents holds substantial promise for survey researchers. There are a number of methodological challenges with generating the links between the data sources, but there may also be administrative challenges in linking the datasets. This issue becomes particularly important when conducting cross-national research where research standards and requirements may vary substantially across countries. This chapter provides an overview of process of linking in a comparative context and highlights several issues that researchers are likely to encounter when conducting this type of work.

Catastrophic sinkholes are formed through the collapse of natural or human-made subterranean caverns, and are common in areas with evaporite and carbonate rock. Despite their danger, advance warning of these events is rare. We report a measurement of precursory surface deformation of as much as 260 mm, derived with interferometric synthetic aperture radar (InSAR) and evident over a month before surface collapse, at the site of the Bayou Corne, Louisiana (USA) sinkhole that formed in August 2012. Data collected by the airborne Uninhabited Aerial Vehicle SAR (UAVSAR) instrument were used for the study. Analysis of data acquired from two flight tracks with near-opposing imaging geometries reveal a deformation pattern consistent with compressive loading at the surface due to loss of support from a subterranean cavity collapse related to Texas Brine Oxy Geismar Well #3. The precursor deformation was nearly entirely horizontal, i.e., oriented along the surface, and manifested as movement of surface material toward the location where the sinkhole later formed. The sinkhole formed in the area with the largest gradient in surface strain, but did not cover the full extent of the precursory deformation detected with radar. This work suggests that InSAR data collected operationally for hazard monitoring could, in some cases, identify sinkhole development before surface collapse, and decrease subsequent danger to people and property.

Onlineumfragen haben fur die sozialwissenschaftliche Forschung in den vergangen Jahren zunehmend an Bedeutung gewonnen, nicht zuletzt wegen der Moglichkeit, viele Personen innerhalb kurzer Zeit kosteneffizient befragen zu konnen. Im Vergleich zu interviewer-administrierten Befragungen haben Onlineinterviews aufgrund der selbst-administrierten Befragung einen geringeren Messfehler (Kreuter et al. 2008). Hauptkritikpunkt bei Onlineumfragen ist die Reprasentativitat dieser Studien im Hinblick auf die Allgemeinbevolkerung.

Inferential statistics teach us that we need a random probability sample to infer from a sample to the general population. In online survey research, however, volunteer access panels, in which respondents self-select themselves into the sample, dominate the landscape. Such panels are attractive due to their low costs. Nevertheless, recent years have seen increasing numbers of debates about the quality, in particular about errors in the representativeness and measurement, of such panels. In this article, we describe four probability-based online and mixed-mode panels for the general population, namely, the Longitudinal Internet Studies for the Social Sciences (LISS) Panel in the Netherlands, the German Internet Panel (GIP) and the GESIS Panel in Germany, and the Longitudinal Study by Internet for the Social Sciences (ELIPSS) Panel in France. We compare them in terms of sampling strategies, offline recruitment procedures, and panel characteristics. Our aim is to provide an overview to the scientific community of the availability of such data sources to demonstrate the potential strategies for recruiting and maintaining probability-based online panels to practitioners and to direct analysts of the comparative data collected across these panels to methodological differences that may affect comparative estimates.

The past decade has seen a rise in the use of online panels for conducting survey research. However, the popularity of online panels, largely driven by relatively low implementation costs and high rates of Internet penetration, has been met with criticisms regarding their ability to accurately represent their intended target populations. This criticism largely stems from the fact that (1) non-Internet (or offline) households, despite their relatively small size, constitute a highly selective group unaccounted for in Internet panels, and (2) the preeminent use of nonprobability-based recruitment methods likely contributes a self-selection bias that further compromises the representativeness of online panels. In response to these criticisms, some online panel studies have taken steps to recruit probability-based samples of individuals and providing them with the means to participate online. Using data from one such study, the German Internet Panel, this article investigates the impact of including offline households in the sample on the representativeness of the panel. Consistent with studies in other countries, we find that the exclusion of offline households produces significant coverage biases in online panel surveys, and the inclusion of these households in the sample improves the representativeness of the survey despite their lower propensity to respond.