Web Survey Bibliography
In Web surveys, rating scales measuring the respondents’ attitudes and self-descriptions by means of a series of related statements are commonly presented in grid (or matrix) questions. Despite the benefits of displaying multiple rating scale items neatly arranged and supposedly easy to complete on a single screen, respondents are often tempted to rely on cognitive shortcuts in order to reduce the extent of cognitive and navigational effort required to answer a set of rating scale items. In order to minimize this risk of cognitive shortcuts resulting in satisfying rather than optimal answers, respondents have to be motivated to spend extra time and effort on the attentive and careful processing of rating scales. A wide range of visual and dynamic features are available in interactive Web surveys allowing for visual enhancement and greater interactivity in the presentation of survey questions. To date, however, only a few studies have systematically examined new rating scale designs using data input methods other than conventional radio buttons. In the present study, two different rating scales were designed using drag-and-drop as a more interactive data input method: Respondents have to drag the response options towards the rating scale items (‘drag-response’), or in the reverse direction, the rating scale items towards the response options (‘drag-item’). In both drag-and-drop rating scales, the visual highlighting of the items and response options as well as the dynamic strengthening of the link between these key components are aimed at encouraging the respondents to process a rating scale more attentively and carefully. The effectiveness of the drag-and-drop rating scales in preventing the respondents’ susceptibility to cognitive shortcuts is assessed on the basis of five systematic response tendencies that are typically accompanied by rating scales, i.e., careless, nondifferentiated, acquiescent, and extreme responding as well as the respondents’ systematic tendency to select one of the first response options, so called primacy effects. Moreover, item missing data, response times, and respondent evaluation are examined. The findings of the present study revealed that although both drag-and-drop scales entail a higher level of respondent burden as indicated by an increase in item missing data and longer response times compared to conventional radio button scales, they promote the respondents’ attentiveness and carefulness towards the response task which is accompanied by the respondents’ reduced susceptibility to cognitive shortcuts in processing rating scales.
Ratingskalen zu Erfassung von Einstellungen und Persönlichkeitsmerkmalen des Befragten werden in Online-Befragungen bevorzugt in Form einer Matrixfrage dargestellt. Matrixfragen bieten zwar gewisse Vorzüge hinsichtlich der übersichtlichen Darstellung und einer vermeintlich einfachen Bearbeitung mehrerer Items. Gleichzeitig sind sie jedoch auch anfälliger für systematische Antworttendenzen, die zur Verringerung der Datenqualität führen können. Um dem Risiko derartiger Abkürzungsstrategien entgegenzuwirken, müssen die Befragten zur aufmerksamen und sorgfältigen Bearbeitung von Ratingskalen motiviert werden. Online-Befragungen ermöglichen den Einsatz visueller und interaktiver Elemente zur optischen Aufwertung einzelner Fragen und zur Steigung der Interaktivität des Befragungsprozesses insgesamt. Bislang gibt es jedoch nur wenige Studien, die den Einsatz solcher Gestaltungselemente in Ratingskalen untersuchen. Vor diesem Hintergrund werden im Rahmen der vorliegenden Studie zwei unterschiedliche Drag-and-Drop-Ratingskalen konzipiert: In der Drag-Response-Skala sind die Befragten aufgefordert, mit dem Mauszeiger eine ausgewählte Antwortmöglichkeit zum jeweiligen Item zu ziehen, wohingegen in der Drag-Item-Skala das jeweilige Item zur ausgewählten Antwortmöglichkeit gezogen wird. Durch den Einsatz der Drag-and-Drop Technik soll die Aufmerksamkeit gezielt auf die Items und Antwortmöglichkeiten gelenkt sowie die Verbindung zwischen dem jeweiligen Item und der ausgewählten Antwortmöglichkeit verstärkt werden. Zur Überprüfung der Effektivität der beiden Drag-and-Drop-Ratingskalen hinsichtlich einer aufmerksameren und sorgfältigeren Bearbeitung und letztlich einer Vorbeugung von systematischen Antworttendenzen werden mehrere Indikatoren der Datenqualität herangezogen, darunter ‚Careless Responding‘, ‚Nondifferentiation‘, ‚Acquiescence‘, ‚Extremity‘ sowie ‚Primacy Effekte‘. Darüber hinaus werden das Ausmaß fehlender Werte, die Antwortzeiten und Bewertungen der Befragten ausgewertet. Die Ergebnisse der vorliegenden Untersuchung zeigen, dass die Drag-and-Drop-Ratingskalen zwar mit einem gesteigerten Aufwand für Kognition und Navigation einhergehen, welcher zu mehr fehlenden Werten und längeren Antwortzeiten führt. Gleichzeitig jedoch werden die Befragten zu einem aufmerksameren und sorgfältigeren Antwortverhalten motiviert, was wiederum systematischen Antworttendenzen entgegenwirkt.
Web survey bibliography (367)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.
- Analyzing Survey Characteristics, Participation, and Evaluation Across 186 Surveys in an Online Opt-...; 2017; Revilla, M.
- Careless Response and Attrition as Sources of Bias in Online Survey Assessments of Personality Traits...; 2017; Meade, A. W.; Ward, M. K.; Alfred, C. M.; Pappalardo, G.; Stoughton, J. W.
- Do Incentives Increase Response Rates to an Internet Survey of American Evaluation Association Members...; 2017; Wilson, L. N.
- Examining Completion Rates in Web Surveys via Over 25,000 Real-World Surveys; 2017; Liu, M.; Wronski, L.
- Data collection mode differences between national face-to-face and web surveys on gender inequality...; 2017; Liu, M.
- Improving survey response rates: The effect of embedded questions in web survey email Invitations; 2017; Liu, M.; Inchausti, N.
- An experimental comparison of web-push vs. paper-only survey procedures for conducting an in-depth health...; 2017; McMaster, H. S.; LeardMann, C. A.; Speigle, S.; Dillman, D. A.
- Demographic Question Placement: Effect on Item Response Rates and Means of a Veterans Health Administration...; 2017; Teclaw, R.; Price, M.; Osatuke, K.
- Effects of Applying Multimedia and Dialogue Box to Web Survey Design; 2017; Chen, H.
- Role of online survey tools in creating temporally accurate Environmental Product Declarations (EPD)...; 2017; Ganguly, I.; Bowers, T.; Pierobon, F.; Eastin, I.
- A test of sample matching using a pseudo-web sample; 2017; Chatrchi, G., Gambino, J.
- A Partially Successful Attempt to Integrate a Web-Recruited Cohort into an Address-Based Sample; 2017; Kott, P. S., Farrelly, M., Kamyab, K.
- Grundzüge des Datenschutzrechts und aktuelle Datenschutzprobleme in der Markt- und Sozialforschung; 2017; Schweizer, A.
- Data chunking for mobile web: effects on data quality; 2017; Lugtig, P. J.; Toepoel, V.
- Comparing data quality and cost from three modes of on-board transit surveys ; 2017; Agrawal, A. W.; Granger-Bevan, S.; W.; Newmark, G. L.; Nixon, H.
- Finding and Investigating Geographical Data Online; 2017; Martin, D.; Cockings, S.; Leung, S.
- Three Methods for Occupation Coding Based on Statistical Learning; 2017; Geweon, H.; Schonlau, L.; Blohum, M.; Steiner, St.
- Dynamic Question Ordering in Online Surveys; 2016; Early, K.; Mankoff, J.; Fienberg, S. E.
- How to use online surveys to understand human behaviour concerning window opening in terms of building...; 2016; Fabbri, K.
- Impact of satisficing behavior in online surveys on consumer preference and welfare estimates; 2016; Gao, Z.; House, L. A.; Bi, X.
- Targeted Appeals for Participation in Letters to Panel Survey Members; 2016; Lynn, P.
- Can we assess representativeness of cross-national surveys using the education variable?; 2016; Ortmanns, V.; Schneider, S.
- Methodological Aspects of Central Left-Right Scale Placement in a Cross-national Perspective; 2016; Scholz, E.; Zuell, C.
- Fieldwork Effort, Response Rate, and the Distribution of Survey Outcomes: A Multilevel Meta-analysis; 2016; Sturgis, P.; Williams, Jo.; Brunton-Smith, I.; Moore, J.
- Comparison of Face-to-Face and Web Surveys on the Topic of Homosexual Rights; 2016; Liu, M.; Wang, Yic.
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Web-Based Statistical Sampling and Analysis; 2016; Quinn, A.; Larson, K.