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 (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- 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.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- 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.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- 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.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- 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.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- 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.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- 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.