Web Survey Bibliography
Encouraging survey completion rates in a cost-efficient manner is typically a challenging endeavor. This paper will use data from the 2012 National Mental Health Services Survey (NMHSS) Locator Survey to examine whether one type of respondent reminder is more costefficient than another. The 2012 N-MHSS is sponsored by the federal government’s Substance Abuse and Mental Health Services Administration and includes 22,455 mental health facilities across the United States. Data for this survey were collected using the Web mode with computer-assisted telephone interviewing (CATI) follow-up over a four-month period. Using 4,300 randomly selected facilities equally divided between treatment and control groups, facilities received one of two types of reminder. A specialized reminder letter was mailed first class to the control group and to nonresponders in the non-experiment sample. The treatment group received CATI reminder calls, starting on the same day that the letters were mailed. A two-week field period was established to complete the reminder calls and to allow the letters to arrive at facilities. Our findings will include an analysis of the percentage of facilities that completed the survey during or shortly after the reminder period and an examination of facility characteristics that might affect the completion rate, in addition to analyzing costs. The results of this experiment will help determine whether a particular reminder method is more efficient, both in cost measures and completion rate, and can help inform the survey research field of evolving trends in respondent behavior and reminder mode salience.
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Web survey bibliography (95)
- Virtual reality meets sensory research; 2017; Depoortere, L.
- Methods for Evaluating Respondent Attrition in Web-Based Surveys; 2016; Hochheimer, C. J.; Sabo, R. T.; Krist, A. H.; Day, T.; Cyrus, J.; Woolf, S. H.
- Exploration of Methods for Blending Unconventional Samples with Traditional Probability Samples; 2016; Gellar, J.; Zhou, H.; D.; Sinclair, M. D.
- Ratio of Vector Lengths as an Indicator of Sample Representativeness ; 2016; Shin, H. C.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Validating self-reported mobile phone use in adults using a newly developed smartphone application; 2015; Goedhart, G., Kromhout, H., Wiart, J., Vermeulen, R.
- Innovative Uses of Paradata Across Diverse Contexts ; 2015; Cheung, G.; Pennell, B.-E.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Picking up the Bread Crumbs: Holistic Insights from Social Media; 2014; Souda, P.
- Survey optimisation considerations for Android, Apple and Windows 8 mobile devices; 2013; Owen, R.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Assessing Nonresponse Bias in the Green Technologies and Practices Survey; 2013; Meekins, B., Sverchkov, M., Stang, S.
- Why Big Data is a Small Idea…and Why You Shouldn’t Worry So Much; 2013; Needel, S.
- Doing real time research: Opportunities and challenges; 2013; Back, L., Lury, C., Zimmer, R.
- Digital technology and data collection; 2013; Henriksen, B., Jewitt, C., Price, S., Sakr, M.
- Effects of Self-Awareness on Disclosure During Skype Survey Interviews; 2013; Feuer, S., Schober, M. F.
- Cognitive Interviewing in Online Modes: a Comparison of Data Collected in Second Life and Skype; 2013; Swicegood, J. E., Head, B., Dean, E., Keating, M.
- Effects of Displaying Videos on Measurement in a Web Survey; 2013; Mendelson, J., Gibson, J. L., Romano Bergstrom, J. C.
- Classifying Mouse Movements to Predict Respondent Difficulty; 2013; Horwitz, R.
- Are You Seeing What I am Seeing? Exploring Response Option Visual Design Effects With Eye-Tracking; 2013; Libman, A., Smyth, J. D., Olson, K.
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Internet-Mediated Technologies and Mixed Methods Research; Problems and Prospects; 2012; Hesse-Biber, S.; Griffin, A. J.
- An Introduction to Using Video for Research; 2012; Jewitt, C.
- Online Surveys Aren't Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone...; 2012; Buskirk, T. D., Andrus, C.
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Specific mixed-mode methodology to reach sensory disabled people in quantitative surveys; 2012; Fontaine, S.
- Facing The Future Webcams as a survey tool in China; 2012; Gordon, A., Llewellyn, T., Gu, E.
- Comfortable in the new medium: How online qual can benefit from our share-happy culture ; 2012; Rubenstein, P.
- Using Collaborative Web Technology to Construct the Health Information National Trends Survey; 2012; Moser, R. P., Beckjord, E. B., Finney Rutten, L. J., Blake, K., Hesse, B. W.
- The Representativity of Web Surveys of the General Population compared to Traditional Modes and Mixed...; 2012; Klausch, L. T., Schouten, B., Hox, J.
- Time use data collection using Smartphones: Results of a pilot study among experienced and inexperienced...; 2012; Scherpenzeel, A., Sonck, N., Fernee, H., Morren, Me.
- Using Webinar Polls to Collect Online Survey Data: The Case of a Behavioral Finance Problem; 2012; Sahu, C.
- The Game Experiments: Researching how gaming techniques can be used to improve the quality of feedback...; 2011; Sleep, D., Puleston, J.
- The benefits and constraints of e-mail interviews and discussions as methods of accessing valid data; 2011; Roberts, An.
- Facial imaging: The new face of online survey research; 2011; Gordon, A., McCallum, D., Sorci, M., Llewellyn, T.
- On Affordances and Technological Intersubjectivity; 2011; Vatrapu, R.
- Building online communities; 2011; Mlačić, B., Milas, G., Mikloušić, I.
- Eye Tracking in testing questionnaires: What’s the added value?; 2011; Tries, S.
- Video enhanced web survey; 2011; Fuchs, M., Kunz, T., Gebhard, F.
- Engagement, Consistency, Reach – why the Technology Landscape Precludes All Three; 2011; Johnson, A., Rolfe, G.
- Twitter mood predicts the stock market.; 2011; Bollen, J., Mao, H., Zeng, X.-J.
- Web based CATI on Amazon Elastic Compute Cloud and VirtualBox using queXS; 2011; Zammit, A.
- Web/Cloud Based CATI Using queXS; 2011; Zammit, A.
- Partnership-Driven Resources to Improve and Enhance Research (PRIMER): A Survey of Community-Engaged...; 2011; Dolor, R. J., Greene, S. M., Thompson, E., Baldwin, L.-M., Neale, A. V.
- Weaving the Web into Personal Communication Networks: A Mobile Phone Based Study of Smartphone Users; 2011; Kobayashi, T., Boase, J.
- Different functioning of rating scale formats – results from psychometric and physiological experiments...; 2011; Koller, M., Salzberger, T.
- Measurement invariance in training evaluation: Old question, new context; 2011; P., Gissel, A., Stoughton, J. W., Whelan, T. J.Clark, A. P.