Web Survey Bibliography
Background: The majority of Internet-mediated studies use measures developed as paper-and-pencil measures or face-to-face-delivered material. Previous research suggests that the equivalence between online and offline measures must be demonstrated rather than assumed.
Objective: The objective of this study was to explore the equivalence 4 measures completed in an online or offline setting.
Methods: A sample of students (n = 1969) was randomly assigned to complete 4 popular scales (the SF-12v2, the Hospital Anxiety and Depression Scale (HADS), the Fatigue Symptom Inventory, and a single-item fatigue measure) either online or by mail survey (pencil and paper). The response rate was 52.51% (n = 1034) and comparable between the online and offline groups.
Results: Significant differences were noted in fatigue levels between the online and offline group (P = .01) as measured by the Fatigue Symptom Inventory, with the online sample demonstrating higher levels of fatigue. Equivalency was noted for the SF-12v2, the Hospital Anxiety and Depression Scale, and the single-item fatigue measure. Internal consistency was high except for the SF-12v2. The SF-12v2 may not be an ideal measure to use for remote administration.
Conclusions: Equivalency of the Hospital Anxiety and Depression Scale (HADS) and the Physical Component Score and Mental Component Score of the SF-12v2 for online and offline data were demonstrated. Equivalency was not demonstrated for the Fatigue Symptom Inventory. Explanations for the difference in fatigue score between the online and offline samples are unclear. Research that seeks to match samples and control for extraneous online and offline variables is called for, along with exploration of factors that may mediate the completion of questionnaires or alter the respondents’ relationship with the same, to enhance progress in this area.
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Web survey bibliography (4086)
- The Best of Both Worlds: Utilizing Best Practices From Web and Survey Design ; 2016; Libman Barry, A.; Langer Tesfaye, C.; Levy, J.
- Characterizing Satisficers in Web Surveys Using Paradata to Target Interventions; 2016; Vetting, S. S.; Horwitz, R.; Bray, R.; Hernandez Vivier, A.; Tancreto, J.; Reiser, C.
- A Closer Look at Response Time Outliers in Online S urveys Using Paradata Survey Focus ; 2016; Schlosser, S.; Hoehne, J. K.
- Exploring Mode Effects Between Smartphone and Perso nal Computer Mode of Administration of a National...; 2016; Fahrney Wiant, K.; Richards, A.; Zimmer, S.; Mayclin, D.
- Response Order Effects on a Web Survey of Nurse Pra ctitioners ; 2016; Quintana, G.; Riley, L. E.
- Using Paradata to Identify Questions with High Resp ondent Burden for Improvement in Future Surveys ; 2016; Powell, R.Richards, A.Yu, S.Brackbill, R.
- Investigating Cognitive Effort of Response Formats in Web Surveys using Paradata ; 2016; Hoehne, J. K.; Schlosser, S.; Krebs, D.
- Assessing the Effects and Effectiveness of Attention-check Questions in Web Surveys: Evidence From a...; 2016; Vannette, D.
- Conducting Survey Experiments Using an Online Labor Market ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Ferrer, R.; Berrigan...
- Mode Effect on Racial Sensitive Questions between W eb and Computer-assisted Self-interview ; 2016; Liu, M.; Wang, Y.; Lepkowski, J. M.
- A Test of Web/PAPI Protocols and Incentives for the Residential Energy Consumption Survey ; 2016; Biemer, P. P.; Murphy, J.; Zimmer, S.; Berry, J.; Lewis, K.; Shaofen, D.
- Mode Effects in American Trends Panel: Bayesian Analysis of a Cross-classified Item-person Mixed Model...; 2016; Gill, Je.; Kolenikov, S.; McGeeney, K.
- Mobile Device Use in Web Surveys Among College Students: Predictors and Consequences for Data Quality...; 2016; Beach, S.; Musa, D.; Strotmeyer, S.; Schlarb, J.
- Mode Effects on Subjective Well-being Research: Do they Affect Regression Coefficients? ; 2016; Sanchez Tome, R.; Roberts, C.; Staehli, M. E.; Joye, D.
- Effects of an Initial Offering of Multiple Survey Response Options on Response Rates; 2016; Steele, E. A.; Marlar, J.; Allen, L.; Kanitkar, K. N.
- How to Invite? Methods for Increasing Internet Surv ey Response Rate ; 2016; Huang, A. R.; Noel, H.; Hargraves, L.
- The Mobile Web Only Population: Socio-demographic Characteristics and Potential Bias ; 2016; Fuchs, M.; Metzler, A.
- Unintentional Mobile Respondents in Official Statis tics and Their Effect on Data Quality ; 2016; Bakker, J.
- Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages ; 2016; West, B. T.; Ghimire, D.; Axinn, W.
- Testing Web-Based Survey Measures of Gender Identity and Sexual Orientation Using Mark-All-That-Apply...; 2016; Brenner, P.; Bulgar - Medina, J.
- Mode and Eligibility Rates in a Dual-mode Web and Mail Survey ; 2016; Ventura, I.; Bilgen, I.; Stern, M. J.
- The Impact of Response Scale Direction on Survey Responses in a Mixed-mode Survey ; 2016; Hu, M.; Yan, T.; Keusch, F.
- Examining Trends in the Presence of Survey Mode Effects ; 2016; Hisako Kitada, H.; Lesser, V. M.
- Best Practice Instrument & Communications Evaluation: An Examination of the NSCH Redesign ; 2016; Higgins, W. B.; Welch, R.; Tortora, R. D.; Vladutiu, C. J.
- The Effect of Respondent Commitment and Tailored Fe edback on Response Quality in an Online Survey ; 2016; Cibelli Hibben, K.; Conrad, F. G.
- Effectiveness of Messaging to Encourage Response to the ACS ; 2016; Fulton, J.; Hunter Childs, J. E.; Morales, G.
- Reaching the Mobile Generation: Reducing Web Survey Non-response through SMS Reminders ; 2016; Kanitkar, K. N.; Marlar, J.
- The Effect of Using Text Messages for Survey Invitations and Reminders ; 2016; McGeeney, K.; Yan, H. Y.
- "Don't be Afraid ... We're Researchers!": The Impact of Informal Contact Language...; 2016; Foster, K. N.; Hagemeier, N. E.; Alamain, A. A.; Pack, R.; Sevak, R. J.
- Does Embedding a Survey Question in the Survey Invi tation E-mail Affect Response Rates? Evidence from...; 2016; Vannette, D.
- Mode Effects in Electoral Polls: A Comparative Perspective ; 2016; Durand, C.
- Safety First: Ensuring the Anonymity and Privacy of Iranian Panellists’ While Creating Iran...; 2016; Farmanesh, A.; Mohseni, E.
- Novel Methodology for Reaching a Statewide Represen tative Sample of Youth Ages 12-18 ; 2016; Freedner-Maguire, N.; ZuWallack, R. S.
- Communication Channels that Predict and Mediate Self-response ; 2016; Walejko, G. K.
- Encouraging Online Response among Hard-to-Survey Po pulations: Digital Advertising and Influencer Calls...; 2016; Bates, N.; Virgile, M.
- ...; 2016; Mccaffrey, K. M.; Otmany, J.; Hagedorn, S.
- Simulating a Census Environment to Test Online Self -response ; 2016; Vines, M.
- Using a Response Propensity Model to Allocate Non-c ontingent Incentives in a Web Panel ; 2016; Masterton, M.
- Promoting Participation in Web Surveys; 2016; Hupp, A.; Chan, W.
- Does Asking for Linkage Consent in the Beginning of the Questionnaire Affect Respondents' Answers...; 2016; Haas, G. C.; Eckman, S.
- Implications of Response Device Type for Sensitive Web Surveys: Examining Data Quality and Respondent...; 2016; C.; Richards, A.; C.; Peterson, K.; Smith, A. C.
- Influence of Multiple Factors on Response Rate; 2016; Chaney,B.H.; Chaney, B. H.; Kindlon, A.
- What’s Your Number? Evaluating the Success of Telep hone Number Acquisition Via Record Match,...; 2016; Linville, J. C.; Carley- R.; Carley- R.; Grant, D. B.; Carley- R.; Jans, M.; Carley- R.; Park, R.; Becker...
- Tracking the Representativeness of an Online Panel Over Time ; 2016; Klausch, L. T.; Scherpenzeel, A.
- Can Using a Mixed Mode Approach Improve the Representativeness and Data Quality in Panel Surveys?; 2016; Stern, M. J.
- Surveying American Indian and Alaska Native Parents : Identifying Characteristics of Survey Mode Preference...; 2016; Feeney, K.; Masters, F.
- The Impact of Scale Direction, Alignment and Length on Responses to Rating Scale Questions in a Web...; 2016; Keusch, F.; Liu, M.; Yan, T.
- Pre-election Surveys Using a Multi-modal Interviewing Strategy ; 2016; Redman, J.; Thompson, Sc.; Yost, B.
- Methods for Detecting Telescoping Error in a Cross- sectional Web Design Survey ; 2016; Shook-Sa, B. E.; Berzofsky, M.; Peterson, K.; Lindquist, C.; Krebs, C.
- Introduction Breakoffs, Questionnaire Breakoffs and Web Questionnaire Length: A Metastudy ; 2016; Cehovin, G.; Vehovar, V.