Advertisement

Web-Based Survey Methodology

  • Kevin B. WrightEmail author
Reference work entry

Abstract

This chapter examines a number of issues related to online survey research designed to access populations of various stakeholders in the health care system, including patients, caregivers, and providers. Specifically, the chapter focuses on such issues as finding an adequate sampling frame for obtaining samples of online populations, measurement issues, enhancing response rates, overseeing web-based survey data collection, and data analysis issues. Moreover, it examines issues such as measurement validity and reliability in web-based surveys as well as problems with selection biases and generalizability of study findings. Finally, the chapter assesses the pros and cons of using SurveyMonkey and Qualtrics as web-survey platforms/services and their utility for studying various online contexts that may be of interest to social science and health scholars.

Keywords

Online data collection External validity Response rates Sampling Survey research Websurveys 

References

  1. Bosnjak M, Tuten TL. Classifying response behaviors in web-based surveys. J Comput Mediated Commun. 2001;6. Retrieved from http://www.ascusc.org/jcmc/vol6/issue3/boznjak.html.CrossRefGoogle Scholar
  2. Cook C, Heath F, Thompson R. A meta-analysis of response rates in web or internet based surveys. Educ Psychol Meas. 2000;60:821–36.CrossRefGoogle Scholar
  3. Couper MP. Designing effective web surveys. New York: Cambridge University Press; 2008.CrossRefGoogle Scholar
  4. Curtis BL. Social networking and online recruiting for HIV research: ethical challenges. J Empir Res Hum Res Ethics. 2014;9(1):58–70.CrossRefGoogle Scholar
  5. Denissen JJ, Neumann L, van Zalk M. How the internet is changing the implementation of traditional research methods, people’s daily lives, and the way in which developmental scientists conduct research. Int J Behav Dev. 2010;34(6):564–75.CrossRefGoogle Scholar
  6. Dillman DA. Mail and internet surveys: the tailored design method. New York: Wiley; 2000.Google Scholar
  7. Evans JR, Mathur A. The value of online surveys. Internet Res. 2005;15(2):195–219.CrossRefGoogle Scholar
  8. Eysenbach G, Wyatt J. Using the internet for surveys and health research. J Med Internet Res. 2002;4(2):e13.CrossRefGoogle Scholar
  9. Fan W, Yan Z. Factors affecting response rates of the websurvey: a systematic review. Comput Hum Behav. 2010;26:132–9.CrossRefGoogle Scholar
  10. Galesic M, Bosnjak M. Effects of questionnaire length on participation and indicators of response quality in a web survey. Public Opin Q. 2009;73(2):349–60.CrossRefGoogle Scholar
  11. Greenlaw C, Brown-Welty S. A comparison of web-based and paper-based survey methods: testing assumptions of survey mode and response cost. Eval Rev. 2009;33(5):464–80.CrossRefGoogle Scholar
  12. Johnson JA. Ascertaining the validity of individual protocols from web-based personality inventories. J Res Pers. 2005;39(1):103–29.CrossRefGoogle Scholar
  13. Kaplowitz MD, Hadlock TD, Levine R. A comparison of web and mail survey response rates. Public Opin Q. 2004;68(1):94–101.CrossRefGoogle Scholar
  14. Konstan JA, Simon Rosser BR, Ross MW, Stanton J, Edwards WM. The story of subject naught: a cautionary but optimistic tale of internet survey research. J Comput Mediated Commun. 2005;10(2):Article 11. http://jcmc.indiana/edu/vol10/issue2/konstan.html.Google Scholar
  15. Kramer J, Rubin A, Coster W, Helmuth E, Hermos J, Rosenbloom D, … Brief D. Strategies to address participant misrepresentation for eligibility in web-based research. Int J Methods Psychiatr Res. 2014;23(1):120–29.CrossRefGoogle Scholar
  16. Lieberman DZ. Evaluation of the stability and validity of participant samples recruited over the internet. Cyberpsychol Behav Soc Netw. 2008;11(6):743–5.CrossRefGoogle Scholar
  17. Manfreda KL, Bosnjak M, Berzelak J, Haas I, Vehovar V, Berzelak N. Web surveys versus other survey modes: a meta-analysis comparing response rates. J Mark Res Soc. 2008;50(1):79.Google Scholar
  18. Murray E, Khadjesari Z, White IR, Kalaitzaki E, Godfrey C, McCambridge J, Thompson SG, Wallace P. Methodological challenges in online trials. J Med Internet Res. 2009;11(2):e9.  https://doi.org/10.2196/jmir.1052.CrossRefGoogle Scholar
  19. Owen DJ, Fang MLE. Information-seeking behavior in complementary and alternative medicine (CAM): an online survey of faculty at a health sciences campus. J Med Libr Assoc. 2003;91(3): 311.Google Scholar
  20. Payne J, Barnfather N. Online data collection in developing nations: an investigation into sample bias in a sample of South African university students. Soc Sci Comput Rev. 2012;30(3):389–97.CrossRefGoogle Scholar
  21. Pedersen ER, Helmuth ED, Marshall GN, Schell TL, PunKay M, Kurz J. Using Facebook to recruit young adult veterans: online mental health research. JMIR Res Protocol. 2015;4(2):e63.CrossRefGoogle Scholar
  22. Porter SR, Whitcomb ME. The impact of contact type on web survey response rates. Public Opin Q. 2003;67(4):579–88.CrossRefGoogle Scholar
  23. Pullmann H, Allik J, Realo A. Global self-esteem across the life span: a cross-sectional comparison between representative and self-selected internet samples. Exp Aging Res. 2009;35:20–44.CrossRefGoogle Scholar
  24. Riper H, Spek V, Boon B, Conijn B, Kramer J, Martin-Abello K, Smit F. Effectiveness of e-self-help interventions for curbing adult problem drinking: a meta-analysis. J Med Internet Res. 2011;13(2):e24.  https://doi.org/10.2196/jmir.1691.CrossRefGoogle Scholar
  25. Shaw LH, Gant LM. In defense of the internet: the relationship between internet communication and depression, loneliness, self-esteem, and perceived social support. Cyberpsychol Behav. 2002;5(2):157–71.CrossRefGoogle Scholar
  26. Shih TH, Fan X. Comparing response rates from web and mail surveys: a meta-analysis. Field Methods. 2008;20(3):249–71.CrossRefGoogle Scholar
  27. Siegel MB, Tanwar KL, Wood KS. Electronic cigarettes as a smoking-cessation tool: results from an online survey. Am J Prev Med. 2011;40(4):472–5.CrossRefGoogle Scholar
  28. Simon Rosser BR, Gurak L, Horvath KJ, Michael Oakes J, Konstan J, Danilenko GP. The challenges of ensuring participant consent in internet-based sex studies: a case study of the men’s INTernet sex (MINTS-I and II) studies. J Comput-Mediat Commun. 2009;14(3):602–26.CrossRefGoogle Scholar
  29. Valkenburg PM, Peter J. Social consequences of the internet for adolescents. Curr Dir Psychol Sci. 2009;18:1–5.CrossRefGoogle Scholar
  30. van Ingen EJ, Wright KB. Predictors of mobilizing online coping versus offline coping resources after negative life events. Comput Hum Behav. 2016;59:431–9.CrossRefGoogle Scholar
  31. Wilson PM, Petticrew M, Calnan M, Nazareth I. Effects of a financial incentive on health researchers’ response to an online survey: a randomized controlled trial. J Med Internet Res. 2010;12(2):e13.CrossRefGoogle Scholar
  32. Wright KB. Perceptions of on-line support providers: an examination of perceived homophily, source credibility, communication and social support within on-line support groups. Commun Q. 2000;48:44–59.CrossRefGoogle Scholar
  33. Wright KB. Researching internet-based populations: advantages and disadvantages of online survey research, online questionnaire authoring software packages, and web survey services. J Comput Mediat Commun. 2005;10:Article 11. Retrieved from http://jcmc.indiana.edu/vol10/issue3/wright.html.Google Scholar
  34. Wright KB. A communication competence approach to healthcare worker conflict, job stress, job burnout, and job satisfaction. J Healthc Qual. 2011;33:7–14.CrossRefGoogle Scholar
  35. Wright KB, Miller CH. A measure of weak tie/strong tie support network preference. Commun Monogr. 2010;77:502–20.CrossRefGoogle Scholar
  36. Wright KB, Banas JA, Bessarabova E, Bernard DR. A communication competence approach to examining health care social support, stress, and job burnout. Health Commun. 2010a;25(4): 375–82.CrossRefGoogle Scholar
  37. Wright KB, Rains S, Banas J. Weak tie support network preference and perceived life stress among participants in health-related, computer-mediated support groups. J Comput-Mediat Commun. 2010b;15:606–24.CrossRefGoogle Scholar
  38. Wright KB, Rains S. Weak tie support preference and preferred coping style as predictors of perceived credibility within health-related computer-mediated support groups. Health Commun. 2013;29:281–287.CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of CommunicationGeorge Mason UniversityFairfaxUSA

Personalised recommendations