IDEAS home Printed from https://ideas.repec.org/a/spr/ijphth/v63y2018i6d10.1007_s00038-018-1108-4.html
   My bibliography  Save this article

Response rate differences between web and alternative data collection methods for public health research: a systematic review of the literature

Author

Listed:
  • Cauane Blumenberg

    (Federal University of Pelotas)

  • Aluísio J. D. Barros

    (Federal University of Pelotas)

Abstract

Objectives To systematically review the literature and compare response rates (RRs) of web surveys to alternative data collection methods in the context of epidemiologic and public health studies. Methods We reviewed the literature using PubMed, LILACS, SciELO, WebSM, and Google Scholar databases. We selected epidemiologic and public health studies that considered the general population and used two parallel data collection methods, being one web-based. RR differences were analyzed using two-sample test of proportions, and pooled using random effects. We investigated agreement using Bland-and-Altman, and correlation using Pearson’s coefficient. Results We selected 19 studies (nine randomized trials). The RR of the web-based data collection was 12.9 percentage points (p.p.) lower (95% CI = − 19.0, − 6.8) than the alternative methods, and 15.7 p.p. lower (95% CI = − 24.2, − 7.3) considering only randomized trials. Monetary incentives did not reduce the RR differences. A strong positive correlation (r = 0.83) between the RRs was observed. Conclusions Web-based data collection present lower RRs compared to alternative methods. However, it is not recommended to interpret this as a meta-analytical evidence due to the high heterogeneity of the studies.

Suggested Citation

  • Cauane Blumenberg & Aluísio J. D. Barros, 2018. "Response rate differences between web and alternative data collection methods for public health research: a systematic review of the literature," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(6), pages 765-773, July.
  • Handle: RePEc:spr:ijphth:v:63:y:2018:i:6:d:10.1007_s00038-018-1108-4
    DOI: 10.1007/s00038-018-1108-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00038-018-1108-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00038-018-1108-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Choong-Ki Lee & Ki-Joon Back & Robert J. Williams & Sung-Sik Ahn, 2015. "Comparison of telephone RDD and online panel survey modes on CPGI scores and co-morbidities," International Gambling Studies, Taylor & Francis Journals, vol. 15(3), pages 435-449, December.
    2. Niels Keiding & Thomas A. Louis, 2016. "Perils and potentials of self-selected entry to epidemiological studies and surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 319-376, February.
    3. Aleksandra Gajic & David Cameron & Jeremiah Hurley, 2012. "The cost-effectiveness of cash versus lottery incentives for a web-based, stated-preference community survey," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(6), pages 789-799, December.
    4. Braunsberger, Karin & Wybenga, Hans & Gates, Roger, 2007. "A comparison of reliability between telephone and web-based surveys," Journal of Business Research, Elsevier, vol. 60(7), pages 758-764, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ioannis Chanias & C. Matthias Wilk & Rudolf Benz & Michael Daskalakis & Georg Stüssi & Adrian Schmidt & Ulrike Bacher & Nicolas Bonadies & on behalf of the Swiss MDS Study Group, 2020. "Survey on Recommended Health Care for Adult Patients with Myelodysplastic Syndromes Identifies Areas for Improvement," IJERPH, MDPI, vol. 17(24), pages 1-18, December.
    2. Knut Stavem & Waleed Ghanima & Magnus K. Olsen & Hanne M. Gilboe & Gunnar Einvik, 2021. "Prevalence and Determinants of Fatigue after COVID-19 in Non-Hospitalized Subjects: A Population-Based Study," IJERPH, MDPI, vol. 18(4), pages 1-11, February.
    3. Sadaf Batool Naqvi & Abad A. Shah, 2018. "Modeling Historically mHealth Care Environments," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 7(3), pages 57-75, July.
    4. Matthias Fink & Johannes Gartner & Rainer Harms & Isabella Hatak, 2023. "Ethical Orientation and Research Misconduct Among Business Researchers Under the Condition of Autonomy and Competition," Journal of Business Ethics, Springer, vol. 183(2), pages 619-636, March.
    5. Christine M. Prissel & Brandon R. Grossardt & Gregory S. Klinger & Jennifer L. St. Sauver & Walter A. Rocca, 2023. "Integrating Environmental Data with Medical Data in a Records-Linkage System to Explore Groundwater Nitrogen Levels and Child Health Outcomes," IJERPH, MDPI, vol. 20(6), pages 1-14, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lehmann, Nico & Sloot, Daniel & Schüle, Christopher & Ardone, Armin & Fichtner, Wolf, 2023. "The motivational drivers behind consumer preferences for regional electricity – Results of a choice experiment in Southern Germany," Energy Economics, Elsevier, vol. 120(C).
    2. Nunkoo, Robin & Smith, Stephen L.J., 2013. "Political economy of tourism: Trust in government actors, political support, and their determinants," Tourism Management, Elsevier, vol. 36(C), pages 120-132.
    3. Jeremiah Hurley & Emmanouil Mentzakis & Mita Giacomini & Deirdre DeJean & Michel Grignon, 2017. "Non-market resource allocation and the public’s interpretation of need: an empirical investigation in the context of health care," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 49(1), pages 117-143, June.
    4. Samuel L. Perry, 2014. "Conservative Christians and Support for Transracial Adoption as an Alternative to Abortion," Social Science Quarterly, Southwestern Social Science Association, vol. 95(2), pages 380-392, June.
    5. Tachizawa, Elcio M. & Gimenez, Cristina, 2010. "Supply flexibility strategies in Spanish firms: Results from a survey," International Journal of Production Economics, Elsevier, vol. 124(1), pages 214-224, March.
    6. Paul Allin & David J. Hand, 2017. "New statistics for old?—measuring the wellbeing of the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 3-43, January.
    7. Yingli Pan & Wen Cai & Zhan Liu, 2022. "Inference for non-probability samples under high-dimensional covariate-adjusted superpopulation model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 955-979, October.
    8. Stefania Capecchi & Romina Gambacorta & Rosaria Simone & Domenico Piccolo, 2024. "Modelling cognitive response patterns to survey questions using the class of CUB models," Questioni di Economia e Finanza (Occasional Papers) 885, Bank of Italy, Economic Research and International Relations Area.
    9. J. N. K. Rao, 2021. "On Making Valid Inferences by Integrating Data from Surveys and Other Sources," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 242-272, May.
    10. Magdalena Smyk & Joanna Tyrowicz & Lucas van der Velde, 2021. "A Cautionary Note on the Reliability of the Online Survey Data: The Case of Wage Indicator," Sociological Methods & Research, , vol. 50(1), pages 429-464, February.
    11. Xiaojun Mao & Zhonglei Wang & Shu Yang, 2023. "Matrix completion under complex survey sampling," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(3), pages 463-492, June.
    12. Schoefer, Klaus & Wäppling, Anders & Heirati, Nima & Blut, Markus, 2019. "The moderating effect of cultural value orientations on behavioral responses to dissatisfactory service experiences," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 247-256.
    13. Raphaëlle Butori & Béatrice Parguel, 2010. "When students give biased responses to researchers: An exploration of traditional paper vs. computerized self-administration," Post-Print halshs-00636231, HAL.
    14. Hung, Kam & Law, Rob, 2011. "An overview of Internet-based surveys in hospitality and tourism journals," Tourism Management, Elsevier, vol. 32(4), pages 717-724.
    15. Rendtel, Ulrich & Alho, Juha M., 2022. "On the fade-away of an initial bias in longitudinal surveys," Discussion Papers 2022/4, Free University Berlin, School of Business & Economics.
    16. Ashley L. Buchanan & Michael G. Hudgens & Stephen R. Cole & Katie R. Mollan & Paul E. Sax & Eric S. Daar & Adaora A. Adimora & Joseph J. Eron & Michael J. Mugavero, 2018. "Generalizing evidence from randomized trials using inverse probability of sampling weights," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1193-1209, October.
    17. Bo-Hyun Seong & Chang-Yu Hong, 2022. "When It Comes to Screen Golf and Baseball, What Do Participants Think?," IJERPH, MDPI, vol. 19(20), pages 1-15, October.
    18. Lingxiao Wang & Barry I. Graubard & Hormuzd A. Katki & and Yan Li, 2020. "Improving external validity of epidemiologic cohort analyses: a kernel weighting approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1293-1311, June.
    19. Uttam Khanal & Clevo Wilson & Shunsuke Managi & Boon Lee & Viet-Ngu Hoang & Robert Gifford, 2018. "Psychological influence on survey incentives: valuing climate change adaptation benefits in agriculture," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 20(2), pages 305-324, April.
    20. Jiayin Zheng & Yingye Zheng & Li Hsu, 2022. "Re‐calibrating pure risk integrating individual data from two‐phase studies with external summary statistics," Biometrics, The International Biometric Society, vol. 78(4), pages 1515-1529, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijphth:v:63:y:2018:i:6:d:10.1007_s00038-018-1108-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.