JOURNAL ARTICLE

When to Text? How the Timing of Text Message Contacts in Mixed-Mode Surveys Impacts Response.

  • Published In: Journal of Survey Statistics & Methodology, 2024, v. 12, n. 3. P. 674 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Christian, Leah Melani; Sun, Hanyu; Slowinski, Zoe; Hansen, Christopher; Mcroy, Martha 3 of 3

Abstract

This article examines the effectiveness of text messaging as a contact mode in mixed-mode survey designs, specifically within the 2022 National Survey of Fishing, Hunting, and Wildlife-Associated Recreation (FHWAR). A full factorial experiment tested variations in the sequencing of text messages (text invitation, early reminder, late reminder) and the time of day texts were sent (morning versus afternoon) among two respondent groups: Cooperative Respondents and Other Respondents. Results indicate that early text reminders were generally more effective than late reminders or text invitations in increasing completion rates and speeding response, without negatively impacting data quality or sample composition. The timing of text messages (morning vs. afternoon) showed minimal effect on response rates, though afternoon texts slightly accelerated completion among Other Respondents. The study suggests that integrating text reminders into mixed-mode contact strategies can enhance survey participation, especially when combined with traditional mail contacts, and calls for further research on texting strategies in diverse survey contexts.

Additional Information

  • Source:Journal of Survey Statistics & Methodology. 2024/06, Vol. 12, Issue 3, p674
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:2325-0984
  • DOI:10.1093/jssam/smae014
  • Accession Number:178321331
  • Copyright Statement:Copyright of Journal of Survey Statistics & Methodology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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