Literature DB >> 26322137

Evaluating a Modular Design Approach to Collecting Survey Data Using Text Messages.

Brady T West1, Dirgha Ghimire2, William G Axinn1.   

Abstract

This article presents analyses of data from a pilot study in Nepal that was designed to provide an initial examination of the errors and costs associated with an innovative methodology for survey data collection. We embedded a randomized experiment within a long-standing panel survey, collecting data on a small number of items with varying sensitivity from a probability sample of 450 young Nepalese adults. Survey items ranged from simple demographics to indicators of substance abuse and mental health problems. Sampled adults were randomly assigned to one of three different modes of data collection: 1) a standard one-time telephone interview, 2) a "single sitting" back-and-forth interview with an interviewer using text messaging, and 3) an interview using text messages within a modular design framework (which generally involves breaking the survey response task into distinct parts over a short period of time). Respondents in the modular group were asked to respond (via text message exchanges with an interviewer) to only one question on a given day, rather than complete the entire survey. Both bivariate and multivariate analyses demonstrate that the two text messaging modes increased the probability of disclosing sensitive information relative to the telephone mode, and that respondents in the modular design group, while responding less frequently, found the survey to be significantly easier. Further, those who responded in the modular group were not unique in terms of available covariates, suggesting that the reduced item response rates only introduced limited nonresponse bias. Future research should consider enhancing this methodology, applying it with other modes of data collection (e. g., web surveys), and continuously evaluating its effectiveness from a total survey error perspective.

Entities:  

Keywords:  modular survey design; survey costs; survey methodology; survey nonresponse; text message surveys; total survey error

Year:  2015        PMID: 26322137      PMCID: PMC4551499     

Source DB:  PubMed          Journal:  Surv Res Methods        ISSN: 1864-3361


  12 in total

Review 1.  Methodologies for improving response rates in surveys of physicians: a systematic review.

Authors:  Jonathan B VanGeest; Timothy P Johnson; Verna L Welch
Journal:  Eval Health Prof       Date:  2007-12       Impact factor: 2.651

Review 2.  Ecological momentary assessment.

Authors:  Saul Shiffman; Arthur A Stone; Michael R Hufford
Journal:  Annu Rev Clin Psychol       Date:  2008       Impact factor: 18.561

3.  Wireless substitution: state-level estimates from the National Health Interview Survey, 2010-2011.

Authors:  Stephen J Blumberg; Julian V Luke; Nadarajasundaram Ganesh; Michael E Davern; Michel H Boudreaux
Journal:  Natl Health Stat Report       Date:  2012-10-12

4.  Response of sensitive behaviors to frequent measurement.

Authors:  William G Axinn; Elyse A Jennings; Mick P Couper
Journal:  Soc Sci Res       Date:  2014-07-22

5.  Project TwEATs. A feasibility study testing the use of automated text messaging to monitor appetite ratings in a free-living population.

Authors:  Susan M Schembre; Jessica Yuen
Journal:  Appetite       Date:  2011-01-18       Impact factor: 3.868

6.  A survey method for characterizing daily life experience: the day reconstruction method.

Authors:  Daniel Kahneman; Alan B Krueger; David A Schkade; Norbert Schwarz; Arthur A Stone
Journal:  Science       Date:  2004-12-03       Impact factor: 47.728

7.  Collecting Survey Data during Armed Conflict.

Authors:  William G Axinn; Dirgha Ghimire; Nathalie E Williams
Journal:  J Off Stat       Date:  2012-06       Impact factor: 0.920

8.  Short message service (SMS) technology in alcohol research--a feasibility study.

Authors:  Emmanuel Kuntsche; Benjamin Robert
Journal:  Alcohol Alcohol       Date:  2009-05-29       Impact factor: 2.826

Review 9.  Follow-up by mail in clinical trials: does questionnaire length matter?

Authors:  Phil Edwards; Ian Roberts; Peter Sandercock; Chris Frost
Journal:  Control Clin Trials       Date:  2004-02

10.  Precision and Disclosure in Text and Voice Interviews on Smartphones.

Authors:  Michael F Schober; Frederick G Conrad; Christopher Antoun; Patrick Ehlen; Stefanie Fail; Andrew L Hupp; Michael Johnston; Lucas Vickers; H Yanna Yan; Chan Zhang
Journal:  PLoS One       Date:  2015-06-10       Impact factor: 3.240

View more
  4 in total

1.  A Web-Based Event History Calendar Approach for Measuring Contraceptive Use Behavior.

Authors:  Brady T West; William G Axinn; Mick P Couper; Heather Gatny; Heather Schroeder
Journal:  Field methods       Date:  2022-01-02

2.  Building the Evidence Base for Remote Data Collection in Low- and Middle-Income Countries: Comparing Reliability and Accuracy Across Survey Modalities.

Authors:  Abigail R Greenleaf; Dustin G Gibson; Christelle Khattar; Alain B Labrique; George W Pariyo
Journal:  J Med Internet Res       Date:  2017-05-05       Impact factor: 5.428

3.  Does mobile phone survey method matter? Reliability of computer-assisted telephone interviews and interactive voice response non-communicable diseases risk factor surveys in low and middle income countries.

Authors:  George W Pariyo; Abigail R Greenleaf; Dustin G Gibson; Joseph Ali; Hannah Selig; Alain B Labrique; Gulam Muhammed Al Kibria; Iqbal Ansary Khan; Honorati Masanja; Meerjady Sabrina Flora; Saifuddin Ahmed; Adnan A Hyder
Journal:  PLoS One       Date:  2019-04-10       Impact factor: 3.240

4.  Best practices for collecting repeated measures data using text messages.

Authors:  Noa'a Shimoni; Siripanth Nippita; Paula M Castaño
Journal:  BMC Med Res Methodol       Date:  2020-01-03       Impact factor: 4.615

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.