Literature DB >> 17998079

Mixed-mode administration reduced bias and enhanced poststratification adjustments in a health behavior survey.

Alisha D Baines1, Melissa R Partin, Michael Davern, Todd H Rockwood.   

Abstract

OBJECTIVE: To assess whether a mixed-mode survey design reduced bias and enhanced methods commonly used to correct for bias (poststratification weighting). STUDY DESIGN AND
SETTING: The data for this paper are from a study of 1,900 adult patients enrolled in a randomized controlled trial to promote repeat treatment for relapsed smokers at five Veteran's Affairs Medical Centers. A sequential mixed-mode design was used for data collection whereby the initial attempt was conducted using phone administration, with mail follow-up for nonresponders. Analyses examined demographic, health, and smoking cessation treatment seeking differences between telephone responders, mail responders, and nonresponders and compared the relative effectiveness of global vs. targeted poststratification weighting adjustments for correcting for response bias.
RESULTS: The findings suggest (1) that responders to the additional survey mode (mail) did not significantly differ from responders to the first mode (phone) or nonresponders and (2) that poststratification weighting adjustments that take this additional information into account perform better than the standard global adjustments.
CONCLUSIONS: A mixed-mode design can improve survey representativeness and enhance the performance of poststratification weighting adjustments.

Entities:  

Mesh:

Year:  2007        PMID: 17998079     DOI: 10.1016/j.jclinepi.2007.02.011

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  7 in total

1.  Are lower response rates hazardous to your health survey? An analysis of three state telephone health surveys.

Authors:  Michael Davern; Donna McAlpine; Timothy J Beebe; Jeanette Ziegenfuss; Todd Rockwood; Kathleen Thiede Call
Journal:  Health Serv Res       Date:  2010-10       Impact factor: 3.402

2.  Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias.

Authors:  Jonathon R B Halbesleben; Marilyn V Whitman
Journal:  Health Serv Res       Date:  2012-10-10       Impact factor: 3.402

3.  Nonresponse bias in survey research: lessons from a prospective study of breast reconstruction.

Authors:  Nicholas L Berlin; Jennifer B Hamill; Ji Qi; Hyungjin M Kim; Andrea L Pusic; Edwin G Wilkins
Journal:  J Surg Res       Date:  2017-12-22       Impact factor: 2.192

4.  Deployment of a mixed-mode data collection strategy does not reduce nonresponse bias in a general population health survey.

Authors:  Timothy J Beebe; Donna D McAlpine; Jeanette Y Ziegenfuss; Sarah Jenkins; Lindsey Haas; Michael E Davern
Journal:  Health Serv Res       Date:  2012-01-17       Impact factor: 3.402

5.  Benefits of extensive recruitment effort persist during follow-ups and are consistent across age group and survey method. The TRAILS study.

Authors:  Esther Nederhof; Frederike Jörg; Dennis Raven; René Veenstra; Frank C Verhulst; Johan Ormel; Albertine J Oldehinkel
Journal:  BMC Med Res Methodol       Date:  2012-07-02       Impact factor: 4.615

6.  Mixing modes in a population-based interview survey: comparison of a sequential and a concurrent mixed-mode design for public health research.

Authors:  Elvira Mauz; Elena von der Lippe; Jennifer Allen; Ralph Schilling; Stephan Müters; Jens Hoebel; Patrick Schmich; Matthias Wetzstein; Panagiotis Kamtsiuris; Cornelia Lange
Journal:  Arch Public Health       Date:  2018-01-04

7.  Web-Based Data Collection for Older Adults Living With HIV in a Clinical Research Setting: Pilot Observational Study.

Authors:  Katherine Tassiopoulos; Carla Roberts-Toler; Carl J Fichtenbaum; Susan L Koletar
Journal:  J Med Internet Res       Date:  2020-11-11       Impact factor: 7.076

  7 in total

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