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The role of choice in health education intervention trials: a review and case study

Author

Listed:
  • Janevic, Mary R.
  • Janz, Nancy K.
  • Dodge, Julia A.
  • Lin, Xihong
  • Pan, Wenqin
  • Sinco, Brandy R.
  • Clark, Noreen M.

Abstract

Although the randomized, controlled trial (RCT) is considered the gold standard in research for determining the efficacy of health education interventions, such trials may be vulnerable to "preference effects"; that is, differential outcomes depending on whether an individual is randomized to his or her preferred treatment. In this study, we review theoretical and empirical literature regarding designs that account for such effects in medical research, and consider the appropriateness of these designs to health education research. To illustrate the application of a preference design to health education research, we present analyses using process data from a mixed RCT/preference trial comparing two formats (Group or Self-Directed) of the "Women take PRIDE" heart disease management program. Results indicate that being able to choose one's program format did not significantly affect the decision to participate in the study. However, women who chose the Group format were over 4 times as likely to attend at least one class and were twice as likely to attend a greater number of classes than those who were randomized to the Group format. Several predictors of format preference were also identified, with important implications for targeting disease-management education to this population.

Suggested Citation

  • Janevic, Mary R. & Janz, Nancy K. & Dodge, Julia A. & Lin, Xihong & Pan, Wenqin & Sinco, Brandy R. & Clark, Noreen M., 2003. "The role of choice in health education intervention trials: a review and case study," Social Science & Medicine, Elsevier, vol. 56(7), pages 1581-1594, April.
  • Handle: RePEc:eee:socmed:v:56:y:2003:i:7:p:1581-1594
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    Citations

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    Cited by:

    1. Wunsch, Conny & Strobl, Renate, 2018. "Identification of causal mechanisms based on between-subject double randomization designs," CEPR Discussion Papers 13028, C.E.P.R. Discussion Papers.
    2. Bower, Peter & King, Michael & Nazareth, Irwin & Lampe, Fiona & Sibbald, Bonnie, 2005. "Patient preferences in randomised controlled trials: Conceptual framework and implications for research," Social Science & Medicine, Elsevier, vol. 61(3), pages 685-695, August.
    3. Kirsten J. McCaffery & Robin Turner & Petra Macaskill & Stephen D. Walter & Siew Foong Chan & Les Irwig, 2011. "Determining the Impact of Informed Choice," Medical Decision Making, , vol. 31(2), pages 229-236, March.
    4. Long, Qi & Little, Roderick J. & Lin, Xihong, 2008. "Causal Inference in Hybrid Intervention Trials Involving Treatment Choice," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 474-484, June.
    5. Birthe Andrea Lehmann & Lara Lindert & Silke Ohlmeier & Lara Schlomann & Holger Pfaff & Kyung-Eun Choi, 2020. "“And Then He Got into the Wrong Group”: A Qualitative Study Exploring the Effects of Randomization in Recruitment to a Randomized Controlled Trial," IJERPH, MDPI, vol. 17(6), pages 1-16, March.
    6. Kirsten McCaffery & Les Irwig & Patrick Bossuyt, 2007. "Patient Decision Aids to Support Clinical Decision Making: Evaluating the Decision or the Outcomes of the Decision," Medical Decision Making, , vol. 27(5), pages 619-625, September.
    7. Roderick J. Little & Qi Long & Xihong Lin, 2009. "A Comparison of Methods for Estimating the Causal Effect of a Treatment in Randomized Clinical Trials Subject to Noncompliance," Biometrics, The International Biometric Society, vol. 65(2), pages 640-649, June.
    8. Qi Long & Roderick J. A. Little & Xihong Lin, 2010. "Estimating causal effects in trials involving multitreatment arms subject to non‐compliance: a Bayesian framework," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(3), pages 513-531, May.
    9. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2022. "Choosing Who Chooses: Selection-Driven Targeting in Energy Rebate Programs," NBER Working Papers 30469, National Bureau of Economic Research, Inc.
    10. Robin M. Turner & Stephen D. Walter & Petra Macaskill & Kirsten J. McCaffery & Les Irwig, 2014. "Sample Size and Power When Designing a Randomized Trial for the Estimation of Treatment, Selection, and Preference Effects," Medical Decision Making, , vol. 34(6), pages 711-719, August.
    11. Daido Kido, 2023. "Incorporating Preferences Into Treatment Assignment Problems," Papers 2311.08963, arXiv.org.
    12. Takanori Ida & Takunori Ishihara & Koichiro Ito & Daido Kido & Toru Kitagawa & Shosei Sakaguchi & Shusaku Sasaki, 2021. "Paternalism, Autonomy, or Both? Experimental Evidence from Energy Saving Programs," Papers 2112.09850, arXiv.org.

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