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Tailored Cigarette Warning Messages: How Individualized Loss Aversion and Delay Discounting Rates Can Influence Perceived Message Effectiveness

Author

Listed:
  • Hollie L. Tripp

    (Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA)

  • Justin C. Strickland

    (Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, MD 21224, USA)

  • Melissa Mercincavage

    (Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA)

  • Janet Audrain-McGovern

    (Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA)

  • Eric C. Donny

    (Department of Physiology and Pharmacology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA)

  • Andrew A. Strasser

    (Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA)

Abstract

Current text-only cigarette warning labels (long-term, loss-framed messages) may not motivate positive changes in smoking behavior. The current project was a cross-sectional study examining the effects of tailored cigarette warnings on perceived message effectiveness (PME) in adult smokers ( n = 512) conducted using Amazon Mechanical Turk (M-Turk) in January–February 2020. Participants were an average age of 40.7 (SD = 11.6), with the majority of the sample being female (62.2%) and White (88.9%). Participants reported smoking an average of 14.6 cigarettes/day (SD = 9.2) with an average FTND score of 4.6 (SD = 2.2). Participants were asked to complete a tobacco use history questionnaire, and mixed gambles and delay discounting tasks before random assignment to one of five message groups. The groups were based on a 2 (gain versus loss framing) ×2 (short-term versus long-term framing) between-subject design; a fifth group served as the control group. All experimental messages reported higher PME scores than the control ( p values < 0.001, Cohen’s d = 1.88–2.48). Participants with shallower delayed reward discounting and lower loss aversion rates reported higher total PME scores, p values < 0.05. Our findings also suggest that loss aversion rates vary widely among smokers and that individuals are more responsive to messages congruent with their behavioral economic profile. Specifically, smokers who viewed messages congruent with their loss aversion and delay discounting rates reported higher PME scores than those who viewed incongruent messages ( p = 0.04, Cohen’s d = 0.24). These preliminary findings suggest that anti-smoking campaigns may best impact smokers by tailoring messages based on individual loss aversion and delay discounting rates versus a one-size-fits-all approach.

Suggested Citation

  • Hollie L. Tripp & Justin C. Strickland & Melissa Mercincavage & Janet Audrain-McGovern & Eric C. Donny & Andrew A. Strasser, 2021. "Tailored Cigarette Warning Messages: How Individualized Loss Aversion and Delay Discounting Rates Can Influence Perceived Message Effectiveness," IJERPH, MDPI, vol. 18(19), pages 1-11, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:19:p:10492-:d:650695
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    References listed on IDEAS

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    1. Manel Baucells & Silvia Bellezza, 2017. "Temporal Profiles of Instant Utility During Anticipation, Event, and Recall," Management Science, INFORMS, vol. 63(3), pages 729-748, March.
    2. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    3. Thaler, Richard, 1981. "Some empirical evidence on dynamic inconsistency," Economics Letters, Elsevier, vol. 8(3), pages 201-207.
    4. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    5. Nicholas C. Barberis, 2013. "Thirty Years of Prospect Theory in Economics: A Review and Assessment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 173-196, Winter.
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    Cited by:

    1. Gideon P. Naudé & Sean B. Dolan & Justin C. Strickland & Meredith S. Berry & David J. Cox & Matthew W. Johnson, 2021. "The Influence of Episodic Future Thinking and Graphic Warning Labels on Delay Discounting and Cigarette Demand," IJERPH, MDPI, vol. 18(23), pages 1-15, November.
    2. Mario Cesare Nurchis & Marcello Di Pumpo & Alessio Perilli & Giuseppe Greco & Gianfranco Damiani, 2023. "Nudging Interventions on Alcohol and Tobacco Consumption in Adults: A Scoping Review of the Literature," IJERPH, MDPI, vol. 20(3), pages 1-10, January.

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