IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v43y2023i7-8p789-802.html
   My bibliography  Save this article

Assessing and Understanding Reactance, Self-Exemption, Disbelief, Source Derogation and Information Conflict in Reaction to Overdiagnosis in Mammography Screening: Scale Development and Preliminary Validation

Author

Listed:
  • Laura D. Scherer

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Adult and Child Center for Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO, USA
    CO Center of Innovation (COIN), VA Eastern Colorado, Aurora, CO, USA)

  • Krithika Suresh

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado School of Medicine, Aurora, CO, USA)

  • Carmen L. Lewis

    (Adult and Child Center for Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO, USA
    Division of General Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA)

  • Kirsten J. McCaffery

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    School of Public Health, The University of Sydney, Sydney, Australia)

  • Jolyn Hersch

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    School of Public Health, The University of Sydney, Sydney, Australia)

  • Joseph N. Cappella

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Annenburg School for Communication, University of Pennsylvania, Philadelphia, PA, USA)

  • Brad Morse

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Division of General Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA)

  • Channing E. Tate

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Adult and Child Center for Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO, USA
    Division of General Internal Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA)

  • Bridget S. Mosley

    (Adult and Child Center for Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora, CO, USA)

  • Sarah Schmiege

    (Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA)

  • Marilyn M. Schapira

    (Department of Medicine, University of Pennsylvania School of Medicine, Center for Health Equity Research & Promotion (CHERP), Philadelphia VA Medical Center, Philadelphia, PA, USA)

Abstract

Purpose Overdiagnosis is a concept central to making informed breast cancer screening decisions, and yet some people may react to overdiagnosis with doubt and skepticism. The present research assessed 4 related reactions to overdiagnosis: reactance, self-exemption, disbelief, and source derogation (REDS). The degree to which the concept of overdiagnosis conflicts with participants’ prior beliefs and health messages (information conflict) was also assessed as a potential antecedent of REDS. We developed a scale to assess these reactions, evaluated how those reactions are related, and identified their potential implications for screening decision making. Methods Female participants aged 39 to 49 years read information about overdiagnosis in mammography screening and completed survey questions assessing their reactions to that information. We used a multidimensional theoretical framework to assess dimensionality and overall domain-specific internal consistency of the REDS and Information Conflict questions. Exploratory and confirmatory factor analyses were performed using data randomly split into a training set and test set. Correlations between REDS, screening intentions, and other outcomes were evaluated. Results Five-hundred twenty-five participants completed an online survey. Exploratory and confirmatory factor analyses identified that Reactance, Self Exemption, Disbelief, Source Derogation, and Information Conflict represent unique constructs. A reduced 20-item scale was created by selecting 4 items per construct, which showed good model fit. Reactance, Disbelief, and Source Derogation were associated with lower intent to use information about overdiagnosis in decision making and the belief that informing people about overdiagnosis is unimportant. Conclusions REDS and Information Conflict are distinct but correlated constructs that are common reactions to overdiagnosis. Some of these reactions may have negative implications for making informed screening decisions. Highlights Overdiagnosis is a concept central to making informed breast cancer screening decisions, and yet when provided information about overdiagnosis, some people are skeptical. This research developed a measure that assessed different ways in which people might express skepticism about overdiagnosis (reactance, self-exemption, disbelief, source derogation) and also the perception that overdiagnosis conflicts with prior knowledge and health messages (information conflict). These different reactions are distinct but correlated and are common reactions when people learn about overdiagnosis. Reactance, disbelief, and source derogation are associated with lower intent to use information about overdiagnosis in decision making as well as the belief that informing people about overdiagnosis is unimportant.

Suggested Citation

  • Laura D. Scherer & Krithika Suresh & Carmen L. Lewis & Kirsten J. McCaffery & Jolyn Hersch & Joseph N. Cappella & Brad Morse & Channing E. Tate & Bridget S. Mosley & Sarah Schmiege & Marilyn M. Schapi, 2023. "Assessing and Understanding Reactance, Self-Exemption, Disbelief, Source Derogation and Information Conflict in Reaction to Overdiagnosis in Mammography Screening: Scale Development and Preliminary Va," Medical Decision Making, , vol. 43(7-8), pages 789-802, October.
    • Handle: RePEc:sae:medema:v:43:y:2023:i:7-8:p:789-802
    DOI: 10.1177/0272989X231195603
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X231195603
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X231195603?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Angela Fagerlin & Brian J. Zikmund-Fisher & Peter A. Ubel & Aleksandra Jankovic & Holly A. Derry & Dylan M. Smith, 2007. "Measuring Numeracy without a Math Test: Development of the Subjective Numeracy Scale," Medical Decision Making, , vol. 27(5), pages 672-680, September.
    2. Rotem Botvinik-Nezer & Matt Jones & Tor D. Wager, 2023. "A belief systems analysis of fraud beliefs following the 2020 US election," Nature Human Behaviour, Nature, vol. 7(7), pages 1106-1119, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yaniv Hanoch & Talya Miron-Shatz & Mary Himmelstein, 2010. "Genetic testing and risk interpretation: How do women understand lifetime risk results?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(2), pages 116-123, April.
    2. repec:cup:judgdm:v:9:y:2014:i:2:p:152-158 is not listed on IDEAS
    3. Huls, Samare P.I. & de Bekker-Grob, Esther W., 2022. "Can healthcare choice be predicted using stated preference data? The role of model complexity in a discrete choice experiment about colorectal cancer screening," Social Science & Medicine, Elsevier, vol. 315(C).
    4. Chavez, Daniel E. & Palma, Marco A. & Nayga Jr., Rodolfo M., 2017. "When does real become consequential in non-hypothetical choice experiments?," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266327, Southern Agricultural Economics Association.
    5. Stortz, Laura & Lee, Yu Na & Von Massow, Michael, 2020. "Do Front-of-Package Warning Labels Reduce Demand for Foods ‘High In’ Saturated Fat, Sugar, or Sodium?," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304581, Agricultural and Applied Economics Association.
    6. Aseervatham, Vijay & Jaspersen, Johannes G. & Richter, Andreas, 2015. "The affection effect in an incentive compatible insurance demand experiment," Economics Letters, Elsevier, vol. 131(C), pages 34-37.
    7. Swait, J. & de Bekker-Grob, E.W., 2022. "A discrete choice model implementing gist-based categorization of alternatives, with applications to patient preferences for cancer screening and treatment," Journal of Health Economics, Elsevier, vol. 85(C).
    8. Wändi Bruine de Bruin & Paul Slovic, 2021. "Low numeracy is associated with poor financial well-being around the world," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-15, November.
    9. Talya Miron-Shatz & Yaniv Hanoch & Benjamin A. Katz & Glen M. Doniger & Elissa M. Ozanne, 2015. "Willingness to test for BRCA1/2 in high risk women: Influenced by risk perception and family experience, rather than by objective or subjective numeracy?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(4), pages 386-399, July.
    10. Andrea Kampmann & Burkhard Pedell, 2022. "Using Storytelling to Promote Organizational Resilience: An Experimental Study of Different Forms of Risk Communication," Schmalenbach Journal of Business Research, Springer, vol. 74(4), pages 695-725, December.
    11. Kevin E. Tiede & Wolfgang Gaissmaier, 2023. "How Do People Process Different Representations of Statistical Information? Insights into Cognitive Effort, Representational Inconsistencies, and Individual Differences," Medical Decision Making, , vol. 43(7-8), pages 803-820, October.
    12. Nicolas Eber & Patrick Roger & Tristan Roger, 2024. "Finance and intelligence: An overview of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 38(2), pages 503-554, April.
    13. repec:cup:judgdm:v:14:y:2019:i:4:p:412-422 is not listed on IDEAS
    14. Saima Ghazal & Edward T. Cokely & Rocio Garcia-Retamero, 2014. "Predicting biases in very highly educated samples: Numeracy and metacognition," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(1), pages 15-34, January.
    15. Tamara Stotz & Angela Bearth & Signe Maria Ghelfi & Michael Siegrist, 2020. "Evaluating the Perceived Efficacy of Randomized Security Measures at Airports," Risk Analysis, John Wiley & Sons, vol. 40(7), pages 1469-1480, July.
    16. repec:cup:judgdm:v:7:y:2012:i:1:p:25-47 is not listed on IDEAS
    17. Becky L. Choma & David Sumantry & Yaniv Hanoch, 2019. "Right-wing ideology and numeracy: A perception of greater ability, but poorer performance," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 14(4), pages 412-422, July.
    18. Signe Waechter & Bernadette Sütterlin & Michael Siegrist, 2017. "Decision-Making Strategies for the Choice of Energy-friendly Products," Journal of Consumer Policy, Springer, vol. 40(1), pages 81-103, March.
    19. repec:cup:judgdm:v:10:y:2015:i:4:p:386-399 is not listed on IDEAS
    20. Anna G. Devlin & Wedad Elmaghraby & Rebecca W. Hamilton, 2018. "Why do suppliers choose wholesale price contracts? End-of-season payments disincentivize retailer marketing effort," Journal of the Academy of Marketing Science, Springer, vol. 46(2), pages 212-233, March.
    21. Wändi Bruine de Bruin & Yasmina Okan & Tamar Krishnamurti & Mark D. Huffman, 2023. "The Role of Confidence and Knowledge in Intentions to (Not) Seek Care for Hypertension: Evidence From a National Survey," Medical Decision Making, , vol. 43(4), pages 461-477, May.
    22. Jakub Traczyk & Agata Sobkow & Kamil Fulawka & Jakub Kus & Dafina Petrova & Rocio Garcia-Retamero, 2018. "Numerate decision makers don't use more effortful strategies unless it pays: A process tracing investigation of skilled and adaptive strategy selection in risky decision making," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 13(4), pages 372-381, July.
    23. Cornelia Betsch & Niels Haase & Frank Renkewitz & Philipp Schmid, 2015. "The narrative bias revisited: What drives the biasing influence of narrative information on risk perceptions?," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(3), pages 241-264, May.
    24. repec:cup:judgdm:v:10:y:2015:i:3:p:241-264 is not listed on IDEAS
    25. Sobkow, Agata & Olszewska, Angelika & Traczyk, Jakub, 2020. "Multiple numeric competencies predict decision outcomes beyond fluid intelligence and cognitive reflection," Intelligence, Elsevier, vol. 80(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:43:y:2023:i:7-8:p:789-802. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.