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

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  • 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
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    References listed on IDEAS

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    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.
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