Context Matters: Emotional Sensitivity to Probabilities and the Bias for Action in Cancer Treatment Decisions.

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Medical Decision Making Pub Date : 2023-05-01 Epub Date: 2023-03-23 DOI:10.1177/0272989X231161341
Heather P Lacey, Steven C Lacey, Prerna Dayal, Caroline Forest, Dana Blasi
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引用次数: 0

Abstract

Background: Past studies have shown a commission bias for cancer treatment, a tendency to choose active treatment even when watchful waiting is less risky. This bias suggests motivations for action beyond mortality statistics, but recent evidence suggests that individuals differ in their emotional sensitivity to probabilities (ESP), the tendency to calibrate emotional reactions to probability. The current study aims to examine the role of ESP in the commission bias, specifically whether those higher in ESP are more likely to choose watchful waiting when risk probabilities align with that choice.

Methods: Participants (N = 1,055) read a scenario describing a hypothetical cancer diagnosis and chose between surgery and watchful waiting, with random assignment between versions where the mortality rate was either lower for surgery or for watchful waiting. We modeled choice using the Possibility Probability Questionnaire (PPQ), a measure of ESP, and several other individual differences in a logistic regression.

Results: We observed a commission bias as in past studies with most participants choosing surgery both when surgery was optimal (71%) and when watchful waiting was optimal (58%). An ESP × Condition interaction indicated that the predictive role of ESP depended on condition. Those higher in ESP were more likely to choose surgery when probabilities favored surgery, β = 0.57, P < 0.001, but when probabilities favored watchful waiting, ESP had a near-zero relationship with choice, β = 0.05, P < 0.99.

Conclusions: The role of ESP in decision making is context specific. Higher levels of ESP predict choosing action when that action is warranted but do not predict a shift away from surgery when watchful waiting offers better chances of survival. ESP does not overcome the commission bias.

Highlights: Past studies have identified a "commission bias," a tendency to choose active treatment over watchful waiting, even when mortality rate is lower for waiting.Evaluation of risk probabilities is related to individual differences in emotional sensitivity to probabilities (ESP) and has been shown to predict reactions to and decisions about health risk situations.ESP appears to be selectively factored into decision making. ESP was a robust predictor of choosing surgery when probability information supported surgery but did not predict decisions when probability information supported watchful waiting.Those who are most emotionally attuned to probabilities are just as susceptible to the commission bias as those who are less attuned.

情境影响:癌症治疗决策中对概率的情绪敏感性和行动偏差。
背景:过去的研究表明,癌症治疗存在委员会偏见,即即使在谨慎等待风险较低的情况下,也倾向于选择积极治疗。这种偏见表明,行动的动机超出了死亡率统计数据,但最近的证据表明,个体对概率的情绪敏感性(ESP)不同,即根据概率校准情绪反应的倾向。目前的研究旨在检验ESP在佣金偏见中的作用,特别是当风险概率与该选择一致时,ESP较高的人是否更有可能选择警惕等待。方法:参与者(N=1055)阅读描述假设癌症诊断的场景,在手术和密切等待之间进行选择,在手术或密切等待死亡率较低的版本之间随机分配。我们使用可能性概率问卷(PPQ)对选择进行建模,PPQ是ESP的一种测量方法,以及逻辑回归中的其他几个个体差异。结果:在过去的研究中,我们观察到了委托偏差,大多数参与者在手术最佳(71%)和观察等待最佳(58%)时都选择了手术。ESP×条件交互作用表明ESP的预测作用取决于条件。当概率支持手术时,ESP较高的人更有可能选择手术,β=0.57,P<0.001,但当概率支持警惕等待时,ESP与选择的关系几乎为零,β=0.05,P<0.009。结论:ESP在决策中的作用是特定的。更高水平的ESP可以预测在有必要的情况下选择手术,但不能预测在警惕等待提供更好的生存机会时会放弃手术。ESP无法克服佣金偏见。亮点:过去的研究发现了一种“委托偏差”,即即使等待的死亡率较低,也倾向于选择积极治疗而非密切等待。风险概率的评估与个体对概率的情感敏感性(ESP)的差异有关,并已被证明可以预测对健康风险情况的反应和决策。ESP似乎被选择性地纳入决策中。当概率信息支持手术时,ESP是选择手术的有力预测因子,但当概率信息支撑警惕等待时,ESP不能预测决策。那些在情感上对概率最敏感的人和那些不太敏感的人一样容易受到委员会偏见的影响。
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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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