Department of Psychology, The University of Warwick, Coventry, CV4 7AL, UK.
Cogn Res Princ Implic. 2023 May 24;8(1):30. doi: 10.1186/s41235-023-00485-y.
Computer-Aided Detection (CAD) has been proposed to help operators search for cancers in mammograms. Previous studies have found that although accurate CAD leads to an improvement in cancer detection, inaccurate CAD leads to an increase in both missed cancers and false alarms. This is known as the over-reliance effect. We investigated whether providing framing statements of CAD fallibility could keep the benefits of CAD while reducing over-reliance. In Experiment 1, participants were told about the benefits or costs of CAD, prior to the experiment. Experiment 2 was similar, except that participants were given a stronger warning and instruction set in relation to the costs of CAD. The results showed that although there was no effect of framing in Experiment 1, a stronger message in Experiment 2 led to a reduction in the over-reliance effect. A similar result was found in Experiment 3 where the target had a lower prevalence. The results show that although the presence of CAD can result in over-reliance on the technology, these effects can be mitigated by framing and instruction sets in relation to CAD fallibility.
计算机辅助检测(CAD)被提议用于帮助操作人员在乳房 X 光片中寻找癌症。以前的研究发现,尽管准确的 CAD 导致癌症检测的改善,但不准确的 CAD 会导致漏诊癌症和误报的增加。这被称为过度依赖效应。我们研究了提供 CAD 易出错性的框架陈述是否可以在减少过度依赖的同时保持 CAD 的益处。在实验 1 中,参与者在实验前被告知 CAD 的益处或成本。实验 2 类似,只是参与者在 CAD 成本方面得到了更强的警告和指令集。结果表明,尽管实验 1 中没有框架效应,但实验 2 中更强的信息导致过度依赖效应的减少。在目标患病率较低的实验 3 中也发现了类似的结果。结果表明,尽管 CAD 的存在可能导致对技术的过度依赖,但可以通过与 CAD 易出错性相关的框架和指令集来减轻这些影响。