Framing the Fallibility of Computer-Aided Detection Aids Cancer Detection

Autor/inn/en	Kunar, Melina A.; Watson, Derrick G.
Titel	Framing the Fallibility of Computer-Aided Detection Aids Cancer Detection
Quelle	In: Cognitive Research: Principles and Implications, 8 (2023), Artikel 30 (17 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Kunar, Melina A.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
DOI	10.1186/s41235-023-00485-y
Schlagwörter	Assistive Technology; Computer Use; Clinical Diagnosis; Screening Tests; Cancer; Reliability; Costs + Suchen Sie Ihr Suchwort? Screening-Verfahren; Carcinoma; Karzinom; Krebs (med); Krebserkrankung; Reliabilität; Cost; Kosten
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01