Algorithm-based advice taking and clinical judgement: impact of advice distance and algorithm information.

Evidence-based algorithms can improve both lay and professional judgements and decisions, yet they remain underutilised. Research on advice taking established that humans tend to discount advice-especially when it contradicts their own judgement ("egocentric advice discounting")-but this can be mitigated by knowledge about the advisor's past performance. Advice discounting has typically been investigated using tasks with outcomes of low importance (e.

Using cancer risk algorithms to improve risk estimates and referral decisions.

Background: Cancer risk algorithms were introduced to clinical practice in the last decade, but they remain underused. We investigated whether General Practitioners (GPs) change their referral decisions in response to an unnamed algorithm, if decisions improve, and if changing decisions depends on having information about the algorithm and on whether GPs overestimated or underestimated risk.

Methods: 157 UK GPs were presented with 20 vignettes describing patients with possible colorectal cancer symptoms.