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Making an accurate assessment
Published in Helen Taylor, Ian Stuart-Hamilton, Assessing the Nursing and Care Needs of Older Adults, 2021
The effects of the nurse’s past experiences have been found to make a significant contribution to the decision-makingprocess.31 Earlier research by Cioffi32 indicates that when making decisions about simulated patients with whom they have not had (nor will have) any actual contact, there was a higher probability of more experienced than inexperienced nurses relying on their memory of previous cases encountered. Cioffi32 terms this the ‘representativeness heuristic’ (p. 189), more often operationalised with experienced nurses, who also collected fewer data than their less experienced colleagues. This is further evidence of the experienced nurses’ reliance on their memories. Cioffi described these as heuristics, or ‘rules of thumb’ or ‘subjective probability judgements’32 (p. 185), based on work by Tversky and Kahneman.33,34 These may also include the ‘availability’ heuristic, which depends on the nurse recalling a previous similar incident or case, and the ‘anchoring and adjustment heuristic’, where the assessment decision is made within the context of what the nurse would expect for someone who fulfilled certain criteria (e.g. ‘This person is diabetic, I would expect their blood sugar level to be within such a range, but it is…’).
Restricted rule-outs
Published in Caroline J Rodgers, Richard Harrington, Helping Hands: An Introduction to Diagnostic Strategy and Clinical Reasoning, 2019
Caroline J Rodgers, Richard Harrington
The restricted rule-out strategy uses the ‘availability heuristic’ – a rule of thumb that clinicians develop which involves knowing the most significant ‘must rule out’ diagnoses for a given presentation.2 For example, subarachnoid haemorrhage would be included in the list of significant rule-outs for a patient with a severe headache.
Psychology and Human Development EMIs
Published in Michael Reilly, Bangaru Raju, Extended Matching Items for the MRCPsych Part 1, 2018
Availability heuristic.Convergent thinking.Divergent thinking.Lateral thinking.Negative transfer effect.Positive transfer effect.Representativeness bias.Trial-and-error learning.
Extending the purview of risk perception attitude (RPA) framework to understand health insurance-related information seeking as a long-term self-protective behavior
Published in Journal of American College Health, 2023
Intriguingly, these speculations above are aligned with the findings in RQ1. Across the attitudinal groups, the avoidance group reported most frequent experience of worry, which is consistent with the findings from prior literature.24 However, the responsive group did not statistically differ from the avoidance group in their experience of worry. That is, people with high risk perception tend to experience worry more frequently relative to those with low risk perception (e.g. availability heuristic).59 To make informed health decisions, these groups may need additional information to cope with perceived high risk; the avoidance group needs efficacy information to deal with their worry and high perceived risk. And, the responsive group needs further information to meet their need for information sufficiency, which possibly helps cope with their worry and high perceived risk.27
The Enigma of Reason
Published in Psychiatry, 2019
The authors cite several specific ways in which our reasoning process can fool us. One is the “availability heuristic.” This trickery, studied by Tversky and Kahneman, involves our tendency to give greater relative weight to whatever comes easiest into our minds. They cite how this may also work in bumble bees just as it does in humans! The experiment they cite, showing this in bumblebees, illustrates “ … the exquisite ways in which even relatively simple cognitive systems adjust the time and energy they spend on a cognitive task … ” (p. 209). This example is used to point out in more detail how our minds and the bees “automatically calculate” the relative costs of a false negative versus a false positive. This difference results in humans and bumblebees making more false positive mistakes, because this bias, although an error, “is beneficial” (p. 209).
Twelve tips for thriving in the face of clinical uncertainty
Published in Medical Teacher, 2020
Galina Gheihman, Mark Johnson, Arabella L. Simpkin
Our desire for certainty leaves us open to the influence of cognitive biases. To prosper in the face of increasing knowledge and a busy workplace, well-versed experts learn to recognize patterns that allow them to think and act quickly. Such quick-thinking heuristics, first identified by Tversky and Kahneman (1974), serve a useful purpose – for example, recognizing the cardinal signs of an acute stroke or myocardial infarction and initiating appropriate therapy and organizing the appropriate personnel – yet they leave clinicians vulnerable to cognitive bias, and in turn, false assumptions, misdiagnosis, and errors (Trowbridge 2008). Becoming aware of the common cognitive pitfalls and biases is important:Availability heuristic: when physicians make a diagnosis based on what is easily accessible in their minds, rather than what is actually most probable.Anchoring heuristic: when physicians settle on a diagnosis early in the diagnostic process and subsequently become “anchored” to that diagnosis, despite evidence to the contrary.Confirmation bias: as a result of anchoring, physicians may discount clinical information discordant with the original provisional diagnosis and accept only that which supports their original diagnosis.Representativeness heuristic: physicians depend greatly on this cognitive short-cut in which a patient’s presentation is compared to a “typical” case of specific diagnoses but leaves off the “atypical” presentations.