Believing Is Seeing: The Influence of a Diagnostic Hypothesis on the Interpretation of Clinical Features

Many clinical decisions are made on the basis of information gathered from patients, whether in the form of chief complaints, patient appearance, or physical findings. Errors made in gathering and interpreting such clinical information could result in serious consequences in patient care, such as delays or errors in treatment. Little research has been devoted to understanding the mechanisms underlying such errors. In psychology, it has long been known that context influences perception. Phenomena such as visual illusions and the word superiority effect, in which letters are more easily recognized when presented in words rather than in unrelated letter strings, are pertinent examples of how the context influences feature interpretation. Similarly, research in radiology demonstrates that information such as the location of tenderness and swelling and tentative diagnoses increases the likelihood that physicians will detect fractures and lesions. Even with less ambiguous visual stimuli, such as patient appearance or electrocardiograms, the consideration of the correct diagnosis leads to an increase in detecting clinical signs compared with having no diagnosis in mind. These studies demonstrate that the identification of clinical signs is influenced by the diagnostic hypotheses held by diagnosticians. However, by measuring only performance in reporting the depicted correct features from the clinical stimuli, these researchers do not allow for conclusions to be drawn regarding the specific influence of a diagnostic hypothesis on feature identification. Once a diagnosis is considered, it can activate a representation of the disease presentation, bringing to mind the possible features that can be visible on a patient suffering from the given condition. The diagnosticians can then run through this list of features, checking for the presence or absence of each. This diagnosis would thus serve as a focus of attention, determining which features to look for and where to look for them. Additionally, the diagnostic hypothesis might have a stronger impact of inducing a bias in the identification of the observed physical characteristics, e.g., knowing that a moon-shaped face is a feature of Cushing’s disease and believing the diagnosis to be Cushing’s might lead diagnosticians to interpret a slightly obese face as moon-shaped. This interaction between the diagnosis and feature identification, if present, might be sufficient to lead clinicians to report features that are not present in patients. Given that there are a number of clinical situations where potentially biasing effects on diagnostic suggestions can occur, such as in referral letters or patient charts, it is important to understand the impact of such suggestions on the interpretation of clinical information. In the present study, we investigated whether the influence of the diagnosis (and accompanying brief case history) is strong enough to bias the interpretation of clinical information. Medical students and residents are suggested either the correct diagnosis or an alternate but plausible diagnosis prior to reporting all clinically important features from photographs of patients. If a diagnosis simply focuses attention on the relevant features, participants who are biased toward an alternate diagnosis should report fewer of the correct features than participants biased toward a correct diagnosis. However, the two groups should not differ in terms of reporting features that are consistent with the alternate diagnosis but not present in the photograph. Alternatively, if a diagnostic hypothesis does change the interpretation provided to the clinical data, participants biased toward an alternate diagnosis should be more likely to misinterpret correct features or normal variations in appearance as features supporting the alternate diagnosis. Therefore, they should report more alternate features than participants biased toward the correct diagnosis.