Clinical Judgement

Introduction

‘Clinical judgement’ refers generally to the result of a set of cognitive activities that aim to: (a) classify an observed behavioural pattern into a nosological system category (diagnostic judgement); (b) predict the development of an observed behavioural pattern under a given treatment, or under particular environmental conditions (predictive judgement, or prognosis); (c) estimate the degree of severity of a disorder (severity judgement); and (d) make an informed decision about the best treatment (treatment judgement).

Many published works describe how diagnostic and prognostic judgements are made. Some propose theoretical models to represent diagnostic and prognostic judgements, but little has been published about severity- and treatment-judgements.

A clinical judgement is the result of three main complex activities: data collection, data evaluation, and information integration. Because these activities are sequential, clinical-judgement making is often considered a process and, in this case, each activity might be considered a process stage. Usually, at the conclusion of the last stage, the judgement is communicated externally as a formal ‘clinical report’ or ‘diagnostic report’.

Many psychological models of judgement-making only focus on one or two stages of the internal cognitive process, not all three, and none includes the clinical report stage.

Psychological Study of Clinical Judgement

The empirical study of clinical judgement was stimulated by the so called clinical-statistical controversy (see entry Prediction: Clinical vs. Statistical). From the beginning these studies revealed that statistical predictions are more accurate than the intuitive predictions of clinicians, and two research strategies evolved. One describes professional judgements empirically and develops theoretical models to improve clinical training and judgement performance. The other aims to develop expert systems and computerized support systems to help clinicians to solve clinical problems. Computerized strategies helped develop artificial intelligence that, although closely associated with cognitive psychology, lies beyond the scope of this entry.