Clinical versus actuarial judgement - a summary of an article by Dawes, R, M., Faust, D., & Meehl, P, E. (1989)

Critical thinking
Article: Dawes, R, M., Faust, D., & Meehl, P, E. (1989)
Clinical versus actuarial judgment

Methods of judgment and means of comparison

In the clinical method, the decision maker combines or processes information in his or her head.
In the actuarial or statistical method, conclusions rest solely on empirically established relations between data and the condition or event of interest.

The actuarial method should not be equated with automated decision rules alone.
To be truly actuarial, interpretations must be both automatic (pre-specified or routinised) and based on empirically established relations.
Virtually any type of data is amenable to actuarial interpretation.

The combination of clinical and actuarial methods offers a third potential judgment strategy, one for which certain viable approaches have been proposed.
But, most proposals for clinical-actuarial combination presume that the two judgment methods work together harmoniously and overlook the many situations that require dichotomous choices.
Conditions for a fair comparison of the two methods:

  • both methods should base judgments on the same data
  • one must avoid conditions that can artificially inflate the accuracy of actuarial methods.

Results of comparative studies

Actuarial methods seem to have advantages over the clinical method.
Although most comparative research in medicine favours the actuarial method overall, the studies that suggest a slight clinical advantage seem to involve circumstances in which judgments rest on firm theoretical grounds.

Consideration of utilities. Depending on the task, certain judgment errors may be more serious than others.
The adjustment of decision rules or cutting scores to reduce either false-negative or false-positive errors can decrease the procedure’s overall accuracy by may still be justified if the consequences of these opposing forms of error are unequal.

The clinician’s potential capacity to capitalize on configural patterns or relations among predictive cues raises two related but separable issues:

  • the capacity to recognize configural relations
    Certain forms of human pattern recognition still cannot be duplicated or equalled by artificial means.
  • the capacity to use these observations to diagnose and predict.
    The possession of unique observational capacities clearly implies that human input or interaction is often needed to achieve maximal predictive accuracy but tempts us to draw an additional, dubious inference (because actuarial methods are often more accurate).

A unique capacity to observe is not the same as a unique capacity to predict on the bases of integration of observations.
Greater accuracy may be achieved if the skilled observer performs this function and then steps aside, leaving the interpretation of observational and other data to the actuarial method.

Factors underlying the superiority of actuarial methods

  • Actuarial procedures, unlike the human judge, always lead tot the same conclusion for a given data set.
  • when properly derived, the mathematical features of actuarial methods ensure that variables contribute to conclusions based on their actual predictive power and relation to the criterion of interest. These achievements are essentially automatic with actuarial prediction but present formidable obstacles for human judges.
  • Individuals have considerable difficulty distinguishing valid and invalid variables and commonly develop false beliefs in associations between variables.
  • clinical judgments may produce self-fulfilling prophecies.
  • clinical judgements may see known outcomes more predictable than they are in advance, and past predictions are mistakenly recalled as overly consistent with actual outcomes.
  • The clinician is exposed to a skewed sample of humanity and, short of exposure to truly representative samples, it may be difficult, if not impossible, to determine relations among variables.

Even should a valid relation exist, one cannot determine the sign’s actual utility unless one knows:

  • how much more frequently it occurs when the condition is present than when it is absent
  • the frequency of the condition

Lack of impact and sources of resistance

Research on clinical versus statistical judgment has had little impact on everyday decision making.

  • Lack of impact is sometimes due to lack of familiarity with the scientific evidence
  • Others who know the evidence may still dismiss it based in tendentiousness or misconception.
    A common misconception is that group statistics do not apply to single individuals or events.
  • Subjective appraisal may lead to inflated confidence in the accuracy of clinical judgement and the false impression that the actuarial method is inferior.

Application of actuarial methods: limits, benefits, and implications

The research reviewed in this article indicates that a properly developed and applied actuarial method is likely to help in diagnosing and predicting human behaviour as well or better than the clinical method, even when the clinical judge has access to equal or greater amounts of information.
But, research demonstrating the general superiority of actuarial approaches, should be tempered by an awareness of limitations and needed quality controls.

  • although surpassing clinical methods, actuarial procedures are far from infallible, sometimes achieving only modest results
  • even a specific procedure that proves successful in one setting should be periodically re-evaluated within that setting and should not be applied to new settings mindlessly

When developed and used appropriately, actuarial procedures can provide various benefits.

  • they may save considerable time and expense.
  • when actuarial methods prove more accurate than clinical judgment, the benefits to individuals and society are apparent.
  • Actuarial methods are explicit, in contrast to clinical judgment, with rests on mental processes that are often difficult to specify.
  • Actuarial methods reveal the upper bounds in our current capacities to predict human behaviour.

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