Interpreting clinical evidence of malingering: a Bayesian perspective

Customary ways of reporting on or testifying about malingering have shortcomings. Stating an opinion "with reasonable medical certainty" tells fact-finders little about how much confidence the opinion deserves; stating that an individual's behavior is similar to that of known malingerers does not convey the information that fact-finders really need to know, which is the likelihood that the evaluee in question is a malingerer, given the evaluator's findings. Mossman and Hart (Mossman D, Hart KJ: Presenting evidence of malingering to courts: insights from decision theory. Behav. Sci. Law 14:271-91, 1996) recommend that mental health professionals address this problem by using Bayes' theorem to interpret test data from evaluations. However, these authors do not discuss the use of evidence obtained during interviews and from other clinical contexts, nor do they describe a method for quantifying imprecision in Bayesian probabilities. This article provides examples of how forensic evaluators might use a Bayesian perspective to interpret clinical indicia of malingering observed during evaluations of adjudicatory competence. The article discusses sources of imprecision in Bayesian posterior probabilities, describes a method for characterizing that imprecision using confidence intervals, and then presents several sample calculations that illustrate how interview findings change the likelihood of malingering. The article also discusses the implications of the Bayesian approach for forensic evaluations and for future research on malingered incompetence.