Making mental health diagnoses clearer by making the logic of diagnosis fuzzier

On 23rd April I attended a short talk, hosted by the British Psychological Society, by Dr Ralph Goldstein, on the subject of models of mental health. The talk began with a little history, specifically about Virchow’s revolutionary ideas in 1848 that changed how we think about disease and led to him being considered one of the founding figures of modern medical science.

In the field of mental health, the way we think about disease, diagnosis and recovery is still somewhat debated. Notably, the latest edition of the diagnostic and statistical manual, DSM-V, by the American Psychiatric Association, came under heavy criticism when it was released, in part due to its lack of precision when defining many disorders. Another issue Dr Goldstein touched upon was the way mental health professionals focus on statistical differences as evidence perhaps too much.

One pertinent example, which Dr Goldstein briefly mentioned but didn’t go into much depth about, was something that has troubled me considerably when I came across it in my own studies, is the controversy currently surrounding antidepressants and how it’s possible that they might be completely ineffective (any perceived effect can be attributed to placebo) and drug companies seem to be obfuscating evidence that would perhaps harm their profits from the use of these drugs.

These kinds of issues stem from the problem of quantifying qualitatively variable symptoms and setting clear categories of how ill a patient is. For example, a common scale used when diagnosing depression is the Beck Depression Inventory (BDI) which classifies patients as either minimally, mildly, moderately or severely depressed- note there is no category for “not depressed”. A possible solution that Dr Goldstein pointed to, which as of yet, has not been researched, is the application of fuzzy logic to how mental health practitioners perform diagnoses.

Fuzzy logic is useful for dealing with approximate rather than fixed and exact values and has been used for decades in other fields. Examples Dr Goldstein pointed to included automatic gearboxes and central heating controllers. Applying fuzzy logic to mental health pathology would mean addressing the fact that many determinations made by practitioners are somewhat vague- therefore diagnostic systems should use logic capable of dealing with that.

Editor’s note: This post was originally written for TheKnowledge


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