Despite a growing body of knowledge regarding suicide risk and protective factors, as well as neurological and neuropsychological correlates of suicidal behavior, assessment has remained strikingly similar to what it was four decades ago. Many psychologists and researchers across the country have been investigating assessment tools for suicide risk – and these efforts are suggestive of a promising future for suicide prevention.
Suicide assessment in practice is remarkably complex, as not everyone who presents with ideation will follow with an attempt. There are intricate, currently unrecognizable nuances that seem to predispose certain individuals to the physical act. Brain function, specifically executive dysfunction, has been implicated in suicide attempters. However, in populations with high rates of comorbidities and complex trauma (TBI, etc.), these associations do not always remain strong.
Attempts to quantify suicide risk are coming closer to answers, but there remains the uniqueness of the individual that is quite elusive to current objective measures and imaging techniques.
Self-report measures of depression and suicidality have maintained their long-standing utility in settings across the healthcare system, including emergency departments. These measures, however, are based on the premises that individuals at risk for suicidal behavior will not only disclose this information, but are consciously aware of their risk in the first place.
These premises appear to be flawed from the outset, suggesting that a combination of neuropsychological and psychological components may be necessary to accurately predict risk of suicide.
Studies coming out of universities such as Harvard and Yale have been investigating associations between objective psychological measures and suicide risk with high success. Implicit association tests (IATs) illustrate what may be the part of a suicidal brain that remains unconscious to its beholder.
IATs have been developed to confront associations specific to dealth/suicide. Their use in various settings has demonstrated an ability to accurately predict suicide attempts approximately six months in advance.
This is a tremendous advancement in assessment, which will likely yield more specific measures. Of importance is the ability to predict suicide attempts that may occur in the following week, as empirically based treatment approaches will differ significantly for these two groups of suicidal patients.
While suicide assessment has not taken the same leaps as other modalities and measures, those at work are now making great strides to uncover how the suicidal brain may look, behave and respond to objective measures. In time, with knowledge of the complexities of the suicidal brain, a mouse model may be possible, opening the doors to preclinical studies on neuropathology and treatment.
Jack Lennon is a fifth-year doctoral student in clinical neuropsychology/psychology at Adler University, with a research appointment at Northwestern University Feinberg School of Medicine and clinical externships at Rush Neurobehavioral Center and Rush University Medical Center’s Division of Movement Disorders. His email address is: email@example.com