Determining who is at risk for suicide is an arduous and inexact endeavor. Even trained clinicians can miss warning signs.
Researchers have now developed an instrument they believe will help predict those at risk.
Matthew Nock of Harvard University, along with colleagues from Harvard University and Massachusetts General Hospital, modified a well-known word-association test to measure associations between life and death/ suicide and examined if it could be effective in predicting suicide risk.
The Implicit Association Test (IAT) is a widely used test that measures automatic associations people hold about various topics. Participants are shown pairs of words; the speed of their response indicates if they unconsciously associate those words.
In the IAT version used in this study, participants classified words related to “life” (e.g., breathing) and “death” (e.g., dead) and “me” (e.g., mine) and “not me” (e.g., them).
Faster responses to “death”/”me” stimuli than “life”/”me” stimuli would suggest a stronger association between death and self.
People seeking treatment at a psychiatric emergency room participated in this study. They completed the IAT and various mental health assessments. In addition, their medical records were examined six months later to see if they had attempted suicide within that time.
The results, reported in Psychological Science, a journal of the Association for Psychological Science, revealed that participants presenting to the emergency room after a suicide attempt had a stronger implicit association between death/ suicide and self than did participants presenting with other psychiatric emergencies.
In addition, participants with strong associations between death/ suicide and self were significantly more likely to make a suicide attempt within the next six months than were those who had stronger associations between life and self.
These results suggest that an implicit association between death/ suicide and self may be a behavioral marker for suicide attempts. These findings also indicate that measures of implicit cognition may be useful for identifying and predicting clinical behaviors that tend not be reported.
As Nock explains, “these results are really exciting because they address a long-standing scientific and clinical dilemma by identifying a method of measuring how people are thinking about death and suicide that does not rely on their self-report.”
He adds, “we are hopeful that this line of research ultimately will provide scientists and clinicians with new tools for measuring how people think about sensitive clinical behaviors that they may be unwilling or unable to report on verbally.”
Mahzarin Banaji, also of Harvard University and a co-author of this study, adds that this work presents a strong argument for the importance of funding basic behavioral research.
“These results are an example of basic research helping to solving a troubling and devastating problem in every society. The method we used was designed to understand the mind, but it turned into a technique that can predict disorders of a variety of sorts. One wonders why funding agencies that should know better about the value of basic research seem so naive when it comes to decisions about what is in the public’s interest.”