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Primary care suicide screenings commonly rely on imprecise questions that are distal from suicidal ideation or intent. Current approaches aim to capture as many at-risk patients as possible. As these authors emphasize, this may result in misallocation of treatment resources or unnecessary hospitalizations.
In addition to these considerations, there are other factors to weigh.
Might harm result from imprecise measures of risk?
Being flagged as “at risk” has consequences for some individuals, particularly those in certain occupations. For example, a military service member’s career may be derailed if he or she is “med-boarded” out of the service.(1) In fact, some marines refer to mental health providers as “wizards” because they have the power to “make service members disappear (from the Marine Corps).”
Further, hospitalization is not always therapeutic. In the worst cases, imprecise measures can result in poor decisions that break therapeutic trust and dissuade those who suffer from engaging in care in the future.
In this article, Bryan and colleagues demonstrated gains in discerning suicide risk from the addition of two items from the Suicide Cognitions Scale (SCS) that:
1) Bring the focus to the individual in a way that PHQ-2 items do not and
2) Are more specific (i.e., “proximal”), to suicidal intent as they home in on the tolerability of distress.
The performance of this combined PHQ/SCS items approach was actually superior to complex suicide prediction models derived from like machine learning algorithms.
Adding just a couple SCS items will better equip clinicians to accurately discern risk. This matters because discerning risk accurately is meaningfully related to decreasing risk, both for those who need care now, and those who may need urgent care in the future.
(1) The grief of losing the life one always wanted to lead as a career military service member is both substantial and often unaddressed in treatment settings where veterans are seen.