Each September, 7th Infantry Division concentrates its efforts of strengthening its suicide prevention programs and enhancing a culture that values life. While the end state is reduction of suicidal deaths, these actions also promote healthy living, social connectedness, leadership engagement and increased functioning.
The weakness in the program however is not knowing which of the known risks are elevated in a unit. We also lack adequate measurements of effectiveness.
Suicide prevention is a complex challenge. A long series of decisions and interventions are required where each decision and intervention influence the subsequent decisions. The suicide related casualties, however, do not care about the decisional challenges leaders and commanders face.
According to the most recent report on suicides from 2015, the Army lost 277 Soldiers to suicides. Adjusted for demographics, the rates of suicides are similar to those of general U.S. population.
While this is reassuring, it is still not clear why the rates of suicides in the Army went from being lower than general U.S. population, prior to 2006, to a sharp rise that remains to-date.
We have significant knowledge gaps to help translate data into decisions. In the complex world of human behaviors, the commanders still rely on very crude metrics.
In most units, these include trending suicidal ideations, failed suicide attempts and suicidal deaths. Given the low base rate of these events, the trend typifies small deviations.
With these metrics, it is hard to differentiate normal fluctuations from significant changes. It serves to provide situational awareness but does not lead to meaningful knowledge. Ideal metrics instead would serve to provide a shared mental model — a state of shared understanding.
Additionally, metrics must provide causal knowledge — not just the “what” but the “why’s” of a given problem.
Without metrics that provide shared understanding, it makes this complex problem even more challenging. Currently, several assessments indirectly look at some of these risks.
These include Command Climate Surveys or the Unit Risk Inventories. However, they are not explicitly nested under known suicide risk factors.
Often interventions are done either based on Army requirements or on leadership’s intuition. However, there are not good ways to know their efficacy.
This problem of understanding the problem must be resolved.
The Army is an ideal institution to tackle this problem. Our solution in 7th Infantry Division to these problems is still in its infancy. However, the initial pilot has been encouraging.
We took an historical Unit Behavioral Health Needs Assessment developed by Walter Reed Institute of Research and modified it. We have made it more feasible and unobtrusive by making it available online.
Our Soldiers take the 10-minute survey anonymously via their smartphones during lunch break. Specific company-level units are sampled throughout the year. The resulting data is permitting us to see true differences among our subordinate units.
Given its longitudinal nature, we hope to develop a database of causal knowledge that will enable commanders to actively modify suicide related risk factors.
As an Army of the future, more focus should be invested on machine learning and targeted surveillance of risk and resiliency factors. Facebook has recently shown that it can know you better than your friends can by simply analyzing your “likes” on your profile.
Relying on technological solutions while grooming our tribal subculture may be the answer to marrying the new with the old. This odd couple may help us better understand and respond to the problem of suicides among our ranks.