Health

Study identifies way to predict homelessness among veterans before they leave the service

A new study has pinpointed a way to help predict homelessness among veterans before they leave the service.

the studyconducted by researchers at Massachusetts General Hospital, Harvard Medical School and several other institutions around the country, looked at more than 2,000 lifetime variables among approximately 16,000 soldiers in the US Army, noted by questionnaires they took during their service.

The researchers used machine learning to isolate the three risk factors most strongly associated with vets becoming homeless: a history of depression, post traumatic stress disorder and the trauma of a loved one being murdered.

The veterans self-reported homelessness in surveys after their discharge from the military.

“We have never before had tools to be able to predict homelessness with the degree of accuracy that our model found,” said lead author Dr. Katherine Koh, a psychiatrist at Massachusetts General Hospital and Boston Health Care for the Homeless. “The soldiers that our model predicted were most likely to become homeless made up the majority of those who did actually become homeless. And second, our study further underscored the strong link between mental illness, trauma and risk of homelessness.”

Up until now, Koh said, programs to combat homelessness among veterans — and the general population — have focused on housing people who are already homeless and preventing recurring homelessness, as opposed to preventing it from happening in the first place. But, she said, this new tool could help change that.

The study is published in the American Journal of Preventive Medicine.

Koh and his colleagues are working with the US. Department of Defense and Department of Veterans Affairs to develop an intervention based on the model identified in the study, she said. It would first be rolled out in the Army, before developing similar programs for other branches of the military.

Soldiers would take a brief questionnaire, ideally about six months before their discharge from the Army.

“Our hope is to be able to identify these individuals before leaving so that they already are linked up with support and a person that they can trust prior to leaving,” Koh said, adding that case managers would follow veterans identified as being at high risk for homelessness and connect them with housing support, psychiatric care and other services.

“We hope that this study can help shift the conversation to preventing homelessness, not just among veterans, but also other high-risk groups, such as incarcerated people leaving jails and prisons, or children leaving foster care,” she said.

Leaders of the New England Center and Home for Veterans (NECHV) in Boston, which runs transitional housing, permanent supportive housing and homelessness prevention services, said the homelessness predictors identified in the study align with what the center sees in the veterans it serves.

Andy McCawley, NECHV’s president and chief executive officer, said while he welcomes the research and potential screening tool to advance homelessness prevention, seeing that veterans remain stable and housed involves a great deal — from early on in people’s military careers.

“The goal is not necessarily to avoid homelessness. Homelessness is the symptom,” McCawley said. “Certainly we do not want people to fall into homelessness, but the idea is to provide them with sufficient support … while they’re in the military, during their transition … and on into a life after military, [to] ensure that people can be connected and are willing to access the services that they may need to help them be successful, stay safe, guard their well-being, and not fall into that disruptive and disabling condition of homelessness.”

According to the US Department of Housing and Urban Development’s most recent report to Congress on homelessness, there were 505 veterans experiencing sheltered homelessness in Massachusetts at the time of the annual homeless census in January 2021, a 37% drop from the year before.

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