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Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors
by
Nock, Matthew K.
, Geraci, Joseph C.
, Hwang, Irving
, Kessler, Ronald C.
, Borowski, Shelby
, Sampson, Nancy A.
, Ursano, Robert J.
, Gildea, Sarah M.
, Stein, Murray B.
, Wagner, James
, Capaldi, Vincent F.
, Naifeh, James A.
, Luedtke, Alex
, Benedek, David M.
, Liu, Howard
, Edwards, Emily R.
, Kennedy, Chris J.
in
692/308
/ 692/499
/ 692/699
/ 692/700
/ Armed forces
/ Datasets
/ Family
/ Group and Systematic Therapy
/ Longitudinal studies
/ Machine learning
/ Medicine
/ Medicine & Public Health
/ Military deployment
/ Military personnel
/ Military recruitment
/ Military reserves
/ Neurobiology
/ Outreach services
/ Polls & surveys
/ Psychiatry
/ Psychology
/ Psychotherapy
/ Public Health
/ Response rates
/ Statistical power
/ Suicides & suicide attempts
/ Unemployment
2026
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Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors
by
Nock, Matthew K.
, Geraci, Joseph C.
, Hwang, Irving
, Kessler, Ronald C.
, Borowski, Shelby
, Sampson, Nancy A.
, Ursano, Robert J.
, Gildea, Sarah M.
, Stein, Murray B.
, Wagner, James
, Capaldi, Vincent F.
, Naifeh, James A.
, Luedtke, Alex
, Benedek, David M.
, Liu, Howard
, Edwards, Emily R.
, Kennedy, Chris J.
in
692/308
/ 692/499
/ 692/699
/ 692/700
/ Armed forces
/ Datasets
/ Family
/ Group and Systematic Therapy
/ Longitudinal studies
/ Machine learning
/ Medicine
/ Medicine & Public Health
/ Military deployment
/ Military personnel
/ Military recruitment
/ Military reserves
/ Neurobiology
/ Outreach services
/ Polls & surveys
/ Psychiatry
/ Psychology
/ Psychotherapy
/ Public Health
/ Response rates
/ Statistical power
/ Suicides & suicide attempts
/ Unemployment
2026
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Do you wish to request the book?
Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors
by
Nock, Matthew K.
, Geraci, Joseph C.
, Hwang, Irving
, Kessler, Ronald C.
, Borowski, Shelby
, Sampson, Nancy A.
, Ursano, Robert J.
, Gildea, Sarah M.
, Stein, Murray B.
, Wagner, James
, Capaldi, Vincent F.
, Naifeh, James A.
, Luedtke, Alex
, Benedek, David M.
, Liu, Howard
, Edwards, Emily R.
, Kennedy, Chris J.
in
692/308
/ 692/499
/ 692/699
/ 692/700
/ Armed forces
/ Datasets
/ Family
/ Group and Systematic Therapy
/ Longitudinal studies
/ Machine learning
/ Medicine
/ Medicine & Public Health
/ Military deployment
/ Military personnel
/ Military recruitment
/ Military reserves
/ Neurobiology
/ Outreach services
/ Polls & surveys
/ Psychiatry
/ Psychology
/ Psychotherapy
/ Public Health
/ Response rates
/ Statistical power
/ Suicides & suicide attempts
/ Unemployment
2026
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Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors
Journal Article
Joint models targeting U.S. Army soldiers at high-risk of post-separation unemployment, homelessness, and suicide-related behaviors
2026
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ABSTRACT
Transitioning service members (TSMs) leaving military service have high risks of unemployment, homelessness, nonfatal suicide attempt (SA), and suicide death. Data from
n
= 7188 recently separated TSMs from the U.S. Army were used to update previously developed models for post-separation homelessness and SA based on data at the time of separation and to develop a new unemployment model. Predicted probabilities of suicide from a model developed elsewhere were imputed for comparison purposes. Cross-validated predictions were significant for the homelessness (AU-ROC = 0.68) and SA (AU-ROC = 0.78) models but not the unemployment model (AU-ROC = 0.60). Elevated cross-validated risk was found for the 10% of TSMs at the highest predicted risk of homelessness (SN = 26.6%), 20% for SA (SN = 60.9%), and 10% for suicide death (SN = 34.1%). 28% of TSMs were in the highest risk categories for at least one and 10% for more than one outcome. Findings regarding incomplete overlap highlight the complexities of risk targeting when multiple outcomes are of interest.
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