Correlation Engine 2.0
Clear Search sequence regions

  • behavior (3)
  • control group (1)
  • humans (1)
  • spouses (1)
  • v e (9)
  • veterans (16)
  • Sizes of these terms reflect their relevance to your search.

    VA S.A.V.E. (Signs; Ask; Validate; Encourage/Expedite) is a gatekeeper training developed by the Department of Veterans Affairs (VA) that teaches individuals to identify and assist veterans at risk for suicide. Although VA S.A.V.E. has been widely disseminated, rigorous evaluation is lacking. In a pilot randomized controlled trial of a brief, video-based version of VA S.A.V.E., individuals were recruited through Facebook, randomized to VA S.A.V.E. versus an attention control condition, and completed 6-month follow-up. A subgroup (n = 15) completed interviews. We used a mixed methods framework to integrate quantitative and qualitative findings. Among 214 participants, 61% were spouses/partners of veterans and 77% had prior suicide exposure. Sixty-seven percent (n = 68) of VA S.A.V.E. participants watched the entire video, and satisfaction and usability were highly rated. At 6-month follow-up, compared to the control group, the VA S.A.V.E. group had a higher proportion of participants use each gatekeeper behavior (66.7%-84.9% vs. 44.4%-77.1%), and used significantly more total gatekeeper behaviors (2.3 ± 0.9 vs. 1.8 ± 1.0; p = 0.01). Interviews supported positive reactions, learning, and behavior change from VA S.A.V.E. VA S.A.V.E. merits further investigation into its effectiveness as a brief, scalable gatekeeper training for suicide prevention in veterans. © 2023 American Association of Suicidology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.


    Alan R Teo, Elizabeth R Hooker, Aaron A Call, Steven K Dobscha, Stephanie Gamble, Wendi F Cross, Carie Rodgers. Brief video training for suicide prevention in veterans: A randomized controlled trial of VA S.A.V.E. Suicide & life-threatening behavior. 2024 Feb;54(1):154-166

    Expand section icon Mesh Tags

    PMID: 38095049

    View Full Text