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J Psychiatr Res ; 176: 259-264, 2024 Aug.
Article in English | MEDLINE | ID: mdl-38901390

ABSTRACT

Behavioral warning signs (WS) are near-term changes within individuals, which aid in determining imminent risk for suicide attempts. However, those who attempt suicide differ in their engagement of WS, and it is unclear if these differences relate to future risk of suicidal behavior. Using a sample of 132 adults presenting to a hospital following a suicide attempt, the current study sought to determine if differences in engagement in WS for the index attempt prospectively predicted suicide attempt, frequency of ideation, and intensity of suicide ideation 12 months post discharge. Latent class analyses (LCAs) conducted on 6 behaviors (i.e., alcohol use, nightmares, interpersonal negative life events, suicide communication, risky behavior, low sleep, and high sleep) found a 5-class solution optimally fit the data. One identified class, characterized by engagement in risky behaviors the hours before an attempt differed from other identified classes in terms of risk for future suicidal ideation and behaviors. More specifically, participants in "High Risky Behavior" class had higher rates of 12-month suicide reattempt, significantly more frequent suicide ideation, and significantly worse intensity of suicide ideation during the 12 months following their index attempt compared to participants endorsing typical patterns of WS. These results held when adjusting for various traditional baseline covariates (e.g., depressive symptoms). The current study demonstrates that patterns of behavioral WS may be utilized as their own prognostic indicator of future suicidal ideation and behaviors among high-risk individuals reporting a recent suicide attempt, which can inform post-discharge clinical intervention and prevention efforts.


Subject(s)
Suicidal Ideation , Suicide, Attempted , Humans , Suicide, Attempted/statistics & numerical data , Male , Female , Adult , Middle Aged , Follow-Up Studies , Risk-Taking , Young Adult , Patient Discharge/statistics & numerical data
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