Nonlinear change processes and the emergence of suicidal behavior: A conceptual model based on the fluid vulnerability theory of suicide

Bryan, Craig J.; Butner, Jonathan; May, Alexis M.; Rugo, Kelsi F.; Harris, John F.; Oakey, D. Nicolas; Rozek, David C.

doi:10.1016/j.newideapsych.2019.100758

Cited by 90 publications

(92 citation statements)

References 53 publications

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“…FVT also hypothesizes that suicide risk follows a discontinuous, nonlinear process [ 7 ]. Different types of nonlinear processes may characterize different risk states [ 8 ]. If so, improved understanding of these change processes could improve assessment and treatment.…”

Section: Methodsmentioning

confidence: 99%

“…Consistent with the fluid vulnerability theory of suicide [ 5 , 8 , 58 ], this study will explore both dynamic and stable properties of the change in suicide risk. For individuals with lower risk profiles, suicide risk is purported to demonstrate high stability because individuals with this profile gravitate toward a single stable state: low risk.…”

Section: Methodsmentioning

confidence: 99%

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Identifying suicidal subtypes and dynamic indicators of increasing and decreasing suicide risk in active duty military personnel: Study protocol

Brown

Bryan

Butner

et al. 2021

Contemporary Clinical Trials Communications

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Objectives Several recent studies have demonstrated that posttraumatic stress disorder (PTSD) and insomnia treatments are associated with significant reductions in suicidal ideation (SI) among service members. However, few investigations have evaluated the manner in which suicide risk changes over time among military personnel receiving PTSD or insomnia treatments. This paper describes the study protocol for a project with these aims: (1) explore potential genetic, clinical, and demographic subtypes of suicide risk in a large cohort of deployed service members; (2) explore subtype change in SI as a result of evidence-based psychotherapies for PTSD and insomnia; (3) evaluate the speed of change in suicide risk; and (4) identify predictors of higher- and lower-risk for suicide. Methods Active duty military personnel were recruited for four clinical trials (three for PTSD treatment and one for insomnia treatment) and a large prospective epidemiological study of deployed service members, all conducted through the South Texas Research Organizational Network Guiding Studies on Trauma and Resilience (STRONG STAR Consortium). Participants completed similar measures of demographic and clinical characteristics and subsets provided blood samples for genetic testing. The primary measures that we will analyze are the Beck Scale for Suicide Ideation, Beck Depression Inventory, and the PTSD Checklist for DSM-IV. Discussion Results from this study will offer new insights into the presence of discrete subtypes of suicide risk among active duty personnel, changes in risk over time among those subtypes, and predictors of subtypes. Findings will inform treatment development for military service members at risk for suicide.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Identifying suicidal subtypes and dynamic indicators of increasing and decreasing suicide risk in active duty military personnel: Study protocol

Brown

Bryan

Butner

et al. 2021

Contemporary Clinical Trials Communications

Self Cite

View full text Add to dashboard Cite

show abstract

“…Models of suicidality likewise suggest that suicide risk is a combination of stable and dynamic properties [4]. Suicide risk has stable characteristics that resist change over time (e.g., biological/ genetic characteristics) and dynamic characteristics that fluctuate in response to environmental and individual processes.…”

Section: Introductionmentioning

confidence: 99%

“…Suicide risk has stable characteristics that resist change over time (e.g., biological/ genetic characteristics) and dynamic characteristics that fluctuate in response to environmental and individual processes. According to the fluid vulnerability theory, suicidal behaviors emerge as a result of the interaction between dynamic and stable risk processes [4]. The fluid vulnerability theory suggests that there are factors that play an important role in the chronicity of suicide symptoms that are aggravated over time due to associated factors [5].…”

Section: Introductionmentioning

confidence: 99%

“…According to the fluid vulnerability theory, suicidal behaviors emerge as a result of the interaction between dynamic and stable risk processes [4]. The fluid vulnerability theory suggests that there are factors that play an important role in the chronicity of suicide symptoms that are aggravated over time due to associated factors [5]. Given the stresses associated with caregiving (e.g., social isolation, lack of sleep, interrupting education, ending employment, changes in roles/identity), which may add to or accentuate the stable risk processes, suicidal ideation, attempt, and completion may be significantly elevated in caregivers.…”

Section: Introductionmentioning

confidence: 99%

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Phenotypes of caregiver distress in military and veteran caregivers: Suicidal ideation associations

et al. 2021

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The United States (US) has been at war for almost two decades, resulting in a high prevalence of injuries and illnesses in service members and veterans. Family members and friends are frequently becoming the caregivers of service members and veterans who require long-term assistance for their medical conditions. There is a significant body of research regarding the physical, emotional, and social toll of caregiving and the associated adverse health-related outcomes. Despite strong evidence of the emotional toll and associated mental health conditions in family caregivers, the literature regarding suicidal ideation among family caregivers is scarce and even less is known about suicidal ideation in military caregivers. This study sought to identify clusters of characteristics and health factors (phenotypes) associated with suicidal ideation in a sample of military caregivers using a cross-sectional, web-based survey. Measures included the context of caregiving, physical, emotional, social health, and health history of caregivers. Military caregivers in this sample (n = 458) were mostly young adults (M = 39.8, SD = 9.9), caring for complex medical conditions for five or more years. They reported high symptomology on measures of pain, depression, and stress. Many (39%) experienced interruptions in their education and 23.6% reported suicidal ideation since becoming a caregiver. General latent variable analyses revealed three distinct classes or phenotypes (low, medium, high) associated with suicidality. Individuals in the high suicidality phenotype were significantly more likely to have interrupted their education due to caregiving and live closer (within 25 miles) to a VA medical center. This study indicates that interruption of life events, loss of self, and caring for a veteran with mental health conditions/suicidality are significant predictors of suicidality in military caregivers. Future research should examine caregiver life experiences in more detail to determine the feasibility of developing effective interventions to mitigate suicide-related risk for military caregivers.

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Ecological Momentary Assessment and Machine Learning for Predicting Suicidal Ideation Among Sexual and Gender Minority Individuals

Lei,

Qu,

Liu

et al. 2023

JAMA Netw Open

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ImportanceSuicidality poses a serious global health concern, particularly in the sexual and gender minority population. While various studies have focused on investigating chronic stressors, the precise prediction effect of daily experiences on suicide ideation remains uncertain.ObjectiveTo test the extent to which mood fluctuations and contextual stressful events experienced by sexual and gender minority individuals may predict later short- and long-term suicide ideation.Design, Setting, and ParticipantsThis diagnostic study collected twice-daily data on mood states and stressful events from sexual and gender minority individuals over 25 days throughout 3 waves of the Chinese Lunar New Year (before, during, and after), and follow-up surveys assessing suicidal ideation were conducted 1, 3, and 8 months later. Online recruitment advertisements were used to recruit young adults throughout China. Eligible participants were self-identified as sexual and gender minority individuals aged 18 to 29 years. Those who were diagnosed with psychotic disorders (eg, schizophrenia spectrum or schizotypal disorder) or prevented from objective factors (ie, not having a phone or having an irregular sleep rhythm) were excluded. Data were collected from January to October 2022.Main Outcomes and MeasuresTo predict short-term (1 month) and longer-term (3 and 8 months) suicidal ideation, the study tested several approaches by using machine learning including chronic stress baseline data (baseline approach), dynamic patterns of mood states and stressful events (ecological momentary assessment [EMA] approach), and a combination of baseline data and dynamic patterns (EMA plus baseline approach).ResultsA total of 103 sexual and gender minority individuals participated in the study (mean [SD] age, 24.2 [2.5] years; 72 [70%] female). Of these, 19 (18.4%; 95% CI, 10.9%-25.9%), 25 (24.8%; 95% CI, 16.4%-33.2%), 30 (29.4%; 95% CI, 20.6%-38.2%), and 32 (31.1%; 95% CI, 22.2%-40.0%) reported suicidal ideation at baseline, 1, 3, and 8 months follow-up, respectively. The EMA approach showed better performance than the baseline and baseline plus EMA approaches at 1-month follow-up (area under the receiver operating characteristic curve [AUC], 0.80; 95% CI, 0.78-0.81) and slightly better performance on the prediction of suicidal ideation at 3 and 8 months’ follow-up. In addition, the best approach predicting suicidal ideation was obtained during Lunar New Year period at 1-month follow-up, which had a mean AUC of 0.77 (95% CI, 0.74-0.79) and better performance at 3 and 8 months’ follow-up (AUC, 0.74; 95% CI, 0.72-0.76 and AUC, 0.72; 95% CI, 0.69-0.74, respectively).Conclusions and RelevanceThe findings in this study emphasize the importance of contextual risk factors experienced by sexual and gender minority individuals at different stages. The use of machine learning may facilitate the identification of individuals who are at risk and aid in the development of personalized process-based early prevention programs to mitigate future suicide risk.

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Nonlinear change processes and the emergence of suicidal behavior: A conceptual model based on the fluid vulnerability theory of suicide

Cited by 90 publications

References 53 publications

Identifying suicidal subtypes and dynamic indicators of increasing and decreasing suicide risk in active duty military personnel: Study protocol

Identifying suicidal subtypes and dynamic indicators of increasing and decreasing suicide risk in active duty military personnel: Study protocol

Phenotypes of caregiver distress in military and veteran caregivers: Suicidal ideation associations

Ecological Momentary Assessment and Machine Learning for Predicting Suicidal Ideation Among Sexual and Gender Minority Individuals

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