Nexus of despair: A network analysis of suicidal ideation among veterans

Simons, Jeffrey S.; Simons, Raluca M.; Walters, Kyle J.; Keith, Jessica A.; O’Brien, Carol; Andal, Kate; Stoltenberg, Scott F.

doi:10.1080/13811118.2019.1574689

Cited by 22 publications

(15 citation statements)

References 90 publications

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“…The association between suicidal ideation and depression was the strongest of these relationships, with a moderate positive correlation estimated between these variables. In previous suicide network research , Simons et al (2019) resilience, which the results of the present study support. Furthermore, a number of nonnetwork studies report similar findings to the present study, with negative relationships between suicidality and self-esteem (Fergusson et al, 2003;Thompson & Light, 2011), access to mental health services (Reynders et al, 2015;Stanley et al, 2016), and positive attitude towards mental health services (Stanley et al, 2016).…”

Section: Discussionsupporting

confidence: 87%

Suicide Risk and Protective Factors: A Network Approach

Holman¹,

Williams²

2020

Preprint

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Objective: Suicide is a complex phenomenon, with numerous factors contributing to an individual’s risk of suicide. The aim of the present study was to explore how risk and protective factors for suicide interact with one another in a network sense, and to determine which factors were most central to a network of these factors.Method: Using an online survey, cross-sectional data was collected from a sample of 515 individuals who lived in New Zealand, Australia, the United Kingdom, and the United States of America. Participants were recruited through either social media or Prolific Academic. A network of 18 risk and protective factors for suicide was estimated using network analysis. Analyses were preregistered on the Open Science Framework.Results: Factors that had the highest strength centrality were feeling depressed, feeling hopeless, perceived burdensomeness, self-esteem, and social support. Factors that were directly associated with suicidal ideation included feeling depressed, perceived burdensomeness, feeling hopeless, self-esteem, resilience, access to mental health services and a positive attitude towards these services.Conclusion: This research demonstrates the importance of examining protective factors as well as risk factors when determining an individual’s suicide risk. The results suggest that interventions targeting depression may be particularly beneficial in reducing suicide risk, but further longitudinal research is required.

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Section: Discussionsupporting

confidence: 87%

Suicide Risk and Protective Factors: A Network Approach

Holman¹,

Williams²

2020

Preprint

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“…The association between suicidal ideation and depression was the strongest of these relationships, with a moderate positive correlation estimated between these variables. In previous suicide network research, Simons et al (2019) andDe Beurs et al (2019) reported a positive association between suicidal ideation and depression or depressive symptoms. Additionally, De Beurs et al (2019) reported an association between suicidal ideation and both perceived burdensomeness and resilience, which the results of the present study support.…”

Section: Discussionmentioning

confidence: 87%

Suicide Risk and Protective Factors: A Network Approach

Holman¹,

Williams²

2020

Archives of Suicide Research

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Method: Using an online survey, cross-sectional data was collected from a sample of 515 individuals who lived in New Zealand, Australia, the United Kingdom, and the United States of America. Participants were recruited through either social media or Prolific Academic. A network of 18 risk and protective factors for suicide was estimated using network analysis. Analyses were preregistered on the Open Science Framework.Results: Factors that had the highest strength centrality were feeling depressed, feeling hopeless, perceived burdensomeness, self-esteem, and social support.Factors that were directly associated with suicidal ideation included feeling depressed, perceived burdensomeness, feeling hopeless, self-esteem, resilience, access to mental health services and a positive attitude towards these services.Conclusion: This research demonstrates the importance of examining protective factors as well as risk factors when determining an individual's suicide risk. The results suggest that interventions targeting depression may be particularly beneficial in reducing suicide risk, but further longitudinal research is required.

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“…One of the fast-expanding research fields focused on identifying associations between a wide array of symptoms and other factors, and commonly utilizing network models, is the field of post-traumatic stress. Over the past half-decade, numerous studies investigating associations between symptomatology (Mcnally et al, 2015;van Loo et al, 2018), potential risk factors (Armour et al, 2017;Choi et al, 2017;Mancini et al, 2019;Simons et al, 2019) and pathways to comorbidity (Djelantik et al, 2020;Gilbar, 2020;Lazarov et al, 2019;Malgaroli et al, 2018;Price et al, 2019;Vanzhula et al, 2019) have been published and yielded novel results and hypotheses. In response to this rapid research expansion and in an aim to synthesize current findings in the field, a thorough systematic review of the network approach to posttraumatic stress disorder (PTSD) has been recently carried out (Birkeland et al, 2020a).…”

Section: Introductionmentioning

confidence: 99%

Network Models of Post-traumatic Stress Disorder: A Meta-analysis

Isvoranu¹,

Epskamp²,

Cheung³

2020

Preprint

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Post-traumatic stress disorder (PTSD) researchers have increasingly used psychological network models to investigate PTSD symptom interactions, as well as to identify central driver symptoms. It is unclear, however, how generalizable such results are. We have developed a meta-analytic framework for aggregating network studies while taking between-study heterogeneity into account, and applied this framework to the first-ever meta-analytic study of network models. We analyzed the correlational structures of 52 different samples with a total sample size of n = 29,561, and estimated a single pooled network model underlying the datasets, investigated the scope of between-study heterogeneity, and assessed the performance of network models estimated from single studies. Our main findings are that: (1) While several clear symptom-links and interpretable clusters can be identified in the network, most symptoms feature very similar levels of centrality. To this end, aiming to identify central symptoms in PTSD symptom networks may not be fruitful. (2) We identified large between-study heterogeneity, indicating that it should be expected for networks of single studies to not perfectly align with one-another, and meta-analytic approaches are vital for the study of PTSD networks. (3) Nonetheless, we found evidence that networks estimated from single studies may give rise to generalizable results, as our results aligned with previous descriptive analyses of reported network studies, and network models estimated from single samples lead to similar network structures as the pooled network model. We discuss the implications of these findings for both the PTSD literature as well as methodological literature on network psychometrics.

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Nexus of despair: A network analysis of suicidal ideation among veterans

Cited by 22 publications

References 90 publications

Suicide Risk and Protective Factors: A Network Approach

Suicide Risk and Protective Factors: A Network Approach

Suicide Risk and Protective Factors: A Network Approach

Network Models of Post-traumatic Stress Disorder: A Meta-analysis

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