A network perspective on suicidal behavior: Understanding suicidality as a complex system

Randomized controlled trial for the Attempted Suicide Short Intervention Program (ASSIP): An independent non-replication study

Following the call for rigorous replication practices in crisis intervention and suicide prevention research, this study re-evaluated the efficacy of a brief intervention (ASSIP - Attempted Suicide Short Intervention Program) for patients with a recent suicide attempt in reducing repeated suicidal behavior. In this open-label, randomized, controlled parallel-group trial, 92 patients were assigned to treatment as usual (TAU) or TAU plus ASSIP. The primary outcome was suicidal behavior (suicide attempts and suicide deaths) during a 12-month observation period. Secondary outcomes included the number of suicide attempts and psychiatric inpatient admissions. Twelve patients in the intervention group and six patients in the control group engaged in suicidal behavior, including one suicide death in each group. The intention-to-treat (ITT) analysis found no significant effect of ASSIP in reducing suicidal behavior or admission to psychiatric hospitals. Surprisingly, the per-protocol (PP) analysis revealed a significantly higher incidence rate of suicide re-attempts in the intervention group. Contrary to the original findings, this non-replication study suggests that ASSIP combined with TAU does not significantly reduce suicidal behavior compared to TAU alone. Further research is needed to refine indications for ASSIP therapy and enhance its effectiveness.

The underlying dynamics of a suicidal ideation latent network model: The role of hopelessness, psychopathology, emotion regulation, and behavioral coping skills in adolescents from the general population

BACKGROUND

Suicide is a major cause of death among adolescents, with suicidal ideation (SI) being a common symptom in this group. SI arises from a complex mix of biological, environmental, and psychological factors, however, the specific relationships between them is not yet fully understood. Network theory has been proposed as a promising framework to analyze these relationships, with latent network models (LNM) offering a novel approach to capture their complex underlying dynamics.

METHODS

We examined a SI-based LNM in a sample of 1539 students from secondary public schools (M = 15.336; SD = 1.022; female = 52.39 %). The model included depressive and anxiety symptoms, feelings of hopelessness, emotion regulation strategies, and cognitive-behavioral and problem-solving skills. Strength and expected influence indices were calculated for each variable.

RESULTS

Hopelessness and depressive symptoms showed the highest strength and expected influence values within the model, respectively. Our findings suggest that hopelessness might play a crucial mediating role linking common mental disorders and emotion regulation strategies with SI in adolescents. Expressive suppression had a direct and negative association with SI, showing its underlying regulatory role when other factors are controlled. Cognitive-behavioral and problem-solving skills showed weak links with SI.

CONCLUSIONS

Primary care- and school-based interventions should center on hopelessness as a relevant direct predictor for SI, and potential mediator in the course of SI. A combination of research and intervention efforts directed at reducing hopelessness in youths may prove to be essential for reducing suicide-related behaviors altogether.

Do the Relative Importance and Pattern of Correlates of Suicidal Ideation Vary by Age and Gender? Network Analyses

This study examined age- and gender-related differences in correlates of suicidal ideation (SI) and their interrelationships. We used data from a nationally representative sample of adults aged 19 years or older who participated in the 2021 Korea Welfare Panel Study (N = 10,364). We examined six networks of SI and its sociodemographic, physical health, and psychological correlates by age (young, 19-39 years; middle-aged, 40-64 years; and old, over 65 years old) and by gender. Depression, subjective well-being (SWB), and self-esteem were the key SI correlates across all groups. Depression had the strongest direct associations with SI in all groups (edge weights: 0.23 in old women to 1.00 in middle-aged men). SWB was directly associated with SI in middle-aged men (-0.26), middle-aged women (0.27), and old women (-0.37). Self-esteem was indirectly related to SI through depression and SWB. Age- and gender-specific correlates included chronic illness for young women, job satisfaction and subjective physical health for middle-aged women, and family relationship satisfaction for older men and women, each showing stronger associations with SI than other correlates within their respective groups. Suicide prevention efforts may benefit from addressing both common and age- and gender-specific correlates of SI.

Situational impact, psychosocial risk factors, and suicidality among young adults in Hong Kong during and after the COVID-19 pandemic: A repeated cross-sectional network analysis

BACKGROUND

The COVID-19 pandemic has brought substantial impacts and mental distress to young adults. No existing studies have investigated the roles of situational impact and psychosocial risk factors on suicidality under the pandemic context.

AIMS

The present study examined the relationships between situational impact, psychosocial factors, and suicidality via a network approach during and after the COVID-19 pandemic.

METHOD

Cross-sectional telephone surveys recruited three samples of young adults in Hong Kong via random sampling in autumns of 2021 to 2023 (N = 1,226-1,472). The respondents completed measures on situational impact, meaning in life, societal pessimism, Patient Health Questionnaire-4 (PHQ-4), hikikomori, and suicidality. Mixed graphical modeling was used to estimate the network and identify the partial correlations among the study variables in the three waves.

RESULTS

The 2023 wave showed lower levels of COVID-19 distress and PHQ-4 but higher suicidality than 2021 and 2022 waves. Social impact, physical impact, and PHQ-4 were the central nodes in the 2021 and 2023 networks. Meaning in life showed negative linkages with other psychosocial factors. Suicidality showed positive linkages with societal pessimism, hikikomori, and PHQ-4 in the networks. Network comparison found no significant differences in network structure and global strength across gender, age, and waves. Societal pessimism showed significantly stronger linkages with financial impact, meaning in life, and suicidality in 2023 than 2021.

CONCLUSIONS

Our results enhance the understanding of comorbidity among psychosocial and situational risk factors of suicidality, which have implications for future interventions to improve mental health outcomes among young adults at risk.

The geographic identification of elevated suicide risk model: evaluating a method for examining suicide-related behaviors at the neighborhood level in Harris County, Texas

BACKGROUND

The 2024 National Strategy for Suicide Prevention has called for the development of community-based suicide prevention resources, and improved existing prevention efforts. In line with such efforts, Hill and colleagues developed the Geospatial Identification of Elevated Suicide Risk model that estimates the relative prevalence of adolescent suicide risk within specific geographical areas. The current study seeks to further evaluate and refine the model for use as a tool to evaluate risk and protective factors at the neighborhood level.

METHOD

Drawing from multiple sources, data was collected detailing adolescent suicidal ideation, suicide attempts, suicide fatalities, and census tract characteristics. Utilizing data resulting from an initial pool of 74,883 suicidal ideation and attempt screens found in electronic health records, suicidal ideation and attempt rates were calculated, described, and mapped onto relevant census tracts via the Census Geocoder. Once mapped, a total of 1,098 census tracts were examined for criterion validity and minimum data evaluations.

RESULTS

Data indicate that rates of positive suicide risk screens are relatively normally distributed when using a minimum cell size of at least n = 5, with additional improvements at n = 10 screens per census tract. Of 48,928 records with completed screens and patient address data listed in the electronic health record, 44,776 addresses (91.5%) were matched to U.S. census tracts via the Census Geocoder database. When evaluating criterion validity, the simultaneous multivariate logistic regression revealed that the model did not fit well to the data, and suicide attempts and suicidal ideation only predicted 0.02% of the variance in the probability of suicide fatality. Finally, a classification tree revealed that a minimum of 10 data points were required to delineate between high and low-risk census tracts.

CONCLUSION

The refined model may act as a helpful tool to evaluate neighborhood level risk and protective factors. Findings suggest a prevention-oriented, as opposed to risk prediction, approach to suicide risk management at the community level may be needed; such an approach would prioritize community connectedness, adequate mental health support services, and reduction of community-level risk factors (e.g., substance misuse), among others.

Multiple pathways to suicide: A network analysis based on three components of psychological pain

BACKGROUND

Psychological pain is a multidimensional structure that has long been recognized as an important risk factor for suicidal ideation and behavior. The roles of interactions among psychological pain subfactors at different stages of suicidality remain unclear.

METHODS

A relatively large sample of outpatients with major depressive disorder (N = 501) was recruited to complete the Three-Dimensional Psychological Pain Scale (TDPPS). Exploratory graphical analysis (EGA) was conducted to explore the factor structure of TDPPS, thereby ensuring that the psychological pain subfactor was measured accurately. Network analysis included all TDPPS items, depression, passive suicidal ideation (PSI), active suicidal ideation (ASI), and history of suicidal action (SA) to identify key loops of suicidality.

RESULTS

EGA disclosed a three-factor structure of TDPPS comprising cognitive, affective, and motivational factors. Network analysis revealed that items of motivational factors, but none of the items of cognitive and affective factors, were directly linked to PSI, ASI, and SA. Furthermore, three communities were identified by a "walktrap" algorithm. Depression and cognitive factor coalesced into a 'cognitive' community, affective factor constituted an 'affective' community, and motivational factor, PSI, ASI, and SA comprised a 'suicidal' community.

LIMITATIONS

This study used a cross-sectional design that cannot provide information on causal relationships among variables in the network.

CONCLUSIONS

Psychological pain avoidance may be a direct driver of suicidality, and therefore its assessment and intervention in clinical practice is necessary.

Mapping the maze: A network analysis of social-emotional skills among children and adolescents with social-emotional difficulties

Developing social-emotional skills is crucial for all children and adolescents, particularly those experiencing social and emotional difficulties. This study used network analysis to identify the central skills and network association of different social-emotional skills and investigated how these networks differ between childhood and adolescence. Data were obtained from the 2019 Survey on Social and Emotional Skills by the Organization for Economic Co-operation and Development. Our study focused on the bottom quartile of participants aged 10 and 15 years, including 7737 and 7439 individuals from each age group. Optimism and cooperation consistently emerged as the central skills of social-emotional competence across both age groups. When comparing network structures, there was a significant difference between children and adolescents. The connectivity of social-emotional networks was stronger among adolescents, indicating closer skill associations. Understanding these developmental differences is important for educators and practitioners to more effectively support the social-emotional development of children and adolescents experiencing social-emotional difficulties.

Assessing the dimensions and structure of thwarted interpersonal needs

INTRODUCTION

The Interpersonal Needs Questionnaire-15 (INQ-15) assesses interpersonal needs comprising suicidal desire based on the Interpersonal Theory of Suicide (IPTS): Thwarted belongingness (TB) and perceived burdensomeness (PB). The IPTS is applied to many psychological-affective states and disorders, collectively showing state-specific pathways to suicidal features. Given the prevalent application of the IPTS, determining how the constructs are comprised and operate is critical. Consistent with the network perspective of psychological constructs, we used network and algorithmic methods to evaluate thwarted interpersonal needs.

METHODS

A sample (N = 863) aggregated from two independent studies (Sokol & Serper, 2019; Sokol et al., 2023) was used for analysis.

RESULTS

Network analysis identified three dimensions that were invariant by suicide-risk status: PB, and two dimensions from the TB items. Accounting for wording effects, one-dimensional structures presented in 9 %-23 % of replicates. The loadings comparison test algorithm suggested that the constructs were consistent with a network composition (over latent), and centrality indices identified meaningful strong and bridge features.

LIMITATIONS

The samples were demographically homogeneous, and more diverse samples in terms of sexuality, racial/ethnic identification, culture, and socioeconomic status might yield different findings.

CONCLUSION

Findings indicate that thwarted interpersonal needs are comprised of perceived burdensomeness, loneliness, and absence of reciprocal care dimensions and that loneliness-related experiences may be mechanisms by which PB and TB-related experiences co-occur. Additionally, results showed that the INQ-15 may have previously unquantified method effects, but the overall identified dimensions are stable. These results yield a nuanced conceptualization of interpersonal needs and their function.

Symptomatic networks in suicide attempt and reattempt: Relevance of psychiatric comorbidity

BACKGROUND

One of the most relevant risk factors for suicide is the presence of previous attempts. The symptomatic profile of people who reattempt suicide deserves attention. Network analysis is a promising tool to study this field.

OBJECTIVE

To analyze the symptomatic network of patients who have attempted suicide recently and compare networks of people with several attempts and people with just one at baseline.

METHODS

1043 adult participants from the Spanish cohort "SURVIVE" were part of this study. Participants were classified into two groups: single attempt group (n = 390) and reattempt group (n = 653). Different network analyses were carried out to study the relationships between suicidal ideation, behavior, psychiatric symptoms, diagnoses, childhood trauma, and impulsivity. A general network and one for each subgroup were estimated.

RESULTS

People with several suicide attempts at baseline scored significantly higher across all clinical scales. The symptomatic networks were equivalent in both groups of patients (p > .05). Although there were no overall differences between the networks, some nodes were more relevant according to group belonging.

CONCLUSIONS

People with a history of previous attempts have greater psychiatric symptom severity but the relationships between risk factors show the same structure when compared with the single attempt group. All risk factors deserve attention regardless of the number of attempts, but assessments can be adjusted to better monitor the occurrence of reattempts.

Ambivalence model of suicidality [ABS-model]: an orientation model for the treatment of suicidal individuals

The existing models for understanding suicidal ideation and behavior do not provide satisfactory orientation for clinical-therapeutic work with suicidal clients. Based on the observation that ambivalence accompanies the entire suicidal process and building on the empirical knowledge about suicidal ambivalence, this article presents the ambivalence model of suicidality (ABS model), a new clinical working model that aims to provide a framework for risk assessment, case conceptualization and treatment planning in the treatment of suicidal individuals. The model divides the suicidal process into three phases (uncertainty phase, transition phase and action phase), describes the psychological state within the different phases, and identifies phase-specific therapeutic interventions. The ABS model is a descriptive model that can be used to structure and organize crisis intervention and psychotherapy with suicidal patients.

Unravelling the complexity of suicidality: a network analysis of theory-driven and culturally relevant suicide risk factors in a country with high suicide rates

PURPOSE

This study aimed to explore whether individual theory-based constructs are sufficient in explaining suicidality in a culture marked by high suicide rates and whether, if any, culturally relevant factors need to be considered additionally.

METHODS

The study used a community sample of 1873 Lithuanian adults (age M = 43.61 SD = 16.96, 69.1% female). A survey using online and pen-and-paper formats was conducted, measuring suicidality, the main constructs from two predominant theories of suicide (thwarted belongingness, perceived burdensomeness, acquired capability for suicide, and defeat and entrapment), and culturally relevant factors (gender role expectations, attitudes towards help-seeking, perfectionism, negative social comparisons, alcohol use, child-parent relationships and childhood experiences). Network analysis method was used in the analysis.

RESULTS

From the key factors identified in the two theories perceived burdensomeness had stronger links with self-perceived risk for suicide compared to thwarted belongingness and entrapment. Acquired capability to suicide had no direct links with other factors in the network apart from a weak link with history of suicidal behavior. In the network some of the culturally relevant variables (reasons for alcohol use, experience of sexual abuse, emotional neglect, and cultural norms representing restricted emotionality and attitudes towards psychological help) had direct relationships with suicidality, not only via key theory based factors.

CONCLUSIONS

The results suggest the need to consider cultural context when applying universal suicide theories.

A systematic review on passive sensing for the prediction of suicidal thoughts and behaviors

Passive sensing data from smartphones and wearables may help improve the prediction of suicidal thoughts and behaviors (STB). In this systematic review, we explored the feasibility and predictive validity of passive sensing for STB. On June 24, 2024, we systematically searched Medline, Embase, Web of Science, PubMed, and PsycINFO. Studies were eligible if they investigated the association between STB and passive sensing, or the feasibility of passive sensing in this context. From 2107 unique records, we identified eleven prediction studies, ten feasibility studies, and seven protocols. Studies indicated generally lower model performance for passive compared to active data, with three out of four studies finding no incremental value. PROBAST ratings revealed major shortcomings in methodology and reporting. Studies suggested that passive sensing is feasible in high-risk populations. In conclusion, there is limited evidence on the predictive value of passive sensing for STB. We highlight important quality characteristics for future research.

Examining contemporaneous and temporal associations of real-time suicidal ideation using network analysis

BACKGROUND

Suicidal ideation arises from a complex interplay of multiple interacting risk factors over time. Recently, ecological momentary assessment (EMA) has increased our understanding of factors associated with real-time suicidal ideation, as well as those predicting ideation at the level of hours and days. Here we used statistical network methods to investigate which cognitive-affective risk and protective factors are associated with the temporal dynamics of suicidal ideation.

METHODS

The SAFE study is a longitudinal cohort study of 82 participants with current suicidal ideation who completed 4×/day EMA over 21 days. We modeled contemporaneous (t) and temporal (t + 1) associations of three suicidal ideation components (passive ideation, active ideation, and acquired capability) and their predictors (positive and negative affect, anxiety, hopelessness, loneliness, burdensomeness, and optimism) using multilevel vector auto-regression models.

RESULTS

Contemporaneously, passive suicidal ideation was positively associated with sadness, hopelessness, loneliness, and burdensomeness, and negatively with happiness, calmness, and optimism; active suicidal ideation was positively associated with passive suicidal ideation, sadness, and shame; and acquired capability only with passive and active suicidal ideation. Acquired capability and hopelessness positively predicted passive ideation at t + 1, which in turn predicted active ideation; acquired capability was positively predicted at t + 1 by shame, and negatively by burdensomeness.

CONCLUSIONS

Our findings show that systematic real-time associations exist between suicidal ideation and its predictors, and that different factors may uniquely influence distinct components of ideation. These factors may represent important targets for safety planning and risk detection.

Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning

Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervasive online, STB risk detection may be improved through development of uniquely insightful digital markers. Focusing on Sanctioned Suicide, an online pro-choice suicide forum, this work derived 17 egocentric network features to capture dynamics of social interaction and engagement within this uniquely uncensored community. Using network data generated from over 3.2 million unique interactions of N = 192 individuals, n = 48 of which were determined to be highest risk users (HRUs), a machine learning classification model was trained, validated, and tested to predict HRU status. Model prediction dynamics were analyzed using introspection techniques to uncover patterns in feature influence and highlight social phenomena. The model achieved a test AUC = 0.73 ([0.61, 0.85], 95% CI), suggesting that network-based socio-behavioral patterns of online interaction can signal for heightened suicide risk. Transitivity, density, and in-degree centrality were among the most important features driving this performance. Moreover, predicted HRUs tended to be targets of social exchanges with lesser frequency and possessed egocentric networks with "small world" network properties. Through the implementation of an underutilized method on an unlikely data source, findings support future incorporation of network-based social interaction features in descriptive, predictive, and preventative STB research.

Suicide Behavior Among Indigenous and Non-Indigenous Living with HIV: A Cross-Sectional Study in Indonesia

Suicide remains a major public health problem, with nearly 1 million deaths per year. The number tends to increase over time and factors leading to suicide suicidal behaviors are complex. However, there is a paucity of evidence on suicidal behaviors and the associated factors among people living with HIV (PLWH) in Indonesia. Therefore, this study aimed to estimate the prevalence and associated factors of suicidal behavior between indigenous and non-indigenous living with HIV who were on Dolutegravir and Efavirenz therapies. The cross-sectional data were collected using questionnaires. Participants completed the Suicidal Behaviors Questionnaire-Revised (SBQ-R), Depression Anxiety Stress Scale-42 (DASS-42), HIV Stigma-Sowell Scale, and demographic information questions. The outcome was low and high self-reported suicidal behaviors, while logistic regression analyses were used to estimate adjusted odds ratios (aOR) for associated factors of high suicidal behaviors. A total of 200 PLWH were enrolled and 8.5% of the participants had high levels of suicidal behaviors. The majority of participants were Efavirenz users (84.0%), and Papuans as Indigenous (75.5%). More than half had a high school education (60.5%), were female (58%), married (54%), and unpaid (59%). The multiple logistic regression model showed that indigenous (aOR = 0.122; 95% CI = 0.029-0.514), and people who had children (aOR = 0.221; 95% CI = 0.051-0.957) were more likely to have low suicidal behaviors. Participants who were aged 18-27 years (aOR = 5.894; 95% CI = 1.336-30.579), had high self-blame (aOR = 1.342; 95% CI) = 1.004-1.792), and detectable HIV viral load (aOR = 6.177; 95%CI = 1.118-34.119) had high suicidal behavior. This study identified the risk of suicidality among PLWHs is high and routine suicide assessment is prioritized. The findings are also useful for intervention design and the development of clinical practice guidelines to manage the well-being of PLWH such as using digital intervention to cope with hindrances.

Assessing the effectiveness of internet-based interventions for mental health outcomes: an umbrella review

Internet-based interventions (IBIs) for behavioural health have been prevalent for over two decades, and a growing proportion of individuals with mental health concerns prefer these emerging digital alternatives. However, the effectiveness and acceptability of IBIs for various mental health disorders continue to be subject to scholarly debate. We performed an umbrella review of meta-analyses (MAs), conducting literature searches in PubMed, Web of Science, Embase, Cochrane and Ovid Medline from their inception to 17 January 2023. A total of 87 MAs, reporting on 1683 randomised controlled trials and 295 589 patients, were included. The results indicated that IBIs had a moderate effect on anxiety disorder (standardised mean difference (SMD)=0.53, 95% CI 0.44 to 0.62) and post-traumatic stress disorder (PTSD) (SMD=0.63, 95% CI 0.38 to 0.89). In contrast, the efficacy on depression (SMD=0.45, 95% CI 0.39 to 0.52), addiction (SMD=0.23, 95% CI 0.16 to 0.31), suicidal ideation (SMD=0.23, 95% CI 0.16 to 0.30), stress (SMD=0.41, 95% CI 0.33 to 0.48) and obsessive-compulsive disorder (SMD=0.47, 95% CI 0.22 to 0.73) was relatively small. However, no significant effects were observed for personality disorders (SMD=0.07, 95% CI -0.13 to 0.26). Our findings suggest a significant association between IBIs and improved mental health outcomes, with particular effectiveness noted in treating anxiety disorders and PTSD. However, it is noteworthy that the effectiveness of IBIs was impacted by high dropout rates during treatment. Furthermore, our results indicated that guided IBIs proved to be more effective than unguided ones, playing a positive role in reducing dropout rates and enhancing patient adherence rates. PROSPERO registration number: CRD42023417366.

Suicide Crisis Syndrome: A systematic review

BACKGROUND

The objective of this systematic review is to describe the scientific evidence for the Suicide Crisis Syndrome (SCS), a presuicidal cognitive and affective state consisting of five symptomatic dimensions: entrapment, affective disturbance, loss of cognitive control, hyperarousal, and social withdrawal. The aim of this article is to summarize the emerging literature on the SCS and to assess the extent to which a uniform syndrome can be assumed.

METHODS

A systematic literature search was conducted in three different databases (PubMed, PsycInfo, and Google Scholar) using the search terms "Suicide Crisis Inventory," "Suicide Crisis Syndrome," "Narrative Crisis Model of Suicide," and "Suicide Trigger State."

RESULTS

In total, 37 articles from 2010 to 2022 were identified by search criteria. Twenty-one articles published between 2017 and 2022 were included in the systematic review. All but three studies were conducted in the United States and examined clinical samples of adult high-risk psychiatric in- and outpatients. Sample sizes ranged from N = 170 to 4846. The findings confirm the unidimensional structure of the proposed disorder and support the predictive validity for short-term suicidal behavior above and beyond suicidal ideation.

CONCLUSION

Despite the promising predictive validity of the SCS, a precise prediction of future suicidal behavior remains difficult.

Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies

OBJECTIVE

Suicide is a complex and multifactorial public health problem. Understanding and addressing the various factors associated with suicide is crucial for prevention and intervention efforts. Machine learning (ML) could enhance the prediction of suicide attempts.

METHOD

A systematic review was performed using PubMed, Scopus, Web of Science and SID databases. We aim to evaluate the performance of ML algorithms and summarize their effects, gather relevant and reliable information to synthesize existing evidence, identify knowledge gaps, and provide a comprehensive list of the suicide risk factors using mixed method approach.

RESULTS

Forty-one studies published between 2011 and 2022, which matched inclusion criteria, were chosen as suitable. We included studies aimed at predicting the suicide risk by machine learning algorithms except natural language processing (NLP) and image processing. The neural network (NN) algorithm exhibited the lowest accuracy at 0.70, whereas the random forest demonstrated the highest accuracy, reaching 0.94. The study assessed the COX and random forest models and observed a minimum area under the curve (AUC) value of 0.54. In contrast, the XGBoost classifier yielded the highest AUC value, reaching 0.97. These specific AUC values emphasize the algorithm-specific performance in capturing the trade-off between sensitivity and specificity for suicide risk prediction. Furthermore, our investigation identified several common suicide risk factors, including age, gender, substance abuse, depression, anxiety, alcohol consumption, marital status, income, education, and occupation. This comprehensive analysis contributes valuable insights into the multifaceted nature of suicide risk, providing a foundation for targeted preventive strategies and intervention efforts.

CONCLUSIONS

The effectiveness of ML algorithms and their application in predicting suicide risk has been controversial. There is a need for more studies on these algorithms in clinical settings, and the related ethical concerns require further clarification.

Evaluating potential effects of distress symptoms' interventions on suicidality: Analyses of in silico scenarios

BACKGROUND

Complexity science perspectives like the network approach to psychopathology have emerged as a prominent methodological toolkit to generate novel hypotheses on complex etiologies surrounding various mental health problems and inform intervention targets. Such approach may be pivotal in advancing early intervention of suicidality among the younger generation (10-35 year-olds), the increasing burden of which needs to be reversed within a limited window of opportunity to avoid massive long-term repercussions. However, the network approach currently lends limited insight into the potential extent of proposed intervention targets' effectiveness, particularly for target outcomes in comorbid conditions.

METHODS

This paper proposes an in silico (i.e., computer-simulated) intervention approach that maps symptoms' complex interactions onto dynamic processes and analyzes their evolution. The proposed methodology is applied to investigate potential effects of changes in 1968 community-dwelling individuals' distress symptoms on their suicidal ideation. Analyses on specific subgroups were conducted. Results were also compared with centrality indices employed in typical network analyses.

RESULTS

Findings concur with symptom networks' centrality indices in suggesting that timely deactivating hopelessness among distressed individuals may be instrumental in preventing distress to develop into suicidal ideation. Additionally, however, they depict nuances beyond those provided by centrality indices, e.g., among young adults, reducing nervousness and tension may have similar effectiveness as deactivating hopeless in reducing suicidal ideation.

LIMITATIONS

Caution is warranted when generalizing findings here to the general population.

CONCLUSION

The proposed methodology may help facilitate timely agenda-setting in population mental health measures, and may also be augmented for future co-creation projects.

Social-ecological perspective on the suicidal behaviour factors of early adolescents in China: a network analysis

Background

In early adolescence, youth are highly prone to suicidal behaviours. Identifying modifiable risk factors during this critical phase is a priority to inform effective suicide prevention strategies.

Aims

To explore the risk and protective factors of suicidal behaviours (ie, suicidal ideation, plans and attempts) in early adolescence in China using a social-ecological perspective.

Methods

Using data from the cross-sectional project 'Healthy and Risky Behaviours Among Middle School Students in Anhui Province, China', stratified random cluster sampling was used to select 5724 middle school students who had completed self-report questionnaires in November 2020. Network analysis was employed to examine the correlates of suicidal ideation, plans and attempts at four levels, namely individual (sex, academic performance, serious physical illness/disability, history of self-harm, depression, impulsivity, sleep problems, resilience), family (family economic status, relationship with mother, relationship with father, family violence, childhood abuse, parental mental illness), school (relationship with teachers, relationship with classmates, school-bullying victimisation and perpetration) and social (social support, satisfaction with society).

Results

In total, 37.9%, 19.0% and 5.5% of the students reported suicidal ideation, plans and attempts in the past 6 months, respectively. The estimated network revealed that suicidal ideation, plans and attempts were collectively associated with a history of self-harm, sleep problems, childhood abuse, school bullying and victimisation. Centrality analysis indicated that the most influential nodes in the network were history of self-harm and childhood abuse. Notably, the network also showed unique correlates of suicidal ideation (sex, weight=0.60; impulsivity, weight=0.24; family violence, weight=0.17; relationship with teachers, weight=-0.03; school-bullying perpetration, weight=0.22), suicidal plans (social support, weight=-0.15) and suicidal attempts (relationship with mother, weight=-0.10; parental mental illness, weight=0.61).

Conclusions

This study identified the correlates of suicidal ideation, plans and attempts, and provided practical implications for suicide prevention for young adolescents in China. Firstly, this study highlighted the importance of joint interventions across multiple departments. Secondly, the common risk factors of suicidal ideation, plans and attempts were elucidated. Thirdly, this study proposed target interventions to address the unique influencing factors of suicidal ideation, plans and attempts.

Violent behavior and the network properties of psychopathological symptoms and real-life functioning in patients with schizophrenia

Objective

To assess the interplay among psychopathological symptoms and real-life functioning, and to further detect their influence with violent behavior in patient with schizophrenia.

Methods

A sample of 1,664 patients with post-violence assessments and their propensity score-matched controls without violence from a disease registration report system of community mental health service in Guangdong, China, were studied by network analysis. Ising-Model was used to estimate networks of psychopathological symptoms and real-life functioning. Then, we tested whether network properties indicated the patterns of interaction were different between cases and controls, and calculated centrality indices of each node to identify the central nodes. Sensitivity analysis was conducted to examine the difference of interaction patterns between pre-violence and post-violence assessments in violence cases.

Results

Some nodes in the same domain were highly positive interrelations, while psychopathological symptoms were negatively related to real-life functioning in all networks. Many symptom-symptom connections and symptom-functioning connections were disconnected after the violence. The network density decreased from 23.53% to 12.42% without statistical significance (p = 0.338). The network structure, the global network strength, and the global clustering coefficient decreased significantly after the violence (p < 0.001, p = 0.019, and p = 0.045, respectively). Real-life functioning had a higher node strength. The strength of sleeping, lack of spontaneity and flow of conversation, and preoccupation were decreased in post-violence network of patients.

Conclusion

The decreasing connectivity may indicate an increased risk of violence and early warning for detecting violence. Interventions and improving health state based on nodes with high strength might prevent violence in schizophrenia patients.

Tinnitus, Suicide, and Suicidal Ideation: A Scoping Review of Primary Research

Tinnitus (the perception of sound in the absence of any corresponding external source) is highly prevalent and can be distressing. There are unanswered questions about how tinnitus, suicidal thoughts, and suicidal behaviours co-occur and interact. To establish the extent of scientific literature, this scoping review catalogued primary reports addressing the associations between tinnitus, suicidal ideation, attempted suicide, and death by suicide. We searched OvidSP, Medline, EMBASE, PsycINFO, CINAHL, Google Scholar, EThoS, and ProQuest for all studies and case reports on ideation and/or attempted and/or completed suicide in the context of tinnitus. Twenty-three studies were included, and data were charted according to study type. Several epidemiological and other observational studies gave evidence of risk factors and an association between suicidal ideation, suicidal behaviour, and tinnitus. However, there was no evidence of the direction of causality. Qualitative studies are indicated to explore the patient's experience and understand the dynamics of any interaction between tinnitus and suicidal thoughts and behaviours. A theory-informed model of tinnitus and suicide needs to be developed to inform the development of interventions and how tinnitus patients are supported clinically.

Predicting suicide attempts among Norwegian adolescents without using suicide-related items: a machine learning approach

Introduction

Research on the classification models of suicide attempts has predominantly depended on the collection of sensitive data related to suicide. Gathering this type of information at the population level can be challenging, especially when it pertains to adolescents. We addressed two main objectives: (1) the feasibility of classifying adolescents at high risk of attempting suicide without relying on specific suicide-related survey items such as history of suicide attempts, suicide plan, or suicide ideation, and (2) identifying the most important predictors of suicide attempts among adolescents.

Methods

Nationwide survey data from 173,664 Norwegian adolescents (ages 13-18) were utilized to train a binary classification model, using 169 questionnaire items. The Extreme Gradient Boosting (XGBoost) algorithm was fine-tuned to classify adolescent suicide attempts, and the most important predictors were identified.

Results

XGBoost achieved a sensitivity of 77% with a specificity of 90%, and an AUC of 92.1% and an AUPRC of 47.1%. A coherent set of predictors in the domains of internalizing problems, substance use, interpersonal relationships, and victimization were pinpointed as the most important items related to recent suicide attempts.

Conclusion

This study underscores the potential of machine learning for screening adolescent suicide attempts on a population scale without requiring sensitive suicide-related survey items. Future research investigating the etiology of suicidal behavior may direct particular attention to internalizing problems, interpersonal relationships, victimization, and substance use.

A network approach to understand co-occurrence and relative importance of different reasons for suicide: a territory-wide study using 2002-2019 Hong Kong Coroner's Court reports

Background

Suicide is a complex and multifaceted issue, and suicidal behaviors are often driven by multiple, interacting factors. It has been challenging to identify reasons for suicide using existing scientific methodologies. This study aims to identify critical reasons for suicide and suicidal behaviors through the application of novel network science methods.

Methods

Based on cases investigated by the Hong Kong Coroner's Court from 2002 to 2019, we modelled identified reasons for 13,001 suicide cases as a co-occurrence network, and calculated each reason's eigencentrality to determine their respective relative importance. We then analyzed the temporal and demographic changes in the structure and eigencentrality of the network. We further conducted simulation studies based on the United Nations population projection to assess potential burden of different reasons for suicide on the population in the coming years.

Findings

School-related issues had the highest eigencentrality (eigencentrality = 0.49) for individuals younger than 20 years of age. Financial issues were crucial for adults aged 20-59 years, but their importance differed between males (eigencentrality = 0.51) and females (eigencentrality = 0.14). Physical illness (eigencentrality = 0.80) was the core concern for adults over 60 years. Across the Hong Kong population, the reasons for suicide appear to have shifted from financial issues in the early 2000s (eigencentrality = 0.46) to issues related to physical illnesses since 2011 (eigencentrality = 0.58). Simulation findings indicate that, by 2050, most suicides in Hong Kong will be due to physical illness-related issues (eigencentrality = 0.69) due to the rapidly aging population.

Interpretation

There have been important sex and age differences over time, in reasons for suicide. Given the projected increasing age of the Hong Kong population over the next decades, older adults with physical illnesses appear to be the highest contributors to suicide cases in the overall population. This novel network analysis approach provides important data-driven information upon which to base effective proactive public health suicide prevention strategies and interventions.

Funding

Hong Kong Jockey Club Charities Trust, Collaborative Research Fund (C7151-20G), and General Research Fund (17606521).

Prevalence and correlates of suicidal behaviours in a representative epidemiological youth sample in Hong Kong: the significance of suicide-related rumination, family functioning, and ongoing population-level stressors

BACKGROUND

Young people are most vulnerable to suicidal behaviours but least likely to seek help. A more elaborate study of the intrinsic and extrinsic correlates of suicidal ideation and behaviours particularly amid ongoing population-level stressors and the identification of less stigmatising markers in representative youth populations is essential.

METHODS

Participants (n = 2540, aged 15-25) were consecutively recruited from an ongoing large-scale household-based epidemiological youth mental health study in Hong Kong between September 2019 and 2021. Lifetime and 12-month prevalence of suicidal ideation, plan, and attempt were assessed, alongside suicide-related rumination, hopelessness and neuroticism, personal and population-level stressors, family functioning, cognitive ability, lifetime non-suicidal self-harm, 12-month major depressive disorder (MDD), and alcohol use.

RESULTS

The 12-month prevalence of suicidal ideation, ideation-only (no plan or attempt), plan, and attempt was 20.0, 15.4, 4.6, and 1.3%, respectively. Importantly, multivariable logistic regression findings revealed that suicide-related rumination was the only factor associated with all four suicidal outcomes (all p < 0.01). Among those with suicidal ideation (two-stage approach), intrinsic factors, including suicide-related rumination, poorer cognitive ability, and 12-month MDE, were specifically associated with suicide plan, while extrinsic factors, including coronavirus disease 2019 (COVID-19) stressors, poorer family functioning, and personal life stressors, as well as non-suicidal self-harm, were specifically associated with suicide attempt.

CONCLUSIONS

Suicide-related rumination, population-level COVID-19 stressors, and poorer family functioning may be important less-stigmatising markers for youth suicidal risks. The respective roles played by not only intrinsic but also extrinsic factors in suicide plan and attempt using a two-stage approach should be considered in future preventative intervention work.

The role of anxiety and depression in suicidal thoughts for autistic and non-autistic people: A theory-driven network analysis

BACKGROUND

Autistic adults experience more frequent suicidal thoughts and mental health difficulties than non-autistic adults, but research has yet to explain how these experiences are connected. This study explored how anxiety and depression contribute to suicidal thoughts according to the Interpersonal Theory of Suicide for autistic and non-autistic adults.

METHODS

Participants (autistic adults n = 463, 61% female; non-autistic n = 342, 64% female) completed online measures of anxiety, depression, thwarted belonging, and perceived burdensomeness. Network analysis explored whether: (i) being autistic is a risk marker for suicide; and (ii) pathways to suicidal thoughts are consistent for autistic and non-autistic adults.

RESULTS

Being autistic connected closely with feeling like an outsider, anxiety, and movement, which connected to suicidal thoughts through somatic experiences, low mood, and burdensomeness. Networks were largely consistent for autistic and non-autistic people, but connections from mood symptoms to somatic and thwarted belonging experiences were absent for autistic adults.

CONCLUSION

Autistic people experience more life stressors than non-autistic people leading to reduced coping, low mood, and suicidal thoughts. Promoting belonging, reducing anxiety, and understanding the role of movement could inform suicide prevention for autistic people. Research should accurately capture autistic lived experience when modeling suicide to ensure suicide prevention meets autistic needs.

The use of advanced technology and statistical methods to predict and prevent suicide

In the past decade, two themes have emerged across suicide research. First, according to meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker than would be expected for the size of the field. Second, review and commentary papers propose that technological and statistical methods (such as smartphones, wearables, digital phenotyping and machine learning) might become solutions to this problem. In this Review, we aim to strike a balance between the pessimistic picture presented by these meta-analyses and the optimistic picture presented by review and commentary papers about the promise of advanced technological and statistical methods to improve the ability to understand, predict and prevent suicide. We divide our discussion into two broad categories. First, we discuss the research aimed at assessment, with the goal of better understanding or more accurately predicting suicidal thoughts and behaviours. Second, we discuss the literature that focuses on prevention of suicidal thoughts and behaviours. Ecological momentary assessment, wearables and other technological and statistical advances hold great promise for predicting and preventing suicide, but there is much yet to do.

Bayesian network analysis of antidepressant treatment trajectories

It is currently difficult to successfully choose the correct type of antidepressant for individual patients. To discover patterns in patient characteristics, treatment choices and outcomes, we performed retrospective Bayesian network analysis combined with natural language processing (NLP). This study was conducted at two mental healthcare facilities in the Netherlands. Adult patients admitted and treated with antidepressants between 2014 and 2020 were included. Outcome measures were antidepressant continuation, prescription duration and four treatment outcome topics: core complaints, social functioning, general well-being and patient experience, extracted through NLP of clinical notes. Combined with patient and treatment characteristics, Bayesian networks were constructed at both facilities and compared. Antidepressant choices were continued in 66% and 89% of antidepressant trajectories. Score-based network analysis revealed 28 dependencies between treatment choices, patient characteristics and outcomes. Treatment outcomes and prescription duration were tightly intertwined and interacted with antipsychotics and benzodiazepine co-medication. Tricyclic antidepressant prescription and depressive disorder were important predictors for antidepressant continuation. We show a feasible way of pattern discovery in psychiatry data, through combining network analysis with NLP. Further research should explore the found patterns in patient characteristics, treatment choices and outcomes prospectively, and the possibility of translating these into a tool for clinical decision support.

Mapping the timescale of suicidal thinking

This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h.

A cultural-ecosocial systems view for psychiatry

While contemporary psychiatry seeks the mechanisms of mental disorders in neurobiology, mental health problems clearly depend on developmental processes of learning and adaptation through ongoing interactions with the social environment. Symptoms or disorders emerge in specific social contexts and involve predicaments that cannot be fully characterized in terms of brain function but require a larger social-ecological view. Causal processes that result in mental health problems can begin anywhere within the extended system of body-person-environment. In particular, individuals' narrative self-construal, culturally mediated interpretations of symptoms and coping strategies as well as the responses of others in the social world contribute to the mechanisms of mental disorders, illness experience, and recovery. In this paper, we outline the conceptual basis and practical implications of a hierarchical ecosocial systems view for an integrative approach to psychiatric theory and practice. The cultural-ecosocial systems view we propose understands mind, brain and person as situated in the social world and as constituted by cultural and self-reflexive processes. This view can be incorporated into a pragmatic approach to clinical assessment and case formulation that characterizes mechanisms of pathology and identifies targets for intervention.

A Longitudinal Network Analysis of the Interactions of Risk and Protective Factors for Suicidal Potential in Early Adolescents

Few studies have applied the "ideation-to-action" theories and the buffering hypothesis of resilience to suicide in early adolescents, and existing research is primarily cross-sectional. This study examined the interactions between risk factors (i.e., thwarted belongingness, perceived burdensomeness, and hopelessness), protective factors (i.e., resilience, self-efficacy, and subjective happiness), and suicidal potential (i.e., family distress, anxious-impulsive depression, and suicidal ideation or acts) in early adolescents. The participants (N = 1615; 55.6% females; M age = 10.93, SD age = 1.14, range: 9-15) who were recruited from four primary and four secondary schools in Hong Kong completed the survey in 2020 and 2021. The contemporaneous networks suggested that perceived burdensomeness and hopelessness were positively associated with suicidal potential. Protective factors were negatively associated with risk factors studied and suicidal potential. The node with the greatest centrality strength was anxious-impulsive depression. The nodes most likely to connect with other constructs were self-efficacy and hopelessness. A temporal network suggested the predictive effect of hopelessness and the protective effect of subjective happiness on future suicidal ideation or acts. Moreover, self-efficacy was found to buffer the impact of hopelessness on future suicidal ideation or acts. These findings highlighted the contribution of hopelessness to suicidal potential among early adolescents and the buffering effects of subjective happiness and self-efficacy.

Investigating the relationship between bullying involvement and self-harmful thoughts and behaviour in young people: A systematic review

BACKGROUND

There is a complex and inconsistent relationship between bullying involvement and self-harmful thoughts and behaviour (SHTB) in young people. This novel systematic review aims to establish key interacting, moderating and mediating variables associated with SHTB in young people involved in bullying.

METHODS

The systematic review was registered with PROSPERO: CRD42020192023. A search was conducted (until February 2021) across databases: PubMed/MEDLINE, EMBASE, PsycINFO (Ovid), Cochrane Library, Scopus (Elsevier), Web of Science, ERIC and CINAHL (EBSCOhost). Observational studies containing quantitative primary or secondary data analyses were included in the review, on the basis that they examined interactions, moderators, or mediators between bullying involvement and SHTB in young people. Versions of the Newcastle-Ottawa Scale were used to assess risk of bias in the included studies.

RESULTS

A total of 57 studies were included. Overall, 3 studies identified interactions, 25 studies identified moderators and 21 studies identified mediators. 9 studies identified moderator-mediators. The findings were categorised as either self-harmful thoughts or self-harmful behaviours and synthesised under the following themes: socio-demographic; depression; parental; personality/psychological; and social/environmental.

LIMITATIONS

This review uncovered significant heterogeneity and a paucity of replicated studies in the field, therefore, tentative conclusions have been drawn.

CONCLUSIONS

This comprehensive review highlights the key role of depression as a mediator between traditional/cyber victimisation and SHTB in young people. The moderating effects of gender on mediation models investigating the role of depression suggest the possibility that females involved in bullying may be at increased suicide risk.

Suicidality in psychiatric emergency department situations during the first and the second wave of COVID-19 pandemic

Psychiatric patients are prone to mental health deterioration during the Covid-19 pandemic. Little is known about suicidality in psychiatric patients during the Covid-19 pandemic. This study is a retrospective chart review of psychiatric emergency department (pED) presentations with present or absent suicidality (5634 pED attendances, 4110 patients) in an academic pED in Berlin, Germany. Poisson regression analysis was performed on the effect of Covid-19 period on suicidality (suicidal ideation (SI), suicide plans (SP) or suicide attempt (SA)) during the first (3/2/2020-5/24/2020 "first-wave") and second (9/15/2020-3/1/2021 "second-wave") wave of the Covid-19 pandemic compared to the same periods one year earlier. During the first-wave the number of pED visits per person with SI, SP and SA was higher compared to one year earlier (SI RR = 1.614; p = 0.016; SP RR = 2.900; p = 0.004; SA RR = 9.862; p = 0.003). SI and SP were predicted by interaction between substance use disorder (SUD) and second-wave (SI RR = 1.305, p = 0.043; SP RR = 1.645, p = 0.018), SA was predicted by interaction between borderline personality disorder (BPD) and second-wave (RR = 7.128; p = 0.012). Suicidality increased during the first-wave of Covid-19 pandemic in our sample. In the second-wave this was found in patients with SUD and BPD. These patients may be at particular risk of suicidality during the Covid-19 pandemic.

Examining the Interrelationships Among Suicide Cognitions, Suicidal Ideation, and Theoretically Derived Protective Factors

INTRODUCTION

Several protective factors for mitigating suicidal ideation (SI) such as positive affect, reasons for living, purpose in life, meaning in life, gratitude, grit, optimism, social support, and hope have been identified and received empirical support. However, few studies have examined the interrelationships of these protective factors and the identification of protective factors most closely linked to lower levels of SI may be useful for both theory-building initiatives and improvement of suicide-specific interventions. Network analysis offers an approach for testing the relation among these constructs, SI, and suicide risk factors.

METHODS

A sample N = 557 undergraduate students oversampled for lifetime SI completed a cross-sectional, online survey. The data was used to estimate an undirected, cross-sectional network of the aforementioned protective factors.

RESULTS

The resulting inferred network implicates strong negative influence of suicide cognitions, but not recent SI, and the strong positive influence of presence of meaning in life, trait hope, and low negative affect.

CONCLUSIONS

Implications for dimensionality of SI versus suicide cognitions, targeting presence of meaning in life, trait hope, and negative affect in treatment, and cross-cultural variations in reasons for living are discussed. The study is limited by the cross-sectional and convenience sampling methodology.HighlightsProtective factors may have less direct influence on suicidal ideationSuicide cognitions and the suicidal mode may be of phenomenological importancePresence of meaning and trait hope may be primary targets for suicide interventions.

Rethinking minority stress: A social safety perspective on the health effects of stigma in sexually-diverse and gender-diverse populations

For over two decades, the minority stress model has guided research on the health of sexually-diverse individuals (those who are not exclusively heterosexual) and gender-diverse individuals (those whose gender identity/expression differs from their birth-assigned sex/gender). According to this model, the cumulative stress caused by stigma and social marginalization fosters stress-related health problems. Yet studies linking minority stress to physical health outcomes have yielded mixed results, suggesting that something is missing from our understanding of stigma and health. Social safety may be the missing piece. Social safety refers to reliable social connection, inclusion, and protection, which are core human needs that are imperiled by stigma. The absence of social safety is just as health-consequential for stigmatized individuals as the presence of minority stress, because the chronic threat-vigilance fostered by insufficient safety has negative long-term effects on cognitive, emotional, and immunological functioning, even when exposure to minority stress is low. We argue that insufficient social safety is a primary cause of stigma-related health disparities and a key target for intervention.

The interpersonal-psychological theory of suicide and the role of psychological pain during the COVID-19 pandemic: A network analysis

INTRODUCTION

Among the most investigated theories explaining suicidal behavior there are the interpersonal-psychological theory of suicide (IPTS) by Thomas E. Joiner and the one focused on the construct of psychological pain (or psychache, or mental pain).

OBJECTIVE

Since it remains unclear whether these two different theories correlate with each other in the explanation of suicidal risk, we used a network analysis approach to investigate the complex interplay between both IPTS and psychological pain theories and history of suicidal planning and/or suicide attempt (SP/SA).

METHODS

A sample of 1,586 university students from various Italian universities was recruited between April 24th, 2020 and February 23rd, 2021, hence during the COVID-19 pandemic. To be included subjects should have been university students and aged between 18 and 35 years old.

RESULTS

Within a network that included the core factors from both models (IPTS and psychological pain), higher fearlessness about death (Acquired Capability for Suicide Scale-Fearlessness About Death, ACSS-FAD) and higher psychological pain (Psychache Scale) were the variables most strongly associated with history of SP/SA.

CONCLUSIONS

Considering a large number of variables, history of SP/SA was explained in particular by fearlessness about death and psychological pain in university students. Hence these aspects should be targeted in the treatment for suicide prevention.

Risk and Protective Factors in Adolescent Suicidal Behaviour: A Network Analysis

Given that death by suicide continues to rank among the top three causes of death during adolescence, new psychological models may contribute critical insight towards understanding the complex interactions between risk and protective factors in suicidal behaviour. The main objective of this study was to analyse the psychological network structure of suicidal behaviour and putative risk and protective factors in school-aged adolescents. Methods: Stratified random cluster sampling was performed. The final sample comprised 1790 students (53.7% female, M = 15.7 years, SD = 1.26). Instruments were administered to assess suicidal behaviour, emotional and behavioural difficulties, prosocial behaviour, subjective well-being, self-esteem, depressive symptomatology, academic performance, socio-economic status, school engagement, bullying, and cyberbullying. Results: In the estimated psychological network, the node with the highest strength was depressive symptomatology, and that with the highest expected influence value was bullying. Suicidal behaviour was positively connected to symptoms of depression and behavioural problems. In addition, suicidal behaviour was negatively connected to self-esteem and personal well-being. The results of the stability analysis indicated that the network was accurately estimated. Conclusions: Suicidal behaviour can be conceptualised as a dynamic, complex system of cognitive, emotional, and affective characteristics. New psychological models allow us to analyse and understand human behaviour from a new perspective, suggesting new forms of conceptualisation, evaluation, intervention, and prevention.

Identifying Central Symptoms and Bridge Pathways Between Autism Spectrum Disorder Traits and Suicidality Within an Active Duty Sample

OBJECTIVE

This study employed network analysis to characterize central autism spectrum disorder (ASD) traits and suicide symptoms within an active duty military sample as well as to identify symptoms that may bridge between ASD traits and suicidality (i.e., suicidal ideation and behaviors).

METHOD

Participants were active duty U.S. military service members (N = 287). Autism spectrum traits, suicidality, depression, and suicide related constructs were assessed online via self-report.

RESULTS

Within the combined ASD trait-suicidality network, suicide rumination, suicide behaviors, and depression had the highest strength centrality. The most central bridge symptoms between ASD and suicidality were thwarted belongingness, social skills deficits, and depressive symptoms.

CONCLUSIONS

Social skills deficits and thwarted belongingness may function as a meaningful bridge between ASD symptoms and suicidality within active duty members. Individuals with ASD symptoms who additionally present with high levels of thwarted belongingness and/or considerable social skills deficits may be at increased risk for suicidality.HIGHLIGHTSWithin an ASD-suicidality network, social skills deficits, low belonging, and depression had the greatest bridge strength.Although low belonging emerged as a bridge symptom, perceived burdensomeness did not.Suicide rumination, suicide behaviors, and depression were the most central symptom in an ASD-suicidality network.Symptoms related to social skills deficits may connect ASD traits and suicidality.

A network perspective on suicidal behavior: Understanding suicidality as a complex system

BACKGROUND

Suicidal behavior is the result of complex interactions between many different factors that change over time. A network perspective may improve our understanding of these complex dynamics. Within the network perspective, psychopathology is considered to be a consequence of symptoms that directly interact with one another in a network structure. To view suicidal behavior as the result of such a complex system is a good starting point to facilitate moving away from traditional linear thinking.

OBJECTIVE

To review the existing paradigms and theories and their application to suicidal behavior.

METHODS

In the first part of this paper, we introduce the relevant concepts within network analysis such as network density and centrality. Where possible, we refer to studies that have applied these concepts within the field of suicide prevention. In the second part, we move one step further, by understanding the network perspective as an initial step toward complex system theory. The latter is a branch of science that models interacting variables in order to understand the dynamics of complex systems, such as tipping points and hysteresis.

RESULTS

Few studies have applied network analysis to study suicidal behavior. The studies that do highlight the complexity of suicidality. Complexity science offers potential useful concepts such as alternative stable states and resilience to study psychopathology and suicidal behavior, as demonstrated within the field of depression. To date, one innovative study has applied concepts from complexity science to better understand suicidal behavior. Complexity science and its application to human behavior are in its infancy, and it requires more collaboration between complexity scientists and behavioral scientists.

CONCLUSIONS

Clinicians and scientists are increasingly conceptualizing suicidal behavior as the result of the complex interaction between many different biological, social, and psychological risk and protective factors. Novel statistical techniques such as network analysis can help the field to better understand this complexity. The application of concepts from complexity science to the field of psychopathology and suicide research offers exciting and promising possibilities for our understanding and prevention of suicide.