Modelling suicide ideation from beep to beep: Application of network analysis to ecological momentary assessment data

Temporal prediction of suicidal ideation in an ecological momentary assessment study with recurrent neural networks

INTRODUCTION

Ecological Momentary Assessment (EMA) holds promise for providing insights into daily life experiences when studying mental health phenomena. However, commonly used mixed-effects linear statistical models do not fully utilize the richness of the ultidimensional time-varying data that EMA yields. Recurrent Neural Networks (RNNs) provide an alternative data analytic method to leverage more information and potentially improve prediction, particularly for non-normally distributed outcomes.

METHODS

As part of a broader research study of suicidal thoughts and behavior in people with borderline personality disorder (BPD), eighty-four participants engaged in EMA data collection over one week, answering questions multiple times each day about suicidal ideation (SI), stressful events, coping strategy use, and affect. RNNs and mixed-effects linear regression models (MEMs) were trained and used to predict SI. Root mean squared error (RMSE), mean absolute percent error (MAPE), and a pseudo-R2 accuracy metric were used to compare SI prediction accuracy between the two modeling methods.

RESULTS

RNNs had superior accuracy metrics (full model: RMSE = 3.41, MAPE = 42 %, pseudo-R2 = 26 %) compared with MEMs (full model: RMSE = 3.84, MAPE = 56 %, pseudo-R2 = 16 %). Importantly, RNNs showed significantly more accurate prediction at higher values of SI. Additionally, RNNs predicted, with significantly higher accuracy, the SI scores of participants with depression diagnoses and of participants with higher depression scores at baseline.

CONCLUSION

In this EMA study with a moderately sized sample, RNNs were better able to learn and predict daily SI compared with mixed-effects models. RNNs should be considered as an option for EMA analysis.

Experience sampling of suicidality, religiosity and spirituality in depression: Network analyses using dynamic time warping

BACKGROUND

Suicidality is a clinically important and multifaceted phenomenon, frequently present in depressed subjects. Religiosity and spirituality (R/S) can have an attenuating as well as a reinforcing effect on suicidality.

METHODS

From two Dutch mental health care settings, a sample of 31 depressed and in- and outpatients with suicidal ideation, self-identifying as being religious or spiritual, was selected by convenience sampling. Using an experience sampling method (ESM) mobile application, during six days (mean of 42 assessments per subject), the association between symptoms of depression, suicidality, and specific positive-supportive affective R/S and positive psychology variables. For 28 participants symptom network plots on a group level, and on an individual level, were analyzed using dynamic time warping (DTW).

RESULTS

Participants were on average 35.7 years old, and 65 % were women. In the group-level undirected network, R/S variables were linked to positive psychology variables via a bridge function of inner peace. Changes in the experience of inner peace and enjoying a physical activity preceded changes of several other symptoms. A network dynamic appeared with a dense cluster of 'positive psychology' items.

LIMITATIONS

Only a limited number of R/S variables were included.

CONCLUSION

The results of this study suggest that religiosity and spirituality function as meaningful factors in depression and suicidality in religiously or spiritually engaged persons. Experienced inner peace has a positive association with reasons to live. Experience sampling method data can be effectively analyzed using dynamic time warping. Exploring individual religious or spiritual engagement can prove important in treating suicidality and depression.

Heterogeneity in suicide risk: Evidence from personalized dynamic models

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

A longitudinal network analysis of suicide risk factors among service members and veterans sampled for suicidal ideation or attempt

BACKGROUND

Suicidal thoughts and behaviors are elevated among active-duty service members (ADSM) and veterans compared to the general population. Hence, it is a priority to examine maintenance factors underlying suicidal ideation among ADSM and veterans to develop effective, targeted interventions. In particular, interpersonal risk factors, hopelessness, and overarousal have been robustly connected to suicidal ideation and intent.

METHODS

To identify the suicidal ideation risk factors that are most relevant, we employed network analysis to examine between-subjects (cross-sectional), contemporaneous (within seconds), and temporal (across four hours) group-level networks of suicidal ideation and related risk factors in a sample of ADSM and veterans (participant n = 92, observations n = 10 650). Participants completed ecological momentary assessment (EMA) surveys four times a day for 30 days, where they answered questions related to suicidal ideation, interpersonal risk factors, hopelessness, and overarousal.

RESULTS

The between-subjects and contemporaneous networks identified agitation, not feeling close to others, and ineffectiveness as the most central symptoms. The temporal network revealed that feeling ineffective was most likely to influence other symptoms in the network over time.

CONCLUSION

Our findings suggest that ineffectiveness, low belongingness, and agitation are important drivers of moment-to-moment and longitudinal relations between risk factors for suicidal ideation in ADSM and veterans. Targeting these symptoms may disrupt suicidal ideation.

Centrality measures in psychological networks: A simulation study on identifying effective treatment targets

The network theory of psychopathology suggests that symptoms in a disorder form a network and that identifying central symptoms within this network might be important for an effective and personalized treatment. However, recent evidence has been inconclusive. We analyzed contemporaneous idiographic networks of depression and anxiety symptoms. Two approaches were compared: a cascade-based attack where symptoms were deactivated in decreasing centrality order, and a normal attack where symptoms were deactivated based on original centrality estimates. Results showed that centrality measures significantly affected the attack's magnitude, particularly the number of components and average path length in both normal and cascade attacks. Degree centrality consistently had the highest impact on the network properties. This study emphasizes the importance of considering centrality measures when identifying treatment targets in psychological networks. Further research is needed to better understand the causal relationships and predictive capabilities of centrality measures in personalized treatments for mental disorders.

Parenthood, spatial temporal environmental exposure, and leisure-time physical activity participation: Evidence from a micro-timescale retrospective longitudinal study

Parents with dependent children are at a high risk of physical inactivity. While previous studies have mostly focused on how parents' time constraints and changing social network may inhibit leisure time physical activity (LTPA) over the long-term, less is known about the integrated effects of parenting and spatial-temporal environmental exposure on the execution of LTPA during certain episodes of a day. By adopting an integrated social-spatiotemporal-environmental model (ST-ISEM) based on micro-timescale retrospective longitudinal analysis, we examine the association between LTPA participation and spatial-temporal environmental exposure at a micro-timescale, i.e., at the episode-level in working adults' workday, and specifically how parenting integrated with spatial-temporal environmental exposure can jointly influence episode-level LTPA participation. Using data from the day reconstruction method from 701 individuals in Shenzhen, China, we find that parenting may affect the participation of LTPA on workdays not only by shaping temporal environmental factors (time constraint path and social network path), but also by interacting with built environmental exposures (spatial path), both at the episode-level. This study contributes to the theorizing of an integrated social-environmental model for health and wellbeing by extending the ISEM from the life span to the micro-timescale and also by highlighting the importance of temporality in environmental exposure and health studies. It also contributes to the spatial temporal behavioral perspective of time geography literature by clarifying multiple pathways through which social and spatiotemporal environmental factors could interact and jointly affect health behaviors at a micro-timescale. This study contributes to the literature on parenting and LTPA decline by enriching and deepening the understanding of the time constraint and social network pathways through which parenting leads to LTPA change at the micro-timescale. While time constraints may decrease parents' LTPA at long-term, increasing physical activities related to childcare after work may strongly obstruct moderate-to-vigorous LTPA at a micro-timescale. This study also identifies a spatial pathway by which parenting hinders LTPA due to changing understanding and usage of urban spaces. This pathway warrants attention from social epidemiologists, health geographers, and urban planners since existing interventions promoting physical activity in urban spaces may be ineffective for parents.

Relations among symptoms of depression over time in at-risk youth

Depression consists of symptoms that may relate to each other in ways that go beyond simple co-occurrence. For example, some symptoms may precede and possibly contribute to the emergence of others. The present study examined several potential relations among the symptoms of depression. The overarching goals were to better understand how depression may unfold and to identify potential targets for intervention. The sample included 120 offspring of depressed parents. Youths' symptoms of depression were rated across 89 weeks. First, we investigated which symptoms preceded and potentially contributed to other symptoms 1 week later. This model revealed that sleep disturbance predicted the occurrence of other symptoms (e.g., sad mood, fatigue), and the occurrence of sad mood was predicted by other symptoms (e.g., worthlessness/guilt, psychomotor symptoms, sleep disturbance). Second, we investigated the within-person question of which symptoms tended to co-occur at the same time point. This model identified sad mood, irritability, and anhedonia as symptoms that tended to co-occur with each other and with many other depressive symptoms. Third, we investigated the between-person question of which symptoms tended to co-occur when averaged across time. This model identified worthlessness/guilt, fatigue, and anhedonia as symptoms strongly associated with other depressive symptoms across people irrespective of timing. Results indicate that the relations among the symptoms of depression vary, such that some symptoms preceded others by 1 week, some symptoms occurred at the same time, and other symptoms co-occurred in individuals. This more detailed view of the connections among depressive symptoms informs our understanding of depression as a dynamic set of unique indicators. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The use of psychological network analysis in informal dementia care: an empirical illustration

Objective: Theoretical models in informal dementia care have been developed to understand how risk and protective factors interact to cause caregiver's distress. The development of psychological network analysis provides a rich complement to our current models, as explores how different variables (or nodes) are associated using graph theories. Methods: The present study explored the use of network analysis using data from 125 informal caregivers of their partner with dementia (PwD). The included variables were recipient's dependency, self-efficacy, conflict within the family, dyadic adjustment, and caregiver's distress. Results: The analysis suggests a complex network of interacting variables. The core variable was not the caregiver's distress but rather their dyadic adjustment with their PwD. Variables were associated with caregiver distress through a large array of direct and indirect pathways and were associated with each other in the form of an asymmetric spider's web.Conclusion: The results show the complex interplay of variables in a psychological network. The central role of distress suggests a complex and dynamic role, notably through a bidirectional influence with quality of interactions. In the same way, quality of interactions appeared as one of the strongest nodes, its connectivity suggesting a crucial role to consider in our models and interventions.

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.

Preventing comorbidity between distress and suicidality: a network analysis

Suicidality among individuals between 10 and 35 years of age may be poised to exert massive burdens on society through decreased economic productivity and increased incidence of chronic physical conditions in the individuals' later years, thereby necessitating early prevention of suicide. While research suggests that the pathway to suicidality may begin from episodes of psychological distress, such pathway may involve complex interplays between intermediary psychiatric symptoms and external stimuli that are not easily delineated through conventional means. This study applies the network approach to psychopathology to elucidate this complexity. Comorbidity between psychological distress and suicidality in 1968 community-dwelling individuals is analyzed with regularized partial correlation networks to identify their bridge symptoms and links. Temporal relationships between symptoms are analyzed through temporal symptom network formed from 453 individuals who completed subsequent follow-up surveys. Network analysis shows that feelings of hopelessness and the presence of suicidal ideation are the strongest bridge symptoms in the comorbidity symptom network, and form the only prominent link that bridges psychological distress and suicidality. Effects of sleep troubles, anxiety, and poor social relationships on suicidal ideation appear to be mediated by hopelessness. The same observations hold among individuals with and without diagnoses of psychiatric disorders, as well as young people (10-24 year-olds) and young adults (25-35 year-olds). The edge between hopelessness and suicidal ideation remains the strongest bridge link after controlling for effects of symptoms from the previous time point. Findings here provide an evidence base for both professional training in caregiving professions as well as gatekeeper training in community members to emphasize more on how to effectively recognize hopelessness, and instill hope, in young people and young adults for various types of distress.

Auditing the research practices and statistical analyses of the group-level temporal network approach to psychological constructs: A systematic scoping review

Network analyses have become increasingly common within the field of psychology, and temporal network analyses in particular are quickly gaining traction, with many of the initial articles earning substantial interest. However, substantial heterogeneity exists within the study designs and methodology, rendering it difficult to form a comprehensive view of its application in psychology research. Since the field is quickly growing and since there have been many study-to-study variations in terms of choices made by researchers when collecting, processing, and analyzing data, we saw the need to audit this field and formulate a comprehensive view of current temporal network analyses. To systematically chart researchers' practices when conducting temporal network analyses, we reviewed articles conducting temporal network analyses on psychological variables (published until March 2021) in the framework of a scoping review. We identified 43 articles and present the detailed results of how researchers are currently conducting temporal network analyses. A commonality across results concerns the wide variety of data collection and analytical practices, along with a lack of consistency between articles about what is reported. We use these results, along with relevant literature from the fields of ecological momentary assessment and network analysis, to formulate recommendations on what type of data is suited for temporal network analyses as well as optimal methods to preprocess and analyze data. As the field is new, we also discuss key future steps to help usher the field's progress forward and offer a reporting checklist to help researchers navigate conducting and reporting temporal network analyses.

Risk factors of suicidal behaviors in a high-risk longitudinal veteran sample: A network analysis

INTRODUCTION

Suicide is a substantial public health burden, particularly among veterans. Risk factors have been delineated for suicide; however, the dynamic interrelations between risk factors have not been fully examined. Such research has the potential to elucidate processes that contribute to suicide risk between individuals with a past suicide attempt (attempters) and those without a past suicide attempt (nonattempters).

METHODS

In the current study, network analysis was used to compare networks between attempters and nonattempters in a high-risk veteran sample (N = 770; M_age  = 32.3 years, SD = 6.8; 326 with a past suicide attempt) who were followed over 1 year. Networks were estimated to examine (1) concurrent relations of suicide risk factors at baseline and (2) predictability of prospective suicidal behavior (SB).

RESULTS

There were no differences in the overall connectivity of attempter and nonattempter networks. Perceived burdensomeness and posttraumatic stress disorder (PTSD) symptoms were most central in the attempters' network, whereas PTSD symptoms and insomnia were most central in the nonattempters' network. The risk factors prospective SB in either network. However, attempters were more likely to engage in SB over the course of the study.

CONCLUSION

These findings highlight the difficulty in predicting who will attempt suicide.

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.

Psychosocial work environment as a dynamic network: a multi-wave cohort study

While characteristics of psychosocial work environment have traditionally been studied separately, we propose an alternative approach that treats psychosocial factors as interacting elements in networks where they all potentially affect each other. In this network analysis, we used data from a prospective occupational cohort including 10,892 participants (85% women; mean age 47 years) and repeated measurements of seven psychosocial work characteristics (job demands, job control, job uncertainty, team climate, effort-reward imbalance, procedural justice and interactional justice) assessed in 2000, 2004, 2008 and 2012. Results from multilevel longitudinal vector autoregressive models indicated that job demands as well as interactional and procedural justice were most broadly associated with the subsequent perceptions of the work-related psychosocial factors (high out-Strength), suggesting these factors might be potentially efficient targets of workplace interventions. The results also suggest that modifying almost any of the studied psychosocial factors might be relevant to subsequent perceptions of effort-reward imbalance and interactional justice at the workplace.

The interplay between psychopathological symptoms: transdiagnostic cross-lagged panel network model

BACKGROUND

Recent paradigm shifts suggest that psychopathology manifests through dynamic interactions between individual symptoms.

AIMS

To investigate the longitudinal relationships between symptoms in a transdiagnostic sample of patients with psychiatric disorders.

METHOD

A two-wave, cross-lagged panel network model of 15 nodes representing symptoms of depression, (social) anxiety and attenuated psychotic symptoms was estimated, using baseline and 1-year follow-up data of 222 individuals with psychiatric disorders. Centrality indices were calculated to determine important predictors and outcomes.

RESULTS

Our results demonstrated that the strongest relationships in the network were between (a) more suicidal ideation predicting more negative self-view, and (b) autoregressive relationships of social anxiety symptoms positively reinforcing themselves. Negative self-view was the most predictable node in the network as it had the highest 'in-expected influence' centrality, and may be an important transdiagnostic outcome symptom.

CONCLUSIONS

The results give insight into longitudinal interactions between symptoms, which interact in ways that do not adhere to broader diagnostic categories. Our results suggest that self-view can also be a transdiagnostic outcome of psychopathology rather than just a predictor, as is normally posited, and may especially have an important relationship with suicidal ideation. Overall, our study demonstrates the dynamic complexity of psychopathology, and further supports the importance of investigating symptom interactions of different psychopathological dimensions over time and across disorders.

The temporal relationships between defeat, entrapment and suicidal ideation: ecological momentary assessment study

BACKGROUND

Psychological models of suicidal experiences are largely based on cross-sectional or long-term prospective data with follow-up intervals typically greater than 1 year. Recent time-series analyses suggest that these models may not account for fluctuations in suicidal thinking that occur within a period of hours and/or days.

AIMS

We explored whether previously posited causal relationships between defeat, entrapment and suicidal ideation accounted for temporal associations between these experiences at small time intervals from 3 to 12 h.

METHOD

Participants (N = 51) completed an ecological momentary assessment (EMA) study, comprising repeated assessments at semi-random time points up to six times per day for 1 week, resulting in 1852 completed questionnaires. Multilevel vector autoregression was used to calculate temporal associations between variables at different time intervals (i.e. 3 to 12 h between measurements).

RESULTS

The results showed that entrapment severity was temporally associated with current and later suicidal ideation, consistently over these time intervals. Furthermore, entrapment had two-way temporal associations with defeat and suicidal ideation at time intervals of approximately 3 h. The residual and contemporaneous network revealed significant associations between all variables, of which the association between entrapment and defeat was the strongest.

CONCLUSIONS

Although entrapment is key in the pathways leading to suicidal ideation over time periods of months, our results suggest that entrapment may also account for the emergence of suicidal thoughts across time periods spanning a few hours.

Don't Miss the Moment: A Systematic Review of Ecological Momentary Assessment in Suicide Research

Suicide and suicide-related behaviors are prevalent yet notoriously difficult to predict. Specifically, short-term predictors and correlates of suicide risk remain largely unknown. Ecological momentary assessment (EMA) may be used to assess how suicidal thoughts and behaviors (STBs) unfold in real-world contexts. We conducted a systematic literature review of EMA studies in suicide research to assess (1) how EMA has been utilized in the study of STBs (i.e., methodology, findings), and (2) the feasibility, validity and safety of EMA in the study of STBs. We identified 45 articles, detailing 23 studies. Studies mainly focused on examining how known longitudinal predictors of suicidal ideation perform within shorter (hourly, daily) time frames. Recent studies have explored the prospects of digital phenotyping of individuals with suicidal ideation. The results indicate that suicidal ideation fluctuates substantially over time (hours, days), and that individuals with higher mean ideation also have more fluctuations. Higher suicidal ideation instability may represent a phenotypic indicator for increased suicide risk. Few studies succeeded in establishing prospective predictors of suicidal ideation beyond prior ideation itself. Some studies show negative affect, hopelessness and burdensomeness to predict increased ideation within-day, and sleep characteristics to impact next-day ideation. The feasibility of EMA is encouraging: agreement to participate in EMA research was moderate to high (median = 77%), and compliance rates similar to those in other clinical samples (median response rate = 70%). More individuals reported suicidal ideation through EMA than traditional (retrospective) self-report measures. Regarding safety, no evidence was found of systematic reactivity of mood or suicidal ideation to repeated assessments of STBs. In conclusion, suicidal ideation can fluctuate substantially over short periods of time, and EMA is a suitable method for capturing these fluctuations. Some specific predictors of subsequent ideation have been identified, but these findings warrant further replication. While repeated EMA assessments do not appear to result in systematic reactivity in STBs, participant burden and safety remains a consideration when studying high-risk populations. Considerations for designing and reporting on EMA studies in suicide research are discussed.

Coexisting service-related factors preceding suicide: a network analysis

OBJECTIVES

The overall objective was to analyse service-related factors involved in the complex processes that precede suicide in order to identify potential targets for intervention.

DESIGN AND SETTING

Explorative network analysis study of post-suicide root cause analysis data from Swedish primary and secondary healthcare.

PARTICIPANTS

217 suicide cases reported to the Swedish national root cause analysis database between 2012 and 2017.

PRIMARY AND SECONDARY OUTCOME MEASURES

A total of 961 reported incidents were included. Demographic data and frequencies of reported deficiencies were registered. Topology, centrality indices and communities were explored for three networks. All networks have been tested for robustness and accuracy.

RESULTS

Lack of follow-up, evaluations and insufficient documentation issues emerged as central in the network of major themes, as did the contributing factors representing organisational problems, failing procedures and miscommunication. When analysing the subthemes of deficiencies more closely, disrupted treatments and staffing issues emerged as prominent features. The network covering the subthemes of contributing factors also highlighted discontinuity, fragile work structures, inadequate routines, and lack of resources and relevant competence as potential triggers. However, as the correlation stability coefficients for this network were low, the results need further investigation. Four communities were detected covering nodes for follow-up, evaluation, cooperation, and procedures; communication, documentation and organisation; assessments of suicide risk and psychiatric status; and staffing, missed appointments and declined treatment.

CONCLUSION

The results of this study suggest that healthcare providers may improve patient safety in suicide preventive pathways by taking active measures to provide regular follow-ups to patients with elevated suicide risk. In some cases, declined or cancelled appointments could be a warning sign. Tentative results show organisational instability, in terms of work structure, resources and staffing, as a potential target for intervention, although this must be more extensively explored in the future.

Integrating a functional view on suicide risk into idiographic statistical models

Acute risk of death by suicide manifests in heightened suicidal ideation in certain contexts and time periods. These increases are thought to emerge from complex and mutually reinforcing relationships between dispositional vulnerability factors and individually suicidogenic short-term stressors. Together, these processes inform clinical safety planning and our therapeutic tools accommodate a reasonable degree of idiosyncrasy when we individualize interventions. Unraveling these multifaceted factors and processes on a quantitative level, however, requires estimation frameworks capable of representing idiosyncrasies relevant to intervention and psychotherapy. Using, data from a 21-day ambulatory assessment protocol that included six random prompts per day, we developed personalized (i.e., idiographic) models of interacting risk factors and suicidal ideation via Group Iterative Multiple Model Estimation (GIMME) in a sample of people diagnosed with borderline personality disorder (N = 95) stratified for a history of high lethality suicide attempts. Our models revealed high levels of heterogeneity in state risk factors related to suicidal ideation, with no features shared among the majority of participants or even among relatively homogenous clusters of participants (i.e., empirically derived subgroups). We discuss steps toward clinical implementation of personalized models, which can eventually capture suicidogenic changes in proximal risk factors and inform safety planning and interventions.

Proximal Risk for Suicide: A Daily Diary Study Protocol (Preprint)

Background

Suicide is a prevalent public health concern in the United States across all age groups. Research has emphasized the need to identify risk markers that prevent suicide along shorter timeframes, such as days to weeks. Furthermore, little has been done to explore the relative significance of factors that can predict short-term suicide risk or to evaluate how daily variability in these factors impacts suicidal ideation or behavior. This proposed project aims to identify risk factors that best predict near-time changes in suicidal ideation and examine potential interactions between these factors to predict transitions into suicidal thinking or behaviors.

Objective

The aim of this proposed study is threefold: (1) To identify which psychological risk factors are most strongly associated with proximal changes in suicide risk across days and weeks. (2) To evaluate theoretical assumptions of the Integrative-Motivational-Volitional Theory of Suicide. (3) To determine how disruptions in physiological arousal interact with theoretical mechanisms of risk to predict concurrent and short-term prospective increase in suicidal thoughts and behaviors.

Methods

A daily diary or ecological momentary assessment design will be utilized with 200 participants. Participants will complete 2 in-person visits separated by 3 weeks during which they will complete 3 brief daily assessments within their natural environments using the ilumivu research app on a smart device. Research will occur at the Mayo Clinic Health System (MCHS) Eau Claire site. Participants will be recruited through chart review and standard care delivery assessment.

Results

This manuscript outlines the protocol that will guide the conduct of the forthcoming study.

Conclusions

The proposed project aims to lead efforts using technological advances to capture microchanges in suicidal thinking/behavior over shorter timeframes and thereby guide future clinical assessment and management of suicidal patients. Results of this study will generate robust evidence to evaluate which risk factors predict proximal changes in suicidal ideation and behaviors. They will also provide the ability to examine potential interactions with multiple theoretically derived risk factors to predict proximal transitions into worsening suicidal thinking or behaviors. Such information will provide new targets for intervention that could ultimately reduce suicide-related morbidity and mortality.

International Registered Report Identifier (IRRID)

PRR1-10.2196/37583

Using intensive time sampling methods to capture daily suicidal ideation: A systematic review

INTRODUCTION

There has been an increased emphasis on understanding suicidal thoughts and behaviors as they occur in real-time, resulting in a proliferation of studies utilizing intensive time sampling methods. Given the continued growth in this area, there is a need to synthesize the feasibility of these methods in capturing suicidal ideation at the daily level, in addition to an examination of study factors that may impact suicidal ideation detection, to guide future research.

METHOD

Online databases (i.e., PsychINFO, ERIC, PubMed, MEDLINE) were systematically searched for articles published through December 2020 that assessed suicidal ideation at the daily level.

RESULTS

Twenty-six articles presenting data from sixteen independent datasets met inclusion criteria. Across included articles, suicidal ideation detection ranged from approximately 1-92% of participant-completed surveys, with 18-100% of unique study participants reporting suicidal ideation during the study period. Assessment-based factors (i.e., number of daily assessments, duration of daily assessment period) did not appear to be meaningfully associated with suicidal ideation detection rates. Rather, participant characteristics (i.e., baseline suicide risk history, inclusion criteria) were better indicators of a study's ability to capture suicidal ideation at the daily level.

CONCLUSIONS

Findings highlights the impact of targeting participants with elevated suicide risk at study enrollment.

Distress tolerance as a moderator of the dynamic associations between interpersonal needs and suicidal thoughts

BACKGROUND

Identifying the interaction between dispositional and dynamic risk factors is necessary in understanding, predicting, and managing suicide risk. Interpersonal factors have consistently been linked to suicidal ideation over short-term periods. Additionally, distress tolerance may be a relevant dispositional protective factor against stressful events.

METHODS

Seven hundred and seventeen psychiatric inpatients (Male = 30.31%, Average Age = 40.71 years, Min = 14, Max = 82) self-reported their distress tolerance at hospital admission, and interpersonal needs and suicidal ideation on a daily basis. Dynamic structural equation modelling was used to examine whether within-level dynamics were moderated by distress tolerance.

RESULTS

Both perceived burdensomeness and thwarted belongingness were significantly associated with same-day suicidal ideation. Higher distress tolerance was associated with weaker daily associations between suicidal ideation and both perceived burdensomeness and thwarted belongingness. Distress tolerance was also associated with lower variability in suicidal ideation. Moderating effects were also evident when lifetime suicide attempts were added as a covariate, which was associated with stronger associations between interpersonal dysfunction and suicidal ideation, and higher variability in ideation.

CONCLUSIONS

Distress tolerance may be important to consider when examining the dynamic relationships between suicidal ideation and proximal factors. Psychotherapy that specifically targets distress tolerance may be effective in reducing reactivity to interpersonal stressors.

Suicide Risk and Protective Factors: A Network Approach

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 were 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 toward these services.

CONCLUSION

This research demonstrates the importance of examining protective factors as well as risk factors when estimating 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.HIGHLIGHTSThe network analyses estimated depression to be the most central risk factor.Depression and perceived burdensomeness were risk factors for suicidal ideation.Self-esteem and resilience were protective against suicidal ideation.

Understanding suicidal pathways through the lens of a Dual-System Model of Suicidality in real-time: The potential of ecological momentary assessments

Within the ideation-to-action framework, existing theories of suicidal thoughts and behaviors (STBs) primarily focus on the linear progression of suicide risk. This, however, neglects growing evidence that many suicidal individuals do not experience their suicide attempt as a planned action, and in some instances deny even having experienced any suicidal thoughts. Furthermore, recent research has found that risk factors differ substantially between persons and that this is reflected in the variety of suicidal pathways. Considering the strong variability of STBs, new innovative theoretical concepts and assessment methods are needed to advance our understanding of multiple suicidal pathways. In this review, we apply a dual-system framework to suicidality, the Dual-System Model of Suicidality (DSMS), which accounts for two different systems of information processing and behavior. The first of these described is the reflective system, whereby STBs are viewed from a self-regulation perspective and thusly considered as maladaptive coping behavior to perceived discrepancies regarding important goals. Applying a feedback-based view such as this to STBs provides a deeper understanding into underlying psychological processes involved in the development of STBs. The second system described by the DSMS is the impulsive system. Here, STBs are seen as a maladaptive self-organizing pattern that gets activated in high-risk situations of acute stress, negative affect, and when resources of the reflective system are depleted. In this context, the DSMS is informed by a strength model of self-regulation, which assumes that self-regulation resources are limited, an aspect with important theoretical and clinical implications for the development of STBs. In order to demonstrate the theoretical and practical utility of the DSMS, this review draws mainly on studies using ecological momentary assessment (EMA), a technology that allows to investigate moment-to-moment changes in STBs, and is therefore well suited for capturing the complex interplay of self-regulatory and impulsive processes proposed by the DSMS. The application of a dual-system framework to suicide research represents an innovative and integrative approach for expanding our knowledge about fundamental processes and how their dynamics lead to STBs. The usefulness of the DSMS, implications for future suicide research with EMA, and clinical implications are discussed.

The importance of recognizing worthlessness for suicide prevention in adolescents with Attention-deficit/hyperactivity disorder

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common psychiatric diagnoses among children and adolescents. Depression and general anxiety disorder (GAD) are often co-occurring with ADHD among children and adolescents. Previous studies have found that ADHD, depression and GAD are all strongly correlated with suicidal thoughts and planning.

AIM

The current study aimed to further explore the association between ADHD, GAD and depressive symptoms as well as their association with suicidal thoughts and planning among adolescents.

METHOD

Adolescents with ADHD diagnosis were involved from child psychiatry outpatient clinics and adolescents without a psychiatric treatment or diagnosis were enrolled from high schools in Hungary. The Mini International Neuropsychiatric Interview for Children and Adolescents was used to evaluate psychiatric symptoms and disorders as well as suicidal thoughts and planning. Regularized psychological networks were used to investigate the associations.

RESULTS

Altogether 185 adolescents (58 females and 127 males; mean age 14.79 years, SD = 1.48), 89 with ADHD and 96 without ADHD were enrolled. Depression symptom worthlessness was directly related to suicidal thoughts and planning, CI95 of the logit B between worthlessness and suicidal thought (0.72, 1.66). Both ADHD and anxiety were indirectly related to suicidal thoughts and planning through depression: CI95 of the logit B between being disorganized and feeling worthless is (0.38, 3.02), and CI95 of the logit B between being distressed and feeling worthless is (0.57, 2.52).

CONCLUSIONS

This study draws the attention of clinicians to the importance of recognizing "worthlessness" for suicide prevention in adolescents with ADHD. Furthermore, the results support previous studies, whereby symptoms of depression and anxiety mediate the relationship between ADHD and suicidal thoughts and planning. These results highlight the importance of ADHD comorbidities with depression and GAD and their effect on suicidal thoughts and planning.

Dynamic contextual influences on social motivation and behavior in schizophrenia: a case-control network analysis

Contextual influences on social behavior and affective dynamics are not well understood in schizophrenia. We examined the role of social context on emotions, and the motivation to interact in the future, using dynamic network analysis of ecological momentary assessment (EMA) data. Participants included 105 outpatients with schizophrenia or schizoaffective disorder (SZ) and 76 healthy comparators (HC) who completed 7 days, 7 times a day of EMA. Dynamic networks were constructed using EMA data to visualize causal interactions between emotional states, motivation, and context (e.g., location, social interactions). Models were extended to include the type and frequency of interactions and the motivation to interact in the near future. Results indicated SZ networks were generally similar to HC but that contextual influences on emotion and social motivation were more evident in SZ. Further, feedback loops in HC were likely adaptive (e.g., positive emotions leading to social motivation), but most were likely maladaptive in SZ (e.g., sadness leading to reduced happiness leading to increased sadness). Overall, these findings indicate that network analyses may be useful in specifying emotion regulation problems in SZ and that instability related to contextual influences may be a central aspect of aberrant regulation.

Disorder agnostic network structure of psychopathology symptoms in youth

BACKGROUND

Youth mental health disorders are strong predictors of adult mental health disorders. Early identification of mental health disorders in youth is important as it could aid early intervention and prevention. In a disorder agnostic manner, we aimed to identify influential psychopathology symptoms that could impact mental health in youth.

METHODS

This study sampled 6063 participants from the Philadelphia Neurodevelopmental Cohort and comprised of youth of ages 12-21 years. A mixed graphical model was used to estimate the network structure of 115 symptoms corresponding to 16 psychopathology domains. Importance of individual symptoms in the network were assessed using node influence measures such as strength centrality and predictability.

RESULTS

The generated network had stronger associations between symptoms within a psychopathological domain; overall had no negative associations. A conduct disorder symptom eliciting threatening others and a depression symptom - persistent sadness or depressed mood - had the greatest strength centralities (β = 2.85). Fear of traveling in a car and compulsively going in and out a door had the largest predictability (classification accuracy = 0.99). Conduct disorder, depression, and obsessive compulsive disorder symptoms generally had the largest strength centralities. Suicidal thoughts had the largest bridge strength centrality (β = 2.85). Subgroup networks revealed that network structure differed by socioeconomic status (low versus high, p = 0.04) and network connectivity patterns differed by sex (p = 0.01), but not for age or race.

CONCLUSIONS

Psychopathology symptom networks offer insights that could be leveraged for early identification, intervention, and possibly prevention of mental health disorders.

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.

The after-effects of momentary suicidal ideation: A preliminary examination of emotion intensity changes following suicidal thoughts

Research using ecological momentary assessments has highlighted the importance of negative emotions as predictors of day-to-day suicidal thoughts. Yet only one study has examined the real-time consequences of these thoughts. This preliminary investigation examined changes in emotion intensity following suicidal thoughts. It also explored associations between these changes and endorsement of suicide functions as an escape and/or as a solution, examined both as momentary thoughts and intractable beliefs about suicide. Thirty-nine community participants endorsing suicidal ideation were followed for two-weeks and completed multiple daily surveys related to suicidal thoughts, functions of suicide, and emotion intensity. Participants reported heightened emotion intensity immediately following a suicidal thought across six emotions, with delayed reductions in stress and anxiety following ideation onset. When assessed in the moment, suicide as a solution to a problem predicted increases in hopelessness, sadness, stress and general negative affect immediately following a thought, while suicide as an escape predicted increases in anger immediately after a thought. When measured as intractable beliefs, only stronger belief in suicide as a solution to a problem predicted delayed reductions in stress following ideation. Increased intensity of negative emotions immediately following suicidal ideation suggests a potential vicious cycle of heightened emotion intensity and suicidality.

Ecological momentary assessment of interpersonal theory of suicide constructs in people experiencing psychotic symptoms

BACKGROUND

People with psychotic disorders are at an increased risk of suicide, but there is little understanding of suicidal ideation (SI) in this population. The Interpersonal Psychological Theory of Suicide posits that perceived burdensomeness (PB) and thwarted belonginess (TB) contribute to SI. To our knowledge there are no studies using ecological momentary assessment (EMA) to assess these interpersonal risk factors in a sample of individuals with psychotic disorders. This study investigated the validity and variability of PB and TB, and whether SI, EMA-measured psychotic symptoms, mood, and social context relate to PB and TB.

METHOD

Ninety-six participants with a psychotic disorder, including mood disorders with psychosis completed in-lab assessments of current SI, and then EMA surveys on a smartphone 3×/day for 10 days, answering questions about burdensomeness, belongingness, symptoms (i.e., hearing voices, experiencing suspiciousness), mood (i.e., happy, sad), and social context.

RESULTS

Burdensomeness varied within-participants less than belongingness (t (95) = -3.74, p=< .001). Participants with SI had higher mean burdensomeness ratings (t (94) = -2.70, p < .01) and lower mean belongingness ratings (t (94) = 3.68, p < .001) than did participants without SI. Being with others, greater psychotic experiences, less happiness, and greater sadness related to greater burdensomeness. SI status, being alone, greater psychotic experiences, less happiness, and greater sadness related to less belongingness.

CONCLUSIONS

This study examined the real-time influences of SI and psychotic symptoms on burdensomeness and belongingness. Hearing voices, suspiciousness, mood, and SI are related to interpersonal suicide-related risk factors. In this sample, social context had a differential effect on burdensomeness and belongingness.

Predicting suicidal ideation in a longitudinal high-risk sample: Multilevel analyses and 12-month trajectories

BACKGROUND

The Interpersonal Theory of Suicide states that suicidal ideation (SI) results from perceived burdensomeness (PB) and thwarted belongingness (TB). Cross-sectional studies found associations with SI. This study examined the prospective prediction of SI.

METHODS

Three hundred and eight inpatients reporting severe SI or a recent suicide attempt were assessed four times within 12 months. The prediction of SI was examined using multilevel analyses, group comparisons, and logistic regression analyses.

RESULTS

Cross-sectionally, PB and TB were associated with SI. Prospectively, neither PB nor TB predicted SI. We found no autocorrelation of SI over time. Patients with persistent and fluctuating SI reported higher PB at T0. PB predicted the persistence of SI over 12 months.

CONCLUSION

Results emphasize cross-sectional associations between PB, TB, and SI. PB and TB could not predict the intensity of SI over time. SI did not predict itself over time. PB was associated with a persistent trajectory of SI over 12 months.

Network structure of depression and anxiety symptoms in Chinese female nursing students

BACKGROUND

Comorbidity between depressive and anxiety disorders is common. From network perspective, mental disorders arise from direct interactions between symptoms and comorbidity is due to direct interactions between depression and anxiety symptoms. The current study investigates the network structure of depression and anxiety symptoms in Chinese female nursing students and identifies the central and bridge symptoms as well as how other symptoms in present network are related to depression symptom "thoughts of death".

METHODS

To understand the full spectrum of depression and anxiety, we recruited 776 Chinese female nursing students with symptoms of depression and anxiety that span the full range of normal to abnormal. Depression symptoms were measured by Patient Health Questionnaire-9 while anxiety symptoms were measured by Generalized Anxiety Disorder 7-Item Questionnaire. Network analysis was used to construct networks. Specifically, we computed the predictability, expected influence and bridge expected influence for each symptom and showed a flow network of "thoughts of death".

RESULTS

Nine strongest edges existed in network were from the same disorder. Four were between depression symptoms, like "sleep difficulties" and "fatigue", and "anhedonia" and "fatigue". Five were between anxiety symptoms, like "nervousness or anxiety" and "worry too much", and "restlessness" and "afraid something will happen". The symptom "fatigue", "feeling of worthlessness" and "irritable" had the highest expected influence centrality. Results also revealed two bridge symptoms: "depressed or sad mood" and "irritable". As to "thoughts of death", the direct relations between it and "psychomotor agitation/retardation" and "feeling of worthlessness" were the strongest direct relations.

CONCLUSIONS

The current study highlighted critical central symptoms "fatigue", "feeling of worthlessness" and "irritable" and critical bridge symptoms "depressed or sad mood" and "irritable". Particularly, "psychomotor agitation/retardation" and "feeling of worthlessness" were identified as key priorities due to their strongest associations with suicide ideation. Implications for clinical prevention and intervention based on these symptoms are discussed.

Use of Ecological Momentary Assessment to Study Suicidal Thoughts and Behavior: a Systematic Review

PURPOSE OF REVIEW

Ecological momentary assessment (EMA) is a recently introduced approach to patient evaluation that consists of asking patients questions in real time and in their usual habitat. This method seeks to contribute to suicide prevention by providing psychiatrists with detailed information about suicidal thoughts and behavior, how these fluctuate over short periods of time, and the short-term risk factors presented by patients. We conducted a systematic review of published research using EMA to study suicidal thoughts and behavior.

RECENT FINDINGS

Several systematic reviews of EMA in mental health have been conducted to date, and the literature contains numerous theoretical papers and compilations on EMA and suicide phenomena. To date, however, no systematic reviews have explored the use of this tool to study suicidal thoughts and behavior. We performed a systematic review of five databases (i.e., PubMed, Embase, Scopus, Web of Science, and PsycINFO) to identify studies on EMA and suicidal thoughts and behavior. An initial search revealed 544 articles. Following the study selection process, 35 studies were included in the review. Almost three-quarters of the studies were published in the last 4 years. The studies reviewed concluded that EMA was generally feasible and well accepted. EMA findings correlated well with the results of a retrospective assessment, though tended to over-represent symptom severity. Our review points to important aspects of suicidal thoughts and behavior, such as its wide fluctuation over short periods of time. Negative affect and disturbed sleep, among others, emerged as short-term predictors of suicidal thoughts and behavior. Therefore, EMA is a potentially useful tool in clinical practice, although not without drawbacks, such as participant fatigue with questionnaires and ethical concerns.

Child abuse and suicidality in the context of the Interpersonal Psychological Theory of Suicide: A network analysis

OBJECTIVES

While there is evidence for an association of child abuse with suicidality in the course of life, the underlying mechanisms remain unclear. The Interpersonal Psychological Theory of Suicide (IPTS) provides a theoretical framework to investigate this relationship. The present study examines how different subtypes of child abuse are related to suicidal ideation and to attempts in the context of the IPTS.

METHODS

146 psychiatric inpatients (M = 37.9 years, 62% female) with an acute suicidal crisis (n = 71) or a recent suicide attempt (n = 74) were examined at baseline (T0) and six (T1) months later. We measured emotional, physical, and sexual abuse, the constructs of the IPTS (thwarted belongingness, perceived burdensomeness, and capability for suicide) and suicidal ideation as well as suicide attempts. Using the statistics program R, a network analysis of all named constructs was conducted. Centrality measures were computed.

RESULTS

Emotional abuse was the most central kind of abuse in the network and had a direct relationship with suicide attempts and an indirect relationship with suicidal ideation via perceived burdensomeness. Physical and sexual abuse showed no significant relations with the different constructs of the IPTS.

CONCLUSION

The major limitation of this study was the modest sample size which reduced the number of variables able to be included in the network. Regarding child abuse, the results underline that emotional abuse plays a central role in this network and may be important for suicide risk assessment. Future research should address this topic in a larger sample.

PRACTITIONER POINTS

Emotional abuse was the most central kind of abuse in this network analysis. Sexual abuse was the only kind of abuse with a direct relation to suicidal ideation. Capability for suicide had just a marginal position in the network analysis. Early interventions addressing the effects of child abuse are recommended. Replications in larger samples and with more relevant variables are needed.

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.

New Methods for Assessing Rapid Changes in Suicide Risk

Rapid-acting interventions for the suicide crisis have the potential to transform treatment. In addition, recent innovations in suicide research methods may similarly expand our understanding of the psychological and neurobiological correlates of suicidal thoughts and behaviors. This review discusses the limitations and challenges associated with current methods of suicide risk assessment and presents new techniques currently being developed to measure rapid changes in suicidal thoughts and behavior. These novel assessment strategies include ecological momentary assessment, digital phenotyping, cognitive and implicit bias metrics, and neuroimaging paradigms and analysis methodologies to identify neural circuits associated with suicide risk. This review is intended to both describe the current state of our ability to assess rapid changes in suicide risk as well as to explore future directions for clinical, neurobiological, and computational markers research in suicide-focused clinical trials.

Dynamic fluctuations of emotional states in adolescents with delayed sleep phase-A longitudinal network modeling approach

BACKGROUND

Very late sleep rhythms are risks for social adjustment problems in adolescence. Using ecological momentary assessment data, we quantified and visualized temporal and contemporaneous within-persons dynamical relations of sleepiness and emotions in adolescents with and without late sleep rhythms.

METHODS

We analyzed a temporal network via multilevel vector autoregression (mlVAR) modeling and a contemporaneous network through the partial associations between the residuals of temporal and the between-subject multilevel models. We tested whether these networks were different between those with a late circadian rhythm [concurrent delayed sleep phase (DSP) N = 172, 37% boys, 63% girls] and those without (N = 143, 22% boys, 78% girls).

RESULTS

In adolescents without DSP, the temporal networks showed continuity only for low mood from the previous to the following time point. In adolescents with DSP, there were more predictable patterns of emotions. Feelings of depression led to a decrease of positive emotions and increase of irritation and anxiety. The contemporaneous networks showed clusters of positive and negative emotions in both groups and sleepiness decreased the experience of positive emotions concurrently.

LIMITATIONS

DSP in our current study was based only on one out of three diagnostic criteria of the full disorder (DSM-5) and it was assessed only once.

CONCLUSIONS

These findings indicate that the dynamic organization of emotions and sleepiness is different in adolescents with and without DSP. DSP adolescents have more predictable and maladaptive emotional patterns during the day. Results provide new insight about why individuals with DSP are at a heightened risk for decreased emotional adjustment.

Ecological Momentary Assessment for Monitoring Risk of Suicide Behavior

In recent years the involvement of technology in psychiatric treatment and its usefulness is increasing. The main advantages of its use lie in the possibility of collecting passively data with greater temporal granularity from each patient individually, since these devices are in direct contact almost every minute of the day with them. The variety of data collected by the all the smartphone sensors allows for a better understanding of the patient behavior through what is called the digital phenotype. So the use of a continuous monitoring system for patients at risk of suicide becomes a very useful tool for improving the quality of life of patients and for the early detection of suicide attempts.