Attentional control deficits and suicidal ideation variability: An ecological momentary assessment study in major depression

Differences in suicide-specific attentional bias based on stimuli across the suicide Stroop and disengagement tasks

BACKGROUND

Evidence of suicide-specific attentional bias has been mixed, including the effect of specific suicide words (e.g., "suicide" versus "overdose"). The current study examined the psychometric properties and convergent validity of specific suicide words on the Stroop and disengagement tasks.

METHODS

Adults (79.8 % male, mean age = 42.19 ± 12.66) on a psychiatric inpatient unit completed both tasks, as well as clinical and demographic measures, following a recent suicide attempt (SA) (n = 55) or recent suicidal ideation (SI) with (n = 29) or without (n = 26) a SA history.

RESULTS

Mean reaction times (RTs) on both tasks demonstrated good internal consistency and were moderately correlated across tasks, while interference scores demonstrated poor reliability and were not correlated. Attentional bias to specific suicide words did not differentiate SA groups, except for a small, unexpected effect on the Stroop task showing greater interference to the word "funeral" among the recent SA group. Correlations with suicide risk factors differed for males and females.

LIMITATIONS

Participants all endorsed elevated SI, limiting generalizability beyond a recent suicidal crisis. Different suicide words were used on each task limiting direct comparisons. Groups based on SA history and gender were uneven, and correlations need to be replicated. Effects involving interference scores should be interpreted with caution given poor internal consistency.

CONCLUSION

The suicide Stroop and disengagement tasks partially capture distinct aspects of suicide-relevant attentional bias. Greater attention is needed regarding the particular stimuli and scoring methods as well as the role gender plays in suicide-relevant attentional bias.

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.

A suicide attentional bias as implicit cognitive marker of suicide vulnerability in a high-risk sample

Introduction

Suicide risk assessment based on self-report questionnaires is considered as problematic because risk states are dynamic and at-risk individuals may conceal suicidal intentions for several reasons. Therefore, recent research efforts increasingly focus on implicit risk markers such as the suicide attentional bias (SAB) measured with the Suicide Stroop Task (SST). However, most SST studies failed to demonstrate a SAB in individuals with suicide risk and repeatedly demonstrated insufficient psychometrics of the SST. This study aimed to investigate a SAB using a modified SST (M-SST) and to test its psychometric properties.

Method

We compared n = 61 healthy controls and a high-risk inpatient sample of n = 40 suicide ideators and n = 40 suicide attempters regarding interference scores of positive, negative and suicide-related words. Interference scores were calculated by subtracting the mean reaction time (mean RT) of the neutral words from the mean RT of the suicide-related words (mean RT Suicide -mean RT Neutral), resulting in a suicide-specific interference score. Similarly, interference scores were calculated for the positive and negative words by subtracting the mean RT of neutral words from the mean RT of positive and negative words.

Results

A Group × Interference ANOVA showed a significant interaction effect (p <.001, ηp2 = .09), indicating that group effects significantly vary across interference type. Post hoc comparisons revealed that both ideators and attempters demonstrated greater interferences only for suicide-related words compared to healthy controls, indicating a SAB in patients, while a difference between ideators and attempters was lacking. The suicide interference score classified with an AUC = 0.73, 95% CI [0.65 - 0.82], p <.001, between controls and patients with STBs. The M-SST demonstrated good internal consistency and convergent validity.

Discussion

The study adds evidence to the assumptions of the Cognitive Model of Suicide, viewing a SAB as a cognitive marker of suicide vulnerability independently of the engagement in suicidal behavior. The results' clinical implications are discussed in the context of recommended intervention strategies during an acute suicidal state. Future studies with the M-SST should include non-suicidal patient controls to investigate whether a SAB is uniquely related to suicidality.

Ecological momentary assessments of cognitive dysfunction and passive suicidal ideation among college students

Cognitive dysfunction (CD), inclusive of specific cognitive content (e.g., hopelessness, unbearability) or impaired cognitive processes (e.g., attentional fixation on suicide, rumination), is a key risk factor for suicidal ideation (SI). This study aimed to evaluate multiple forms of CD using ecological momentary assessment (EMA) to determine the unique contributions of CD to concurrent and prospective SI. Fifty-five college students with a history of SI or non-suicidal self-injury completed EMA surveys measuring momentary CD and passive SI ("Wish to Die" [WTD], "Wish to Stay Alive" [WTL]) four times a day for 14 days (2149 total observations). Passive SI and CD variables showed notable within-person variability. Multiple CD variables were significant predictors of concurrent ideation when examined simultaneously in multilevel models with random intercepts and fixed slopes, and associations were stronger when participants were around others. Controlling for concurrent passive SI, between-person rumination was a significant predictor of prospective WTD, and both within-person unbearability and between-person hopelessness were each predictive of prospective WTL. These findings provide evidence for the roles of specific types of CD in conferring risk for passive SI and highlight potentially malleable factors that can be changed through targeted interventions.

Repetitive negative thinking as a unique transdiagnostic risk factor for suicidal ideation

Repetitive negative thinking (RNT) is a transdiagnostic symptom observed across mood and anxiety disorders and is characterized by frequent, distressing thoughts that are perceived as uncontrollable. Specific forms of RNT have been linked to increased suicide risk. However, most work examining links between RNT and suicide has been conducted within specific disorders and subtypes of RNT (e.g., rumination in individuals with depression). The present study aimed to investigate associations between transdiagnostic RNT and suicidal ideation. We hypothesized RNT would be associated with suicide risk beyond disorder-specific clinical symptoms. Fifty-four participants with mood, anxiety, and/or traumatic stress disorders completed an interview assessing suicidal risk (Columbia-Suicide Severity Rating Scale (C-SSRS)) and self-report questionnaires assessing transdiagnostic RNT, depression, and anxiety. Based on C-SSRS, we divided participants into high or low suicide risk groups. We analyzed the relationship between suicidal risk group and RNT and found that RNT was uniquely associated with suicidal risk group, controlling for depression and anxiety severity. Our results suggest including assessments of RNT may have clinical utility for understanding the degree of suicide risk in individuals and point to the potential utility of including clinical interventions to target this symptom for those at high risk of suicide.

Plasma Phospholipid Polyunsaturated Fatty Acid Associations with Neurocognition

Neurocognitive deficits are implicated in major depressive disorder (MDD) and suicidal behavior, and cognitive function may be affected by blood levels of polyunsaturated fatty acids (PUFAs). Neuroprotective functions have been described for omega-3 (n-3) PUFAs, while omega-6 (n-6) PUFAs exhibit broadly opposing activities. Both classes of PUFAs are linked to MDD and suicidal behavior. However, few studies have investigated the relationships between PUFAs and neurocognitive function with respect to MDD or suicidal behavior. Among participants with MDD (n = 45) and healthy volunteers (HV, n = 30) we assessed performance on tasks of attentional capacity and executive function and its relationship to plasma phospholipid PUFA levels, expressed as a percentage of total plasma phospholipids, for eicosapentaenoic acid (EPA%), docosahexaenoic acid (DHA%), and arachidonic acid (AA%). Regression models tested the correlations between PUFA levels and task performance in three groups: MDD with a history of suicide attempt (SA, n = 20), MDD with no attempts (NA, n = 25), and HV. Interaction testing indicated a significant positive correlation of EPA% with continuous performance test scores in the NA group (F = 4.883, df = 2,72, p = 0.01), a measure of sustained attention. The AA% correlated negatively with performance on two executive function tasks, object alternation (beta = -3.97, z-score = -2.67, p = 0.008) and the Wisconsin card sort (beta = 0.80, t-score = -2.16, df = 69, p = 0.035), after adjustment for group and age, with no group effects. Our findings suggest a role for PUFA imbalance in attentional functioning and executive performance; however, no MDD-specific effect was observed.

Psychosocial and neurocognitive correlates of suicidal thoughts and behaviours amongst siblings of persons with and without neurodevelopmental conditions

OBJECTIVE

Siblings of individuals with neurodevelopmental conditions (NDCs) have greater incidence of neuropsychiatric diagnoses and neurocognitive difficulties compared to siblings of persons without NDCs. Despite suicidality being labelled a global health crisis (WHO, 2014) and NDC siblings experiencing risk factors implicated in suicidality, no previous studies examined suicidality amongst adolescent and young adult siblings of persons with NDCs. Our study aimed to bridge this gap.

METHOD

The present study used Bayesian analyses and risk classification models to examine individual and environmental risk factors associated with suicidal thoughts and behaviours amongst siblings of persons with and without NDCs (n = 267; 132 NDC, 135 control group, mean age 20.61, range 14-27, 76.40% female, 76.78% White Caucasian), as measured using self-report survey data and remote self-administered cognitive tests.

RESULTS

NDC siblings had higher rates of current nonsuicidal self-injury (NSSI; 18.94% versus 14.07%, δ = -0.32), suicidal ideation (25.76% versus 8.89%, δ = -0.40) and history of suicide attempts (18.18% versus 4.44%, δ = -0.43) compared to controls. Classification models using boosting and random forest demonstrated adequate performance: positive predictive value 0.86-0.91, negative predictive value 0.81-0.90, false negative rates 0.11-0.24. Cognitive inflexibility, alexithymia, inattention, bullying, depression, NSSI, and eating or psychotic disorder history had the highest relative importance in predicting lifetime suicidality. Poorer executive functioning (measured by the Wisconsin Card Sorting Task, Sustained Attention to Response Task, Stop Signal Task, and N-Back 2-back task) was strongly correlated with suicidality.

CONCLUSIONS

Screening for proximal and modifiable risk factors is critical to inform suicidal behaviour intervention and prevention programs for at-risk siblings.

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.