Who are the patients who deny suicidal intent? Exploring patients' characteristics associated with self-disclosure and denial of suicidal intent

Suicide attempt risk predicts inconsistent self-reported suicide attempts: A machine learning approach using longitudinal data

INTRODUCTION

Inconsistent self-reports of lifetime suicide attempts (LSAs) are a major obstacle for accurate assessment of suicidal behavior. This study is the first to posit that adolescents at higher risk report LSAs more consistently than those at lower risk, revealing a link between suicide attempt risk and consistent reporting.

METHODS

A machine learning model was trained with 70 % of the baseline assessment data of a longitudinal sample of Norwegian adolescents (n = 10,739). The model was used to estimate the LSA risk score for the remaining 30 % of the testing dataset. The relationship between these baseline risk scores and the consistency of reporting LSAs was assessed using a 2-year follow-up reassessment of the testing dataset.

RESULTS

Internalizing problems, optimism about the future, conduct problems, substance use, and disordered eating were important factors associated with suicide attempt risk. Of the participants, 63.41 % had inconsistent self-reports at the two-year follow-up. Adolescents who consistently reported LSAs had significantly higher scores of suicide attempt risk at baseline. Two logistic regression analyses confirmed an association between suicide attempt risk and inconsistent self-reported LSAs and showed that sex (being male), and lower levels of depression and conduct problems significantly predicted such inconsistencies. Those who inconsistently reported LSAs were more likely than the others to be classified by the model as false negatives at the baseline risk assessment due to their lower estimated risk scores.

LIMITATIONS

Suicide attempts were measured with a single item in this study.

CONCLUSION

These risk factors support the theory of adolescent suicidality (TAS) and could improve suicide attempt risk assessment. Inconsistent self-reported LSAs signal lower suicide attempt risk.

Machine learning approach for the development of a crucial tool in suicide prevention: The Suicide Crisis Inventory-2 (SCI-2) Short Form

The Suicide Crisis Syndrome (SCS) describes a suicidal mental state marked by entrapment, affective disturbance, loss of cognitive control, hyperarousal, and social withdrawal that has predictive capacity for near-term suicidal behavior. The Suicide Crisis Inventory-2 (SCI-2), a reliable clinical tool that assesses SCS, lacks a short form for use in clinical settings which we sought to address with statistical analysis. To address this need, a community sample of 10,357 participants responded to an anonymous survey after which predictive performance for suicidal ideation (SI) and SI with preparatory behavior (SI-P) was measured using logistic regression, random forest, and gradient boosting algorithms. Four-fold cross-validation was used to split the dataset in 1,000 iterations. We compared rankings to the SCI-Short Form to inform the short form of the SCI-2. Logistic regression performed best in every analysis. The SI results were used to build the SCI-2-Short Form (SCI-2-SF) utilizing the two top ranking items from each SCS criterion. SHAP analysis of the SCI-2 resulted in meaningful rankings of its items. The SCI-2-SF, derived from these rankings, will be tested for predictive validity and utility in future studies.

New pharmacotherapies to tackle the unmet needs in bipolar disorder: a focus on acute suicidality

INTRODUCTION

Suicidal behavior is relatively frequent in patients with bipolar disorder (BD) and constitutes their most frequent cause of death. Suicide rates remain high in patients with BD despite adherence to guidelines recommending lithium as first line, and/or antidepressants, antipsychotics, psychotherapy, psychosocial interventions, and electroconvulsive therapy. Hence the need to identify more effective and rapid anti-suicide interventions.

AREAS COVERED

To tackle the unmet needs of pharmacotherapy, we investigated the PubMed database on 24-25 January 2024 using strategies like ('acute suicid*'[ti] OR 'suicide crisis syndrome' OR 'acute suicidal affective disturbance') AND (lithium[ti] OR clozapine[ti]), which obtained 3 results, and ('acute suicid*'[ti] OR 'suicide crisis syndrome' OR 'acute suicidal affective disturbance') AND (ketamine[ti] OR esketamine[ti] OR NMDA[ti] OR glutamat*[ti]), which yielded 14 results. We explored glutamatergic abnormalities in BD and suicide and found alterations in both. The noncompetitive NMDS antagonist ketamine and its S-enantiomer esketamine reportedly decrease acute suicidality.

EXPERT OPINION

Intranasal esketamine or subcutaneous ketamine, single-bolus or intravenous, and possibly other glutamate receptor modulators may improve suicidal behavior in patients with unipolar and bipolar depression. This may be achieved through prompt remodulation of glutamate activity. The correct use of glutamatergic modulators could reduce acute suicidality and mortality in patients with BD.

Electroretinography and suicidal behaviors: a systematic review

BACKGROUND

Electroretinogram (ERG) is one of the tools used to investigate the electrophysiological underpinnings of mental health illnesses and major clinical phenomena (e.g., suicide) to improve their diagnosis and care. While multiple studies have reported specific ERG changes among individuals with suicidal behaviors, we know of no review that has been done to characterize their findings to inform future research.

METHODS

This review included available literature concerning ERG and suicidal behaviors. The paper's first section briefly overviews the theoretical basis of ERG and neurotransmitters involved in suicidal behaviors. The second section describes the findings of a review of studies reporting ERG findings among individuals with suicidal behaviors.

RESULTS

Most reviewed studies reported normal amplitude and implicit time of the a-waves, but the latency in individuals with suicidal behaviors was lower than normal. Additionally, the b-waves amplitude was reduced, but the implicit time and latency were increased. The b-a amplitude ratio and oscillatory potential were decreased.

CONCLUSION

Despite identifying certain ERG correlates with suicidal behaviors in the existing studies, there is a need for adequately powered and methodologically robust studies to advance clinical translation.