" Theory of mind " skills and a range of social behaviour in everyday life were assessed in a sample of 21 children with pervasive developmental disorders and 22 normally-developing preschoolers. Parents, teachers and therapists were interviewed using the Vineland Adaptive Behaviour Scales (Sparrow, Balla & Cicchetti, 1984) avid a new supplementary scale, the " Echelle d'Adaptation Sociale pour Enfants " (EASE). Teachers and therapists were able to differentiate subtle forms of social problems in everyday life between subgroups of children diagnosed later to have either autism (n = 13) or PDDNOS (n = 8) according to DSM3-R (1987) criteria. This study offers a (small) cross-cultural replication of recent work suggesting that differences in the mentalising skills of children with autism are reflected in the everyday social behaviour of this group. A significant effect of informant was found for the PDD group, and this effect was particularly pronounced when children with autism were considerated separately. The implications of informant differences are discussed.

Social behaviour in pervasive developmental disorders: effects of informant, group and "theory-of-mind".

Previous studies suggest that deficits in cognition may increase the risk of suicide. Our study aims to develop a machine learning (ML) algorithm-based suicide risk prediction model using cognition in patients with major depressive disorder (MDD).Participants comprised 52 depressed suicide attempters (DSA) and 61 depressed non-suicide attempters (DNS), and 98 healthy controls (HC). All participants were required to complete a series of questionnaires, the Suicide Stroop Task (SST) and the Iowa Gambling Task (IGT). The performance in IGT was analyzed using repeated measures ANOVA. ML with extreme gradient boosting (XGBoost) classification algorithm and locally explanatory techniques assessed performance and relative importance of characteristics for predicting suicide attempts. Prediction performances were compared with the area under the curve (AUC), decision curve analysis (DCA), and net reclassification improvement (NRI).DSA and DNS preferred to select the card from disadvantageous decks (decks "A" + "B") under risky situation (p = 0.023) and showed a significantly poorer learning effect during the IGT (F = 2.331, p = 0.019) compared with HC. Performance of XGBoost model based on demographic and clinical characteristics was compared with that of the model created after adding cognition data (AUC, 0.779 vs. 0.819, p > 0.05). The net benefit of model was improved and cognition resulted in continuous reclassification improvement with NRI of 5.3%. Several clinical dimensions were significant predictors in the XGBoost classification algorithm.A limited sample size and failure to include sufficient suicide risk factors in the predictive model.This study demonstrate that cognitive deficits may serve as an important risk factor to predict suicide attempts in patients with MDD. Combined with other demographic characteristics and attributes drawn from clinical questionnaires, cognitive function can improve the predictive effectiveness of the ML model. Additionally, explanatory ML models can help clinicians detect specific risk factors for each suicide attempter within MDD patients. These findings may be helpful for clinicians to detect those at high risk of suicide attempts quickly and accurately, and help them make proactive treatment decisions. 

/pdf/can-cognition-help-predict-suicide-risk-in-patients-with-18kxsvi0.pdf

Can cognition help predict suicide risk in patients with major depressive disorder? A machine learning study

This study explored the differences in emotional memory between adolescents with and without suicidal ideation. Fifty adolescents with depression and suicidal ideation, 36 with depression but no suicidal ideation, and 41 healthy controls rated the emotional valence of positive, neutral, and negative pictures. Then, the recognition of the images was evaluated 72 h later. Adolescents with suicidal ideation reported more negative emotional valence scores for positive and neutral pictures and were significantly less likely to recognize negative pictures than were those without suicidal ideation. The performance of adolescents with suicidal ideation on the negative picture recognition test was closely related to anxiety, depression severity, and intensity of suicidal ideation. The negative bias toward neutral stimuli and cognitive impairment may be important risk factors for adolescents with suicidal ideation. Improving emotional memory via targeted management approaches may help young people with suicidal ideation. 

/pdf/correlation-between-suicidal-ideation-and-emotional-memory-28ynez3w.pdf

Correlation between suicidal ideation and emotional memory in adolescents with depressive disorder

Neurocognitive functioning and impulsivity in first-episode psychosis with suicidal ideation and behavior: A systematic review

Background: In schizophrenia, the relationship between suicide and cognition is unclear. We aimed to assess cognitive functions and insight in schizophrenia patients with and without suicide attempts. Methods: In our study consisting of 77 patients, 36 of the patients had attempted suicide at least once in their lives and the remaining 41 had never attempted suicide. Sociodemographic data scale, Beck Cognitive Insight Scale, and Cambridge Neurophysiological Assessment Battery were applied. Results: In this study, patients with schizophrenia who attempted suicide had higher Beck Cognitive Insight Scale self-reflectiveness scores (P = .004), lower Beck Cognitive Insight Scale self-certainty scores (P = .040), and higher Beck Cognitive Insight Scale total score (P = .004). Delay aversion (P = .003) and risk-taking scores (P = .044) of Cambridge Neurophysiological Assessment Battery Cambridge gambling task were higher in patients who attempted suicide. In logistic regression analysis, as independent factors, the number of hospitalizations increased the risk of suicide 1.5 times per hospitalization (P = .021), Cambridge gambling task delay aversion increased the risk of suicide 8.4 times per score (P = .044), and the Beck Cognitive Insight Scale self-certainty score was shown as the factor that decreased the risk of suicide by 0.78 times (P = .024). Conclusion: The causes of suicide attempts in schizophrenia still preserve its uncertainty. Our results proposed a statistically significant relationship between cognitive insight and increased suicide attempts. This study also sustains that cognitive impulsivity is associated with suicidal behavior in patients with schizophrenia.

The Relationship Between Suicidal Behavior, Neurocognitive Functions and Insight in Patients with Schizophrenia

Early thinking about cognitive process and suicidal behaviors tended to focus on the immediate situation surrounding the individual - typically the underlying psychiatric condition that was seen as leading to his or her distress. However, we now know that the cognitive processes involved in a range of suicidal thoughts and behaviors can exert a significant impact on the expression or development of these behaviors, even without an environmental stressor or psychiatric condition. In this chapter, we summarize theoretical perspectives that led to this realization and explore the current understanding of the link between cognition and suicide from recent research and clinical findings. We present these findings first by psychiatric disorder, then by cognitive domains, and finally by specific suicidal construct in order to highlight the importance of these factors in determining the role of cognition in the suicidal process.Within and across psychiatric disorders, certain cognitive processes - negativistic thinking, impulsivity, cognitive rigidity, and altered emotional processing - are frequently found to be linked to suicidal thoughts and behaviors. Overall cognitive performance, decreased processing speed, executive dysfunction, and negative biases in memory and attention have also been linked to suicidal thoughts and behaviors. However, these findings do not hold true for all populations. There seems to be a role both for cognitive distortions (such as hopelessness) and neurocognitive deficits (such as poor overall cognitive performance, slower processing speed, and executive dysfunction) in the suicidal process, which warrant further exploration both separately and together.

Neurocognition and the Suicidal Process.

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Neurocognition and the Suicidal Process.