BACKGROUND\nAIMS\nMETHOD\nRESULTS\nCONCLUSIONS\nDespite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained... Show moreBACKGROUND\nAIMS\nMETHOD\nRESULTS\nCONCLUSIONS\nDespite efforts to predict suicide risk in children, the ability to reliably identify who will engage in suicide thoughts or behaviours has remained unsuccessful.\nWe apply a novel machine-learning approach and examine whether children with suicide thoughts or behaviours could be differentiated from children without suicide thoughts or behaviours based on a combination of traditional (sociodemographic, physical health, social-environmental, clinical psychiatric) risk factors, but also more novel risk factors (cognitive, neuroimaging and genetic characteristics).\nThe study included 5885 unrelated children (50% female, 67% White, 9-11 years of age) from the Adolescent Brain Cognitive Development (ABCD) study. We performed penalised logistic regression analysis to distinguish between: (a) children with current or past suicide thoughts or behaviours; (b) children with a mental illness but no suicide thoughts or behaviours (clinical controls); and (c) healthy control children (no suicide thoughts or behaviours and no history of mental illness). The model was subsequently validated with data from seven independent sites involved in the ABCD study (n = 1712).\nOur results showed that we were able to distinguish the suicide thoughts or behaviours group from healthy controls (area under the receiver operating characteristics curve: 0.80 child-report, 0.81 for parent-report) and clinical controls (0.71 child-report and 0.76-0.77 parent-report). However, we could not distinguish children with suicidal ideation from those who attempted suicide (AUROC: 0.55-0.58 child-report; 0.49-0.53 parent-report). The factors that differentiated the suicide thoughts or behaviours group from the clinical control group included family conflict, prodromal psychosis symptoms, impulsivity, depression severity and history of mental health treatment.\nThis work highlights that mostly clinical psychiatric factors were able to distinguish children with suicide thoughts or behaviours from children without suicide thoughts or behaviours. Future research is needed to determine if these variables prospectively predict subsequent suicidal behaviour. Show less
Background It is unclear whether altered hypothalamic-pituitary-adrenal (HPA) axis regulation, which frequently accompanies depression and anxiety disorders, represents a trait rather than a state... Show moreBackground It is unclear whether altered hypothalamic-pituitary-adrenal (HPA) axis regulation, which frequently accompanies depression and anxiety disorders, represents a trait rather than a state factor. Aims To examine whether HPA axis dysregulation represents a biological vulnerability for these disorders, we compared cortisol levels in unaffected people with and without a parental history of depressive or anxiety disorders. We additionally examined whether possible HPA axis dysregulations resemble those observed in participants with depression or anxiety disorders. Method Data were from the Netherlands Study of Depression and Anxiety. Within the participants without a lifetime diagnoses of depression or anxiety disorders, three groups were distinguished: 180 people without parental history, 114 with self-reported parental history and 74 with CIDI-diagnosed parental history. These groups were additionally compared with people with major depressive disorder or panic disorder with agoraphobia (n = 1262). Salivary cortisol samples were obtained upon awakening, and 30, 45 and 60 min later. Results As compared with unaffected participants without parental history, unaffected individuals with diagnosed parental history of depression or anxiety showed a significantly higher cortisol awakening curve (effect size (d) = 0.50), which was similar to that observed in the participants with depression or anxiety disorders. Unaffected people with self-reported parental history did not differ in awakening cortisol levels from unaffected people without parental history. Conclusions Unaffected individuals with parental history of depression or anxiety showed a higher cortisol awakening curve, similar to that of the participants with depression or anxiety disorders. This suggests that a higher cortisol awakening curve reflects a trait marker, indicating an underlying biological vulnerability for the development of depressive and anxiety disorders. Show less
Meulenbeek, P.; Willemse, G.; Smit, F.; Balkom, A. van; Spinhoven, P.; Cuijpers, P. 2010
Background Many people suffer from subthreshold and mild panic disorder and are at risk of developing more severe panic disorder. Aims This study (trial registration: ISRCTN33407455) was conducted... Show moreBackground Many people suffer from subthreshold and mild panic disorder and are at risk of developing more severe panic disorder. Aims This study (trial registration: ISRCTN33407455) was conducted to evaluate the effectiveness of an early group intervention based on cognitive-behavioural principles to reduce panic disorder symptomatology. Method Participants with subthreshold or mild panic disorder were recruited from the general population and randomised to the intervention (n = 109) or a waiting-list control group (n = 108). The course was offered by 17 community mental health centres. Results In the early intervention group, 43/109 (39%) participants presented with a clinically significant change on the Panic Disorder Severity Scale-Self Report (PDSS-SR) V. 17/108 (16%) in the control group (odds ratio (OR) for favourable treatment response 3.49, 95% CI 1.77-6.88, P=0.001). The course also had a positive effect on DSM-IV panic disorder status (OR = 1.96, 95% CI=1.05-3.66, P=0.037). The PDSS-SR symptom reduction was also substantial (between-group standardised mean difference of 0.68). The effects were maintained at 6-month follow-up. Conclusions People presenting with subthreshold and mild panic disorder benefit from this brief intervention. Show less
Slee, N.; Garnefski, N.; Leeden, M. van der; Arensman, E.; Spinhoven, P. 2008
