Search

Abstract Background Adverse childhood experiences (ACE) can affect educational attainments, but little is known about their impact on educational achievements in people at clinical high risk of psychosis (CHR). Methods In total, 344 CHR individuals and 67 healthy controls (HC) were recruited as part of the European Community’s Seventh Framework Programme-funded multicenter study the European Network of National Schizophrenia Networks Studying Gene–Environment Interactions (EU-GEI). The brief version of the Child Trauma Questionnaire was used to measure ACE, while educational attainments were assessed using a semi-structured interview. Results At baseline, compared with HC, the CHR group spent less time in education and had higher rates of ACE, lower rates of employment, and lower estimated intelligence quotient (IQ). Across both groups, the total number of ACE was associated with fewer days in education and lower level of education. Emotional abuse was associated with fewer days in education in HC. Emotional neglect was associated with a lower level of education in CHR, while sexual abuse was associated with a lower level of education in HC. In the CHR group, the total number of ACE, physical abuse, and neglect was significantly associated with unemployment, while emotional neglect was associated with employment. Conclusions ACE are strongly associated with developmental outcomes such as educational achievement. Early intervention for psychosis programs should aim at integrating specific interventions to support young CHR people in their educational and vocational recovery. More generally, public health and social interventions focused on the prevention of ACE (or reduce their impact if ACE occur) are recommended.

Introduction Role functioning is key to optimal health and inoculates against life-long inequality. Depression is a leading cause of functional disability. In most cases, improved symptomatology corresponds with improved functioning; however, functioning does not always return to “normal”, despite symptom remission. Furthermore, the relationship between symptom remission and the likelihood of being Not in Employment, Education or Training (NEET) is unknown. Objectives and aim To examine the temporal associations between depression course, functioning, and NEET status in young adults with mental health problems. Methods A prospective and multisite clinical cohort study of young people aged 15–25 years seeking help from a primary mental health service ( n = 448). Participants completed a clinical interview (incl. QIDS-C16) and self-report battery (incl. WHODAS 2.0, employment, education) at baseline which was repeated at 12-month follow-up whilst continuing treatment as usual. Results Remitted depression was significantly associated with improved functioning; however, 12 month functioning was still lower than the normative ranges for age-matched peers. Remittance of depression did not change the likelihood of being NEET. Only 10% of those who were NEET had received vocational support during the study. Conclusion Remittance of depression was associated with improved functioning but it did not reduce the likelihood of being NEET. This may be explained by economic influences or alternatively, a time lag may exist where improvements in functioning do not immediately correspond with reduced NEET rates. Lastly, there may be a scarring effect of depression such that change in NEET status requires an additional intervention to depression treatment. [ABSTRACT FROM AUTHOR]

Introduction Predicting transition from clinical high risk (CHR) to first episode psychosis has proven difficult. Assessment of oxidative stress biomarkers and the niacin skin flush response (NSFR) may improve prediction accuracy. Objectives To predict transition to psychosis based on combined clinical and blood biomarker. Aims To analyse data from patients in placebo group of a 12-week trial of omega-3 fatty acid supplementation in CHR. Transition likelihood ratios (LRs) for baseline historical risks, clinical assessments (PANSS subscales and total, GAF), NSFR and blood markers (nervonic acid, superoxide dismutase, glutathione) were calculated. Variables with the highest positive and lowest negative LRs were included in an odds ratio form of Bayes’ rule transition prediction models. Model accuracy was calculated by area under the receiver operating curves (AUROC) of each model. Results 1-year transition to psychosis was 28% (n=40). Historical data showed no predictability (sensitivity 30%, specificity 100% (AUROC)=0.688, p=0.085). Clinical assessments alone produced a sensitivity of 30% at a specificity of 95% (AUROC=0.83, p<0.0001). The biomarker panel alone predicted transition with 40% sensitivity and 100% specificity (AUROC=0.73, p=0.03). Combining history and clinical assessment provided no improvement above clinical data alone (sensitivity = 30%, specificity = 100%, AUROC=0.85, p< 0.0001). The combination of history, clinical assessment and biomarkers identified transition with a sensitivity of 60% and specificity of 100% (AUROC=0.87, p< 0.0001). Conclusions Probabilistic models combining biomarkers and clinical data are able to target high-risk subgroups within CHR and may help to personalise treatment. [ABSTRACT FROM AUTHOR]