Visual perceptual deficit commonly occurs in people with schizophrenia. The Test of Visual Perceptual Skills-4th Edition (TVPS-4) is a motor-free visual perceptual measure, which includes seven subtests: visual discrimination, visual memory, spatial relationships, form constancy, sequential memory, visual figure-ground, and visual closure. However, convergent validity and ecological validity of the TVPS-4 is largely unknown, which limits its use in clinical and research settings.

The purpose of this study was to examine convergent validity and ecological validity in people with schizophrenia.

Ninety-nine people with schizophrenia were assessed the TVPS-4, the Mini Mental State Examination (MMSE), the Behavioral Assessment of the Dysexecutive Syndrome (BADS), and the Activities of Daily Living Rating Scale III (ADLRS-III). To evaluate convergent validity, Pearson’s r were calculated among the TVPS-4 and two cognitive measures (the MMSE and the BADS). To evaluate ecological validity, we computed correlation (r) between the TVPS-4 and the ADLRS-III.

The TVPS-4 total score showed moderate correlations with two cognitive measures (r=0.65-0.70). The seven TVSP-4 domains revealed moderate correlations with two cognitive measures (r=0.42-0.69). Moderate correlation (r=0.56) was found between the TVPS-4 total score and the ADLRS-III. Moderate to high correlations (r=0.33-0.61) were noticed among the seven TVPS-4 domains and the ADLRS-III.

The TVPS-4 has good convergent validity and ecological validity in people with schizophrenia. The multiple domains of the TVPS-4 are useful to comprehensively identify visual perception deficits in people with schizophrenia. The TVPS-4 can adequately exhibit the degree of living independently in people with schizophrenia.

No significant relationships.

Metabolic abnormality is common among schizophrenia patients. Some metabolic traits were found associated with subgroups of schizophrenia patients.

We examined a possible relationship between metabolic abnormality and psychosis profile in schizophrenia patients.

Three hundred and seventy-two chronic schizophrenia patients treated with antipsychotics for more than 2 years were assessed with the Positive and Negative Syndrome Scale. A set of metabolic traits was measured at scheduled checkpoints between October 2004 and September 2006.

Multiple regressions adjusted for sex showed negative correlations between body mass index (BMI) and total score and all subscales; triglycerides (TG) was negatively correlated with total score and negative syndrome, while HDLC was positively correlated with negative syndrome. When sex interaction was concerned, total score was negatively correlated with BMI but not with others; negative syndrome was negatively correlated with BMI and positively with HDLC. No metabolic traits were correlated with positive syndrome or general psychopathology.

Loss of body weight is a serious health problem in schizophrenia patients with severe psychosis syndrome, especially the negative syndrome. Schizophrenia patients with severe negative syndrome may have a distinct lipid pathophysiology in comparison with those who were less severe in the domain.

Deep learning using convolutional neural networks represents a form of artificial intelligence where computers recognise patterns and make predictions based upon provided datasets. This study aimed to determine if a convolutional neural network could be trained to differentiate the location of the anterior ethmoidal artery as either adhered to the skull base or within a bone ‘mesentery’ on sinus computed tomography scans.

Coronal sinus computed tomography scans were reviewed by two otolaryngology residents for anterior ethmoidal artery location and used as data for the Google Inception-V3 convolutional neural network base. The classification layer of Inception-V3 was retrained in Python (programming language software) using a transfer learning method to interpret the computed tomography images.

A total of 675 images from 388 patients were used to train the convolutional neural network. A further 197 unique images were used to test the algorithm; this yielded a total accuracy of 82.7 per cent (95 per cent confidence interval = 77.7–87.8), kappa statistic of 0.62 and area under the curve of 0.86.

Convolutional neural networks demonstrate promise in identifying clinically important structures in functional endoscopic sinus surgery, such as anterior ethmoidal artery location on pre-operative sinus computed tomography.

The treatment gap between the number of people with mental disorders and the number treated represents a major public health challenge. We examine this gap by socio-economic status (SES; indicated by family income and respondent education) and service sector in a cross-national analysis of community epidemiological survey data.

Data come from 16 753 respondents with 12-month DSM-IV disorders from community surveys in 25 countries in the WHO World Mental Health Survey Initiative. DSM-IV anxiety, mood, or substance disorders and treatment of these disorders were assessed with the WHO Composite International Diagnostic Interview (CIDI).

Only 13.7% of 12-month DSM-IV/CIDI cases in lower-middle-income countries, 22.0% in upper-middle-income countries, and 36.8% in high-income countries received treatment. Highest-SES respondents were somewhat more likely to receive treatment, but this was true mostly for specialty mental health treatment, where the association was positive with education (highest treatment among respondents with the highest education and a weak association of education with treatment among other respondents) but non-monotonic with income (somewhat lower treatment rates among middle-income respondents and equivalent among those with high and low incomes).

The modest, but nonetheless stronger, an association of education than income with treatment raises questions about a financial barriers interpretation of the inverse association of SES with treatment, although future within-country analyses that consider contextual factors might document other important specifications. While beyond the scope of this report, such an expanded analysis could have important implications for designing interventions aimed at increasing mental disorder treatment among socio-economically disadvantaged people.

The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service.

21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011–2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.

The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.

Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.

Civilian suicide rates vary by occupation in ways related to occupational stress exposure. Comparable military research finds suicide rates elevated in combat arms occupations. However, no research has evaluated variation in this pattern by deployment history, the indicator of occupation stress widely considered responsible for the recent rise in the military suicide rate.

The joint associations of Army occupation and deployment history in predicting suicides were analysed in an administrative dataset for the 729 337 male enlisted Regular Army soldiers in the US Army between 2004 and 2009.

There were 496 suicides over the study period (22.4/100 000 person-years). Only two occupational categories, both in combat arms, had significantly elevated suicide rates: infantrymen (37.2/100 000 person-years) and combat engineers (38.2/100 000 person-years). However, the suicide rates in these two categories were significantly lower when currently deployed (30.6/100 000 person-years) than never deployed or previously deployed (41.2–39.1/100 000 person-years), whereas the suicide rate of other soldiers was significantly higher when currently deployed and previously deployed (20.2–22.4/100 000 person-years) than never deployed (14.5/100 000 person-years), resulting in the adjusted suicide rate of infantrymen and combat engineers being most elevated when never deployed [odds ratio (OR) 2.9, 95% confidence interval (CI) 2.1–4.1], less so when previously deployed (OR 1.6, 95% CI 1.1–2.1), and not at all when currently deployed (OR 1.2, 95% CI 0.8–1.8). Adjustment for a differential ‘healthy warrior effect’ cannot explain this variation in the relative suicide rates of never-deployed infantrymen and combat engineers by deployment status.

Efforts are needed to elucidate the causal mechanisms underlying this interaction to guide preventive interventions for soldiers at high suicide risk.

Suicide is a leading cause of death worldwide; however, little information is available about the treatment of suicidal people, or about barriers to treatment.

To examine the receipt of mental health treatment and barriers to care among suicidal people around the world.

Twenty-one nationally representative samples worldwide(n=55 302; age 18 years and over) from the World Health Organization's World Mental Health Surveys were interviewed regarding past-year suicidal behaviour and past-year healthcare use. Suicidal respondents who had not used services in the past year were asked why they had not sought care.

Two-fifths of the suicidal respondents had received treatment (from 17% in low-income countries to 56% in high-income countries), mostly from a general medical practitioner (22%), psychiatrist (15%) or non-psychiatrist (15%). Those who had actually attempted suicide were more likely to receive care. Low perceived need was the most important reason for not seeking help (58%), followed by attitudinal barriers such as the wish to handle the problem alone (40%) and structural barriers such as financial concerns (15%). Only 7% of respondents endorsed stigma as a reason for not seeking treatment.

Most people with suicide ideation, plans and attempts receive no treatment. This is a consistent and pervasive finding, especially in low-income countries. Improving the receipt of treatment worldwide will have to take into account culture-specific factors that may influence the process of help-seeking.

We investigated cerebral structural connectivity and its relationship to symptoms in never-medicated individuals with first-onset schizophrenia using diffusion tensor imaging (DTI).

We recruited subjects with first episode DSM-IV schizophrenia who had never been exposed to antipsychotic medication (n=34) and age-matched healthy volunteers (n=32). All subjects received DTI and structural magnetic resonance imaging scans. Patients' symptoms were assessed on the Positive and Negative Syndrome Scale. Voxel-based analysis was performed to investigate brain regions where fractional anisotropy (FA) values significantly correlated with symptom scores.

In patients with first-episode schizophrenia, positive symptoms correlated positively with FA scores in white matter associated with the right frontal lobe, left anterior cingulate gyrus, left superior temporal gyrus, right middle temporal gyrus, right middle cingulate gyrus, and left cuneus. Importantly, FA in each of these regions was lower in patients than controls, but patients with more positive symptoms had FA values closer to controls. We found no significant correlations between FA and negative symptoms.

The newly-diagnosed, neuroleptic-naive patients had lower FA scores in the brain compared with controls. There was positive correlation between FA scores and positive symptoms scores in frontotemporal tracts, including left fronto-occipital fasciculus and left inferior longitudinal fasciculus. This implies that white matter dysintegrity is already present in the pre-treatment phase and that FA is likely to decrease after clinical treatment or symptom remission.

Children with attention-deficit hyperactivity disorder (ADHD) have difficulties with executive function and impulse control which may improve with age.

To map the brain correlates of executive function in ADHD and determine age-related changes in reaction times and brain volumes.

Attention-deficit hyperactivity disorder and control groups were compared on the change task measures of response inhibition (stop signal reaction time, SSRT) and shifting (change response reaction time, CRRT). Voxel-wise magnetic resonance imaging (MRI) correlations of reaction times and grey matter volume were determined, along with bivariate correlations of reaction times, brain volumes and age.

Individuals in the ADHD group had longer SSRTs and CRRTs. Anterior cingulate, striatal and medial temporal volumes highly correlated with SSRT. Striatal and cerebellar volumes strongly correlated with CRRT. Older children had faster reaction times and larger regional brain volumes. In controls, orbitofrontal, medial temporal and cerebellar volumes correlated with CRRT but not SSRT. Neither reaction times nor regional brain volumes were strongly age-dependent.

Our evidence supports delayed brain maturation in ADHD and implies that some features of ADHD improve with age.