Barriers of mental health treatment utilization among first-year college students: First cross-national results from the WHO World Mental Health International College Student Initiative.

BACKGROUND: Although mental disorders and suicidal thoughts-behaviors (suicidal thoughts and behaviors) are common among university students, the majority of students with these problems remain untreated. It is unclear what the barriers are to these students seeking treatment. AIMS: The aim of this study is to examine the barriers to future help-seeking and the associations of clinical characteristics with these barriers in a cross-national sample of first-year college students. METHOD: As part of the World Mental Health International College Student (WMH-ICS) initiative, web-based self-report surveys were obtained from 13,984 first-year students in eight countries across the world. Clinical characteristics examined included screens for common mental disorders and reports about suicidal thoughts and behaviors. Multivariate regression models adjusted for socio-demographic, college-, and treatment-related variables were used to examine correlates of help-seeking intention and barriers to seeking treatment. RESULTS: Only 24.6% of students reported that they would definitely seek treatment if they had a future emotional problem. The most commonly reported reasons not to seek treatment among students who failed to report that they would definitely seek help were the preference to handle the problem alone (56.4%) and wanting to talk with friends or relatives instead (48.0%). Preference to handle the problem alone and feeling too embarrassed were also associated with significantly reduced odds of having at least some intention to seek help among students who failed to report that they would definitely seek help. Having 12-month major depression, alcohol use disorder, and suicidal thoughts and behaviors were also associated with significantly reduced reported odds of the latter outcome. CONCLUSIONS: The majority of first-year college students in the WMH-ICS surveys report that they would be hesitant to seek help in case of future emotional problems. Attitudinal barriers and not structural barriers were found to be the most important reported reasons for this hesitation. Experimental research is needed to determine whether intention to seek help and, more importantly, actual help-seeking behavior could be increased with the extent to which intervention strategies need to be tailored to particular student characteristics. Given that the preference to handle problems alone and stigma and appear to be critical, there could be value in determining if internet-based psychological treatments, which can be accessed privately and are often build as self-help approaches, would be more acceptable than other types of treatments to student who report hesitation about seeking treatment.status: publishe

Gene expression imputation across multiple brain regions provides insights into schizophrenia risk

Transcriptomic imputation approaches combine eQTL reference panels with large-scale genotype data in order to test associations between disease and gene expression. These genic associations could elucidate signals in complex genome-wide association study (GWAS) loci and may disentangle the role of different tissues in disease development. We used the largest eQTL reference panel for the dorso-lateral prefrontal cortex (DLPFC) to create a set of gene expression predictors and demonstrate their utility. We applied DLPFC and 12 GTEx-brain predictors to 40,299 schizophrenia cases and 65,264 matched controls for a large transcriptomic imputation study of schizophrenia. We identified 413 genic associations across 13 brain regions. Stepwise conditioning identified 67 non-MHC genes, of which 14 did not fall within previous GWAS loci. We identified 36 significantly enriched pathways, including hexosaminidase-A deficiency, and multiple porphyric disorder pathways. We investigated developmental expression patterns among the 67 non-MHC genes and identified specific groups of pre- and postnatal expression

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe