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Background Patient-reported outcome measures (PROM) provide clinicians with information about patients’ perceptions of distress. When linked with treatment and diagnostic registers, new information on common mental health disorders (CMHD) and service use, may be obtained, which might be useful clinically and for policy decision-making. This study reports the prevalence of CMHD and their association with PROM severity. Further, subgroups of self-reported symptoms of depression and anxiety were examined, and their association with clinician-assessed mental disorders, functional impairment, and service use. Methods In a cohort study of 2473 (63% female) outpatients, CMHD was examined with pre-treatment scores of self-reported depression and anxiety, and the number of assessments and psychotherapy appointments one year after treatment start. Factor mixture modelling (FMM) of anxiety and depression was used to examine latent subgroups. Results Overall, 22% of patients with a CMHD had an additional comorbid mood/anxiety disorder, making the prevalence lower than expected. This comorbid group reported higher symptoms of anxiety and depression compared to patients with non-comorbid disorders. FMM revealed three classes: “anxiety and somatic depression” (33%), “mixed depression and anxiety” (40%), and “cognitive depression” (27%). The anxiety and somatic depression class was associated with older age, being single and on sick leave, higher probability of depressive-, anxiety-, and comorbid disorders, having more appointments and higher functional impairment. Although the cognitive depression class had less somatic distress than the mixed depression and anxiety class, they reported more functional impairment and had higher service use. Conclusion The results show that higher levels of somatic symptoms of depression could both indicate higher and lower levels of functional impairment and service use. A group of patients with high somatic depression and anxiety was identified, with severe impairment and high service needs. By gaining insights into CMHD factors’ relation with clinical covariates, self-reported risk factors of depression and anxiety could be identified for groups with different levels of aggravating life circumstances, with corresponding service needs. These could be important symptom targets in different groups of patients.

In recent years, there has been a growing recognition of the importance of involving people with lived experience of mental health issues in psychiatric research. User involvement in research goes beyond being merely instrumental and is deeply intertwined with ethical and political considerations. Shifting from traditional research paradigms to collaborative partnerships with users is seen as a crucial step in ensuring that research is more relevant, meaningful, and respectful of the diverse perspectives within the mental health community. While there is a growing interest and responsibility regarding this matter, there is still a need to better understand the differences between participation, engagement, and user-led research alongside a respectful integration of user perspectives.In this presentation, the state-of-the-art regarding user involvement in psychiatric research will be reviewed and possible ways to practically implement such practice will be discussed.Disclosure of InterestNone Declared

The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

LGBTQ+ youth have higher rates of self-harm and suicide than cisgender, heterosexual peers. Less is known about prevalence of risks within these populations. The first systematic review and meta-analysis to investigate the prevalence of risks among young people throughout the LGBTQ+ umbrella with experiences across the dimension of self-harm, suicidal ideation and suicide behaviour; and how they may differ between LGBTQ+ umbrella groups. MEDLINE, Scopus, EMBASE, PsycINFO, and Web of Science searches were run to identify quantitative research papers (database inception to 31st January, 2020). Articles included were empirical quantitative studies, which examined risks associated with self-harm, suicidal ideation or suicidal behaviour in LGBTQ+ young people (12-25 years). 2457 articles were identified for screening which was completed by two independent reviewers. 104 studies met inclusion criteria of which 40 had data which could be meta-analysed in a meaningful way. This analysis represents victimisation and mental health difficulties as risks among LGBTQ+ youth with self-harm and suicide experiences. Random-effects modelling was used for the main analyses with planned subgroup analyses. Victimisation and mental health were key risk factors across the dimension self-harm and suicide identified through all analyses. A pooled prevalence of 0.36 was indicated for victimisation and 0.39 for mental health difficulties within LGBTQ+ young people with experiences of self-harm or suicide. Odds ratios were calculated which demonstrated particularly high levels of victimisation (3.74) and mental health difficulties (2.67) when compared to cisgender, heterosexual counterparts who also had these experiences. Victimisation and mental health difficulties are highly prevalent among LGBTQ+ youth with experiences of self-harm and suicide. Due to inconsistency of reporting, further risk synthesis is limited. Given the global inclusion of studies, these results can be considered across countries and inform policy and suicide prevention initiatives. CRD42019130037.

In addition to the global negative impact on mental health of general population, as well as psychiatric patients, Covid-19 pandemic affected significantly research. Initially, lockdowns and restrictions of human contacts temporarily disrupted clinical research activities, but the unprecedented health crisis also provided unique opportunity to study epidemiology of mental disorders, direct and indirect effects of the pandemic on psychiatric disorders, underlying pathophysiological mechanisms, or long-term neuropsychiatric consequences. Research has refocused now on better understanding of the causes, presentations, outcome trajectories, and therapy of mental illnesses. New research topics are followed by the surge in publications covering Covid-19 and mental health and/or psychiatric disorders and treatments. The impact of the pandemic on research and publications is also evidenced by the results of a survey among psychiatric researchers.

Evidence of executive dysfunction in autism spectrum disorders (ASD) across development remains mixed and establishing its role is critical for guiding diagnosis and intervention. The primary objectives of this meta-analysis is to analyse executive function (EF) performance in ASD, the fractionation across EF subdomains, the clinical utility of EF measures and the influence of multiple moderators (for example, age, gender, diagnosis, measure characteristics). The Embase, Medline and PsychINFO databases were searched to identify peer-reviewed studies published since the inclusion of Autism in DSM-III (1980) up to end of June 2016 that compared EF in ASD with neurotypical controls. A random-effects model was used and moderators were tested using subgroup analysis. The primary outcome measure was Hedges' g effect size for EF and moderator factors. Clinical sensitivity was determined by the overlap percentage statistic (OL%). Results were reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 235 studies comprising 14 081 participants were included (N, ASD=6816, Control=7265). A moderate overall effect size for reduced EF (Hedges' g=0.48, 95% confidence interval (CI) 0.43-0.53) was found with similar effect sizes across each domain. The majority of moderator comparisons were not significant although the overall effect of executive dysfunction has gradually reduced since the introduction of ASD. Only a small number of EF measures achieved clinical sensitivity. This study confirms a broad executive dysfunction in ASD that is relatively stable across development. The fractionation of executive dysfunction into individual subdomains was not supported, nor was diagnostic sensitivity. Development of feasible EF measures focussing on clinical sensitivity for diagnosis and treatment studies should be a priority.

Reports on the modulatory role of the neuropeptide oxytocin on social cognition and behavior have steadily increased over the last two decades, stimulating considerable interest in its psychiatric application. Basic and clinical research in humans primarily employs intranasal application protocols. This approach assumes that intranasal administration increases oxytocin levels in the central nervous system via a direct nose-to-brain route, which in turn acts upon centrally-located oxytocin receptors to exert its behavioral effects. However, debates have emerged on whether intranasally administered oxytocin enters the brain via the nose-to-brain route and whether this route leads to functionally relevant increases in central oxytocin levels. In this review we outline recent advances from human and animal research that provide converging evidence for functionally relevant effects of the intranasal oxytocin administration route, suggesting that direct nose-to-brain delivery underlies the behavioral effects of oxytocin on social cognition and behavior. Moreover, advances in previously debated methodological issues, such as pre-registration, reproducibility, statistical power, interpretation of non-significant results, dosage, and sex differences are discussed and integrated with suggestions for the next steps in translating intranasal oxytocin into psychiatric applications.

Withdrawal from addiction treatment is a frequent but difficult-to-predict contingency. We clarify and contextualize the concept of dropouts in addiction treatment, as well as the external and internal elements that most frequently lead to such dropouts. The main instruments used to measure dropout are summarized, after which a new tool, Predictors of Dropout from Addiction Treatment (PDAT) scale, is presented. The PDAT consists of four factors: 1) Motivation: desire to recover and to actively engage in current treatment; 2) Craving: longing for the use of substances and/or the substance addiction environment; 3) Problem awareness: level of insight, or degree of knowledge, and ability to objectify the problem and the disease, with the renunciations and limitations that this entails; and 4) Dysphoria: dyade inner restlessness - moodiness, i.e., emotional disturbance and depressive anticipation that precedes treatment withdrawal. The sample consisted of 243 addicted subjects in residential treatment, ranging in age from 18 to 63 years (average = 38.43, standard deviation = 10.95), who completed an initial 26-item PDAT questionnaire. The factor structure of the PDAT was determined by factor analysis. Mixed effects logistic regressions and receiver operating characteristics curve (ROC) analyses were applied to assess the predictive validity of the PDAT. Results: The 13-item PDAT showed adequate reliability and convergent and discriminant validity, with both the general scale and each of its factors having predictive validity 7 and 15 days after administration. The scale is a useful instrument with proven clinical efficacy and brevity of application. In addition, its four factors are useful for targeting interventions based on the unbalanced factors.