Psychotropic Medication Prescription Patterns in Down Syndrome in a Large Pediatric Specialty Clinic.

Objectives: Patterns of psychotropic medication use in children and adolescents with Down syndrome (DS) are largely unknown. Clinical decisions are often made from evidence and experience from individuals with autism spectrum disorder (ASD) or intellectual disability (ID). Methods: Longitudinal data from 670 children with DS who received care in a specialty DS clinic from March 2021 to February 2024 were collected. After each clinic visit, the clinician indicated the presence or absence of co-occurring neurodevelopmental (ND) or mental health (MH) diagnoses, as well as whether the individual was prescribed a psychopharmacological treatment. We used descriptive statistics and analyzed associations between psychotropic medication use, co-occurring ND/MH conditions, and demographic data. Results: 19.1% of patients were prescribed at least one psychotropic medication at their most recent clinical visit. Alpha-agonists were the most commonly prescribed medication class (30.8%), followed by stimulants (18.9%), and antidepressants (16.7%). There was a significant difference in psychotropic medication use by age, with older children having increased odds of being prescribed a psychotropic medication. There were no differences in psychotropic medication use across sex (p = 0.10), race (p = 0.10), or household income (p = 0.16). Conclusions: We found that one-fifth of patients with DS were prescribed psychotropic medications. Nearly every individual with DS who was prescribed a psychotropic medication had a co-occurring ND/MH condition, yet these rates were lower than what have been reported in children with ID, ASD, and attention deficit/hyperactivity disorder. Further research needs to include those with DS to further understand medication efficacy and safe dosing practices to ensure optimal outcomes.

The role of an advanced practice midwife in perinatal mental health: Outlining the process of role development and implementation.

INTRODUCTION: Perinatal mental health disorders (PMDs) are a global health concern. In industrialized countries, the prevalence of PMDs is estimated to be 20%, and they are associated with serious negative effects for women, their children and their families, along with high societal costs related to long-term impacts. In Switzerland, the PMD detection rate during obstetrical healthcare provision is very low (1-3%), and specialized healthcare services are limited. This study aimed to develop and implement an advanced practice midwife (APM) role at a Swiss obstetrics and gynecology hospital using the PEPPA framework to provide adequate screening and first-consultation services. METHODS: The study uses a qualitative approach and follows the research stages using the 8-step from the participatory, evidence-based, patient-focused process for advanced practice nursing role development, implementation and evaluation (PEPPA) framework to develop and implement the APM role. RESULTS: Utilizing the PEPPA framework, we were able to develop, implement, and evaluate the APM role in the field of perinatal mental health. Through appropriate screening and first-consultation services, we were able to identify affected women early and facilitate treatment. CONCLUSIONS: In addition to stakeholder engagement and interprofessional collaboration, PEPPA serves as a beneficial framework for the process of role development, implementation, and evaluation in the midwifery profession. This study aims to assist midwives with Master's degrees in establishing corresponding roles within their practice areas, thereby enhancing care delivery. Furthermore, the current APM approach is intended to be continuously evaluated to gain new insights into its effectiveness.

The global prevalence of mental health disorders among runaway and homeless youth: A meta-analysis.

A meta-analysis was performed to identify the pooled prevalence of mental health disorders (MHDs) among runaway and homeless youth (RHY). Relevant studies published between December 1, 1985, and October 1, 2023, were identified in the PubMed, Scopus, Web of Science, and Cochrane Library databases. A preliminary screening of 11,266 papers resulted in the inclusion of 101 studies. The pooled-prevalence estimates were obtained using a random-effects model. The findings showed varying lifetime prevalence rates of MHDs: 47% (conduct disorders and psychological distress), 43% (depression), 34% (major depressive disorders), 33% (post-traumatic stress disorder), 27% (personality disorders), 25% (attention-deficit/hyperactivity disorder), 23% (bipolar disorders), 22% (anxiety), 21% (oppositional defiant disorders), 15% (anorexia), 15% (adjustment disorders), 14% (dysthymia), 11% (schizophrenia), 9% (obsessive-compulsive disorders), and 8% (gambling disorder). The current prevalence rates were: 31% (depression), 23% (major depressive disorder), 23% (anxiety), 21% (post-traumatic stress disorder), 16% (attention-deficit/hyperactivity disorder), 15% (bipolar disorder), 13% (personality disorders), 13% (oppositional defiant disorders), 8% (schizophrenia), and 6% (obsessive-compulsive disorders). Regular screening and the implementation of evidence-based treatments and the promotion of integration and coordination between mental health services for adolescent minors and young adults with other service systems are recommended.

A Note on Ising Network Analysis with Missing Data.

The Ising model has become a popular psychometric model for analyzing item response data. The statistical inference of the Ising model is typically carried out via a pseudo-likelihood, as the standard likelihood approach suffers from a high computational cost when there are many variables (i.e., items). Unfortunately, the presence of missing values can hinder the use of pseudo-likelihood, and a listwise deletion approach for missing data treatment may introduce a substantial bias into the estimation and sometimes yield misleading interpretations. This paper proposes a conditional Bayesian framework for Ising network analysis with missing data, which integrates a pseudo-likelihood approach with iterative data imputation. An asymptotic theory is established for the method. Furthermore, a computationally efficient Pólya-Gamma data augmentation procedure is proposed to streamline the sampling of model parameters. The method's performance is shown through simulations and a real-world application to data on major depressive and generalized anxiety disorders from the National Epidemiological Survey on Alcohol and Related Conditions (NESARC).

The association of the Prime Diet Quality Score (PDQS) with depression and anxiety symptoms: the Isfahan functional disorders (ISFUN) cohort study.

Background: Due to scarce epidemiologic data regarding the Prime Diet Quality Score (PDQS) and mental health disorders, this study aimed to investigate the association of PDQS with depression and anxiety symptoms in Iranian adults.Methods: This cross-sectional analysis was performed using the baseline data collected for the Isfahan functional disorders (ISFUN) cohort study. ISFUN was established in 2017 and enrolled apparently healthy adults, aged 18-65 years in Isfahan, Iran. Information on usual dietary intakes was collected using a validated Dish-based, 106-item food frequency questionnaire. The severity of depression and anxiety was assessed using a validated Iranian version of the Hospital Anxiety and Depression Scale.Results: A total number of1892 participants were enrolled in the present study. In total, 54.50% of subjects were female. In the fully adjusted model, participants with PDQS lower than median compared with those with PDQS higher than median had higher risk of depression (OR = 1.62; 95% CI: 1.11, 2.37) and anxiety (OR: 1.57; 95% CI: 1.08, 2.27). In stratified analysis by sex, males with PDQS lower than median compared with those with PDQS higher than median had greater risk for depressive (OR: 1.57) and anxiety symptoms (OR = 1.52). However, in females, no significant association was found between PDQS and odds of depression, and anxiety in the fully adjusted model.Conclusion: We found evidence indicating a significant inverse association between PDQS and depression and anxiety symptoms among Iranian adults. Further studies, in particular with prospective design, are required to confirm these findings.

Perception and behavior toward neuropsychiatric disorders in Saudi Arabia: A systematic review and quality assessment.

LAY ABSTRACT: In 2010, Saudi Arabia became the first country from the Gulf Cooperation Council states to join the World Mental Health Survey Initiative, which collaborates with Harvard University and has undertaken over 33 countries. The Saudi National Mental Health Survey revealed that 80% of Saudis with severe mental health disorders do not seek treatment. Considering the strong evidence set out in Saudi national study and the recommendations for future research, this systematic literature review was initiated to examine the most studied neurodevelopmental disorders reported in the Kingdom of Saudi Arabia to explore public knowledge, attitudes, and behaviors. Findings have shown that attention deficit hyperactivity disorder and autism spectrum disorder have been the most studied neurodevelopmental disorders in Saudi Arabia since 2010. However, various groups in Saudi society, including healthcare professionals, medical students, and the general public, lacked knowledge about these health conditions, often leading to stigmatized attitudes and behaviors toward people with attention deficit hyperactivity disorder and autism spectrum disorder. However, demographic data showed that most of the studies were carried out in the Central and Western provinces. More research is needed in all regions of the Kingdom of Saudi Arabia to contribute to the knowledge about mental health conditions of attention deficit hyperactivity disorder and autism spectrum disorder children and their parents to increase knowledge about neurodevelopmental disorders and mental health disorders in the Kingdom of Saudi Arabia, thereby enabling people to rethink their attitudes and behavior.

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional lives may negatively impact global flight safety and security. The adverse effects of mental health disorders on their flight performance pose a particular safety risk, especially in sudden unexpected startle situations. Therefore, the early detection, prediction and prevention of mental health deterioration in pilots and ATCs, particularly among those at high risk, are crucial to minimize potential air crash incidents caused by human factors. Recent research in artificial intelligence (AI) demonstrates the potential of machine and deep learning, edge and cloud computing, virtual reality and wearable multimodal physiological sensors for monitoring and predicting mental health disorders. Longitudinal monitoring and analysis of pilots' and ATCs physiological, cognitive and behavioral states could help predict individuals at risk of undisclosed or emerging mental health disorders. Utilizing AI tools and methodologies to identify and select these individuals for preventive mental health training and interventions could be a promising and effective approach to preventing potential air crash accidents attributed to human factors and related mental health problems. Based on these insights, the article advocates for the design of a multidisciplinary mental healthcare ecosystem in modern aviation using AI tools and technologies, to foster more efficient and effective mental health management, thereby enhancing flight safety and security standards. This proposed ecosystem requires the collaboration of multidisciplinary experts, including psychologists, neuroscientists, physiologists, psychiatrists, etc. to address these challenges in modern aviation.

Knowledge and Attitudes Regarding Depression Among a Sample of Iraqi Non-Psychiatric Nurses: A Cross-Sectional Study.

Introduction: Nurses, comprising the largest profession in healthcare, play a significant role in the identification and management of mental health disorders in hospitals. Objectives: The study assessed the knowledge and attitudes of non-psychiatric nurses and their encounters with depressive patients throughout their careers. Methods: This was a cross-sectional descriptive study with 400 non-psychiatric nurses from different hospitals in the Kurdistan Region of Iraq during October and November 2022. The independent Student's t-test, one-way analysis of variance, and binary logistic regression were used to assess possible factors associated with knowledge and attitude toward depression. Results: In this study, 400 non-psychiatric nurses were examined, revealing a mean age of 31.57 ± 8.59 years. Their mean scores for knowledge and attitude toward depression were 5.41 out of a maximum of 11 (standard deviation 1.15) and 5.15 out of 18 (standard deviation 1.83), respectively. Notably, differences in mean knowledge scores were observed concerning participant marital status (P = .044), while disparities in mean attitude scores are related to participant gender (P = .010). Upon binary logistic regression analysis, none of the independent variables exhibited an association with good knowledge. Nevertheless, gender emerged as a significant factor influencing attitude toward depression (odds ratio: 0.51; 95% confidence interval: 0.30-0.86; P = .012). Subsequently, in the multivariate binary logistic regression analysis, gender sustained significance (adjusted odds ratio: 0.573; 95% confidence interval: 0.348-0.942; P = .028) as the key variable impacting attitudes toward depression among non-psychiatric nurses. Conclusion: Based on the results of this study, nurses have insufficient awareness and management skills for depression. It has been experienced and reported that nurses lack knowledge and an attitude toward depression management. The study highlights a significant gap in nurses' skills for managing depression, urging the immediate improvement of training programs. Customizing these programs to enhance nurses' abilities in identifying and managing depression is crucial.

Perils of the nighttime: Impact of behavioral timing and preference on mental health in 73,888 community-dwelling adults.

Mental health is independently influenced by the inclination to sleep at specific times (chronotype) and the actual sleep timing (behavior). Chronotype and timing of actual sleep are, however, often misaligned. This study aims to determine how chronotype, sleep timing, and the alignment between the two impact mental health. In a community-dwelling cohort of middle- and older-aged adults (UK Biobank, n = 73,888), we examined the impact of chronotype (questionnaire-based), the timing of behavior (determined with 7-day accelerometry), and the alignment between the two on mental, behavioral, neurodevelopmental disorders (MBN), depression, and anxiety, as assessed through ICD-10 codes. As compared to morning types with early behavior (aligned), morning types with late behavior (misaligned) had an increased risk of having MBN, depression, and anxiety (p's<0.001). As compared to evening-types with late behavior (aligned), however, evening-types with early behavior (misaligned) had a decreased risk of depression (p < 0.01), with a trend for MBN (p = 0.04) and anxiety (p = 0.05). Longitudinal analyses, in which the likelihood of developing de novo mental health disorders was associated with chronotype, behavioral timing, and alignment between the two, confirmed cross-sectional findings. To age healthily, individuals should start sleeping before 1AM, despite chronobiological preferences.

Experiences using an online therapist-guided psychotherapy platform (OPTT) in correctional workers with depression, anxiety, and PTSD.

Introduction: Correctional workers (CWs) are frequently exposed to potentially traumatic events in the workplace, leading to an increased prevalence of mental health concerns. Online psychotherapy can address many of the barriers CWs face when seeking adequate mental health care. Despite their benefits, CWs' experience using digital mental health interventions is relatively unknown. This information could be valuable in developing enhanced care delivery to improve recruitment, retention, satisfaction, and treatment outcomes. Methods: This study investigated the experiences of a sample of CWs enrolled in a clinical trial evaluating the efficacy of the Online Psychotherapy Tool (OPTT) in this population. Participants were surveyed and interviewed to capture their opinions and feedback on the program. Survey analysis was conducted through Qualtrics statistical analysis software. The interview transcripts and open-ended survey questions were analyzed using thematic analysis methods in NVivo. Results: Participants (n=14) were cis-gender, predominantly white, with an average age of 38 years. While most respondents preferred in-person therapy, they also reported the benefits of the online psychotherapy program. Specifically, they expressed positive perceptions of the platform, the quality and interaction of their care provider, and the homework assignments and skills learned. Lack of motivation to complete weekly homework assignments was a frequently cited challenge. Unhelpful aspects of the therapy noted issues with the online format and frustration with certain program elements. Discussion: Participants expressed a positive outlook on the program, the platform, and treatment outcomes. A preference for in-person therapy was still indicated, demonstrating the need to focus on engagement in digital mental health interventions. In addition, the findings of this study shed light on the factors that can influence help-seeking in this population, including stigma in the work environment, demanding work schedules, workplace perceptions, and previous experiences accessing mental health services.

Using Large Language Models to Understand Suicidality in a Social Media-Based Taxonomy of Mental Health Disorders: Linguistic Analysis of Reddit Posts.

Background: Rates of suicide have increased by over 35% since 1999. Despite concerted efforts, our ability to predict, explain, or treat suicide risk has not significantly improved over the past 50 years. Objective: The aim of this study was to use large language models to understand natural language use during public web-based discussions (on Reddit) around topics related to suicidality. Methods: We used large language model-based sentence embedding to extract the latent linguistic dimensions of user postings derived from several mental health-related subreddits, with a focus on suicidality. We then applied dimensionality reduction to these sentence embeddings, allowing them to be summarized and visualized in a lower-dimensional Euclidean space for further downstream analyses. We analyzed 2.9 million posts extracted from 30 subreddits, including r/SuicideWatch, between October 1 and December 31, 2022, and the same period in 2010. Results: Our results showed that, in line with existing theories of suicide, posters in the suicidality community (r/SuicideWatch) predominantly wrote about feelings of disconnection, burdensomeness, hopeless, desperation, resignation, and trauma. Further, we identified distinct latent linguistic dimensions (well-being, seeking support, and severity of distress) among all mental health subreddits, and many of the resulting subreddit clusters were in line with a statistically driven diagnostic classification system-namely, the Hierarchical Taxonomy of Psychopathology (HiTOP)-by mapping onto the proposed superspectra. Conclusions: Overall, our findings provide data-driven support for several language-based theories of suicide, as well as dimensional classification systems for mental health disorders. Ultimately, this novel combination of natural language processing techniques can assist researchers in gaining deeper insights about emotions and experiences shared on the web and may aid in the validation and refutation of different mental health theories.

Effectiveness of Psychobiotics in the Treatment of Psychiatric and Cognitive Disorders: A Systematic Review of Randomized Clinical Trials.

In this study, a systematic review of randomized clinical trials conducted from January 2000 to December 2023 was performed to examine the efficacy of psychobiotics-probiotics beneficial to mental health via the gut-brain axis-in adults with psychiatric and cognitive disorders. Out of the 51 studies involving 3353 patients where half received psychobiotics, there was a notably high measurement of effectiveness specifically in the treatment of depression symptoms. Most participants were older and female, with treatments commonly utilizing strains of Lactobacillus and Bifidobacteria over periods ranging from 4 to 24 weeks. Although there was a general agreement on the effectiveness of psychobiotics, the variability in treatment approaches and clinical presentations limits the comparability and generalization of the findings. This underscores the need for more personalized treatment optimization and a deeper investigation into the mechanisms through which psychobiotics act. The research corroborates the therapeutic potential of psychobiotics and represents progress in the management of psychiatric and cognitive disorders.

Psychotropic medicine use without current or prior medical advice, storage at home and association with perceived stress in a primary health care setting in Greece / Uso de medicamentos psicotrópicos sin consejo médico actual o previo, almacenamiento en el hogar y asociación con estrés percibido en un entorno de atención primaria en Grecia

Objective: Psychotropic medicines use alters according to socio-economic factors and perceived stress. The study aimed to assess the prevalence of use of psychotropic medicines and supplements (PMS) without medical advice, including storage at home, and its relationship with socio-demographic characteristics and perceived stress in primary care patients. Materials and methods: A cross-sectional sample of adult attendees in an urban primary care unit in Crete, Greece, were surveyed during regularly scheduled appointments during a three-week period in October 2020. A questionnaire was distributed to investigate PMS use during the last 12 months. The validated Greek version of Perceived Stress Scale (PSS-14) was adopted to measure perceived stress. Results: Of 263 respondents (mean age 46.3±14.5 years; 66.5% females), 101 (38.4%; 95%CI 33.1–43.7%) recalled having psychotropic medicines stored at home cabinets and 72 (27.4%; 95%CI 22.4–32.3%) reported using PMS without medical advice in the last 12 months. Conclusions: This study revealed a high prevalence of PMS use without medical advice, including storage at home. People>59 years of age, experiencing irregular sleep and scoring high in PSS, displayed increased prevalence of storing PMS at home or using them without medical advice. The findings could potentially inform primary care providers to focus on patients most likely to be users of PMS without medical advice.(AU)

Objetivo: El uso de medicamentos psicotrópicos cambia según los factores socioeconómicos y el estrés percibido. El estudio tuvo como objetivo evaluar la prevalencia de uso de medicamentos y suplementos psicotrópicos (MSP) sin consejo médico, incluido el almacenamiento en el hogar y su relación con las características sociodemográficas y el estrés inferido en pacientes de atención primaria. Materiales y métodos: Se encuestó a una muestra transversal de asistentes adultos en una Unidad de Atención Primaria Urbana en Crete, Grecia, durante citas programadas regularmente durante un periodo de tres semanas en Octubre de 2020. Se distribuyó un cuestionario para investigar el uso de MSP durante los últimos 12 meses. Se adoptó la versión griega validada de la Escala de Estrés Percibido (Perceived Stress Scale 14, PSS-14) para medir el estrés percibido. Resultado: De 263 encuestados (edad media 46,3 ± 14,5 años; 66,5% mujeres), 101 (38,4%; IC 95%; 33,1-43,7%) recordaban tener medicamentos psicotrópicos almacenados en los armarios de sus casas y 72 (27,4%; IC 95%; 22,4-32,3%) informó haber usado MSP sin consejo médico en los últimos 12 meses. Conclusiones: Este estudio reveló una alta prevalencia de uso de MSP sin consejo médico, incluido el almacenamiento en el hogar. Las personas mayores de 59 años, que experimentaron sueño irregular y puntuaron alto en PSS, mostraron una mayor prevalencia de almacenar MSP en casa o usarlos sin consejo médico. Los hallazgos podrían informar potencialmente a los proveedores de atención primaria para que se centren en los pacientes con mayor probabilidad de usar MSP sin consejo médico.(AU)

The risk factors for mental health disorders in patients with type 2 diabetes: An umbrella review of systematic reviews with and without meta-analysis.

Background: Patients with type 2 diabetes have a nearly twofold higher rate of diagnosed mental disorders than those without diabetes. The association between type 2 diabetes and mental disorders is well established in the literature and recognized as a bidirectional relationship. This study aims to conduct an umbrella review of risk and protective factors for mental health disorders in patients with type 2 diabetes and assess the credibility of the evidence for the association between each factor and mental health disorders. Methods: A comprehensive search was conducted of Medline via PubMed, Web of Science, EMBASE, CINHAL, and PsycINFO from inception to November 17, 2022, to identify systematic reviews with and without meta-analyses examining associations of factors with mental health disorders in patients with type 2 diabetes. For each association, we recalculated the summary effect size and 95% confidence intervals using random-effects models. We also reported the 95% prediction interval and between-group heterogeneity. Results: The study included 11 systematic reviews that met the inclusion criteria, comprising eight meta-analyses and three without meta-analyses. This involved approximately 489,930 participants and encompassed 26 unique factors. Six factors were rated as having suggestive evidence at the Class III level. These factors were obesity (n = 18,456, OR 1.75 [1.2 to 2.59], I2 97.7%), neuropathy (n = 3898, OR 2.01 [1.60 to 2.54], I2 44.5%), diabetes complications (n = 1769, OR 1.90 [1.53 to 2.36], I2 39.3%), peripheral blood concentrations of CRP (n = 1742, SMD 0.31 [0.16 to 0.45], I2 84.1%), female sex (n = 35,162, OR 1.36 [1.19 to 1.54], I2 64.5%), and social support (n = 3151, OR 2.02 [1.51 to 2.70], I2 87.2%). Conclusions: Several factors associated with mental health disorders in patients with type 2 diabetes were identified with varying degrees of supporting evidence. Significantly, obesity, neuropathy, complications, peripheral blood CRP concentrations, female sex, and social support emerged with suggestive evidence. An investigation of these factors should be conducted to target interventions accordingly. It may be helpful to prioritize patients who have these risk factors as high-risk groups and to implement plans and policies to enhance support before mental health disorders occur.

Disparities in the Prevalence of Psychiatric Illness in Hawaii's Houseless Population: A Retrospective Chart Review.

In the State of Hawaii, previous research has suggested that minority groups such as Native Hawaiians and Other Pacific Islanders are disproportionately affected by mental health disorders and have less access to mental health services. The purpose of this study was to determine if similar disparities in the prevalence of psychiatric disorders among different ethnic groups are also present among Hawaii's houseless population. A retrospective chart review of records from one of Oahu's major houseless outreach clinics was performed to gather patient demographics and reported histories of psychiatric diagnoses. Reported disease prevalence rates were compared between larger ethnic categories as well as ethnic sub-groups. Results demonstrated higher rates of certain serious mental illnesses among the houseless; however, several other psychiatric diagnoses were unexpectedly found to be less prevalent than in the general population. Additionally, houseless Pacific Islander groups were unexpectedly found to often have disproportionally lower rates of psychiatric diagnoses despite being identified as high risk by other studies. Overall, our findings may indicate unique ethnic trends in the prevalence of mental health disorders among the houseless in Hawaii or may suggest increased social and/or cultural barriers to diagnosis among certain groups that will require more diligent screening and culturally competent care from providers.

Opaque Ontology: Neuroimaging Classification of ICD-10 Diagnostic Groups in the UK Biobank.

Background: 1.The use of machine learning to classify diagnostic cases versus controls defined based on diagnostic ontologies such as the ICD-10 from neuroimaging features is now commonplace across a wide range of diagnostic fields. However, transdiagnostic comparisons of such classifications are lacking. Such transdiagnostic comparisons are important to establish the specificity of classification models, set benchmarks, and assess the value of diagnostic ontologies. Results: 2.We investigated case-control classification accuracy in 17 different ICD-10 diagnostic groups from Chapter V (mental and behavioral disorders) and Chapter VI (diseases of the nervous system) using data from the UK Biobank. Classification models were trained using either neuroimaging (structural or functional brain MRI feature sets) or socio-demographic features. Random forest classification models were adopted using rigorous shuffle splits to estimate stability as well as accuracy of case-control classifications. Diagnostic classification accuracies were benchmarked against age classification (oldest versus youngest) from the same feature sets and against additional classifier types (K-nearest neighbors and linear support vector machine). In contrast to age classification accuracy, which was high for all feature sets, few ICD-10 diagnostic groups were classified significantly above chance (namely, demyelinating diseases based on structural neuroimaging features, and depression based on socio-demographic and functional neuroimaging features). Conclusion: 3.These findings highlight challenges with the current disease classification system, leading us to recommend caution with the use of ICD-10 diagnostic groups as target labels in brain-based disease prediction studies.

Recovery-supportive interventions for people with substance use disorders: a scoping review.

Background: Recovery-supportive interventions and strategies for people with substance use disorders are a cornerstone of the emergent recovery paradigm. As compared to other services, such approaches have been shown to be holistically focused and improve outcomes (e.g. substance use, supportive relationships, social functioning, and well-being). Even so, a comprehensive overview of the nature, extent, and range of research on the topic is lacking. Methods: A scoping review of the literature was conducted to characterize the main topics on recovery-supportive interventions. A systematic search was conducted in three databases: Scopus, Web of Science, and PubMed from January 2000 to July 2023 using the PRISMA-ScR. Twenty-five studies published between 2005-2022 met the inclusion criteria. Results: Most studies emanated from the United States, and we found a peak in publication frequency between 2018-2022 (n = 13) relative to other years. The most prominent lines of inquiry appear to concern recovery-oriented policies; principles of recovery-oriented services (challenges encountered when implementing recovery-oriented practices, relationships with service providers characterized by trust, and service user-service provider collaboration), and recovery capital (particularly recovery-supportive networks, employment, and housing). Seventeen studies addressed co-occurring disorders, and eight addressed substance use recovery. Conclusion: To advance the field, more context-specific studies are required on supporting peer professionals, (including enabling cooperation with service users, and hiring experts by experience as staff), and training of professionals (e.g., nurses, psychologists, social workers, physicians) in the principles of recovery.

Recording the brain in vivo: emerging technologies for the exploration of mental health conditions.

Standfirst Mounting interest in mental health conditions over the last two decades has been coupled with the increasing sophistication of techniques to study the brain in vivo. [Formula: see text].