Frontiers in Psychiatry

Background: This study examined the association between caregiving demands and depression symptoms among caregivers of individuals with Down syndrome during the COVID-19 pandemic. Method: We conducted an online survey of 200 caregivers of children and adults with Down syndrome, including demographic data, the Patient Health Questionnaire-8 (PHQ-8), and questions about lack of childcare and taking over instruction during the pandemic. A multiple linear regression analysis identified predictors of caregiver depression symptoms. Results: Household income (B = -3.45, p < .001) and having to take over instruction (B = 2.24, p < .001) were significant predictors of PHQ-8 scores. Child age, caregiver gender, difficulty paying for health insurance, and lack of childcare were not significant predictors. Conclusions: Lower income and instructional caregiving demands were associated with higher depression symptoms among caregivers of individuals with Down syndrome, suggesting potential targets for policy and intervention during future public health emergencies.

Introduction: Youth mental health presentations are largely heterogenous, making it difficult to match individuals to the most appropriate interventions. Personalised, measurement-based care has the potential to improve clinical decision-making and support shared decision-making, but remains challenging to implement in routine practice. Advances in digital monitoring and causal modelling offer new opportunities to identify individual-level processes driving mental health difficulties and to generate personalised decision-support. This pilot study aims to evaluate the feasibility and acceptability of the Minding Your Mind computational decision-support approach, a newly developed approach integrating routine outcome monitoring, individual-level causal modelling, and personalised feedback to support shared decision-making between young people and their clinicians. Methods and analysis: The study involves two phases. Phase 1 will recruit young people aged 15-25 years and mental health clinicians to participate in workshops to co-design the decision-support approach and its implementation into routine practice. Phase 2 is a prospective, single-arm feasibility study involving young people receiving mental health care and their treating clinicians. Primary outcomes include feasibility, acceptability, appropriateness, and usability of the decision-support approach, assessed via self-report and objective process indicators. Secondary outcomes include changes in use and experiences with shared decision-making, and clinical and functional outcomes. Quantitative analyses will be primarily descriptive, with exploratory pre-post comparisons and sensitivity analyses. Qualitative interviews will explore user experiences and implementation barriers and facilitators. Ethics and dissemination: This study has been approved by the Sydney Local Health District (RPAH Zone) Human Research Ethics Committee (X25-0341). All participants will provide informed consent prior to participation. Findings will be disseminated through peer-reviewed publications, conference presentations, and accessible summaries co-developed with young people with lived experience.

BackgroundA range of rare chromosomal micro-deletions or -duplications (Copy Number Variants - CNVs) are associated with high risk of neurodevelopmental and mental health conditions (ND-CNVs). There is great individual variability in outcomes, but we lack insights into the contributing social factors, including family functioning. MethodsCaregivers of 598 children and young people (CYP) with a range of 16 ND-CNVs and 222 siblings without ND-CNVs (controls) completed questionnaires on overall family climate (cohesion and conflict) as well as caregiver-CYP relationship warmth and hostility and took part in a research diagnostic interview about CYPs psychiatric symptoms. CYPs intelligence quotient (IQ) was also measured. ResultsComparisons with published data from neurotypical families indicated that families affected by ND-CNVs are characterised by higher family cohesion and conflict as well as lower caregiver-CYP warmth and hostility. Symptoms of oppositional defiant disorder reduced more steeply in CYP with ND-CNVs compared to controls with increasing family cohesion (interaction effect: {beta} = -0.14, p = 4.65 x 10-{superscript 2}). In contrast, they rose more steeply with increasing family conflict (interaction effect: {beta} = 0.18, p = 1.05 x 10-{superscript 2}). Furthermore, symptoms of mood disorder increased more steeply with increased caregiver-CYP hostility in CYP with ND-CNVs (interaction effect: {beta} = 0.15, p = 4.55 x 10-{superscript 2}). ConclusionsRaising a CYP with a rare genetic condition is challenging. Timely access to interventions that support caregivers in fostering a positive family environment may reduce behavioural difficulties in CYP, with subsequent benefits for family functioning.

Background and PurposeEpilepsy is a neurological condition characterized by recurring seizures and neuronal hyperexcitability. Cell-based high-throughput screening applications have been essential for drug development and discovering novel biological processes. However, cell-based screens do not provide information on how drug-targeted pathways are integrated into a whole animal. Our objective was to develop and evaluate a screening application using zebrafish larvae to identify signalling mechanisms that modulate neural activity. Experimental ApproachWe developed an in vivo automated high-content screening assay using zebrafish larvae expressing the calcium sensor CaMPARI (calcium-modulated photoactivatable ratiometric integrator) in neurons. This assay can quantify neural activity of multiple individual larvae per well in a 96-well format. We quantified neural activity in 8725 individual larvae, in response to 1292 different drugs to identify molecules that protect against convulsant-induced neuronal hyperexcitability. Key ResultsThe assay was effective at identifying drugs that target diverse neurotransmitter signalling systems. While some commonly used anti-convulsants (e.g. phenytoin, carbamazepine, valproic acid) had poor activity in the assay, Kv7 potassium channel activators were consistently effective (ICA-069673, ICA-27243, ICA-110381, retigabine, and ML213). Many compounds approved for treatment of other conditions, including amitriptyline (depression), cyclobenzaprine (muscle spasm), clomipramine (obsessive-compulsive disorder) and ganaxolone (seizures), also strongly suppressed excitability in the assay. Conclusion and ImplicationsNeuronal CaMPARI expression in zebrafish larvae is a powerful tool for plate-based compound library screening to identify drugs that suppress hyperexcitability in vivo. Bullet Point SummaryO_ST_ABSWhat is already knownC_ST_ABSO_LICaMPARI is an integrative Ca2+ sensor that can be used to identify active neurons. C_LIO_LIKv7 activators (retigabine, ML213, and ICA-069673) are effective at reducing convulsant-induced (4-AP) neuronal hyperexcitability. C_LI What this study addsO_LIAn automated in vivo high-content drug screening assay to quantify neural activity. C_LIO_LIA series of drug targets that influence convulsant-induced hyperexcitability. C_LI Clinical significanceO_LIOur new tool will help identify novel compounds and signalling mechanisms that could be pursued as therapeutic targets for diseases involving electrical hyperexcitability. C_LI

Importance: Problematic use of the internet (PUI) behaviors, including problematic gaming, social media use, smartphone use, and general internet use, have been increasingly studied worldwide. So far, it is unclear what the global prevalence of PUI is. Objective: To critically appraise existing systematic reviews and meta-analyses on the prevalence of PUI behaviors and generate aggregated global prevalence estimates across different manifestations and definitions. Data Sources: MEDLINE (Ovid), Embase (Ovid), Scopus, Web of Science, CINAHL, and the Cochrane Review Library were searched for relevant articles from database inception to the most recent available search prior to manuscript preparation. Searches targeted systematic reviews and meta-analyses reporting prevalence for PUI-related behaviors. Study Selection: Systematic reviews and meta-analyses of observational studies reporting prevalence estimates for problematic gaming, problematic internet use, problematic smartphone use, problematic social media use, or sexting were included. Scoping reviews were retained for descriptive synthesis only. Data Extraction and Synthesis: An umbrella review methodology was used. Data extraction and methodological appraisal were conducted using AMSTAR-2 to assess the quality of included systematic reviews up to February 2026. Primary studies included in each review were extracted and pooled using random-effects meta-analysis. Analyses were conducted to estimate pooled prevalence with 95% confidence intervals (CIs) and heterogeneity across non-overlapping primary studies. Small-study effects were examined. Main Outcomes and Measures: Global pooled prevalence estimates for PUI behaviors, including problematic gaming, problematic internet use, problematic smartphone use, problematic social media use, and sexting. Results: Eleven reviews, including 10 systematic reviews and 1 scoping review, met inclusion criteria, representing data from 3,145,428 individuals, of whom 3,030,023 were included in pooled prevalence analyses. Across regions, pooled prevalence estimates were 6% (95% CI, 5%-7%) for problematic gaming, 16% (95% CI, 15%-17%) for problematic internet use, 32% (95% CI, 28%-35%) for problematic smartphone use, and 23% (95% CI, 19%-28%) for problematic social media use. Substantial heterogeneity (I2 > 99%) was observed across primary studies, reflecting variation in study methodologies, sampled populations, and definitions of PUI behaviors. Conclusions and Relevance: PUI behaviors appear to affect a substantial proportion of the global population. However, methodological concerns were common, with 9 of 10 systematic reviews rated as having low or critically low confidence according to AMSTAR-2. Evidence remains concentrated in East Asia and Europe, and many reviews combine heterogeneous populations and sampling strategies. Additional high-quality epidemiological research, including studies in underrepresented regions, is needed to refine prevalence estimates, clarify risk factors, and support the development of standardized criteria for PUI behaviors.

Background Treatment guidelines for borderline personality disorder (BPD) recommend assessment, diagnosis, and psychoeducation. We report on the feasibility and safety of a randomized controlled trial protocol of online psychoeducation, assessment, and personalized feedback as an immediate first step of care for BPD. Methods Newly diagnosed participants were randomized to receive 10 videos about BPD or general mental health for two weeks. Half the participants receiving BPD videos were randomized to receive personalized feedback on changes in symptom ratings and cognitive performance. Ecological momentary assessment (EMA) evaluated interpersonal interactions, emotions, and behaviors for 30 days. BPD symptoms, depression, and personality functioning were assessed at baseline, after videos, after feedback, and one month later. Results Eighty-two participants were randomized into three conditions that did not differ significantly in terms of demographics or baseline variables. Dropout occurred for 32.9% of the sample. No differences in rate of emergency room visits, hospitalizations, or other escalations in level of care were reported among groups. Satisfaction was higher for those receiving psychoeducational videos about BPD. Improvement in BPD knowledge in the psychoeducation conditions was significantly greater than the control condition. No statistically significant differences were found regarding reduction of BPD symptoms. The psychoeducation with feedback arm showed significantly greater improvements in self-impairment compared to controls with medium effect size at the final timepoint. Modeling of the relationship between time spent alone and BPD symptoms showed a positive correlation in the control condition, but in the group receiving both psychoeducation about BPD and feedback, this relationship was negative. Conclusion Online psychoeducational videos and assessment were safe, feasible, and acceptable to participants with newly diagnosed BPD. Psychoeducation with personalized feedback appears to be more effective than either BPD or general psychoeducation alone in improving deficits in self-functioning, which may relate to an increased capacity to be alone with fewer symptoms. The protocol was registered with ClinicalTrials.gov (NCT05358925, https://clinicaltrials.gov/study/NCT05358925) on April 28th, 2022.

Brain similarity networks (BSNs), extracted from structural magnetic resonance imaging, provide a validated framework for studying brain network organization and encode neurodevelopmental information relevant for psychiatric disorders. Recently, a neurodevelopmental hypothesis has been proposed for bipolar disorder (BD), where evidence demonstrates neuroprogression phenotypes differing from controls. BSNs offer a promising framework for investigating BD's neural correlates but remain largely underexplored. Parallelly, graph neural networks (GNNs) have emerged as suitable deep learning models for exploiting network-level information. This study aimed to investigate BSNs for discriminating subjects with BD from controls within a GNN framework using the multi-site StratiBip network, composed of 605 controls and 501 subjects with BD. Leveraging advanced analysis tools, we developed a multi-site classification framework including: i) the state-of-the-art MIND algorithm for computing morphometric similarity (MS) networks based on gray matter volumes (GMV), ii) MS integration with age, sex, and GMV, iii) a leave-one-site-out cross-validation for multi-site model generalizability evaluation. The best model achieved a mean multi-site accuracy of 68%. Explainability analyses revealed meaningful MS patterns in the basal ganglia, frontal and temporal lobes, and a particularly relevant integration with age. This study provides interpretable insights into the role of MS in BD and unveils evidence supporting ageing-related processes as a significant component of BD pathophysiology.

Background and PurposeWhile inflammation has been generally considered to exacerbate symptoms of schizophrenia, some clinical observations suggest that acute inflammation may alleviate positive symptoms. However, animal models often use excessive inflammatory stimuli, and the effects of acute inflammation--comparable to levels observed in patients--remain unknown. Experimental ApproachTo address this, we examined whether acute inflammation induced under relatively mild, clinically relevant conditions suppresses behavioural sensitization in methamphetamine (METH)-sensitized mice, a model of psychostimulant-induced psychosis with relevance to certain aspects of positive symptoms of schizophrenia. We used a repeated METH (1 mg/kg) sensitized model to evaluate the effects of acute inflammation on behavioural sensitization. Acute inflammation was induced via two methods using either lipopolysaccharides (LPS; 1 g/kg) to mimic peripheral immune activation or restraint stress (RS; single 2-h exposure) to model the neuroinflammation induced by psychological stress. LPS doses were adjusted with reference to the magnitude of peripheral cytokine elevation reported in patients, and RS was applied in short single sessions to avoid excessive inflammation. Key ResultsBoth LPS and RS significantly suppressed behavioural sensitization, without inducing other behavioural abnormalities. This suppression was dependent on toll-like receptor-4 activation. LPS-mediated suppression involved cyclooxygenase-2, whereas RS-mediated suppression was linked to the microglia-derived tumour necrosis factor-. LPS did not alter, whereas RS significantly reduced the striatal extracellular dopamine levels. Conclusion and ImplicationsThese findings suggest that acute inflammation suppresses behavioural sensitization through distinct mechanisms depending on the inflammatory trigger, providing a framework for understanding how inflammation may influence psychosis-related processes, with potential relevance to schizophrenia.

Objective: Biopsychosocial models recognize multiple determinants of post-trauma mental disorders, but their relative and interactive effects remain unclear. We quantified the independent contribution of traumatic event severity, preexisting vulnerability, social support, and coping capacity, and tested mediation pathways. Methods: In a Brazilian clinical sample reporting traumatic or stressful events (N = 612), constructs were operationalized as composite scores and a dichotomous clinical outcome was derived from intake assessments. Logistic regression (n = 594) and structural equation modeling evaluated prediction and mediation. Results: Vulnerability was the strongest risk factor (OR = 1.46, p < .001) and social support the main protective factor (OR = 0.60, p < .001). Traumatic event severity remained an independent predictor (OR = 1.39, p < .001), whereas coping capacity was not significant (OR = 0.94, p = .410). Discrimination was good (AUC = 0.80). Mediation indicated vulnerability reduced social support and coping capacity, with a significant indirect effect via social support. Conclusions: Findings support a multifactorial model centered on a triad of vulnerability, social support, and traumatic exposure. Risk is shaped primarily by preexisting vulnerability and relational context, alongside a direct trauma effect, providing a clinically relevant framework for assessment and intervention.

Background: We previously examined the burden and predictors of sustained mental health care engagement in Ugandan first episode psychosis patients by retrospective chart review methods. However, the extensive requirements of chart reviews meant that we could only extract data from a random 10% sample of 1677 newly enrolled Ugandan first-episode psychosis patients at Butabika National Referral Mental Hospital in 2018. The Hekima Platform has been designed to transform handwritten files into datasets for analysis. Objectives: This study aims to: (1) utilize the Hekima Platform to transform paper-based clinical charts of all 1677 Ugandan psychosis patients enrolled at Butabika Hospital for the first time in 2018 into a standardized, anonymized longitudinal database and (2) re-examine predictors of sustained MHC engagement in this cohort. Methods: We will digitize and archive all patient charts. We will then use the Hekima Platform to extract handwritten clinical data into machine-readable text using user-trained machine learning and deep learning models and natural language processing (NLP) techniques to generate a structured, anonymized database. A minimum 10% random sample of extracted data will be manually validated using Cohen's kappa. For the analytical aim descriptive statistics bivariate analysis and multivariable logistic regression will model predictors of sustained engagement. Exploratory machine learning approaches are used as a complementary analytical strategy. Ethical approval has been obtained from the Uganda National Council for Science and Technology and Butabika Hospital's Research Ethics Committee. Expected outcomes: Patient clinical charts are a rich data source but there are extensive requirements to be able to use them for research. This study will generate the first AI-assisted standardized longitudinal database from handwritten psychiatric records in Uganda enabling well-powered analyses of predictors of MHC engagement. Findings will inform targeted interventions to improve retention in care and will offer a scalable model for mental health research in low- and middle-income countries.

The proliferation of gambling advertising has intensified concerns regarding its influence on vulnerable populations, yet the neural mechanisms underlying cue-reactivity to these stimuli remain underexplored in ecologically valid settings. This study protocol proposes a novel methodological framework to investigate prefrontal cortical responses to gambling advertisements in individuals with varying degrees of gambling experience. Materials and methods: This cross-sectional study will recruit 44 participants, divided into a clinical group (individuals with high-frequency gambling or gambling disorder) and a matched control group. Neural activity will be recorded using fNIRS while participants view gambling-related, neutral, violent, and sexual stimuli. Secondary measures include validated scales for gambling severity (SOGS), impulsivity, sensation seeking, and alexithymia. Data analysis will primarily utilize inter-subject correlation (ISC) to quantify neural synchronization and multiband frequency decomposition to capture dynamic affective processing. Advanced preprocessing, including short-channel regression, will be applied to ensure signal robustness. Discussion: By combining portable neuroimaging with a data-driven ISC approach, this study aims to identify objective neural markers of gambling vulnerability. The findings will provide novel insights into the idiosyncratic processing of commercial stimuli, potentially informing public health policies and the development of more effective evidence-based regulations for gambling marketing.

Background: Attention Deficit Hyperactivity Disorder (ADHD) is characterized by persistent inattention, hyperactivity, and impulsivity. While documented in children, research on its persistence into young adulthood in Jordan remains scarce. This gap is critical given the cognitive demands of higher education. This study estimated attention deficit hyperactivity disorder (ADHD) symptom prevalence among Jordanian university students, examined associations with gender and academic performance, and identified barriers to mental health service accessibility. Methods: A descriptive cross-sectional study using web-based sampling recruited 389 university students (aged [&ge;] 18 years) from various Jordanian universities. Participants completed an online survey, incorporating the validated English and Arabic versions of the Adult ADHD Self-Report Scale (ASRS-v1.1) to assess symptom prevalence, alongside inquiries regarding demographics, academic history, and barriers to care. Results: The prevalence of probable ADHD was 37.5% (n=146). Males constituted a significantly higher proportion of positive cases (69.9%) compared to females (30.1%). A strong statistical association was found between positive ADHD screening and negative academic impact (p<0.001), as well as negative effects on emotional well-being (p<0.001). Comorbidities including anxiety disorders and emotional abuse were significantly linked to probable ADHD (p=0.019). Notably, positive-screened participants were significantly more likely to cite social stigma as a primary barrier to seeking professional help (p=0.024). Conclusion: Self-reported ADHD symptoms are highly prevalent among Jordanian university students, correlating with substantial academic underachievement and emotional dysfunction. These findings highlight an urgent need for targeted university-based screening programs, academic accommodations, and de-stigmatization campaigns to facilitate early intervention and improve educational outcomes in this population.

Background: Biopsychosocial factors associated with functional changes, including changes in personality, communication, movement, and weight, were evaluated in individuals with Down syndrome (DS) during the COVID-19 pandemic. Method: Caregivers of individuals with DS (aged [&ge;]12, n = 118) completed an online survey. Elastic net regression with bootstrap resampling assessed 31 candidate predictors. Results: Pandemic-related mental health was most strongly associated with functional changes ({beta} = 0.388). Healthcare access barriers were also reliably selected: inability to access mental health treatment, difficulty affording insurance, difficulty accessing specialists, and residing in a low-income health professional shortage area. The model explained 35.2% of variance. Conclusions: Mental health and healthcare access barriers were biopsychosocial correlates of functional changes for people with DS during COVID-19.

Objective: Neuropsychiatric presentations are common across neurological and mental health services but they are often inadequately covered by core clinical psychology and clinical neuropsychology training. Consequently, we aimed to identify components for a neuropsychiatry curriculum for clinical psychologists using a Delphi process. Method: We completed a three-round e-Delphi study with 19 experts (clinical psychologists, neuropsychologists, psychiatrists, neurologists, individuals with lived experience of neuropsychiatric disorders). Round 1 collected ratings on 80 syllabus items derived from textbook reviews, conference topics, and a scoping review of neuropsychiatry syllabuses. Items failing to reach consensus were refined, and new topics added via free-text suggestions. Rounds 2 and 3 repeated rating and thematic analysis, culminating in a consensus meeting where items were classified as core or supplementary. Consensus thresholds were set at mean>=2.0, mean distance from the mean<=0.2, and => 75% agreement for final decisions. Results: The process yielded 40 core and 38 supplementary syllabus items. Core topics include autoimmune and neuroinflammatory disorders, delirium, functional neurological disorders, neuropsychiatric sequelae of epilepsy, stroke, traumatic brain injury, dementia, and multidisciplinary working, among others. Supplementary items covered background knowledge of less frequent but still prevalent disorders as well as competencies in interpreting clinical data alongside conceptual and historical issues. The final component list reflects both clinical competencies and emerging areas of practice, emphasising assessment, formulation, psychological interventions, cultural considerations, and medicolegal aspects. Conclusions: The e-Delphi derived curriculum provides a framework for neuropsychiatric competencies for postgraduate psychology training with modification needed for application in diverse healthcare settings.

Background: Concerns about "AI psychosis" have swirled in the media since ChatGPT's release, but few systematic analyses exist. We therefore conducted an electronic health record (EHR) analysis to identify the frequency, clinical characteristics, and quality of AI interactions in patients experiencing psychosis treated in a medical center. Methods: AI keywords (e.g., ChatGPT, AI) were used to search Vanderbilt University Medical Center's EHR from 12/1/2022-4/1/2026. Records were discarded if they were not AI-related or if the primary diagnosis did not include psychosis. Three raters read notes to determine if a patient was experiencing AI psychosis and classified the interactions using 4 a-priori categories (Catalyst, Amplifier, Co-Author, Object) formulated to explain how AI-related negative outcomes emerge. Findings: 73 patients met our criteria. 28 patients were rated as experiencing AI psychosis, 17 had neutral interactions, and 28 expressed delusional content related to AI without documented evidence of conversational AI use. ChatGPT was the matching keyword for 53.6% patients experiencing AI psychosis. The majority of AI psychosis cases were documented after ChatGPT's "4o" model was released in May 2024. Notably, the AI Psychosis group had significantly more patients experiencing a first psychotic episode (60.7%) compared to the other two groups. Amplifier was the most common (64.3%) qualitative rating in the AI Psychosis group. Interpretation: "AI psychosis" is an infrequent but real phenomenon observed in clinical practice. Most affected patients were experiencing their first psychotic episode and presented with AI psychosis following the release of the more sycophantic GPT-4o. Among the affected patients, AI most often exacerbated an existing condition by reinforcing distorted ideas.

BackgroundA high proportion of autistic people receive off-license antipsychotic medication, often in the absence of a mental illness, primarily for behaviours that challenge, which is a public health concern. Although meta-analyses have been published recently, there is a lack of a comprehensive network meta-analysis to inform clinicians about the relative efficacy and safety of antipsychotic medications. AimsTo conduct a network meta-analysis of available RCTs of antipsychotic medications involving autistic participants to assess the relative efficacy of different antipsychotics and their adverse effects. MethodWe searched seven databases and hand-searched ten relevant journals. Two authors independently screened titles, abstracts, and full papers, extracted data, and assessed their quality. ResultsWe analysed data from 22 RCTs involving 1562 autistic people. The largest mean difference with 95% confidence interval in the Aberrant Behaviour Checklist-Irritability (ABC-I) score compared with placebo was from the combined intervention with risperidone and parent training: -11.16 (-15.13, -7.18), followed by risperidone: -7.59 (-9.22, -5.95), and aripiprazole: -5.59 (-7.18, -4). The largest effect on Clinical Global Impression-Improvement (CGI-I) scores was from risperidone, 7.65 (2.17, 27.04), followed by aripiprazole, 7.02 (1.92, 25.72), compared with placebo. Risperidone (4; 1.57, 10.21) and aripiprazole (2.77; 1.20, 6.39) had significantly higher odds ratios for adverse effects, but aripiprazole showed the least weight gain. ConclusionsCombined parent training and risperidone followed by risperidone and aripiprazole showed the best effects on the ABC-I score, whereas risperidone and aripiprazole showed the greatest effect on the CGI-I score. However, risperidone and aripiprazole showed significantly increased adverse effects.

Background Multimorbidity is increasingly prevalent, and associated with worse clinical and psychosocial burdens. Interoception, the brain's ability to sense and interpret internal bodily signals, may contribute to multimorbidity, through its link with health behaviors, stress regulation, and mental health. This study examines whether self-reported interoceptive accuracy and attention is associated with multimorbidity, by identifying multimorbid subgroups and their interoceptive profiles. Methods Morbidity classes were identified through latent class analyses in two Dutch survey datasets, focusing on depression and alexithymia (DA-dataset; N = 671) and lifestyle factors (L-dataset; N = 1022). Linear regression analyses were used to assess interoceptive accuracy and attention (by the Interoceptive Accuracy Scale and Interoceptive Attention Scale respectively) among different subgroups. Results Multimorbid subgroups were characterized by older age, low socioeconomic position, and elevated physical, psychological, and behavioral problems. Multimorbid classes exhibited lower interoceptive accuracy (DA-dataset: B = -1.14, 95% CI = [-2.89, 0.62]; L-dataset: B = -2.36, 95% CI = [-3.83, -0.89]) and higher attention (DA-dataset: B = 3.62, 95% CI = [0.97, 6.27]; L-dataset: B = 1.07, 95% CI = [-1.42, 3.56]) compared to healthier classes. Conclusion Multimorbid populations demonstrated lower interoceptive accuracy and higher interoceptive attention. This highlights the psychosocial complexity of multimorbid populations which may impact their self-management and health behavior. These findings underscore the need to expand treatments to include psychosocial domains for multimorbid patients.

Objective: Cross-sectional studies indicate associations between self-reported social media use and adolescent wellbeing outcomes. We aimed to evaluate longitudinal associations of objectively measured smartphone and social media use with psychosocial wellbeing. Design: Observational study with one year of follow-up Setting: High schools in Finland from 2022 to 2023 Population: 259 adolescent girls (mean age 16.3 years at baseline) Main outcome measures: screenshots depicting smartphone and social media use, Bergen Social Media Addiction Scale (BSMAS), Generalized Anxiety Disorder-7 questionnaire, Body Appreciation Scale 2 (BAS-2) and visual analogue scales (VAS) of mood, tiredness, and loneliness Results: Across one year of follow-up, anxiety, body appreciation, and mood improved, but possible social media addiction increased from 15% to 17%. Social media addiction at baseline was associated with increased anxiety (r=0.29, p<0.001), lower body appreciation (r=-0.15, p=0.022), and more loneliness (r=0.20, p=0.001) at follow-up. Anxiety at baseline was associated with social media addiction at follow-up (r=0.19, p=0.005). The highest quartile of TikTok users reported more social media addiction (BSMAS 19 [IQR 16-21] vs. 17 [IQR 14-20]; p=0.009) and lower body appreciation (BAS-2 32 [IQR 28-38] vs. 35 [IQR 29-40]; p=0.003) than did others. The highest quartile of Snapchat users reported more social media addiction (BSMAS 19 [IQR 15-21] vs. 17 [IQR 14-20]; p=0.007) and tiredness (VAS 21 [IQR 13-32] vs. 26 [IQR 15-35]; p=0.049) than did others. Conclusions: Consistent with cross-sectional studies, social media addiction was associated with poorer psychosocial outcomes across follow-up. Policies to protect adolescents from social media addiction are urgently needed.

Recent advances in artificial intelligence (AI) have raised interest in its potential to similarly progress biological psychiatry. This study investigates the current utility of AI models in predicting psychiatric phenotypes in youth - a critical window for psychiatric diagnosis - using neuroimaging data from a large developmental clinical cohort. We assessed the predictive performance of machine learning models on diverse psychiatric and non-psychiatric targets. We show that while models are able to predict various targets from EEG and fMRI data, simple models using only readily-available factors such as demographics and recording site match their performance for clinical phenotypes. This pattern holds across clinical targets and replicates for state-of-the-art deep neural networks, suggesting that either neuroimaging data contains limited disease-specific information or that current methods cannot reliably identify such patterns. These benchmarking results provide important context regarding promises of modern AI in the field of biological psychiatry with a focus on youth.

Prader-Willi syndrome (PWS) is a rare multisystemic disorder characterized by obesity, endocrine dysfunctions, and psychiatric comorbidities, which imply frequent use of psychotropic medications. They account for atypical responses to standard dosages of psychiatric drugs. Pharmacogenetics could be part of the reason for this situation, potentially offering a valuable tool for individualized treatment. This study analyzed allelic and phenotypic frequency distributions of five of the main cytochrome P450 enzymes (CYP2D6, CYP2B6, CYP2C19, CYP2C9, CYP3A4) involved in psychiatric drug metabolism in 47 patients with genetically confirmed diagnosis of PWS and compared them to reference frequencies in the general European population. Allelic frequency comparisons between the European reference population and the overall PWS cohort revealed a significant global difference for CYP2B6, with CYP2C19 and CYP2D6 showing trends toward significance. Although no global allelic differences remained significant after false discovery rate correction, post-hoc analyses consistently identified an enrichment of reduced- or non-functional alleles CYP2B619 and CYP2D610 in patients with PWS. Predicted metabolizer phenotype analyses showed a significant shift toward intermediate metabolizers of CYP3A4 in the PWS cohort, with corresponding depletion of normal metabolizers. Subgroup analyses indicated that allelic differences were more pronounced in maternal uniparental disomy and non-deletion subtypes, particularly for CYP2B6, although no significant differences were observed between PWS genetic subtypes. Overall, results imply potential differences in metabolizing activity in PWS patients, and subsequent implications in drug efficacy and tolerability. These results support the idea that pharmacogenetic testing may improve therapeutic decision-making in PWS for psychiatric treatment. Larger studies are needed to confirm these preliminary results.