Psychiatry and Clinical Neurosciences

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.

ObjectiveLate adolescence is a critical developmental period that typically precedes psychosis onset, yet the neural correlates of subclinical hallucinatory experiences that may impact psychosis risk are poorly understood. Given evidence from adult psychosis models implicating abnormal "triple network" connectivity among the frontoparietal (FPN), default mode (DMN) and salience/cingulo-opercular (CON) networks, as well as dopaminergic abnormalities, we examined whether hallucinatory experiences in adolescents are associated with altered triple network organization and dopamine-related measures in the midbrain. MethodsWe performed a cross-sectional analysis of 171 community adolescents aged 14-17 who underwent resting-state functional magnetic resonance imaging and neuromelanin-sensitive MRI. Hallucinatory experience severity was measured using the Specific Psychotic Experiences Questionnaire. Resting-state functional connectivity was calculated among a priori DMN, FPN, and CON cortical regions; we examined associations between connectivity, hallucinatory experience severity, within-network connectivity, system segregation, and neuromelanin signal in the ventral tegmental area (VTA). ResultsGreater hallucinatory experience severity was associated with stronger connectivity in a subnetwork composed of CON-DMN and CON-FPN edges. Greater hallucinatory experience severity was also associated with lower global network segregation. VTA neuromelanin signal was not directly associated with hallucinatory experience severity, but greater VTA signal predicted lower connectivity in the hallucination-related subnetwork. Greater VTA neuromelanin signal was also associated with a distinct pattern of stronger connectivity within DMN midline regions. ConclusionsThese findings implicate altered triple network organization in hallucinatory experiences during late adolescence and suggest that dopamine-related midbrain signal may reflect broader developmental variation in cortical network organization rather than symptom severity directly. Plain Language SummaryHallucinatory experiences during adolescence may signal increased risk for later psychotic disorders, but their brain basis is unclear. We studied 171 adolescents aged 14-17 using resting-state fMRI to measure brain network activity and neuromelanin-sensitive MRI to estimate dopamine-related midbrain signal. More severe hallucinatory experiences were linked to abnormal communication among three brain networks often implicated in psychosis. Dopamine-related signal was not directly related to hallucination severity but was associated with developmentally relevant network organization. Overall, this work serves to improve our understanding of the risk factors that may contribute to psychosis conversion in adulthood.

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.

BackgroundSchizophrenia is associated with widespread cognitive impairments. Several early risk factors for schizophrenia have been identified, and some studies suggest associations between these early risk factors and cognition, yet the literature is sparse in psychosis. MethodsClinical cohorts of child/adolescent and adult patients with first-episode psychosis (FEP) and healthy controls (HC) were linked with register-based information (N=276). Gestational age, Apgar scores, birth weight and length, parental age, and season of birth were extracted from the Danish medical birth registry. Cognition was assessed at time of diagnosis using BACS, CANTAB, and WAIS-III/WISC-IV. Missing data was imputed using MICE. Canonical correlation analysis (CCA) was used to examine patterns of associations. Post hoc analyses explored group differences according to diagnosis, age, and sex. ResultsCCA resulted in two significant patterns of associations. CCA1 was stable across imputations (r=0.44, p=.036, pmin= .017, pmax= .055), and constituted by a risk profile of lower maternal age, lower birth length, being small for gestational age, and lower birth weight and a cognitive profile of lower estimated IQ and poorer working memory, mental flexibility, processing speed, verbal fluency, and motor latency. The pattern was more expressed in FEP compared to HC and in adults compared to children. CCA2 was more unstable across imputations (r=0.38, p=.033, pmin=.003, pmax=.168) and constituted by a broad pattern of minor loadings. ConclusionCognitive functioning later in life is associated with multiple early risk factors, underscoring the complexity of developmental processes and the importance of the early developmental context in shaping cognitive trajectories.

In a single-blind randomized controlled trial, we investigated the effectiveness of real-time fMRI neurofeedback delivered in 7 runs over three sessions across two weeks in N = 65 patients with alcohol use disorder. The intervention targeted modulation of ventral striatal cue reactivity to alcohol-related cues as well as enhancement of prefrontal control mechanisms in the right inferior frontal gyrus. The study design incorporate three experimental groups that either were instructed to downregulate a ventral striatum signal, upregulate the right inferior frontal gyrus, or upregulate negative functional connectivity between these two structures. In two active control groups participants were instructed to either up- or downregulate the primary auditory cortex. We did not find an effect of ventral striatal downregulation or negative connectivity feedback, and a reduced striatal activation in the right inferior frontal gyrus upregulation group was accompanied by concurrent lower activation in the target structure, suggesting that our intended modulation approaches were not effective. Identified problems that might have contributed to this unexpected outcome might have been the use of continuous feedback presentation that potentially confuses regulation target and reward processing in the ventral striatum, counterintuitive regulation directions, a lack of explicit strategy guidance and transparency about the targeted process, and generally the difficulty to recruit a sufficient number of eligible voluntary participants for a well-powered study with a complex design. These insights emphasize the complex challenges of real-time fMRI neurofeedback interventions for the treatment of substance use disorders and could provide guidance for the development of more effective future approaches.

Background: Tobacco use is prevalent in clinical high risk for psychosis (CHR-P) population and has widespread negative health consequences, but understanding of its neural substrates is limited. Abnormal default mode network (DMN) may underlie tobacco dependence in CHR-P. We investigated how tobacco use relates to DMN connectivity and how CHR-P status impacts this relationship. Methods: We used baseline substance use and resting-state functional magnetic resonance imaging data from the North American Prodrome Longitudinal Study (NAPLS2; CHR-P: n=211, mean age 19.2, 37.9% female; healthy control: n=132, mean age 19.9, 47.7% female). Voxel-wise connectivity was calculated from the left lateral parietal (LLP) node of the DMN to the rest of the brain. We regressed LLP-brainwide connectivity against tobacco use frequency in the past month to generate a spatial map of how connectivity relates to current tobacco use. Results: Brainwide connectivity analysis identified two clusters in R hippocampus (peak voxel at MNI [+30,-12,-27]) and in L parahippocampus (peak voxel at MNI [-27,-27,-27]), where higher LLP-cluster connectivity was associated with more frequent tobacco use. LLP - R hippocampus connectivity was higher in current tobacco users compared to non-tobacco users (t=-3.5466, df=101.88, p=0.0006), and higher in CHR-P than controls (t=-2.8651, df=279.47, p=0.0049). Among current tobacco users, there was a significant tobacco-by-diagnosis interaction on LLP - R hippocampus connectivity (estimate=0.306, SE=0.149, t=2.051, p=0.045) such that heavier tobacco use predicted hyperconnectivity only in CHR. Conclusions: More frequent tobacco use was associated with higher DMN-hippocampal connectivity in both CHR-P and controls. CHR-P diagnosis enhanced this relationship.

Background: Prior neuroimaging suggests brain differences between children with attention deficit hyperactivity disorder due to prenatal alcohol exposure (ADHD+PAE) and non-exposed children with ADHD due to other, e.g., familial, causes (ADHD-PAE). There has been interest in regional brain levels of ;gamma-aminobutyric acid (GABA) and glutamate (Glu) measured in vivo with magnetic resonance spectroscopy (MRS) as possible indicators of local inhibitory, respectively, excitatory activity in ADHD. For the first time, we report here a comparison of GABA and Glu in ADHD+PAE vs. ADHD-PAE. Methods: At 3 T, we used J-difference-edited single-voxel MRS to assay GABA and Glu in 28 children with ADHD+PAE, 20 with ADHD-PAE, and 28 typically developing (TD) controls, all aged 8-14 years. MRS was sampled from midline anterior middle cingulate cortex (aMCC), the cognitive cingulate considered functionally relevant to ADHD. Spectra were fit with custom software, including a unique technique for isolating the GABA signal from the confounding macromolecular baseline (MMBL). Results: aMCC GABA was higher in ADHD+PAE and ADHD-PAE than in TD. GABA increased with age in TD, but not in ADHD+PAE or ADHD-PAE. Similar effects were observed for the ratios GABA/Glu and GABA/Glx. For GABA+MMBL (GABA+) these effects were not seen, rather GABA+ and MMBL increased with age for the ADHD+PAE group only. No significant effects were found for Glu or Glx. Conclusions: GABA in the aMCC does not distinguish the two etiologies of ADHD, rather elevated GABA that follows an abnormal developmental appears to be common to both. High GABA may reflect increased inhibition of the aMCC impairing its cognitive functions. GABA+ results in ADHD may not tract reliably with underlying GABA values. Negative results for Glu and Glx should be reexamined at shorter echo-times.

BackgroundDeep brain stimulation (DBS) is effective for approximately two-thirds of patients with treatment-resistant obsessive-compulsive disorder (OCD). While prior work has emphasized the engagement of specific white matter tracts in mediating outcomes, the contribution of region-specific white matter integrity to clinical response remains unclear. MethodsTwelve patients with treatment-resistant OCD underwent preoperative neuroimaging and DBS at our center. We assessed OCD severity preoperatively and at [~]18 months postoperatively. We extracted mean fractional anisotropy (FA) for the anterior limb of the internal capsule (ALIC) and a control tract and used Spearmans rank correlations to evaluate associations between FA and symptom improvement. We additionally evaluated this relationship for 49 white matter bundles. Finally, we used diffusion tractography to determine endpoints connected with ALIC voxels most predictive of symptom improvement. ResultsHigher preoperative ALIC FA was associated with greater clinical improvement following DBS (p=0.002). This effect was specific to the ALIC and not the control tract. Hemispheric asymmetry (right>left) in ALIC FA was moderately correlated with clinical improvement. Among all 49 bundles, the right ALIC demonstrated the strongest association with clinical improvement. Streamlines passing through the ALIC voxels that most strongly correlated with outcome ended in the diencephalon and superior frontal cortex. ConclusionsBaseline structural integrity of the ALIC was associated with the magnitude of clinical improvement following DBS for OCD. These findings suggest that regional variation in white matter integrity may reflect an underlying circuit disruption amenable to DBS, supporting the use of neuroimaging-based metrics as potential biomarkers in DBS treatment.

Abstract Schizophrenia (SCZ) and bipolar disorder (BPD) are highly heritable psychiatric disorders with complex polygenic architectures. Genome-wide association studies (GWASs) have identified numerous common variant associations, but rarer variants detectable through whole-genome sequencing (WGS) remain underexplored. We conducted rare variant association analysis using WGS data from the Portuguese Island Collection (PIC), including 28 families with SCZ (n = 53) and 41 families with BPD (n = 83) cases, and population controls (n = 62). Following ANNOVAR and CADD annotation, burden analysis of deleterious variants showed that both affected and unaffected family members from SCZ and BPD pedigrees had significantly higher burdens of rare deleterious variants compared to controls (p < 0.0001), with no significant differences observed between affected and unaffected relatives, consistent with shared familial genetic liability. Polygenic Risk Score (PRS) analysis confirmed significant genetic contributions to both disorders within PIC. Association analyses were subsequently performed using SAIGE-GENE+ identifying 483 and 583 nominally significant (suggestive associations) gene sets (p-value [&le;] 0.05; FDR > 0.05) for SCZ and BPD, respectively, including gene sets related to neurotransmission, synaptic function and structure, neurodevelopment, and neuroinflammation as well as major signaling pathways. Cross disorder overlaps also identified shared suggestive enrichment of GABA and glutamate signaling, synaptic signaling, and Wnt signaling gene sets in both SCZ and BPD. These findings support shared rare variant burden within multiplex psychiatric families and highlight the role of gene-set based rare variant analysis in identifying neurobiological pathways relevant to SCZ and BPD. Keywords: WGS, Rare Variants, Schizophrenia, Bipolar Disorder

Objective: To test whether two brief mania measures, the Parent General Behavior Inventory-10 Mania form (PGBI-10M) and 7-Up, retain useful psychometric properties in a large population cohort, and to evaluate whether the PGBI-10M can identify Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS)-defined bipolar spectrum disorders in that setting. Method: Analyses used 11,000+ youths across late childhood and early adolescence from the Adolescent Brain Cognitive Development (ABCD) Study. For both PGBI-10M and 7-Up, we estimated descriptive statistics, internal consistency, confirmatory factor models, graded response models, and measurement-based care benchmarks (minimally important difference, reliable change, and clinical cutpoints). For the PGBI-10M, receiver operating characteristic (ROC) analyses estimated concurrent classification accuracy for bipolar diagnoses at baseline and 2-year follow-up and compared area under the curve (AUC) values with prior outpatient and community mental health samples. Results: Scores were lower than in clinical samples, but both measures remained psychometrically sound. The PGBI-10M showed alpha=.87-.88 and omega=.88; the 7-Up showed alpha=.78 and omega=.79. Longitudinal analyses indicated threshold differences across waves, likely reflecting caregiver recalibration and developmental changes, with modest impact on estimates. ABCD-based benchmarks supported meaningful and reliable change. The PGBI-10M discriminated bipolar cases (AUC=0.68 baseline; 0.77 follow-up), though performance was lower than in clinical samples. Positive predictive values were low in this population. Conclusion: The PGBI-10M and 7-Up support monitoring of manic and mixed symptoms, but the PGBI-10M alone is insufficient for universal bipolar screening. Brief mania scales are best used for targeted assessment and longitudinal monitoring within multi-informant workflows.

Evidence from many countries shows that later life cognitive health is shaped by childhood poverty. However, whether it is associated with neurodegenerative biomarkers measured in population settings remains unclear. Methods We conducted a pooled analysis of 5,473 adults aged [&ge;]50 years from Denmark, Sweden and Germany participating in Wave 6 (2015) of the Survey of Health, Ageing and Retirement in Europe. Neurodegenerative biomarkers (neurofilament light chain, glial fibrillary acidic protein and phosphorylated tau) were assayed from dried blood spots. Childhood poverty was constructed as a latent variable from retrospective life histories. Weighted Poisson regression models estimated associations adjusting for age, sex, education, marital status and wealth in later life. Marginal predictions along age and across country were derived. Results Childhood poverty was strongly associated with higher NfL concentrations ({beta}=1.66, p<0.001), but not with GFAP or p-tau217. Predicted values indicated substantially elevated NfL among the childhood poor (10.3 pg/mL vs 2.0 pg/mL for the non-poor). Age profiles showed widening disparities: the childhood poor in midlife exhibited higher NfL levels than the oldest old who grew up not poor. No consistent differences were observed for GFAP or p-tau217. Findings were robust and similar across all three countries with different histories and health systems. Conclusions Childhood poverty is associated with markedly elevated levels of NfL in later life, suggesting long-term neuroaxonal injury consistent with life course shaping of brain health. Moreover, the evidence implies substantial acceleration of neurobiological ageing. These findings emphasise the importance of early-life interventions for brain health in ageing populations.

ObjectiveObsessive-compulsive disorder (OCD) frequently co-occurs with bipolar disorder (BD) or schizophrenia (SCZ), and, importantly, can often precede their onset. However, the genetic architecture and directionality underlying these relationships remain unclear. We leveraged large-scale genome-wide association study (GWAS) data to examine shared genetic architecture and directional relationships among OCD, BD and SCZ, and used major depressive disorder (MDD) as a comparator. MethodsUsing linkage disequilibrium score regression (LDSC), MiXeR, and Generalized Summary-data-based Mendelian Randomization (GSMR) as well as complementary Mendelian randomization approaches, we characterized genetic correlations, polygenic overlap (Dice coefficient), and effect direction concordance ({rho}{beta}) across disorders. ResultsWe observed substantial genetic correlations between OCD and BD (rg=0.37), BD type 2 (BD2) (rg=0.54), and SCZ (rg=0.39), with a large proportion of shared causal variants between OCD and both BD (Dice=0.85) and SCZ (Dice=0.84). MiXeR analyses indicated that OCD and BD2 share a smaller proportion of causal variants (Dice=0.57) but there is a high concordance of effect directions amongst these causal variants ({rho}{beta}=0.96), whereas OCD and MDD showed minimal overlap but strong concordance among shared variants (Dice=0.09, {rho}{beta}=1). Directional GSMR and complementary TwoSampleMR analyses supported a causal effect of genetic risk to OCD on liability to BD (b=0.20, p=1.5x10{square}{square}), SCZ (b=0.52, p=9.5x10{square}{superscript 2}{superscript 1}), and MDD (b=0.24, p=1.06x10{square}{square}), with little evidence for reverse causal effects. ConclusionsTogether, these findings indicate that genetic liability to OCD can represent an early component of transdiagnostic psychiatric risk, with implications for understanding and potentially predicting the emergence of broader psychopathology across the life course.

Background and Hypothesis: Environmental exposures linked to schizophrenia may play a role in shaping long-term clinical outcomes among individuals with psychotic disorders. This study examined whether the Maudsley Environmental Risk Score (ERS), a cumulative measure of five established environmental risk factors, predicts trajectories of symptoms, cognition, and psychosocial functioning over 25 years following first hospitalization for psychosis. Study Design: Participants were drawn from the Suffolk County Mental Health Project, a longitudinal cohort of individuals with first-admission psychosis assessed six times over two decades. A total of 516 participants had sufficient ERS data and repeated assessments of symptoms (SAPS, SANS), cognitive ability, and functioning (GAF). Study Results: Linear mixed-effects models showed that higher ERS was significantly associated with lower global functioning ({beta} = -0.104, p = 0.008), an effect that remained consistent over time. ERS also predicted more severe and worsening reality distortion ({beta} = 0.082, p = 0.023 for intercept; {beta} = 0.005, p = 0.032 for slope of time). No significant associations were observed between ERS and cognitive ability, disorganization, or negative symptoms. Conclusions: These findings highlight the contribution of environmental risk to functional impairment and persistent positive symptoms across the course of psychotic illness. Incorporating ERS into clinical risk models may aid the identification of individuals likely to experience a more severe illness trajectory, and inform long-term treatment planning.

Mental illness poses a substantial global burden, yet existing psychotherapies and psychopharmacologies often produce limited outcomes. Psychedelic assisted therapies have emerged as potential transdiagnostic interventions. In particular, 3,4 methylenedioxymethamphetamine assisted therapy (MDMA AT) has generated interest for its rapid psychological effects and potential to enhance psychotherapy outcomes. However, the incremental efficacy of MDMA AT relative to control interventions across transdiagnostic outcomes remains unclear. Further, there have been emerging concerns regarding harm reporting quality in MDMA AT clinical trials. We conducted a systematic review and meta analysis of MDMA AT randomized controlled trials. Eleven publications representing eight controlled trials with 10 analyzed subgroups (n = 295 participants) were included in meta-analyses. Two additional secondary publications were included for harm reporting syntheses (k = 13 total). Across 114 extracted effect sizes, MDMA AT demonstrated a significant moderate-to-large incremental reduction in psychopathology relative to controls (g = 1.03, 95% CI [0.46, 1.60]), though heterogeneity was high (I squared = 76%). Incremental effects were larger versus inert placebos (g = 1.27) than active controls (g = 0.75). Symptom specific analyses indicated strong incremental effects for trauma reduction (g=1.46 [95% CI: 0.67, 2.25]) and smaller non-significant effects for depression (g=0.51 [95% CI: -0.06, 1.08]). Harm reporting quality synthesis showed only 23% of publications met high-quality reporting standards. Overall, MDMA AT demonstrates potential transdiagnostic efficacy, but small samples, confounding factors, and mediocre harm reporting highlight the need for larger more transparent clinical trials.

Delirium, a dynamic neuropsychiatric condition associated with morbidity and mortality, remains underdiagnosed due to reliance on subjective, intermittent screening tools. Objective and potentially continuous identification is needed to improve clinical care. We developed and validated an analytic framework for delirium classification based on automatically extracted video features. In this prospective cohort study, patients ([&ge;] 18 years) admitted to the inpatient medical or neurological ward of a tertiary academic center between August 2020 and March 2022 with an expected stay longer than one night were enrolled. Daily structured delirium assessments and brief video recordings were performed in consenting patients. Videos were analyzed using deep learning pose estimation to extract keypoints and calculate behavioral features based on eye, face, and limb postures and movements. Four machine learning models (logistic regression, gradient boosting, support vector machines, and random forests) were trained to predict delirium status from extracted features. Model performance was evaluated on 20 repetitions of three-fold cross-validation using the area under the curve of the receiver operating characteristics curve (AUC ROC). The cohort included 109 videos from 25 male and 25 female participants (median age: 72, IQR: 63.25-78). Twenty videos (18%) were from patients with delirium. Keypoints for this dataset were more accurately extracted using a customized ResNet-101 model developed with DeepLabCut (sensitivity 0.94, specificity 0.89, compared to human-labeled gold standards) than using off-the-shelf models. Keypoints were then used to generate behavioral features summarizing movement and postures throughout the video. A support vector machine model achieved an average delirium classification AUC ROC of 0.79 (SD {+/-} 0.09), sensitivity of 0.71 (SD {+/-} 0.16), and specificity of 0.78 (SD {+/-} 0.07). This study demonstrates the feasibility of identifying delirium using brief videos in clinically heterogeneous cohorts and reveals novel features for objective identification. Author SummaryDelirium is a sudden change in attention and awareness that commonly affects hospitalized patients. It is linked with longer hospital stays, cognitive decline, and death. Patients with delirium often show changes in movements and behaviors such as slowed movement, restlessness, or excessive scanning of the environment. Since current screening tools rely on intermittent human interactions, they can be subjective and miss the fluctuating nature of delirium, leading to underdiagnosis. We sought to explore whether short video recordings could be used to detect delirium automatically. In our study, we enrolled 50 hospitalized patients and conducted daily delirium assessments and video recordings. We used a machine learning model to analyze patients eye movements, facial expressions, and body postures. We found that video-derived features could be used to identify delirium in a small clinical cohort. While needing further validation in outside cohorts, this study shows an important proof-of-concept for objective delirium monitoring in heterogeneous clinical contexts without adding burden to clinical staff.

Lower cognitive ability measured in childhood or late adolescence has been consistently associated with higher mortality risk across adulthood. However, this evidence largely relies on single assessments, leaving it unclear to what extent mortality risk reflects cognitive differences established early in life versus developmental divergence during adolescence - a period of substantial neurocognitive plasticity. Using two nationally representative Swedish cohorts comprising 9,412 males born in 1948 and 1953, we linked cognitive ability assessed in primary school at age 13 years and military conscription at age 18 years to all-cause and cause-specific mortality recorded in nationwide registers through 2025. We decomposed late-adolescent cognitive ability into childhood cognitive level and adolescent cognitive change and evaluated their independent associations with mortality. Childhood cognitive level (HR = 0.81; 95% CI, 0.78-0.85) and adolescent cognitive change (HR = 0.84; 95% CI, 0.79-0.89) independently predicted lower mortality risk, also after adjustment for parental education. Childhood cognitive level and adolescent cognitive change showed partially distinct cause-specific patterns. Childhood cognitive level was most strongly associated with mortality from intrinsic causes, whereas adolescent cognitive change showed relatively stronger associations with external causes, particularly accidental deaths. Although adolescent cognitive change was associated with psychosocial factors including education and psychiatric diagnosis at conscription, its association with mortality persisted after adjustment for these factors. These findings suggest that cognitive development during adolescence carries independent prognostic information regarding long-term survival beyond cognitive level established by late childhood, highlighting adolescence as a consequential period for lifelong health.

Background: Self-reported confidence in health information seeking does not reliably predict accurate health knowledge, yet the population-level distribution of this discordance and its demographic predictors have received limited direct study. This study aimed to identify and characterize a Confident-Incorrect phenotype among U.S. adults: individuals with high perceived health information competence who simultaneously hold inaccurate or fatalistic beliefs about cancer. Methods: Cross-sectional analysis of HINTS 7 (N = 7,278). A Confidence Index (3-item digital literacy composite (Cronbach's = 0.674) and an Evidence-Consistent Knowledge Score (factual cancer knowledge minus a cancer fatalism composite; fatalism subscale = 0.563) were computed and combined into a discordance framework. Median-split classification produced four phenotypes. Gaussian Mixture Model clustering with four components provided moderate independent validation (inter-method agreement = 65.2%). Survey-weighted multinomial logistic regression (n = 5,771; McFadden pseudo-R2 = 0.129) examined phenotype predictors. Results: An estimated 20.3% of U.S. adults were classified as Confident-Incorrect. They reported confidence levels similar to Well-Informed adults (z = 0.72 vs. 0.82) but scored 2.8-fold lower on objective cancer knowledge (0.74 vs. 2.06 out of 4) and exhibited the highest cancer fatalism of any phenotype (3.17 vs. 1.65 out of 4). Only 14.3% correctly identified alcohol as a cancer risk factor (vs. 58.8% of Well-Informed adults). Cancer screening rates did not differ meaningfully across phenotypes. Lower education (OR = 0.754), Hispanic ethnicity (OR = 1.788), non-Hispanic Black race (OR = 1.893), higher social media use (OR = 1.097), and lower trust in scientists (OR = 0.749) independently predicted Confident-Incorrect membership. Conclusions: An estimated one in five U.S. adults is overconfident in health information competence while holding substantially inaccurate beliefs about cancer prevention. Cancer screening rates did not follow the expected gradient across phenotypes, a null finding that cautions against inferring immediate behavioral impact from observed belief gaps. Interventions targeting specific factual errors and cancer fatalism are more likely to reach this group than general health literacy programs.

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.

The ability to adjust to changing environments (cognitive flexibility) and optimal decision-making are pivotal brain functions that govern successful human behavior. Anxiety and depressive disorders are strongly pervasive psychiatric conditions across the lifespan that profoundly disrupt mechanisms of attention, working memory, and decision-making. Although existing task evidence documents impaired decision-making and flexibility outcomes for both anxiety and depression, there is a growing need to systematically evaluate the role of anxiety and depression and to quantitatively compare the effects of these disorders on these domains. In the present study, we conducted a meta-analysis of anxiety and depression on decision-making and cognitive flexibility. We utilized a random-effects approach, given that a large amount of between-subject heterogeneity was anticipated. Given the scope of this meta-analysis, we used the machine learning tool asReview to more efficiently conduct a meta-analytic search. Across all outcomes, results showed anxiety and depression were associated with reduced cognitive flexibility and decision-making. These effect sizes were then tested for significance using a fixed-effects (plural) model. Subgroup analyses revealed no significant differences between anxiety and depression for either decision-making or flexibility outcomes, consistent with a transdiagnostic perspective. Results are contextualized in light of the biopsychosocial model and potential transdiagnostic factors.

Background. Something in discourse with a person experiencing psychosis often "feels off" before formal assessment is completed, yet this disturbance has not been quantified at the level of ongoing dyadic conversation. Prior work has largely treated patient speech in isolation, limiting our capacity to measure how communicative disruption emerges within clinical exchange. Methods. We applied a three-level decomposition of conversational alignment in 109 patients with psychotic disorders (26 female) and 60 healthy controls (22 female) at baseline and 12 months (n = 115). Register divergence (dAUCnorm) captured lexical distance between interviewer and patient; embedding-based synchrony (rembed) measured semantic trajectory coupling; within-speaker coherence was computed separately for each speaker. We used linear mixed-effects models adjusted for timepoint and participant clustering. Results. Patients showed significantly greater lexical-semantic divergence from the interviewer (d = 0.48, p < .001) and reduced embedding-based synchrony (d = -0.59, p < .001), both effects replicating at each time point. Critically, the interviewer's within-speaker coherence was reduced during conversations with patients (d = -0.33, p = .016), indicating that the disruption extends beyond the patient to the interaction itself. Register divergence tracked impoverished thinking and synchrony tracked disorganized thinking (both FDR-corrected q = .038). Group differences were persistent at 12 months, indicating a partially stable profile. Conclusions. Conversational alignment in psychosis reveals a dyadic failure of semantic coordination that destabilizes the interviewing clinician's coherence even when patient narrative continuity is preserved. These transcript-derived alignment metrics offer a scalable approach to quantifying interpersonal communicative function from routine clinical encounters.