Visual-motor integration (VMI) impairment is common in Attention-Deficit/Hyperactivity Disorder (ADHD), yet its underlying neurobiological basis remains unclear. This study aimed to explore the characteristics of VMI in children with ADHD and its statistical role in the association between functional connectivity (FC) and core symptoms. A total of 332 children with ADHD and 103 healthy controls (HC) completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI). Group comparisons and dimensional correlation analyses were performed to explore the VMI characteristics of children with ADHD. Subsequently, 127 children with ADHD and 91 HC children underwent resting-state functional near-infrared spectroscopy. Mediation analyses were performed to investigate the role of VMI in the relationship between atypical FC and core symptoms of ADHD. Children with ADHD exhibited deficits in VMI performance, with 28.92% showing abnormal VMI. VMI was negatively correlated with core ADHD symptoms. At the network level, VMI showed significant statistical indirect associations in the relationship between FC of DMN-DMN, DMN-DAN, and DMN-VAN networks and inattention symptoms, and between FC of the DMN-DAN networks and hyperactivity/impulsivity symptoms. At the channel level, VMI was also indirectly associated with FC of the left superior frontal gyrus (SFG)-right middle occipital gyrus (MOG) and ADHD core symptoms. Children with ADHD have deficits in VMI, and poorer VMI performance is associated with greater severity of core ADHD symptoms. Altered intra- and inter- network FC of the DMN may represent a potential neural correlate of VMI impairment in ADHD.

Psychotherapy is a primary treatment for many mental health conditions, yet the dynamic interplay among therapist behaviors, client responses, and the therapeutic relationship remains difficult to disentangle at scale. Traditional process research relies on labor-intensive human coding, limiting the ability to model moment-to-moment therapeutic dynamics across large datasets.

This study aimed to develop and validate a computational framework for modeling therapist-client interaction processes and to examine how therapist behaviors and relational qualities relate to client self-disclosure and emotional expression in psychotherapy sessions.

We developed automated assessment pipelines using large language models (LLMs) to measure therapist behaviors (empathy, exploration), relational quality (rapport), and client outcomes (self-disclosure, self-directed negative emotion, outward-directed negative emotion). Model-generated scores were validated against human annotations. We then applied these measures to approximately 2,000 hours of psychotherapy transcripts from the Alexander Street corpus. This yielded an estimation sample of 119,233 client utterances from 1,573 sessions and 37 clients. Because utterances are nested within sessions and sessions within clients, we estimated a saturated multivariate structural equation model (SEM) with standard errors clustered at the session level. Results were confirmed in a multilevel regression model with random intercepts for session and client.

Following comparative validation of six candidate language models, automated measures showed good to excellent agreement with human annotations (ICC = 0.60-0.81), with rapport (ICC = 0.81), self-disclosure (ICC = 0.78), empathy components (ICC = 0.60-0.75), and emotion measurements (ICC = 0.66-0.80). SEM analyses revealed that therapist empathy and exploration were each associated with increased client disclosure (empathy β=0.086, 95% CI 0.078 to 0.095; exploration β=0.086, 95% CI 0.078 to 0.094; both P<.001) and increased expression of self-directed negative emotions, comprising sadness, anxiety, fear, and depression (empathy β=0.118, 95% CI 0.110 to 0.127; exploration β=0.078, 95% CI 0.070 to 0.087; both P<.001). Both behaviors were also associated with reduced expressions of enjoyment (empathy β=-0.037; exploration β=-0.041; both P<.001). Surprisingly, rapport in the prior session showed no association with client self-disclosure or negative emotion expression.

This study demonstrates that LLM-based measurement combined with structural modeling can capture core therapeutic processes at scale. Empathy and exploration showed small but consistent turn-level associations with client disclosure and emotional expression, whereas prior-session rapport did not show a robust association. These findings provide a computational foundation for precision modeling of psychotherapy processes and may offer actionable insights for scalable therapist training and AI-supported clinical education systems.

University students face occupational disruption during post-secondary transitions, yet existing campus screening tools leave occupational challenges largely unassessed. No comprehensive, occupation-focused screening instrument exists for this population. To describe the theoretical development and content validation of the Occupations in Higher Education Transitions Inventory (OHETI), a screening tool assessing university student adaptation across 10 domains of occupation grounded in the Theory of Occupational Adaptation (OA) a five-phase iterative development process was used: (a) initial item generation; (b) preliminary expert review for face validity (N = 3 occupational therapists with expertise in OA theory); (c) tool reconceptualization based on expert feedback; (d) cognitive interviews with undergraduate students for face validity and comprehensibility (N = 10); and (e) formal content validation using a Content Validity Index (CVI) rating procedure with (N = 6) occupational therapy professionals with clinical and academic experience with emerging adult students. Initial item generation yielded 68 items across seven OA constructs. Expert feedback prompted a fundamental restructuring, producing 116 items across 10 occupations, covering aspects of relative mastery: satisfaction, effectiveness, and efficiency. Revision based on student cognitive interviews resulted in 122 items. Formal content validation produced I-CVI scores ranging from 0.667 to 1.0, with S-CVI scores of 0.9516 for clarity and 0.9435 for relevance. Two items were removed, resulting in a final tool of 120 scorable items across 10 occupations. The OHETI demonstrates strong content and face validity as a theoretically grounded, occupation-focused screening tool for university students. Online administration and individualized feedback distinguish it from existing instruments. Psychometric validation is needed before broad implementation.

To investigate the prevalence of long-term mental disorders in caregivers of ICU sepsis survivors and examine associations with post-intensive care syndrome (PICS) in patients.

Prospective observational study.

Twenty-one mixed ICUs.

Caregivers (the next of kin) of the patients diagnosed with sepsis between November 2020 and April 2022.

None.

Caregivers and patients were assessed at 3, 6, and 12 months after hospital discharge by telephone and mail. The primary outcome was caregiver mental disorders (mental post-intensive care syndrome-family [PICS-F]). Mixed-effects logistic regression analyses were performed to evaluate the association between caregiver PICS-F and patient PICS. Ninety-four caregiver-patient dyads were analyzed. Caregivers were a median of 67 years old (55-79 yr old), 31 (33.0%) were male, and 41 (43.6%) were spouses. Patients were a median of 74 years old (69-82 yr old), and 54 (57.4%) were male. The prevalence of mental PICS-F did not decrease from 3 to 12 months (43% vs. 42%, respectively), whereas the presence of PICS symptoms in patients decreased from 82% to 62%. In mixed-effects logistic regression, the presence of PICS symptoms in patients was significantly associated with PICS-F (adjusted odds ratio, 3.00; 95% CI, 1.54-5.88; p < 0.01). Among the individual patient PICS domains, only mental PICS was significantly associated with PICS-F (3.71; 2.03-6.77; p < 0.01), whereas physical and cognitive impairments in patients were not.

The prevalence of mental PICS-F in caregivers of ICU sepsis survivors was frequent and long-lasting over the first year after hospital discharge. Since it was most strongly associated with patients' mental disorders rather than physical or cognitive impairments, the mental PICS domain in patients may be an important indicator of PICS-F and should be considered in future studies.

Etomidate use disorder (EUD) is an escalating public health issue in East and Southeast Asia, yet its neuroimaging features remain poorly understood. This study used simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to examine multimodal functional connectivity alterations in individuals with EUD.

A total of 54 individuals with EUD and 46 healthy controls (HCs) were recruited and underwent simultaneous resting-state EEG and fNIRS recordings. Psychological dimensions including impulsivity, aggression, and craving were evaluated using standardized and validated scales. Source-level EEG functional connectivity and fNIRS hemodynamic connectivity were analyzed to identify group differences. Associations between altered connectivity features and clinical measures were examined within the EUD group. Machine learning analyses were conducted as exploratory assessments of the discriminative information contained in multimodal connectivity features.

In unadjusted exploratory analyses of BIS-11 and BPAQ subscales, the EUD group showed higher cognitive impulsivity, non-planning impulsivity, physical aggression, anger and self-directed aggression (t=2.32 to 4.54, p<0.05), but lower motor impulsivity, compared with HCs. Source-level EEG analysis revealed significant group differences only in the delta band, with reduced large-scale connectivity in EUD involving default mode, dorsal attention, visual and sensorimotor systems. fNIRS analysis showed reduced hemodynamic connectivity across multiple frontal subregions and motor-related areas. Weaker connectivity between the primary motor cortex and the triangular part of the inferior frontal gyrus was associated with stronger negative reinforcement craving (rho=-0.471, p_FDR<0.05). Exploratory machine learning analysis showed preliminary discriminative performance, with the random forest model producing the numerically highest test-set AUC (0.80) in this particular data split.

Convergent EEG-fNIRS findings suggest delta-band network decoupling and reduced frontal hemodynamic connectivity as multimodal neural features of EUD. These findings provide preliminary evidence for the neural mechanisms of EUD and may inform future objective assessment and treatment-monitoring studies.

Youth in Kashmir are under heightened stress due to numerous challenges. Research on how the youth of Kashmir perceive and manage these occurrences remains limited, despite the fact that coping strategies can mitigate their detrimental effects.

This study examines the factors that contribute to stress and the coping mechanisms employed by youth in Kashmir.

A qualitative design was employed, utilizing semi-structured interviews with 21 youth aged 18 to 24, selected through convenience sampling. The data was analysed using inductive thematic analysis.

Two major themes emerged: [1] causes that contribute to stress and [2] coping strategies, each with three subthemes. Academic difficulties, familial issues, and personal issues were identified as primary stressors. To manage these, the youth employed various coping mechanisms to relieve them.

This study addresses a significant gap in understanding stress and coping among youth of Kashmir and offers insights for future mental health interventions.

This bibliometric study aimed to characterize publication patterns, collaboration networks, keyword structures, and temporal trends in pediatric music therapy. We analyzed 518 PubMed-indexed articles published between January 2016 and August 2025 using CiteSpace, VOSviewer, SCImago Graphica, and Excel. Publication and collaboration activities were concentrated in North America, Europe, and Asia. Keyword analyses identified themes involving cognitive function, language development, motor skills, mental health, quality of life, creative arts therapy, and systems analysis. The literature also spanned pediatrics, nursing, public health, physical therapy, and complementary medicine. Online delivery became more prominent during the COVID-19 period, and recent keywords included digital health-related topics. However, the keyword network remained sparse, indicating limited integration across research themes. These findings describe the intellectual structure and thematic development of the field but do not establish the clinical effectiveness of music therapy. Future research should prioritize methodological standardization, broader collaboration, and rigorous clinical evaluation.

Evidence for the clinical importance of changes in health-related quality of life (HRQoL) over time in unselected patients with ulcerative colitis (UC) and Crohn's disease (CD) is limited. We aimed to describe HRQoL trajectories, determine clinically meaningful HRQoL improvement, and identify factors associated with such improvement during the first 3 years after diagnosis.

Adults with UC and CD from a population-based inception cohort completed the Inflammatory Bowel Disease Questionnaire (IBDQ) and the 36-Item Short Form Survey (SF-36) at inclusion and at the 1-year and 3-year follow-ups. HRQoL trajectories were estimated using linear mixed-effects models. Clinically meaningful improvement was defined using established minimal clinically important difference (MCID) thresholds (IBDQ ≥16; SF-36 physical and mental component summary scores ≥3). Associations between prespecified variables and MCID achievement at follow-up were assessed using multivariable logistic regression.

Among 1016 patients (UC: 68%; CD: 32%), IBDQ and SF-36 physical and mental component summary scores improved at both follow-ups, and approximately half of the patients achieved the corresponding MCID thresholds. HRQoL scores remained below general Norwegian population norms, and trajectories were similar for UC and CD. Symptomatic remission was consistently associated with higher odds of clinically meaningful HRQoL improvement, whereas depressive symptoms, substantial fatigue, and irritable bowel-like symptoms were associated with lower odds. Endoscopic remission, biologic therapy, and bowel surgery during the first year were not significantly associated with clinically meaningful improvement.

Clinically meaningful HRQoL improvement was achieved by about half of the patients and was consistently associated with lower symptom and psychosocial burden.

Cortisol levels provide valuable information regarding physiological stress and abnormalities associated with endocrine and mental health disorders. In this study, an AuNPs/CNT-modified electrochemical aptasensor integrated with machine learning was developed for sensitive cortisol detection and accurate discrimination of cortisol levels. A porous CNT network supported a large specific surface area with high conductivity, and density functional theory (DFT) calculations revealed the AuNPs modified the electronic structures of CNTs and further accelerated the charge transfer efficiency. Once cortisol specifically binds to the aptamer, target-triggered conformational rearrangement could destabilize the aptamer/cDNA duplex and release the aptamer from the electrode surface. The reduced surface nucleic acid density alleviated steric and electrostatic hindrance for the diffusion of the [Fe(CN)₆]^3-/4- probe, which resulted in an accelerated interfacial electron transfer and yielded an enhanced electrochemical signal. The proposed cortisol aptasensor exhibited a good linear relationship between the current variation and the logarithm of cortisol concentration in the range of 10-5000 nM, with a limit of detection of 1.61 nM. Simultaneously, supervised machine learning was applied to classify cortisol concentrations with low, normal, and high levels, thus providing a promising strategy for intelligent stress assessment.

The psychosis continuum conceptualises psychotic phenomena as existing on a spectrum from subclinical experiences to psychotic disorders. Despite epidemiological and clinical evidence in support of this model, few studies have examined polygenic liability across the severity continuum: from subclinical experiences to first-episode psychosis (FEP).

To map polygenic liability for schizophrenia (SCZ), bipolar disorder and major depressive disorder (MDD) across the psychosis continuum. We hypothesised that schizophrenia polygenic scores (SCZ-PGS) would track phenotypic severity most closely across this continuum.

We harmonised data from 5 south-east London cohorts (N = 1315; 860 European, 455 African ancestries) across 4 ordered groups indicative of different levels of phenotypic severity: controls (n = 647), individuals with self-reported psychotic experiences (n = 89), individuals at clinical high risk (CHR) that did not convert to psychosis (n = 124) and individuals with FEP (n = 455). We computed ancestry-specific PGS for SCZ, bipolar disorder and MDD and compared these across groups using ordinal logistic regression.

In European ancestry participants, elevated SCZ-PGS (odds ratio 1.72, p = 4.57 × 10^-15), bipolar disorder-PGS (odds ratio 1.56, p = 1.03 × 10^-10) and MDD-PGS (odds ratio 1.44, p = 4.86 × 10^-8) were individually associated with increasing phenotypic severity. SCZ-PGS explained the largest variance (R² = 0.084) across the psychosis continuum and showed pairwise differences between CHR and controls (β = 0.32, p = 0.027), and between FEP and CHR (β = 0.38, p = 0.017). Multivariable models, combining three PGS, outperformed univariable models (R² = 0.105). Similar trends in SCZ-PGS across the psychosis continuum phenotype were seen in African ancestry participants, but only controls and FEP groups differed significantly (β = 0.27, p = 0.037).

Our findings provide biological evidence supporting the psychosis continuum framework. In European ancestry, SCZ-PGS differences suggest that CHR who do not transition to psychosis have intermediate genetic vulnerability. Multivariable models, utilising all three PGS, explained additional variance compared with univariable ones, supporting transdiagnostic genetic liability. Improving PGS predictive power in African ancestry remains a priority.