We aimed to test associations of participant-reported Long COVID symptom interference with life activities with Long COVID symptoms, presence of U09.9 Long COVID diagnosis code, demographics, and clinical factors. In a subgroup, we documented coding related to Long COVID and post-exertional malaise in the electronic medical record (EMR).

Using a cross-sectional analysis (n = 205) of participant data from a Long COVID survey, we tested associations with Chi-square, Fisher's exact, or Fisher-Freeman-Halton exact statistical tests and Independent Samples T-tests.

Participants were predominately female (67%) with a mean age of 50.9 years. Participants were White (50.0%), African American (47.5%), and Asian (2.5%); 1.5% reported Hispanic ethnicity. 41% of participants reported high Long COVID symptom interference with life activities. Participants who were older (p=.028), were female (p=.002), were obese (p=.049), had worse general health (p<.001), worse physical health (p<.001), had worse mental health (p<.001), and had U09.9 diagnosis (p<.001) were more likely to experience high symptom interference. Among participants with high symptom interference, there were no significant associations with U09.9 diagnosis code. EMR sub-analysis (n = 100) revealed that among participants that reported high symptom interference (n = 39), 64% (n = 25) had a code related to Long COVID.

Although we found discrepancies between self-reported measures and EMR coding, we did not find evidence of demographic biases in diagnosis among participants with high symptom interference.

Not applicable.

Postoperative neuropsychiatric complications most commonly manifest as delirium or cognitive impairment; however, acute isolated mutism in the absence of frank delirium or structural brain injury-referred to in some literature as acute psychogenic mutism (APM)-represents an exceedingly rare and poorly understood postoperative phenomenon. This report presents a case of APM in a 69-year-old woman following elective total hip arthroplasty under general anesthesia. The patient developed acute selective aphonia upon emergence from anesthesia, despite preserved comprehension and nonverbal communication abilities, with symptoms resolving spontaneously 44 h postoperatively. Emergent neuroimaging revealed no evidence of acute ischemic or hemorrhagic stroke, making a macro-scale cerebrovascular event unlikely.This case is notable for three distinctive features: (1) context-dependent preoperative anxiety, reflected by an Observational Anxiety Scale (OAS) score of 0 in the presence of family preoperatively, which escalated to elevated situational anxiety (HADS-A score 12, suggesting clinically relevant anxiety but not necessarily pathological) upon entry into the operating room; (2) the potential contribution of severe cerebral white matter lesions (Fazekas grade III), which may have disrupted prefrontal-limbic regulation under anesthetic stress; and (3) its occurrence in an older patient undergoing orthopedic surgery, challenging the prior association of APM predominantly with younger plastic surgery patients. We propose a tripartite etiological model integrating environmental triggers, neural vulnerability, and psychogenic dissociation, offering preliminary insights into perioperative mental health risk stratification that warrant further investigation. Non-convulsive status epilepticus was considered unlikely given the patient's alertness and interactive behavior, though EEG was not performed acutely.

Psychiatry's reliance on language makes LLMs a natural tool for psychopathological assessment, yet structured, item-level assessments from psychiatric clinical interviews remain under-researched. In this proof-of-concept study, 10 LLMs assessed transcripts of three simulated psychiatric interviews across all 100 items of the Association for Methodology and Documentation in Psychiatry (AMDP) system, benchmarked against 108 early-career clinicians rating full audiovisual recordings, using an expert consensus panel as reference. GPT-5.1 and Gemini-3-Pro-Preview achieved the highest accuracy (0.72; 64th percentile of the clinician distribution) using majority voting across three runs with AMDP definitions as context. GPT-5.1, selected for a marginal advantage, showed per-scenario accuracies of 0.81 (depression), 0.76 (mania), and 0.60 (schizophrenia) versus clinician means of 0.79, 0.68, and 0.58. Clinicians and LLMs showed distinct error profiles: clinicians tended to over-infer symptom presence, whereas LLMs more conservatively flagged items as "not assessable" - most pronounced for observation-dependent items but present even for text-assessable items (19.4% vs. 11.4%, p < 0.001). In post hoc simulated disagreement resolutions (2091 clinician pairs; 35.5% disagreements), LLM and board-certified supervision were associated with more accurate resolutions than unsupervised random clinician selection (p < 0.0002). These proof-of-concept findings require validation in real patient interviews, larger samples, and prospective studies integrating multimodal input.

Both sustained attention (SA) and executive functioning (EF) are critical for adaptive behavior and compromised across a range of psychiatric disorders, yet their etiological relationships remain underexplored. Here, we report the first multivariate characterization of molecular genetic influences on SA (vigilance, lapse recovery cost, lapse propensity) and EF (processing speed, response selection, working memory). In collaboration with 23andMe, we report previously unpublished genome-wide association studies of these phenotypes in a single cohort of more than 20,000 individuals enriched for diagnoses of major depressive disorder and bipolar disorder. We used Genomic Structural Equation Modeling to formally model patterns of genetic covariance among these task-based measures of cognition, and their relationships with other cognitive, clinical, and imaging-derived phenotypes. We identified two distinct latent genetic factors: one influencing EF and one influencing SA. Both the EF and SA factors were genetically correlated with cognitive and clinical phenotypes, with each latent factor uniquely linked to liability for psychiatric disorders, including attention-deficit/hyperactivity disorder. However, genetic correlations with imaging-derived neuroanatomical phenotypes were modest and non-significant after correction for multiple comparisons. Collectively, these results provide an initial multivariate genetic characterization of SA and EF, though replication in larger and more diverse samples will be important. They suggest that genetic influences on sustained attention are generally distinct from those that influence executive function. The EF and SA factors show distinct patterns of genetic overlap with multiple cognitive and psychiatric outcomes, underscoring the need for more granular cognitive phenotyping to generate new insights into the genetic architecture of cognition and the etiology of psychopathology.

Conversational AI is emerging as a scalable tool for psychological support, yet its clinical effectiveness and the relational factors underlying user benefit remain underexplored. This pre-registered randomized controlled trial (N = 977 university students; ages 18-32) compared an AI-based conversational intervention, integrative group therapy, and a waitlist control over 12 weeks, with a 3-month follow-up. The AI intervention produced greater reductions in generalized anxiety symptoms and stronger gains in well-being and life satisfaction than both comparators at post-intervention and follow-up and reduced depression relative to control. Group therapy improved depression at post-intervention and enhanced well-being and life satisfaction, with well-being maintained at follow-up. PTSD symptoms showed no group differences. Relational factors, including loneliness, low perceived social support, and insecure attachment, predicted greater improvement and higher engagement with the AI system, particularly among participants with anxious or avoidant attachment. Participants with high loneliness engaged approximately twice as much with the AI intervention as those with low loneliness, and the association between relational vulnerability and reductions in generalized anxiety symptoms was fully mediated by engagement. Findings suggest that adaptive conversational AI can complement traditional care while addressing relational vulnerability.

As antiretroviral therapy has become widely accessible, the number of elderly people living with HIV (PLWH) (≥ 50 years) has risen markedly. Their health-related quality of life (HRQoL) is shaped by intertwined biological, psychological, and social determinants. This study aimed to characterize the interaction structure of these factors using a network approach and to identify potential targets for intervention. We conducted a cross-sectional study including 802 HIV-positive individuals aged 50 years or older in Chongqing, China. A mixed graphical model (MGM) with EBIC selection and LASSO regularization was applied to estimate a network comprising 17 variables. Edges represent regularized partial correlations. Centrality indices were computed, and stability was evaluated via bootstrap procedures (1,000 iterations). Depressive symptoms occupied a central position in the network and showed strong negative connections with both physical and mental health domains. Income level and peer support served as bridging nodes linking different domains. Behavioral clustering, particularly between smoking and alcohol use, was observed. Clinical indicators such as CD4 count and viral load were positioned at the periphery. A depression-centred interaction system governs HRQoL in elderly PLWH. These findings underscore the importance of integrating psychosocial care into routine HIV management.

Age-related declines in neuromuscular and sensory systems substantially increase fall risk and impair independence in older adults. Exercise interventions improve balance and gait; however, the maintenance of these training-induced gains over time remains uncertain, as most benefits may diminish within months after training ceases. This study determined whether an 8-week Dynamic Neuromuscular Stabilization (DNS) programme produces post-intervention and short-term follow-up improvements in balance, gait speed, fear of falling, and health-related quality of life in community-dwelling older adults. In this assessor-blinded randomised controlled trial, 44 older adults aged 60-75 years were randomly allocated to either supervised DNS (totaling 24 sessions: three sessions per week for 8 weeks, 40-50 min per session) or a usual-activity control group. Outcomes were measured at baseline, immediately post-intervention, and at 2-month follow-up using validated clinical instruments. Thirty-nine participants completed the trial (DNS group, n = 19; control group, n = 20). Mixed-design ANOVA showed significant group × time interactions for all outcomes (all P < 0.001). At post-test, the DNS group exhibited large effect-size improvements compared with controls: static balance errors decreased by 58-74% (Cohen's d = 2-2.65), dynamic balance scores increased by 36% (d = 2.05), gait speed increased by 28% (d = 1.54), fear of falling decreased by 42% (d = 1.92), and physical and mental health-related quality of life (HRQOL) components improved substantially (d = 2.20-2.28). At 2-month follow-up, these improvements were largely maintained without significant deterioration within the follow-up period (P > 0.05). The control group exhibited no meaningful changes. An 8-week DNS intervention yields robust, clinically meaningful, and sustained short-term improvements across multiple domains related to fall risk in older adults. These short-term retained adaptations position DNS as an effective neurophysiologically based approach for fall prevention within the observed follow-up period.Trial registration: RTC, prospectively registered in the Clinical Trial Registry (UMIN000055127) on 29/12/2024.

To explore the knowledge, attitudes and practices of community nurses and other health professionals (e.g., physicians, pharmacists) regarding stroke prevention and pre-hospital management.

From May to July 2023, a cross-sectional online survey was undertaken with community nurses and other health professionals in a city located in central China. The questionnaire included demographic information and knowledge, attitudes and practices assessments. Data analysis included descriptive statistics and multinomial logistic regression models for each item score of knowledge, attitudes and practices questionnaire with adjustment for potential confounders.

Overall 233/250 health professionals (93.2%) participated (58% community nurses; 87% female). Compared with other health professionals, community nurses were more likely to be female (99% vs. 69%) and younger (mean age: 33 years vs. 39 years). Compared with other health professionals, community nurses were less likely to have knowledge of mnemonics of the 'stroke risk score card' (OR = 0.48; 95% CI: 0.24-0.92), the pathophysiological relationships with common complications (OR = 0.43; 95% CI: 0.23-0.80), the ability to use stroke risk predictive tools (OR = 0.53; 95% CI: 0.31-0.93) and the practice of using stroke risk predictive tools (OR = 0.55; 95% CI: 0.31-0.96).

Although overall knowledge was demonstrated in awareness of common stroke signs, symptoms and risk factors, community nurses exhibited significant knowledge gaps compared to other healthcare professionals in critical aspects of stroke prevention and pre-hospital management. Targeted evidence-based training is urgently required to improve their stroke prevention and pre-hospital management capabilities.

Targeted training in stroke pathophysiology, risk management tools and symptom recognition protocols is critical for equipping community nurses to address knowledge-practice gaps in stroke prevention.

This study was reported based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for cross-sectional studies.

Health professionals were recruited to perform the knowledge, attitudes and practices of stroke prevention and pre-hospital management survey in the phase of data collection.

The Additional Roles Reimbursement Scheme (ARRS), introduced by NHS England in 2019, aimed to expand the workforce, promote multidisciplinary team-based care, and improve patient outcomes.

To examine changes in consultation rates and outcomes in relation to ARRS implementation, and compare outcomes across primary care roles.

Longitudinal cohort study using the Clinical Practice Research Datalink (CPRD) AURUM, analysing 12,170,079 consultations (2015-21) from 600,000 randomly sampled patients at 400 English practices.

Joinpoint regression modelled trends in age- and sex-standardised consultation rates, further consultations within 1-14 days, prescribing, and referrals. Multilevel regression compared outcomes between diagnostic-capable roles and general practitioners (GPs).

Most consultations remained GP- or nurse-led, but rates with direct patient care (DPC)-ARRS-eligible roles increased, particularly for pharmacists, physiotherapists, and nursing associates. For paramedics and mental health practitioners, growth preceded formal ARRS inclusion, suggesting the scheme accelerated rather than initiated expansion. Most DPC-ARRS-eligible roles were consulted more frequently in less deprived areas, except physiotherapists. Compared to GPs, most DPC-ARRS-eligible roles delivered more consultations face-to-face (except pharmacists), had lower prescribing (except advanced nurse practitioners) and referral rates, and higher further consultation rates with a diagnostic-capable clinician within 1-14 days. However, all DPC-ARRS-eligible roles had lower odds of a further consultation specifically with a GP.

ARRS has supported and accelerated the diversification of the primary care skill-mix. Patterns of consultation activity suggest an expansion of overall primary care capacity with some redistribution of workload across the multidisciplinary team, rather than a direct reduction in GP workload.