BackgroundAlexithymia is one of the most common psychological characteristics observed in patients with chronic obstructive pulmonary disease (COPD) and is associated with poorer health outcomes. The negative impact of alexithymia on physical illness is reflected in more severe clinical symptoms and poorer quality of life, which adversely affect clinical outcomes and further increase disease burden, potentially contributing to a cycle of worsening health status. Therefore, timely identification of the psychological characteristics of patients with COPD, along with early psychological support, may help improve the quality of life of patients with COPD.ObjectivesTo explore the latent profiles of alexithymia among patients with COPD and to analyze their associated factors.MethodsThis cross-sectional study recruited 312 patients with COPD using convenience sampling between October 2024 and March 2025. Sociodemographic characteristics, physiological and disease-related information, psychospiritual information, environmental factors, and alexithymia scores were collected. Latent profile analysis, univariate analysis, and multinomial logistic regression were conducted to identify alexithymia profiles and examine factors associated with profile membership.ResultsThe results of this study showed that patients with COPD were categorized into three alexithymia profiles: high (28.85%), moderate (63.46%), and low (7.69%). COPD duration, depression, activity intensity, self-perceived social support, psychological resilience, and anxiety were associated with different alexithymia profiles among patients with COPD.ConclusionThis single-center cross-sectional study identified three preliminary alexithymia profiles (high, moderate, and low) among patients with COPD. Due to potential selection bias resulting from convenience sampling, these findings require validation in multicenter studies before generalization. The observed associations among COPD duration, depression, activity intensity, social support, resilience, and anxiety provide empirical evidence to inform the development of tailored patient classification and targeted support strategies for early identification, with the goal of improving quality of life in this population.
Efficacy of digital interventions in social anxiety disorder: a systematic review and Bayesian network meta-analysis
BackgroundSocial anxiety disorder (SAD) is characterized by a significant and persistent fear of social or performance situations. The prevalence of SAD has gradually increased recently, and the unique advantages of digital interventions (DIs) have gained traction in psychiatric disorders. However, there is currently no comprehensive review comparing the effectiveness of diverse DIs for SAD.MethodsRandomized controlled trials (RCTs) evaluating DIs for patients with SAD were identified by searching the PubMed, Cochrane Library, and Embase databases from January 1, 1995, to March 31, 2025. The study protocol for this network meta-analysis was registered in PROSPERO. Data were analyzed via Bayesian framework network meta-analysis.ResultsForty-two RCTs were included. The results showed that DIs exerted better efficacy than non-digital interventions and wait-list controls (WLC). Different forms of internet-based cognitive behavioral therapy (ICBT) demonstrated robust effects across all four outcomes. Internet-based cognitive therapy (ICT) yielded favorable effects in reducing social anxiety and depressive symptoms. VR showed relatively large effect sizes for improving quality of life.ConclusionDIs can be recommended as adjunctive or combined treatments for SAD. Different forms of ICBT show consistent efficacy and can serve as the first-line option among digital interventions. We recommend promoting the application of DIs to expand treatment coverage for SAD and overcome the limitations of traditional psychotherapy.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251077835.
Factors associated with unmet psychological care needs and development of a Neuman systems model-based risk prediction model in patients with hepatocellular carcinoma
BackgroundPatients with hepatocellular carcinoma (HCC) often face symptom distress, treatment decision-making, demands for family support, communication needs, and financial concerns during early hospitalization. This study examined factors associated with unmet psychological care needs and developed a risk prediction model, guided by the Neuman Systems Model, to support early nursing stratification.MethodsThis single-center retrospective study included 345 adults with HCC admitted between January 2020 and December 2024. Unmet psychological care needs were defined as a score of ≥3 on any item in the psychological domain of the Chinese Supportive Care Needs Survey Short Form-34 (SCNS-SF34) within 24–48 h after admission. Candidate predictors were classified as intrapersonal, interpersonal, or extrapersonal stressors. After outcome stratification, the cohort was randomly divided into training and validation sets (7:3). Multiple imputation, least absolute shrinkage and selection operator (LASSO) selection across 20 imputed datasets, and multivariable logistic regression were used to develop the nomogram. Discrimination, calibration, decision curve analysis, bootstrap internal validation, and sensitivity analyses were evaluated.ResultsUnmet psychological care needs were identified in 205 patients (59.4%). The final model retained pain numeric rating scale (NRS) score, sleep disturbance, Patient Health Questionnaire-9 (PHQ-9) score, Generalized Anxiety Disorder-7 (GAD-7) score, family support, cooperation in physician-patient communication, and perceived economic burden. Higher pain scores, sleep disturbance, higher depressive and anxiety symptom scores, poor family support, poor cooperation in physician-patient communication, and heavy perceived economic burden were independently associated with unmet psychological care needs. The areas under the receiver operating characteristic curves (AUCs) were 0.851 in the training set and 0.829 in the validation set; the bootstrap-corrected AUC was 0.836. Calibration-in-the-large, calibration slope, Brier scores, and decision curve analysis indicated acceptable apparent and internal-validation performance. Sensitivity analyses excluding PHQ-9 and GAD-7 and applying a stricter outcome definition showed consistent directions of association for the principal predictors.ConclusionsUnmet psychological care needs were common within 24–48 h after admission among patients with HCC. The internally validated nomogram may support early risk stratification, symptom management, psychosocial screening, family involvement, communication optimization, and referral to medical social work services. Independent external validation is required before routine clinical implementation.
<![CDATA[New Delphi consensus guides off-label IV ketamine for depression, detailing protocols and rapid antisuicidal mechanisms via neuroplasticity and BDNF.]]>
<![CDATA[Consensus guidance clarifies IV ketamine dosing, monitoring, staffing and consent to support safer, evidence-based depression treatment.]]>
Autistic- and attention-deficit/hyperactivity disorder-like traits: differential associations with burnout, depression and anxiety, and empathy among Japanese junior residents
IntroductionBurnout, depression, and anxiety are major concerns among physicians because they affect individual well-being, patient care, and healthcare systems. Neurodevelopmental traits, including autistic-like traits (ALTs) and attention-deficit/hyperactivity disorder (ADHD)-like traits (ADHLTs), may increase vulnerability to psychological distress. However, little is known about how these traits relate to burnout, depression and anxiety, and empathy among junior residents.MethodsIn this cross-sectional study, 148 junior residents from two teaching hospitals in Japan completed validated measures of ALTs (21-item Japanese version of the Autism-Spectrum Quotient), ADHLTs (Adult ADHD Self-Report Scale Screener), burnout (Maslach Burnout Inventory), depression and anxiety (Hospital Anxiety and Depression Scale), physician–patient empathy (Jefferson Scale of Physician Empathy), and psychological flexibility and inflexibility processes (Valuing Questionnaire, Cognitive Fusion Questionnaire-7, and Work-related Acceptance and Action Questionnaire). Associations were examined using multivariable logistic and linear regression analyses. Exploratory statistical mediation analyses using structural equation modeling examined indirect associations through psychological flexibility and inflexibility processes.ResultsThe prevalence of ALTs and ADHLTs was 23.6% for each trait. ALTs were associated with lower personal accomplishment, a burnout dimension; higher depression and anxiety; and lower physician–patient empathy. ADHLTs were associated with greater emotional exhaustion, another burnout dimension. In exploratory statistical mediation analyses, progress toward values, a core process of psychological flexibility, showed a significant indirect association between ALTs and personal accomplishment, and the direct association was attenuated and no longer statistically significant after including the process variables. Significant indirect associations through progress toward values were also observed for the associations of ALT with depression and anxiety and empathy. Cognitive fusion, a core process of psychological inflexibility, showed a significant indirect association between ADHLTs and emotional exhaustion. Overall, neurodevelopmental traits were associated with distinct patterns of psychological functioning, suggesting variability in both vulnerability and adaptive processes.DiscussionNeurodevelopmental traits such as ALTs and ADHLTs were significantly associated with burnout dimensions, depression and anxiety, and physician–patient empathy among junior residents. Psychological flexibility and inflexibility processes, particularly progress toward values and cognitive fusion, may be relevant to these associations. Process-based support strategies may warrant further investigation for residents with elevated neurodevelopmental traits.Clinical trial registrationhttps://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R00005, identifier UMIN000046897.
Loneliness, rumination, and adolescent psychological crisis in China: a pilot moderated mediation study
BackgroundAdolescent psychological crisis—encompassing depressive disorder, anxiety disorder, and suicidal ideation—is a major public health challenge. One in five adolescents experiences a clinically significant mental health condition globally. Loneliness is a well-documented, modifiable risk factor for these outcomes. However, the exact cognitive-emotional pathways linking loneliness to acute psychological crisis remain unclear. This is particularly true in China, where rapid social change and intense academic pressure increasingly strain adolescent mental health. We do not yet fully understand how protective resources might buffer these specific pathways.Objectives and methodsThis pilot study tests a moderated mediation model based on the Evolutionary Theory of Loneliness and the stress-vulnerability framework. We investigate ruminative thinking as a cognitive-emotional mediator between loneliness and psychological crisis. We also test whether perceived social support and psychological resilience moderate distinct stages of this pathway. Based on a pilot sample of N = 312 Chinese adolescents (ages 12–18), we use structural equation modelling (SEM), confirmatory factor analysis (CFA), and Hayes’ PROCESS Macro (Model 14) with 5, 000 bootstrap replications. Two-wave longitudinal data (n = 187, 8-week interval) were available for the depression outcome only; the anxiety and suicidal-ideation pathways were examined cross-sectionally.ResultsLoneliness is significantly associated with depressive symptoms (β = 0.43, p < 0.001), anxiety (β = 0.38, p < 0.001), and suicidal ideation (β = 0.27, p < 0.001). Ruminative thinking accounts for 40–46% of the total indirect association across all three outcomes. Social support buffers the transmission from loneliness to rumination (b = −0.16, p = 0.002, ΔR2 = 0.023), while resilience buffers the transmission from rumination to crisis (b = −0.19, p < 0.001, ΔR2 = 0.031).ConclusionsThese preliminary, exploratory findings are consistent with the possibility that ruminative thinking partially accounts for the cross-sectional association between loneliness and adolescent psychological crisis in China, and with social support and resilience attenuating this association at potentially distinct stages. Because the pilot is underpowered for the moderated mediation model and the available longitudinal evidence covers depression only, the moderation and stage-specificity results should be read as hypothesis-generating rather than confirmatory. A planned full-scale study (N ≥ 1, 200) will test these mechanisms further. We also outline initial practical implications for school-based interventions.
Treating addiction with an addictive drug: the ketamine paradox revisited
BackgroundSubstance use disorders (SUDs) and treatment-resistant depression (TRD) remain a major global health challenge, marked by high relapse rates and limited long-term effectiveness of existing treatments. Ketamine, a glutamatergic modulator with rapid neuroplastic effects, has emerged as a novel intervention for TRD and is increasingly investigated as an adjunctive treatment for addiction, yet concerns about its abuse liability persist.ObjectiveThis review critically evaluates ketamine’s therapeutic potential for SUDs while examining its neurobiological mechanisms, clinical efficacy, and risk of misuse within a unified risk–benefit framework.MethodsA structured narrative review conducted in accordance with the SANRA framework using the PubMed, Scopus, PsycINFO, and Web of Science databases, covering literature published until March 2026. Eligible studies included clinical trials, experimental studies, and mechanistic investigations relevant to ketamine use in addiction and depression. Evidence was synthesized thematically across the domains of efficacy, mechanisms, and safety.ResultsAcross alcohol and cocaine use disorders, ketamine combined with psychotherapy has demonstrated promising reductions in craving and increases in abstinent days in small-to moderate-sized Phase 2 trials. However, findings remain difficult to generalize due to considerable variability in dosing strategies, comparator conditions, and follow-up periods. Effects on relapse prevention have been more inconsistent and less reliably positive. Mechanistically, ketamine promotes synaptic plasticity via NMDA receptor antagonism and downstream glutamatergic signaling, potentially disrupting maladaptive reward-related memories and reversing maladaptive neurocircuitry involved in both depression and addiction. While acute adverse effects are generally transient under clinical supervision, ketamine carries a well-established risk of misuse, particularly in unsupervised or high-dose settings.ConclusionsKetamine represents a promising but still experimental intervention for both refractory depression and selected SUDs. Its clinical use depends on careful patient selection, structured delivery, and integration with psychotherapy. Although ketamine may redefine treatment paradigms for TRD and addiction, larger-scale trials and long-term safety data are essential to define its role within psychiatric and addiction treatment frameworks.
Real-world outcomes of intranasal esketamine and intravenous ketamine induction therapy for treatment-resistant depression in a community clinic: a retrospective cohort study
IntroductionIntravenous (IV) ketamine and intranasal esketamine are NMDA receptor antagonists used for treatment-resistant depression (TRD). Both have demonstrated efficacy in controlled trials, but observational evidence from real-world community settings is limited.MethodsWe conducted a single-center retrospective cohort study of adults aged 18 to 65 receiving induction therapy for TRD with intranasal esketamine or IV ketamine at a community psychiatric clinic from January 1 through December 31, 2025. Patients with prior exposure to either medication or to oral ketamine derivatives were excluded. The primary outcome was change in Patient Health Questionnaire-9 (PHQ-9) score from baseline to end of induction. Secondary outcomes included response (≥50% PHQ-9 reduction), remission (final PHQ-9 ≤4), clinically meaningful improvement (≥5 PHQ-9 reduction), induction completion, and adverse events. Within-group and per-protocol analyses were exploratory.ResultsSixty-three patients met inclusion criteria (esketamine n=37; IV ketamine n=26). Baseline PHQ-9 scores were similar (18.22±4.49 vs. 18.27±5.41; P = 0.967), as was mean change from baseline (-10.31±5.59 vs. -9.50±5.69; mean difference 0.81, 95% CI -2.12 to 3.75; P = 0.589). Response rates were 64.9% vs. 69.2% (RR 0.94, 95% CI 0.66 to 1.33; P = 0.790), remission 32.4% vs. 23.1% (RR 1.41, 95% CI 0.61 to 3.26; P = 0.573), and clinically meaningful improvement 83.8% vs 73.1% (RR 1.15, 95% CI 0.87 to 1.51; P = 0.353). Induction completion exceeded 90% in both groups; one patient per cohort discontinued from intolerable side effects, and no serious adverse events occurred. Within-group PHQ-9 reduction was large: 10.31±5.59 points (paired t[34]=10.91; P<0.001; Cohen’s d=1.84) for esketamine and 9.50±5.69 points (paired t[23]=8.18; P<0.001; Cohen’s d=1.67) for ketamine. Findings remained statistically significant and clinically large under a pre-specified baseline observation carried forward (BOCF) sensitivity analysis (Cohen’s d=1.65 and 1.45).ConclusionsInduction therapy with intranasal esketamine and intravenous ketamine was associated with robust antidepressant effects in a community outpatient setting, consistent with prior trial data. The modest sample size limits power to detect between-group differences and increases the risk of type II error; the absence of statistically significant between-group differences should therefore not be interpreted as evidence of equivalence. Protocol asymmetry between arms (esketamine: 12 sessions over 8 weeks; IV ketamine: 6 sessions over 3 weeks) further limits direct comparison of endpoint values between groups. Practical considerations including insurance coverage, cost, and administration logistics may help guide treatment selection. Longitudinal follow-up is planned to characterize treatment durability.
Virtual Patients Will Train Future Mental Health Clinicians
Researchers from the University of Pennsylvania and New York University have received a $4 million grant from the Wellcome Trust to develop an AI-driven platform to train mental health clinicians using simulations of real patients.
Within the next two years, the partners will work on the development of the STELLAR platform, which stands for Steering-Vector Enhanced LLM Agents for Realistic Digital Twins in Mental Health. The platform will create digital twins of patients that trainees can use to practice conducting clinical interviews and evaluating psychiatric symptoms.
“STELLAR brings together behavioral data, clinical expertise, and AI to ask a very practical question,” said Sharath Chandra Guntuku, PhD, associate professor of computer and information science at Penn Engineering. “Can we build training tools that better prepare clinicians for how varied and complex patients are?”
Preparing future mental health clinicians for clinical interviews can be challenging as patients will often report overlapping symptoms that shift over time and subjective experiences that can be expressed differently by each individual. STELLAR will give trainees an ethical option for trainees to simulate interviewing patients with a broad range of symptoms, backgrounds, and clinical scenarios.
“In psychiatry, the details of symptom experience matter: how someone describes distress, how symptoms overlap, how severity changes over time, and how context shapes the clinical interaction,” said Raquel E. Gur, MD, PhD, professor of psychiatry, neurology, and radiology at Penn’s Perelman School of Medicine.
Patient simulations will be created drawing from clinical data from the Philadelphia Neurodevelopmental Cohort, a repository including psychiatric assessments and clinical interviews from thousands of young people created by Penn Medicine and the Children’s Hospital of Philadelphia. Rather than copying individual patients, the simulations will create composites based on real-world data for clinicians to practice realistic conversations in the context of a clinical interview.
This will allow trainers to precisely control the symptoms students encounter, their intensity, and how they interact with each other. For instance, a trainee may practice interviewing a patient with mild anxiety and another whose anxiety overlaps with depression or psychosis to learn how to distinguish the differences in presentation between both.
Because many mental health symptoms manifest beyond formal clinical settings, the platform will also be trained using data from social media platforms, where people discuss mental health symptoms in everyday language.
“Patient simulations will only be useful for clinician training if they are grounded in real clinical speech and evaluated as clinical interactions, not just plausible AI dialogue,” said Neville Ryant, PhD, researcher at Penn’s Linguistic Data Consortium. “[Our] role is to bring speech and language science into the core of the project: adapting speech-recognition tools to clinical interviews, creating high-quality transcripts and annotations, and helping evaluate both what the simulations say and how they say it. That includes assessing the language generated by the models, the naturalness of synthetic voices, how well those voices reflect target speech patterns, and the behavior of the avatar during real trainee interactions.”
To ensure the conversations are realistic, respectful, and useful to trainees, the team will involve people with lived experience of mental health conditions as well as family members and caregivers to provide their perspective into the evaluation process. Their feedback will help researchers assess the accuracy of simulations, avoid stereotyping patients, and prepare trainees for complex and nuanced clinical conversations with real patients.
“The promise of this approach is that we can move beyond stylized and potentially biased simulations,” said João Sedoc, PhD, assistant professor of technology, operations and statistics at NYU’s Stern School of Business. “If we can create digital patients that simulate controllable plausible symptom expression and responsibly evaluate, we can augment current clinician training practices with the kinds of conversations that are essential to better mental health care.”
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