Tag: Academic research

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Effects of Telerehabilitation on Quality of Life, Physical Capacity, and Symptom Burden Within the Post–COVID-19 Condition: Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background: Post–COVID-19 condition (PCC) is characterized by persistent symptoms and functional limitations that impair quality of life, and rehabilitation is an important component of its management. Because access to conventional face-to-face rehabilitation may be limited, telerehabilitation has emerged as an accessible alternative. However, the effectiveness of telerehabilitation across clinical outcomes remains uncertain, and the influence of different delivery modes is not well understood. Objective: This study aimed to evaluate the effects of telerehabilitation on health-related quality of life (HRQoL), physical capacity, and symptom burden in adults with PCC, and to determine whether delivery mode (synchronous, asynchronous, or hybrid) modified these effects. Methods: Seven databases (PubMed, Cochrane Library, Web of Science, Scopus, Embase, EBSCO, and PEDro) were searched for randomized controlled trials published from January 2020 through December 2025. Eligible trials enrolled adults with PCC and compared telerehabilitation with usual care or another control condition. The primary outcome was HRQoL; secondary outcomes included functional capacity assessed by the 6-minute walk test and sit-to-stand test, dyspnea, fatigue, and symptoms of anxiety and depression. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Mean differences or standardized mean differences (SMDs) with 95% CIs were pooled using random-effects models with the Hartung-Knapp-Sidik-Jonkman adjustment. Heterogeneity was quantified using I² and τ², with 95% prediction intervals reported where estimable. Certainty of evidence was evaluated using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. Results: A total of 22 randomized controlled trials involving 2294 participants were included. Telerehabilitation was associated with significant improvements in HRQoL (SMD 1.26, 95% CI 0.07-2.45; <i>P</i>=.04), dyspnea (SMD 1.95, 95% CI 0.60-3.31; <i>P</i>=.005), and functional aerobic capacity (6-minute walk test : mean difference 77.79 meters, 95% CI 30.44-125.14; <i>P</i>=.001). Fatigue was also significantly reduced (SMD 0.89, 95% CI 0.16-1.62; <i>P</i>=.02), but no significant effects were observed for lower-limb strength (sit-to-stand test: SMD 0.55, 95% CI –0.15 to 1.25; <i>P</i>=.12) or symptoms of anxiety and depression (SMD 0.12, 95% CI –0.13 to 0.38; <i>P</i>=.36). No significant differences between delivery modes were observed for HRQoL (<i>P</i>=.93), functional aerobic capacity (<i>P</i>=.29), or dyspnea (<i>P</i>=.16). A significant subgroup difference was observed for lower-limb strength (<i>P</i>=.02). Conclusions: Telerehabilitation may improve quality of life, aerobic capacity, and symptom burden in PCC and offer an accessible option for post-COVID rehabilitation, although the certainty of evidence was generally limited. Asynchronous delivery appears feasible for general reconditioning, whereas its benefit for lower-limb strength and the value of synchronous supervision remain uncertain. Clinical Trial: PROSPERO CRD42023490863; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023490863
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Stress-induced dorsal striatal dopamine release is associated with changes in functional connectivity to the prefrontal cortex in nicotine-dependent individuals—a preliminary report

IntroductionThe neural mechanism linking stress to addiction pathophysiology remains unclear. A proposed pathway involves stress-induced dopamine (DA) transmission impairing inhibitory control, leading to relapse. Lipopolysaccharide (LPS), a biological stressor inducing systemic inflammation, amplifies DA release. Our prior study demonstrated this effect in smokers. Using the same cohort, we investigated whether DA transmission mediates acute stress effects and impacts striatal-prefrontal functional connectivity (FC) in brain regions governing reward, inhibition, and decision-making.MethodsUsing a within-subject, multimodal design, we collected PET and resting-state functional MRI (rs-fMRI) scans in 8 smokers (6 females; mean age: 32 ± 3.6 years). Stress was induced using LPS; plasma cortisol indexed level of stress. DA release was measured in striatal subregions using [11C]raclopride PET before and after methylphenidate administration, while striatal–prefrontal functional connectivity was assessed using seed-based rs-fMRI. Each participant completed three PET scans (one baseline and two post-methylphenidate scans following LPS or placebo [PCBO] pretreatment) and two rs-fMRI scans (LPS and PCBO), resulting in a total of 24 PET scans and 16 rs-fMRI scans.ResultsLPS elevated cortisol and DA release in striatum compared to Placebo (p < 0.05). Cortisol increases correlated with dorsal striatal DA release (r = 0.708, p = 0.04). FC analyses revealed enhanced FC between dorsal striatum and ventral medial prefrontal cortex (vmPFC) (p < 0.001, FDR-corrected), and between whole striatum and dorsal lateral PFC (dlPFC) (p < 0.001, FDR-corrected). Nonlinear associations showed FC initially increased with stress but plateaued at higher stress levels.ConclusionStress-induced changes in DA release within dorsal striatum influence stress-related alterations in frontal-striatal FC. Our present findings in a limited cohort lead us to hypothesize more broadly that stress alterations in frontal-striatal FC reflect adaptation, whereas excessive stress may disrupt circuits, potentially contributing to addictive behaviors such as smoking. While the present pilot study demonstrates the potential value of PET and rs-fMRI to connect neurotransmitter action to downstream cortical activity future work will be essential to confirm the reproducibility and relevance of the observed associations.
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Family cohesion and adolescent self-esteem: mediating effects of interpersonal self-support and moderating role of school attachment

IntroductionAdolescent mental health is a pressing global concern, and in collectivist societies such as China, family and school contexts are particularly influential. This study examined whether interpersonal self-support mediates the association between family cohesion and self-esteem among Chinese adolescents and whether school attachment moderates the first stage of that mediation pathway.MethodsA cross-sectional survey was conducted with 728 adolescents (mean age = 13.81 years, SD = 0.91, range 12–16; 44.0% male) from five public junior high schools in Hunan Province, China. Confirmatory factor analyses were conducted in Mplus 8.3, and the moderated mediation model was tested with Hayes’ PROCESS macro (Model 7) in SPSS 27 using observed variables and 5,000 bootstrap samples.ResultsFamily cohesion was positively associated with self-esteem and with interpersonal self-support, and interpersonal self-support partially mediated the family cohesion–self-esteem association. School attachment moderated the first stage of the mediation pathway, b = 0.076, 95% CI [0.024, 0.128], ΔR2 = .008: the positive association between family cohesion and interpersonal self-support was significant at all levels of school attachment and was stronger among adolescents reporting higher school attachment, and the conditional indirect effect increased from 0.107 at low to 0.153 at high school attachment.DiscussionThe indirect pathway was secondary to the direct association between family cohesion and self-esteem, and the moderation effect was modest. Because the design was cross-sectional and self-reported, these associations should not be interpreted causally. The findings suggest that schools may support the benefits of family cohesion for adolescent self-esteem by strengthening teacher-student relationships and cultivating a sense of belonging.
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When severe violence becomes a script: a vulnerability-script integration model of media exposure and the form of psychosis-associated maternal filicide

When a publicized act of severe violence is followed by one that resembles it, the resemblance is often read as contagion. This paper argues that resemblance is weak evidence of influence and asks a narrower question: under what conditions can exposure to a publicized crime narrative shape the form of subsequent violence in a person whose antecedent state has already made such violence conceivable? The Vulnerability-Script Integration Model (VSIM) is developed for psychosis-associated maternal filicide. It is an organizing framework with an attached evidentiary protocol and three new propositions: antecedent vulnerability selects exposure as well as moderating its effect; exposure primarily shapes the form rather than the origin of violence; and media influence is inferred only from a dated post-exposure change in narrative-specific behavioral information (acquired or activated) that the documented antecedent state does not parsimoniously explain. The model specifies five functional stages, two moderators, a clinically defined and non-circular vulnerability construct, discriminant coding rules, a causal diagram with explicit estimands, and six predictions with stated classification, test, disconfirming, and inconclusive evidence. A closed, adjudicated case in which a court-tested claim of media scripting proved false illustrates the evidentiary rules. Clinical and reporting implications are framed as research questions.
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Correlation between hypothalamic-pituitary-adrenal function and clinical characteristics in the acute phase of first-episode drug-naive major depressive disorder

BackgroundFirst-episode drug-naïve depressive disorders have high heterogeneity in clinical features, and there is still room for in-depth exploration of the correlation with serum cortisol levels. This study aimed to explore the correlation between hypothalamic-pituitary-adrenal (HPA) function in the acute phase of first-episode drug-naïve major depressive disorder (MDD) and clinical features evaluated by the Hamilton Depression Rating Scale (HAMD-24) and the Zung Self-Rating Depression Scale (SDS).MethodsPatients with first-episode drug-naïve MDD in the acute phase meeting the DSM-V diagnostic criteria were selected as the study group, and healthy individuals matched for gender and age were recruited as the control group. Serum cortisol levels were measured in both groups, and patients in the MDD group were evaluated using HAMD-24 and SDS.ResultsThe serum cortisol level in the MDD group(307.03 ± 77.80 nmol/L) was significantly higher than that in the healthy control group(261.13 ± 58.15 nmol/L) (Z-Value = -3.539, P < 0.05). The serum cortisol level showed a positive correlation trend (ρ > 0) with the anxiety factor, cognitive impairment factor, retardation factor, despair factor, total HAMD score, and SDS score, with statistical significance (p < 0.05). It showed a negative correlation trend (ρ < 0) with the sleep factor, without statistical significance (p > 0.05). It also showed a positive correlation trend (ρ > 0) with the weight factor and diurnal variation factor, without statistical significance (p > 0.05).ConclusionA significant increase in serum cortisol level can serve as one of the biological indicators for predicting the core symptom clusters and disease severity of MDD. Regulation of The HPA axis cortisol pathway may have potential value in alleviating MDD symptoms.
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Multiscale EEG network alterations in adolescents with depressive symptoms: static–dynamic connectivity, topological features, and exploratory scalp-level network hubs

BackgroundAdolescence is a critical period for brain network development and a vulnerable stage for the emergence of depressive symptoms Although altered brain connectivity has been reported in depression, the multiscale organization of resting-state EEG networks in adolescents with depressive symptoms (ADS) remains insufficiently understood. In particular, conventional network analyses are often constrained by fixed thresholding strategies and single-level observations, which may obscure scale-specific and topology-related abnormalities.MethodsEyes-closed resting-state EEG data were collected from 96 adolescents with depressive symptoms and 154 healthy controls. A data-driven adaptive thresholding strategy was used to construct subject-specific brain functional networks. Static functional connectivity, dynamic functional connectivity, and higher-order topological features were analyzed across macro-, meso-, and micro-scale levels. A multidimensional abnormality convergence matrix was further constructed to explore the spatial correspondence between network abnormalities and exploratory scalp-level neuromodulation hubs.ResultsADS showed scale-dependent abnormalities in brain network organization. At the macro- and meso-scale levels, abnormalities were mainly characterized by theta-band static hyperconnectivity, particularly involving central-region networks, together with reduced dynamic transition flexibility involving prefrontal systems. Micro-scale analysis further localized these alterations to specific connections and nodes. Static connectivity abnormalities were mainly observed along the midline prefrontal–central axis, including Fp1/Fz–FCz connections, whereas dynamic instability was mainly found in right prefrontal–occipital pathways, including Fp2/F4–Oz connections. Higher-order topological analysis indicated vulnerability of right prefrontal nodes, particularly Fp2 and F4. The convergence matrix showed spatial overlap between abnormal network features and the approximate scalp projections of prefrontal neuromodulation sites, while also identifying FCz and Oz as additional nodes that may warrant further investigation.ConclusionThis study provides a multiscale EEG network characterization of adolescents with depressive symptoms. The findings suggest that ADS-related network alterations may involve coexisting compensatory connectivity changes, reduced dynamic flexibility, and focal topological vulnerability. These results may help refine network-level features and provide hypothesis-generating computational references for future studies exploring individualized neuromodulation strategies in adolescents with depressive symptoms.
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Human-in-the-Loop Suicide Risk Detection and Clinical Escalation in a Generative AI Mental Health Chatbot: Prospective Implementation Study

<strong>Background:</strong> Mental illness is a leading cause of disability worldwide, affecting more than 1 billion people, and suicide accounts for 720,000-800,000 deaths annually. Although AI-native mental health chatbots have the potential to help address the substantial gap between treatment needs and workforce capacity, their rapid proliferation has outpaced the development of scalable procedures for identifying and responding to suicidal ideation. Although recommendations call for human oversight to support safety monitoring and intervention in AI-based care, research on human clinical oversight and crisis-response procedures remains limited. <strong>Objective:</strong> This study aims to implement a human-in-the-loop (HITL) protocol for suicide risk screening, detection, and clinical escalation in a generative AI (GenAI) mental health chatbot. <strong>Methods:</strong> In this implementation study of a HITL suicide risk detection and escalation protocol, adults were recruited online to participate in a single-arm trial of an AI-native mental health chatbot. Participants completed baseline screening using the 9-item Patient Health Questionnaire (PHQ-9). In phase 1, participants who endorsed suicidal ideation were referred to a human clinician for further assessment, safety planning, and provision of referral resources, as appropriate. In phase 2, escalation was triggered by either PHQ-9 responses or the detection of spontaneous, implicit, or explicit disclosures of suicidality during chatbot interactions. In both phases, the Ask Suicide-Screening Questions guided clinician-led assessment and risk stratification. Outcomes included the prevalence of suicidal ideation, the rate of successful clinician outreach, the time from risk detection to initiation of clinician outreach, and the results of risk stratification. <strong>Results:</strong> In phase 1, 624 participants completed suicide risk screening, of whom 81 (13%) endorsed PHQ-9 item 9 (score ≥1). Clinician outreach was initiated, on average, 11.2 minutes (SD 13.2 minutes; range 1-54 minutes) after the alert, and 25 of the 81 (31%) participants were successfully reached. In phase 2, 650 participants completed screening, of whom 133 (20.5%) screened positive at baseline. During the 30-day postbaseline observation period, 284 risk-alert events were generated among 172 (26.5%) participants, including 50 conversational suicidal ideation alerts. Clinicians successfully reached 73 of the 172 (42.4%) participants. The mean time from risk detection to initiation of clinician outreach was 11.5 minutes (SD 11.7 minutes; range 1-58 minutes). <strong>Conclusions:</strong> Proactive, universal suicide risk screening and conversational detection using a HITL protocol can be operationally implemented in a GenAI mental health chatbot. A subset of participants who were successfully reached by a human clinician described the approach as acceptable and helpful. Given that clinical contact and assessment were not completed for a substantial proportion of alerted participants, further research is needed to optimize assessment and follow-up strategies for individuals who cannot be reached and to characterize the impact of these procedures on clinical outcomes. Nevertheless, the safety procedures described herein provide a framework for developing and refining HITL safety responses and protocols for purpose-built, AI-native mental health chatbots.
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Meta Mesh Ontology for Cross-Domain Mental Health Knowledge Integration: Development and Evaluation Study

Background: Psychiatric diagnostic practice faces persistent challenges in adequately capturing the complexity, heterogeneity, and dynamic nature of mental disorders. Conventional categorical classification systems such as the and the rely on rigid symptom-based criteria that often fail to represent multifactorial etiologies, dimensional symptom profiles, and high rates of comorbidity. Although dimensional models, domain-specific ontologies, and alternative taxonomies have been developed to address these limitations, they are typically applied in isolation, resulting in fragmented knowledge representations and limited interoperability. This lack of semantic integration hampers data harmonization and cross-domain analysis. Objective: The objective of this work is to develop and present the Meta Mesh Ontology (MMO) and its Core Domain Framework (CDF) as an integrative approach for mapping heterogeneous psychiatric knowledge bases and evaluating ontology structure, logical consistency, and specified retrieval and inference behavior. Methods: We designed a modular ontology architecture grounded in the Basic Formal Ontology to ensure structural and semantic consistency across biological, psychological, and social domains. Existing psychiatric frameworks and ontologies—including dimensional models, diagnostic taxonomies, and socioenvironmental knowledge systems—were systematically analyzed and represented through domain modules using a documented alignment and mapping procedure. The MMO was implemented using formal semantic web standards, including the Web Ontology Language and the Resource Description Framework (RDF), and aligned with established biomedical ontologies and informatics standards to support explicit mappings and modular extensions across domains. Evaluation used 2 MMO and CDF metric sets and 10 module metric sets to quantify ontology size, semantic alignments, external integration, and dataset readiness. We also assessed Web Ontology Language 2 Description Logic (OWL 2 DL) conformance, logical consistency, and 11 competency questions (including 1 entailment test) and 4 negative controls, in an outpatient scenario with 50 variables. Results: The MMO provides a shared semantic framework for representing links among heterogeneous psychiatric knowledge sources. Its modular design allows domain-specific subontologies to be incorporated under a common architecture. MMO and CDF comprised 2238 triples, 208 classes, 28 properties, 3 individuals, and 103 alignments (100 external) across 5 frameworks. The 10 modules added 967 triples and 171 alignments (116 external), with 21 integrations and complete label coverage (54/54 resources). The ontology resources conformed to OWL 2 DL; HermiT (Information Systems Group) detected no logical inconsistency, and all 11 competency questions and 4 negative controls produced the expected results. All 50 variables were linked to at least 1 CDF anchor, and 47 had an explicit Simple Knowledge Organization System (SKOS) mapping. Conclusions: The MMO provides a modular foundation for representing links among diverse psychiatric knowledge systems and data modalities. The current evaluation characterizes its structure, mappings, and behavior in the specified tests. Further research should assess mapping validity, governed clinical data, operational performance, and clinical utility.
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Comparison of short-term peripheral nerve stimulation, single-target supraorbital nerve pulsed radiofrequency, and dual-target supraorbital nerve–stellate ganglion pulsed radiofrequency for herpes zoster ophthalmicus–associated pain: a retrospective cohort study

ObjectiveTo compare the clinical outcomes of short-term peripheral nerve stimulation (st-PNS), supraorbital nerve pulsed radiofrequency (SON-PRF), and combined supraorbital nerve and stellate ganglion pulsed radiofrequency (SON + SG-PRF) for herpes zoster ophthalmicus (HZO)-associated pain.MethodsThis retrospective study included patients with HZO-associated pain who underwent st-PNS, SON-PRF, or SON + SG-PRF between January 2023 and January 2026. The primary outcome was the longitudinal change in Numerical Rating Scale (NRS) scores over 24 weeks. Secondary outcomes included the clinical response rate, anxiety (GAD-7), depression (PHQ-9), sleep quality (PSQI), and treatment-related adverse events. The incidence of postherpetic neuralgia (PHN) was assessed as an exploratory outcome only in patients with a disease duration of ≤90 days at treatment. Longitudinal outcomes were analyzed using baseline-adjusted linear mixed-effects models, with propensity score weighting used for sensitivity analyses.ResultsA total of 269 patients were included: 84 in the st-PNS group, 96 in the SON-PRF group, and 89 in the SON + SG-PRF group. NRS scores decreased over follow-up in all three groups. In the primary and both propensity score-weighted analyses, the overall NRS trajectory was lower with st-PNS than with SON-PRF, whereas no significant difference was observed between st-PNS and SON + SG-PRF. The overall GAD-7 trajectory was lower with SON + SG-PRF than with SON-PRF, and the overall PSQI trajectory was lower with SON + SG-PRF than with either st-PNS or SON-PRF; these differences remained statistically significant in both weighted analyses. The overall trajectories of depressive symptoms did not differ significantly among the groups. Exploratory analysis did not establish a difference in PHN risk among the three groups. No serious treatment-related adverse events occurred during follow-up.ConclusionTo our knowledge, this study is the first to compare multidimensional clinical outcomes of st-PNS, SON-PRF, and SON + SG-PRF for HZO-associated pain within the same cohort. st-PNS showed a relatively consistent analgesic benefit over SON-PRF, whereas SON + SG-PRF also provided analgesia and showed potential benefits for anxiety and sleep outcomes. These findings require confirmation in prospective studies.
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A stacking machine learning model for identifying comorbid anxiety disorder in children and adolescents with functional abdominal pain disorders

ObjectiveComorbid anxiety disorder is common in children and adolescents with functional abdominal pain disorders, but clinically usable risk-stratification tools integrating abdominal pain, psychosocial, school-related, and family-level information remain limited.MethodsIn this observational predictive modeling study, children and adolescents aged 7–18 years with Rome IV-defined functional abdominal pain disorders were evaluated between December 2021 and December 2025. Participants were randomly allocated at a 7:3 ratio into training and internal validation cohorts using stratified sampling by anxiety status. Candidate predictors included demographic, abdominal pain-related, somatic, psychosocial, school-related, and family-level variables. After LASSO-based feature selection, four prespecified base learners—explainable boosting machine, calibrated support vector machine, random forest, and CatBoost—were combined using an L2-penalized logistic regression stacking meta-learner. Performance was assessed using discrimination, threshold-dependent metrics, calibration, decision curve analysis, learner diversity, and SHAP-based interpretability.ResultsAmong 629 eligible patients, 210 (33.4%) had comorbid anxiety disorder. The training cohort included 440 patients, and the validation cohort included 189 patients, with similar anxiety prevalence in both cohorts. Clinically relevant correlates of anxiety included older age, longer symptom duration, higher pain frequency, night-time awakening, pain temporally associated with stressful events, higher SDSC and CSI-24 scores, higher parental GAD-7 score, and greater school absence. In out-of-fold training estimates, the stacking model achieved an AUC of 0.831 and a Brier score of 0.151. In the validation cohort, it showed the highest numerical performance among candidate models, with an AUC of 0.846 (95% CI, 0.789–0.894), accuracy of 0.788, sensitivity of 0.762, specificity of 0.802, F1 score of 0.706, and Brier score of 0.146. Decision curve analysis suggested potential clinical utility across selected threshold ranges. SHAP analysis identified school absence, parental GAD-7 score, CSI-24 score, pain-stress association, symptom duration, pain frequency, SDSC score, age, and night-time awakening as leading contributors to the final model output.ConclusionA stacking machine learning model integrating clinical, psychosocial, school-related, and family-level variables showed acceptable internal-validation performance for identifying comorbid anxiety disorder in children and adolescents with functional abdominal pain disorders. External validation is needed before clinical implementation.