Chronic disease management, an ageing global population, and the aftermath of the COVID-19 pandemic have pushed real-time, continuous health monitoring from a research curiosity toward routine clinical practice. Artificial intelligence (AI), the Internet of Medical Things (IoMT), edge computing, and next-generation wireless networks are converging to enable systems that sense, interpret, and act on physiological data outside the traditional hospital setting.

This is a narrative review, not a PRISMA-guided systematic or scoping review; it synthesises 75 sources (a mixture of primary studies, systematic/scoping reviews, and meta-analyses), individually verified against their published record. The topics span IoMT system architecture and security, wearable and implantable sensing, deep learning for electrocardiogram (ECG), fall-related and human-activity signal analysis, edge and TinyML deployment, federated learning, blockchain-based health-record security, medical imaging diagnostics, explainable AI (XAI), continuous glucose monitoring, 5G/6G-enabled telemonitoring, digital twins, consumer-grade and contactless cardiac sensing, neurological and mental health monitoring, and the materials, regulatory, and acute care infrastructure surrounding real-time deployment. Studies were organised into a five-layer architectural taxonomy spanning perception, edge, network, cloud, and application layers.

Reported accuracies for deep learning models on ECG arrhythmia classification range from 91% to 99.5% across the reviewed studies, but the figures come from different datasets, class definitions, and validation protocols and are therefore not directly comparable; within this heterogeneous evidence, edge-deployed models report accuracies in the 85-96% range at substantially reduced power budgets. Deep-learning-based fall detection and chest radiograph classification are each reported, in the individual studies reviewed, to outperform threshold-based or classical alternatives, though this has not been established through head-to-head comparison across the full evidence base. Federated learning and blockchain are discussed as technical mechanisms that can contribute to data privacy and record integrity; neither constitutes regulatory compliance with frameworks such as HIPAA or the GDPR on its own. Persistent obstacles identified across the reviewed literature include dataset heterogeneity, limited external clinical validation, energy-constrained edge hardware, low clinician trust in opaque models, and fragmented interoperability standards.

The evidence reviewed here is consistent with, but does not by itself establish, a layered, privacy-preserving, and explainable architecture that couples lightweight on-device inference with federated or blockchain-secured cloud learning as a design direction for future real-time healthcare monitoring systems. Future work should prioritise standardised benchmarking, prospective clinical validation, and regulatory-aligned data-governance frameworks.

Background/Objectives: Psychobiotics are live microorganisms that, when administered in appropriate amounts, can enhance mental health. Through the production of neuroactive metabolites, regulation of immune responses, and interactions along the gut-brain axis, they modulate host neurophysiology. However, significant strain-specific variability exists in their metabolic capabilities, colonization potential, and functional interactions, necessitating a systematic approach for psychobiotic strain selection. Methods: In the present study, an integrated in silico systems biology approach combining comparative genomics, genome-scale metabolic modeling, network pharmacology, molecular docking, molecular dynamics, and ADMET analysis was employed to computationally evaluate the therapeutic potential and molecular interactions of a quercetin-psychobiotic co-delivery system for managing depression by modulating the gut-brain axis. Results: Comparative genomic analysis of candidate psychobiotic strains from the genera Bifidobacterium and Lactobacillus predicted the presence of key functional genes involved in neuroactive metabolite production, immune modulation, oxidative stress tolerance, and adhesion. The presence of acetate-producing pathways alongside the absence of classical butyrate biosynthesis genes indicated an indirect contribution to short-chain fatty acid production via microbial cross-feeding interactions. Genome-scale metabolic Modeling under the conditions of quercetin supplementation predicted a significant inter-strain variation in terms of predicted biomass flux, nutrient utilization, and metabolic adaptability. Results of molecular docking showed that the binding energies were in the range of -5.854 to -9.489 kcal/mol. Conclusions: Collectively, these in silico findings provided a computational basis for the selection of psychobiotic strains and predicted that a combination of psychobiotics and quercetin could present a promising strategy for the modulation of the gut-brain axis.

Background/Objectives: Mindfulness-based interventions (MBIs) have gained increasing attention in sport psychology due to their potential to enhance psychological well-being and performance-related outcomes among athletes. Despite various systematic reviews and meta-analyses examining mindfulness in athletic contexts, broader scoping evidence mapping randomised controlled trials (RCTs) of MBIs targeting psychological well-being among athletes remains limited. This scoping review aims to map and synthesise empirical evidence from RCTs examining MBIs and psychological outcomes among athletes, identify methodological and conceptual gaps, and guide future systematic reviews and meta-analytic investigations. Methods: The review followed the Joanna Briggs Institute (JBI) methodology for scoping reviews and was reported according to the PRISMA-ScR guidelines. Searches were conducted across Scopus, Web of Science, and PubMed, initially in March 2026 and updated in April 2026. Data were extracted on study characteristics, participant demographics, intervention features, comparator conditions, outcome measures, and key findings. Results: A total of 17 studies met the inclusion criteria and were included in the review. The included studies generally reported beneficial effects of MBIs across psychological well-being, emotion regulation, cognitive functioning, and sport-related psychological outcomes among athletes. Beneficial effects were reported for several outcomes, including mindfulness, mental toughness, emotional intelligence, mental well-being, flow state, self-compassion, psychological flexibility, emotional regulation, attention, life satisfaction, and grit. Reductions in psychological distress, particularly anxiety and stress, were also reported in several studies, although findings for anxiety were not consistent across trials. Findings were mixed for some other outcomes, including self-esteem, acceptance, and depression. Improvements were additionally reported in social relationships, pleasure regulation, and overall psychological functioning. Conclusions: The findings suggest that MBIs may offer beneficial effects across multiple dimensions of psychological functioning among athletes, although effects were not uniform across outcomes or interventions. These findings indicate the potential utility of structured MBI programmes within athlete support settings, particularly when delivered by or in collaboration with sport psychologists and mental performance consultants, while highlighting the need for further well-designed RCTs to clarify intervention-specific effects and longer-term outcomes.

Residential care settings provide not only protection but also therapeutic opportunities for children and adolescents exposed to relational adversity. This study examined attachment-related behaviors, relational dynamics, and perceptions of reference adults in residential care institutions in Portugal. Participants included 33 adolescents aged 12-18 years and 20 adults working in residential care institutions. Adolescents completed the Inventory of Attachment in Childhood and Adolescence, while professionals completed the Observation Checklist and provided qualitative descriptions of adolescents' functioning and intervention strategies. The results revealed a predominance of non-secure attachment profiles, particularly ambivalent attachment, alongside considerable heterogeneity in observed attachment-related behaviors. Avoidant attachment emerged as a significant predictor of increased observational mental health risk, whereas observed secure attachment-related behaviors were negatively associated with psychological vulnerability. Qualitative findings highlighted the importance of emotionally responsive, consistent, and trusting relationships with reference adults, as well as the value of emotional validation, clear boundaries, and attachment-informed caregiving practices. The high heterogeneity of self-reported attachment representations and observational measures underscores the complexity of attachment functioning in trauma-exposed populations and supports the use of multi-method assessment approaches. Overall, the qualitative findings suggest that resilience in residential care is fundamentally relational and may be strengthened through stable, emotionally attuned relationships with caregivers. This study reinforces the importance of attachment-informed and trauma-informed practices in promoting psychological well-being, emotional regulation, and positive developmental trajectories among adolescents living in residential care.

Chinese university students face academic, employment, and interpersonal pressures that may increase their vulnerability to anxiety and depression. Artistic creative activities (ACAs) provide contexts in which individuals may regulate emotions, but the strategies used during these activities require appropriate measurement. A previous Chinese adaptation of the Emotion Regulation Strategies for Artistic Creative Activities (ERS-ACA) Scale was validated among art and design majors and omitted one item. The present study evaluated the psychometric properties of the original 18-item Chinese ERS-ACA in 885 university students from multiple academic disciplines. Participants completed the ERS-ACA, the Emotion Regulation Questionnaire (ERQ), and the Student Well-Being Process Questionnaire (Student-WPQ). Confirmatory factor analysis supported the original three-factor structure. Internal consistency was satisfactory for the total score (Cronbach's alpha = 0.903) and the three subscales (alpha = 0.796-0.814). The three ERS-ACA dimensions were positively associated with cognitive reappraisal, positive well-being, and positive personality, whereas their associations with expressive suppression were small or non-significant. These findings support the structural validity, criterion-related validity, and internal consistency of the 18-item Chinese ERS-ACA in the present university student sample. Further validation in other populations is warranted.

Understanding the relationship between creative self-regulation and adolescent creativity is important for advancing research on creativity development. However, the psychological processes that may account for this association remain insufficiently explored. The present study aimed to examine the relationship between creative self-regulation and self-reported domain-specific creativity among adolescents, with particular attention to the sequential mediating roles of cognitive flexibility and creative self-efficacy. A total of 1204 Chinese adolescents completed the Creative Self-Regulation Questionnaire (CSRQ), the 20-item Kaufman Domains of Creativity Scale (20-K-DOCS), the Cognitive Flexibility Inventory (CFI), and the Creative Self-Efficacy Scale (CSES). The results showed that creative self-regulation was positively associated with self-reported domain-specific creativity, with significant indirect associations through cognitive flexibility and creative self-efficacy. In addition, a significant sequential indirect association was observed through cognitive flexibility and creative self-efficacy. Specifically, higher levels of creative self-regulation were associated with greater cognitive flexibility, which was in turn associated with higher creative self-efficacy and higher self-reported creativity scores. These findings support an integrated cognitive-motivational framework for understanding the interrelationships among creative self-regulation, cognitive flexibility, creative self-efficacy, and self-reported domain-specific creativity among adolescents, while highlighting these constructs as potentially relevant psychological resources in educational contexts. Given the cross-sectional design, these findings should not be interpreted as establishing causal or temporal relationships among the constructs.

Brief campus-based interventions for university students with elevated internet gaming disorder (IGD) symptoms have received little study. This randomized trial evaluated a five-session group program focused on gaming motives, self-regulation, and alternative sources of competence and self-worth. Sixty-three adult students at a Chinese vocational college who scored at least 20 on an adapted Gaming Disorder Scale for Adolescents were randomized to the program (n = 31) or an information-only control condition (n = 32). Assessments were scheduled at baseline, immediately after the intervention, and one month later. Because post-randomization outcome data were unavailable for 19 participants, the comparative analyses were restricted to 44 completers. The originally planned baseline-adjusted ANCOVA showed a lower adjusted T1 IGD score in the intervention group than in the control group (adjusted difference = -4.62, 95% CI -7.33 to -1.91, p = 0.0013). In a post hoc linear mixed-effects model, the between-group difference in change from baseline to post-intervention was -5.16 points (95% CI -7.81 to -2.51; Hedges g = -1.03). At one month, the difference was smaller and not statistically significant (-1.67 points, 95% CI -4.31 to 0.98). None of the secondary outcomes showed a significant interaction. Overall attrition was 30.2%. These preliminary findings concern selected completers rather than an intention-to-treat effect, and the between-group difference was not evident at one month. Retrospective registration, unavailable outcomes for non-completers, and post hoc analyses limit the strength of the inference. The trial was retrospectively registered in UMIN-CTR (UMIN000055209) on 9 August 2024.

School-based prevention programs increasingly incorporate mental health-related components to prevent substance use among adolescents. This study aimed to evaluate the effectiveness of integrated school-based mental health and substance use prevention programs for adolescents through a systematic review and meta-analysis. A systematic literature search was conducted across 12 electronic databases for studies published between January 2016 and April 2026. Randomized controlled trials (RCTs) and cluster randomized controlled trials evaluating school-based integrated prevention programs for adolescents were included. Random-effects meta-analyses were performed for substance-use outcomes, including alcohol-related outcomes and binge drinking, using pooled odds ratios (ORs) and 95% confidence intervals (CIs). Mental health and psychosocial outcomes were synthesized narratively because heterogeneity in outcome definitions, measurement instruments, and assessment periods precluded meaningful quantitative pooling. A total of 16 reports representing 10 independent trials were included in the systematic review, and five independent trial comparisons were included in the primary meta-analysis. Integrated prevention programs significantly reduced alcohol-related behaviors among adolescents compared to control groups (OR = 0.56, 95% CI = 0.37-0.86, p = 0.008). Significant preventive effects were also observed for binge drinking outcomes (OR = 0.32, 95% CI = 0.16-0.64, p = 0.001). Most interventions incorporated emotional regulation, resilience enhancement, coping skills, stress management, and help-seeking promotion. Digital and online approaches were frequently used. Narrative findings suggested potential benefits for selected psychosocial and mental health-related outcomes; however, these outcomes were not quantitatively pooled and were not consistently sustained across follow-up periods. Integrated school-based prevention programs incorporating mental health-related components demonstrated beneficial effects on alcohol-related behaviors and binge drinking among adolescents. Evidence regarding mental health and psychosocial outcomes was based on narrative synthesis and remains less conclusive. These findings support the importance of integrated prevention approaches that simultaneously address substance use and mental health in school settings. However, additional large-scale RCTs with standardized outcome measures and long-term follow-up are needed to strengthen the current evidence base.

Post-neurosurgical bacterial meningitis (PNBM) is a serious complication associated with substantial morbidity and mortality. Bacterial culture presently serves as the gold standard for diagnosis, however, clinical reliance on third-tier reports to address empirical antibiotic concerns, with a turnaround time of 3-5 days, can lead to imprecise antibiotic administration in patients. Therefore, we develop and validate a branch of machine learning method to predict the result of cerebrospinal fluid (CSF) culture, which can shorten the time for precise diagnosis to within 2 h. A cohort study was conducted in nonmaternity inpatient units at Beijing Tiantan Hospital & Capital Medical University during Jan 2016 to Dec 2020. Six machine learning models including 4 decision tree models(Random Forest, Catboost, LightGBM, and XGboost), Support Vector Classification(SVC) and Multi-Layer Perceptron(MLP) were applied for two models construction by utilizing tenfold cross-validation.The performances of these models were assessed in terms of discrimination, calibration, and clinical application in another 3 years cohort. In this study, the derivation cohort included 4014 patients, of whom 995 had positive CSF cultures, including 431 Gram-negative and 564 Gram-positive cultures, and 3019 had negative cultures. The temporal validation cohort included 1059 patients. LightGBM achieved the highest the area under the receiver operating characteristic curve (AUC) for Model 1 and Model 2, at 0.898 and 0.875, respectively. SHapley Additive exPlanations (SHAP) analysis identified CSF leukocyte(C-Leu) count as the leading predictor of culture positivity and Gram-negative cultures, whereas platelet count was the principal contributor to Gram-positive culture classification. Machine learning, specifically leveraging LightGBM modeling showed good discrimination in predicting CSF bacterial culture outcomes after neurosurgery. The model may support early risk stratification while culture results are pending.

This study examines socio-demographic and healthcare-related factors associated with recruitment and participation in a large randomized controlled trial (RCT) of telephone-based self-management support.

This register-based study included 78,861 individuals identified as being at risk of future hospital admissions and invited for eligibility assessment for the Danish Proactive Health Support (PaHS) RCT (2018-2022). National registers provided data on socio-demographics, chronic disease burden, and healthcare utilization prior to recruitment. Multivariate logistic regression was used to analyze factors associated with successful contact and subsequent consent to participation.

Half of the invited population (51%) was never reached despite repeated attempts. Successful contact was more likely among older individuals, those who were married, had higher educational attainment, chronic diseases, and higher healthcare utilization. Among the 11,109 individuals deemed eligible and informed, 55% consented to participate. In contrast to the contact phase, increasing age was strongly associated with lower likelihood of consent. Individuals with multimorbidity and higher healthcare utilization were significantly more likely to consent to participation. Socio-demographic factors were not independently associated with consent after contact was established.

Recruitment to self-management support involves a selection process, where inequities arise primarily during initial contact attempts where older adults and socially vulnerable groups were less likely to be reached. After successful contact, patients with greater healthcare needs were more likely to participate.

Recruitment to self-management support interventions involves a selection process in which inequities may arise before eligibility is fully assessed. Efforts to improve participation should therefore consider not only eligibility criteria but also factors influencing successful contact and willingness to participate. The findings challenge the distinction between eligibility and consent in self-management interventions and underscore the need to reconsider patient preferences and readiness as dynamic, context-dependent factors in intervention design.