Search Results (1,626)

Fitness centers represent high-contact environments where microorganisms can accumulate and persist on shared surfaces. This study aimed to investigate bacterial contamination dynamics on gym equipment and evaluate the effects of hydrogen peroxide (H₂O₂) nebulization combined with preceding professional manual cleaning on the recovery of viable surface-associated microorganisms. A two-phase investigation was conducted in a commercial fitness facility. Repeated environmental sampling was performed on 12 gym devices over five consecutive days at three daily timepoints (morning, midday, evening), followed by a pre–post assessment of the combined terminal decontamination procedure. All isolates were recovered using culture-based methods and identified by MALDI TOF MS. Species were classified by ecological origin, and persistence, diversity, and intervention effects were quantified using ecological metrics. Statistical analyses were performed in R. Across all samples, 248 isolates representing 61 species were detected, with the recovered isolates predominantly belonging to skin-associated families including Micrococcaceae (25.4%), Staphylococcaceae (24.2%), and Moraxellaceae (22.2%). Routine cleaning with an alcohol-based cleaner produced only modest reductions in recovered bacterial isolate counts (p = 0.173), with 68% of environmental species no longer recovered after routine cleaning, whereas 93% of skin-associated species remained detectable following routine cleaning. In contrast, the terminal decontamination procedure consisting of professional manual cleaning followed by H₂O₂ nebulization resulted in 88% of detected species no longer being recovered after treatment, with no Gram-negative species recovered in post-treatment cultures, while only three Gram-positive species (Staphylococcus epidermidis, Staphylococcus hominis, and Dietzia cinnamea) continued to be recovered after treatment. Contamination levels and persistence patterns varied markedly across devices. Gym equipment surfaces repeatedly yielded predominantly human-derived communities of recoverable viable bacteria despite routine cleaning. The combined terminal decontamination procedure produced greater reductions in recoverable bacterial species than routine overnight cleaning under the conditions evaluated, supporting further investigation of this combined intervention as a supplemental terminal decontamination strategy for high-traffic fitness environments. Full article

Aggregate building indicators can obscure substantial differences in electrical demand and thermal operation among monitored spaces. This case study examined 89 days of one-minute building management system (BMS) and smart-meter records from a multi-zone university building. Routine data-quality screening was combined with physical interpretation and task requirements to determine how the available channels could be used in the exploratory analyses. The resulting map specifies each channel’s permitted use and any associated monitoring priority. Meter TR1 was selected as the primary monitored-load proxy, whereas Meter G was retained for comparative diagnosis. Primary energy analysis used 59 fully observed TR1 days without imputation or scaling. Sensitivity analyses used all 61 days meeting the 90% and 95% completeness thresholds and reported their energy values as available-minute energy aggregates. Across the 59 fully observed days, weekday energy exceeded weekend energy, and complete 24 h TR1 energy was strongly inversely associated with daily mean outdoor temperature (Spearman ${\rho }_{\mathrm{s}}=-0.889$). Of the 21 monitored spaces, five were warm-biased, four were cold-biased, and 12 were near setpoint. Within the observed winter-to-shoulder-season period, the data supported exploratory load and zone-temperature modeling. The combined assessment established record eligibility and channel use in this incomplete real-world export, and it identified priorities for later monitoring. Full article

This preliminary study aims to compare homeschooling in Greece and the UK in terms of experiences, arithmetical attainments, parental motivations, implementation practices, and support structures. For this purpose, we employed a multiple case study design, enrolling a total of five Greek and fifteen British homeschooling families. Results suggested that the Greek parents primarily chose homeschooling in response to their child’s severe and complex medical needs and reported limited access to support systems. British parents provided more varied motivations, higher engagement with educational resources, and stronger integration into informal support networks. The sample of UK children demonstrated higher arithmetical attainment than the Greek sample. Cultural, structural, and regulatory factors appear to shape homeschooling experiences differently across the Greek and UK educational systems. Differences also emerged in terms of daily routines, access to support, and parental confidence. Results are discussed in relation to educational provision and policy development. Full article

Introduction: Long COVID-19 is a complex and multifaceted condition characterized by persistent and fluctuating symptoms extending beyond the acute phase of infection. Aim: To explore the health and support experiences of the Spanish population living with long COVID-19. Methodology: A qualitative study with an interpretative phenomenological approach was used. Semi-structured interviews were conducted over 10 months (2023–2024) across 17 Spanish provinces. The sample included 36 participants. Results: Participants reported persistent and fluctuating symptoms that severely limited daily functioning and generated anxiety, depression, and post-traumatic distress. Chronic fatigue and cognitive impairment affected social participation and work performance, frequently leading to absenteeism and job loss. Delayed diagnosis limited professional knowledge, and perceived lack of credibility contributed to dissatisfaction with healthcare services. Family members and patient associations were key sources of emotional and practical support. Conclusions: Long COVID-19 has a multidimensional impact that requires a comprehensive and multidisciplinary approach. Participants’ narratives reveal how underestimation of symptoms, delayed diagnosis, social stigma, limited healthcare and social support, additional family burdens, and disrupted work and social routines create complexity in care and challenge existing health and economic systems. Full article

As population aging accelerates, providing psychosocial support for adults in the retirement transition has become increasingly important. For this population, a central challenge is adapting to changes in social roles, daily routines, and social relationships, yet existing social robot research has paid insufficient attention to these companionship-related needs. From an embodied cognition perspective, this study developed a needs-driven design pathway for a social companion robot for this population in urban China. Sixteen key needs were identified through user interviews and prioritized through a Kano survey with 184 valid responses from urban community-dwelling adults in the retirement transition. Based on the classification and prioritization results, these needs were synthesized into four design strategies: emotional responsiveness and trust building, social connectedness and sustained engagement, low-burden interaction and daily life support, and safety, health, and privacy protection. Privacy and safety were treated as foundational conditions for product design and practical deployment. The strategies were subsequently mapped to technical features and hardware elements through quality function deployment (QFD), using an expert-panel evaluation procedure and sensitivity analysis to determine module-level configuration priorities. A single-session, laboratory-based concept evaluation was conducted with 50 participants using concept renderings and interaction-flow videos. Concept 3, whose overall configuration emphasized coordinated voice, screen-based visual, and expression/action feedback, received a significantly higher mean participant-level Behavioral Intention (BI) score than Concept 2, which placed greater emphasis on spatial mobility assistance through a mobile wheel module (8.94 ± 0.97 vs. 8.51 ± 1.21; adjusted p = 0.003). These evaluation findings informed the final concept configuration and provided preliminary support for its companionship-oriented multimodal interaction approach. Full article

Background/Objectives: Women with breast cancer (BC) and gynaecological cancer (GC) often undergo extensive oncological treatment, which can lead to pelvic floor disorders (PFD). However, there is still limited evidence regarding their real-world treatment practices, patient counselling, and prevalence. This study aims to systematically evaluate the prevalence of PFD and current treatment approaches, identify unmet needs, and improve future care. Methods: This observational multicentre survey was conducted at four university hospitals and one gynaecological oncology outpatient clinic in Germany. Women with BC and GC, who had undergone at least one oncological treatment, completed anonymously a study-specific questionnaire and the validated German Pelvic Floor Questionnaire. Recruitment was undertaken over a period of nine months, reflecting real-world daily care. Results: A total of 246 patients were included (median age 57 years, range 30–88); 74% were postmenopausal, and 52% had at least one vaginal delivery. BC was the most common diagnosis (63.8%). The most common symptoms were urinary incontinence (22.3% in BC, 38.1% in GC) and urgency (32.5% in BC, 35.7% in GC). Pelvic radiotherapy was significantly associated with increased urgency symptoms (p = 0.017), pelvic surgery with urgency symptoms (p = 0.048) and dyspareunia (p = 0.045), and antihormonal therapy with vaginal dryness (p = 0.028). The combination of chemotherapy and antihormonal therapy was associated with significantly higher rates of vaginal dryness in women with GC, whereas no such association was observed in women with BC (p = 0.036). Among the 108 patients classified as having new-onset symptoms, 51 (47.2%) reported symptom onset within one year of the cancer diagnosis. Overall, 34.1% of patients reported impairment in more than one patient-reported domain, including daily life, social life, sexual well-being, and psychological well-being. The median study-specific impact rating for the most bothersome pelvic floor symptom was 5/10. Only 28.0% of patients received prior counselling on PFD, and 19.9% were actively asked about symptoms. In total, 26.0% received urogynaecological treatment, whereas 15.4% reported unmet treatment needs. Conclusions: PFD is highly prevalent in women with BC and GC. Symptoms are clinically relevant but underestimated in routine care. Despite the availability of effective treatment options, significant gaps exist in patient counselling, early detection, and access to specialised care. Full article

Cycling is one of the most popular sports and recreational activities. Millions of new people start to integrate bicycling into their daily routines every year. Fitness and activity trackers are the most powerful motivation tools for cycling novices and serious cycling enthusiasts. For this purpose, we present LaserFit, a laser-based direct force power meter for fitness and activity tracking during cycling. We developed embedded hardware to collect the torque and the wheel rotation data, which is produced by a laser-based position sensing system mounted on the rear wheel to precisely record the power output produced by the rider during cycling. The sensor data is transmitted to a smartphone via Bluetooth/ANT+ for data acquisition and analysis. Our device can be produced at low costs and deliver a level of accuracy similar to that obtained with the most expensive systems available on the market. A component-level cost analysis is also reported, showing that the LaserFit sensing hardware can be manufactured for a small fraction of the retail price of commercially available direct-force power meters. To evaluate the accuracy of our system, extensive experiments were conducted. The results of the present study suggest that the LaserFit power meter provides a strong relationship (r = 0.97) across a range of trials in laboratory and field conditions when compared with the SRM power meter. LaserFit is therefore considered a valid alternative for training and performance measurement during continuous cycling. Full article

Diagnosing faults across different smart homes is hard: sensor names, layouts, and daily routines differ from home to home, so a model trained in one home rarely works in another. We study an ontology-guided framework for cross-home fault diagnosis, but our main contribution is a benchmark-validity audit—a systematic check of whether the datasets used to evaluate such systems actually measure fault detection. Using the public Center for Advanced Studies in Adaptive Systems (CASAS) smart-home datasets (homes hh101–hh110) and real household power data (HomeC, UMass Smart*), we show that much of the high cross-home accuracy reported on these benchmarks is an artifact of features that re-encode the labelling rules rather than evidence of transfer: when those features are removed, the macro-averaged F1 score (macro-F1) collapses toward the level obtained with randomly permuted labels. We therefore treat these datasets as semantic-transfer and benchmark-validity studies, not fault-detection results. The framework’s distinguishing component is a counterfactual calibration layer that returns a probability for its recommended intervention; on a controlled structural causal model with known interventions, it achieves a Brier skill score of $0.369$ for intervention-success probabilities. Separately, on the simulation-derived LBNL Fan Coil Unit benchmark, a conventional gradient-boosted multiclass fault classifier achieves accuracy comparable to a random forest but about six times lower expected calibration error ($0.026$ vs. $0.159$) under a scenario-matched split. This calibration advantage does not generalize to held-out simulation scenarios, where the calibration error rises to $0.372$; we report this negative result as a limitation. We are explicit about scope: the ontology reasoner and the real-stream causal graph are only partially implemented, and the counterfactual recommendations are validated only under controlled or simulated conditions, not in deployed homes. The results are intended for researchers who build or benchmark sensor-based fault-diagnosis models, for dataset curators, and for practitioners who need calibrated rather than merely accurate outputs. All code, the proxy-label rules, and the leakage audit are released. Full article

Malnutrition, a key factor in oncology, affects 20–70% of cancer patients and influences both cancer risk and outcomes, being linked to decreased treatment tolerance, higher toxicity, lower quality of life, and shorter survival. Although international guidelines recommend early and systematic nutritional screening, its adoption in clinical practice remains inconsistent. This study, promoted by the Italian College of Hospital Medical Oncology Directors (CIPOMO), aimed to provide a national snapshot of current organizational practices regarding nutritional screening, assessment, and management in Italian oncology centers. A 15-item survey was sent to 165 centers to investigate organizational practices and awareness of nutrition and physical activity in cancer care. Data were collected and analyzed as overall percentages. A total of 100 centers responded (61%). Although a nutritional assessment is routinely conducted at diagnosis in 67% of centers (n = 67), only 31 centers perform it for all patients. The remaining centers limit nutritional assessment to high-risk or selected patient groups. Moreover, although 86% of centers have dedicated professionals, multidisciplinary integration remains limited. Validated nutritional screening tools are used in 69% of centers, but follow-up reassessment is rarely systematic (15%). However, awareness of the importance of nutrition is high, with nearly all centers supporting educational interventions and dedicated nutritional pathways. Despite this high level of awareness, a significant gap remains between guideline recommendations and daily clinical practice. Standardizing early nutritional screening, enhancing multidisciplinary collaboration, and ensuring equitable and consistent access to nutritional services are crucial to fully integrating nutrition into oncology care and improving patient outcomes. Full article

Background/Objectives: The 2025 Lancet Diabetes & Endocrinology Commission proposed a framework that distinguishes preclinical from clinical obesity based on confirmed excess adiposity and evidence of obesity-related organ dysfunction. We estimated the prevalence and clinical characteristics of preclinical and clinical obesity in Mexican adults and quantified their discordance with conventional body mass index (BMI) categories. Methods: Cross-sectional analysis of 5014 adults aged ≥20 years (weighted population 77,915,402) from the 2023 Mexican National Health and Nutrition Survey (ENSANUT). Excess adiposity was confirmed by a BMI ≥ 30 kg/m² plus one altered measure of central adiposity, by two altered measures irrespective of BMI, or by a BMI ≥ 40 kg/m² alone. Obesity-related dysfunction was ascertained from available cardiovascular, metabolic, and functional indicators. All analyses accounted for the complex sampling design. Results: Preclinical obesity affected 30.9% of adults and clinical obesity 19.6%. Among adults with clinical obesity, 4.9% had a normal BMI and 18.3% were overweight so that 23.2% fell below the conventional 30 kg/m² threshold. Cardiovascular dysfunction was the most frequent qualifying domain (78.1%), followed by limitations in activities of daily living (27.6%) and metabolic dysfunction (6.7%). Conclusions: BMI alone underestimates obesity-related clinical severity and misses a substantial share of adults with organ dysfunction, supporting the integration of central adiposity measures and assessment of obesity-related dysfunction into routine obesity surveillance. Full article

Background: Individuals with complex communication needs (CCNs) require comprehensive communication profiles to guide effective interventions, yet the clinical literature offers limited tools to support this process. To address this gap, the “Italian CP & Language Network”—a multidisciplinary group of speech–language pathologists, psychologists, and child neuropsychiatrists—developed a novel, comprehensive clinical instrument specifically designed to evaluate the communication skills of children and adolescents with CCNs. Methods: The development process was informed by an initial preliminary survey conducted across participating clinical centres to map out the observation tools routinely used in daily practice. Results: Based on these insights, the network designed a structured clinical interview named the Italian IVCAA (Intervista sulla Valutazione delle Competenze e delle Abilità Comunicative). The instrument was structured to systematically assess four core areas: core communication abilities, communicative behaviours, communicative functions, and communicative modalities (vocal, gestural, graphic/symbolic, and written). The Italian IVCAA provides a structured framework that successfully describes an individual’s unique communication profile. It maps out specific strengths and weaknesses across diverse modalities, establishing a standardized baseline for clinical use. Conclusions: The Italian IVCAA serves as a valuable clinical tool for identifying communication profiles in individuals with CCNs. It offers a practical starting point for setting tailored goals in augmentative and alternative communication (AAC) interventions and establishes a reliable framework for monitoring changes in communicative competence over time. Full article

Reliable visibility forecasting is important for transportation safety and sustainable urban environmental management, particularly in the Sichuan Basin, where poor visibility remains a persistent concern. This study developed a comparative diagnostic framework for one-day-ahead prediction of continuous daily visibility in Chengdu using meteorological and air-quality observations from November 2021 to October 2024. Grey relational analysis and temporal diagnostics were used to characterize variable associations and temporal dependence. Seven methods—seasonal autoregressive integrated moving average with exogenous variables (SARIMAX), CatBoost, long short-term memory (LSTM), Transformer, convolutional neural network–LSTM (CNN–LSTM), CNN–Transformer, and Transformer–LSTM—were evaluated under four input configurations, yielding 28 model–input combinations. SARIMAX achieved the best overall balance between predictive accuracy and generalization stability. CatBoost was the most accurate data-driven method and obtained the highest coefficient of determination (R² = 0.644) under meteorological-only inputs. Meteorological-only inputs outperformed pollutant-only and full multivariate inputs for all models. Among the deep-learning models, LSTM performed better under univariate, meteorological-only, and pollutant-only inputs, whereas Transformer benefited more from the full multivariate input. CNN preprocessing improved LSTM mainly under the full multivariate and pollutant-only configurations. The moderate maximum R² suggests that routine observations did not fully capture aerosol composition, particle number and size distributions, hygroscopic growth, aerosol–water interactions, and fog-related processes. These findings support model and input selection for daily visibility forecasting. Full article

Background: Multimorbidity imposes a substantial burden on older populations, yet research neglects how physical activity (PA) relates to severe disease burden in established cases. Moreover, the efficacy of combining low-cost PA assessments with routine indicators to identify high-burden patients in resource-constrained settings remains unclear. This study explores associations between PA levels and severe multimorbidity (≥4 conditions), evaluating PA’s utility for auxiliary status identification via interpretable machine learning. Methods: This cross-sectional study included the CHARLS 2018 sample (n = 10,130) and a supplementary community sample (n = 315). Multivariable logistic regression evaluated associations between PA and severe multimorbidity. An XGBoost model assessed routine indicators’ classification performance, utilizing SHAP values to analyze feature contributions to the model. Results: PA was inversely associated with severe multimorbidity specifically among those meeting the WHO criteria (MPA > 300 or VPA > 150 min/week) for additional health benefits (OR = 0.80, 95% CI: 0.73–0.88, p < 0.001), especially in adults ≥60 years. Although models using solely routine indicators showed modest discrimination (AUC = 0.673), SHAP analysis revealed PA as the foremost modifiable behavioral feature in classification, with local patterns aligning closely with regression findings. Conclusions: Among middle-aged and older adults with multimorbidity, PA levels exhibit significant categorical associations with severe multimorbidity. In community management, low-cost PA evaluation serves as an auxiliary indicator to preliminarily classify high-burden individuals. Given potential reverse causality, future longitudinal cohorts are required to clarify causal relationships, providing direct evidence for daily activity management. Full article

Wearable technologies are reshaping women’s health by extending observation beyond episodic clinical encounters into daily life. Across the reproductive lifespan, they can capture physiological, behavioral, symptom, and functional trajectories that are often missed in routine care. Yet more data do not automatically translate into better care. Clinical value depends on whether multimodal signals can be modeled and interpreted in relation to reproductive biology, temporal change, and meaningful clinical or functional endpoints. In this perspective, we examine how women’s health wearables can move beyond consumer tracking toward validated digital phenotyping across menstruation, fertility, pregnancy, postpartum recovery, and menopause. We propose a four-layer framework spanning data capture, physiological domain mapping, computational phenotyping, and actionable translation. We then apply this framework across key reproductive life stages. Menstrual health and fertility applications illustrate the shift from calendar-based prediction toward physiological, metabolic, and hormone-aware monitoring. Pregnancy and postpartum applications highlight the need for safety-focused validation, maternal–infant risk awareness, and clinician-governed escalation pathways. Menopause and midlife health represent underdeveloped areas where longitudinal digital phenotyping may better capture vasomotor, sleep, mood, fatigue, and functional symptoms. Across these domains, we identify key barriers to translation, including limited hormone-linked validation, inconsistent evidence standards, underrepresentation of diverse populations, privacy risks, algorithmic bias, and weak workflow integration. By organizing wearable-derived signals across reproductive life stages and identifying major translational barriers, this perspective provides a roadmap toward biologically grounded, equitable, and clinically actionable digital phenotyping for women’s health. Full article

Background: Patients with cystic fibrosis frequently require repeated courses of intravenous antibiotic therapy, resulting in cumulative vascular injury, progressive depletion of peripheral venous access, and increasing complexity in long-term vascular access management. Integrating structured vascular access planning into multidisciplinary care pathways has become increasingly important for preserving venous capital, optimising vascular access decision-making, and ensuring continuity of care. Objective: To describe the development and implementation of an Advanced Practice Nursing-led multidisciplinary vascular access care pathway for patients with cystic fibrosis requiring prolonged intravenous therapy. Methods: A practice-based descriptive analysis of a multidisciplinary vascular access pathway was conducted, incorporating ultrasound vascular assessment, structured clinical decision-making, and coordinated care across the Emergency Department, Cystic Fibrosis Unit, Vascular Access and Infusion Team, Hospital Pharmacy Service, and Hospital-at-Home Programme. An illustrative patient example was used to demonstrate pathway implementation in routine clinical practice. Results: Pathway implementation illustrated the feasibility of integrating ultrasound-guided vascular assessment, evidence-informed selection of vascular access devices, and coordinated home-based intravenous therapy within a multidisciplinary care model. Ultrasound-guided vascular assessment identified a suitable upper-arm basilic vein despite severe peripheral venous depletion. An Advanced Practice Nurse successfully performed ultrasound-guided midline catheter insertion, achieving first-attempt cannulation and no immediate complications. The illustrative patient completed four weeks of home-based intravenous antibiotic therapy without observed catheter-related infection, thrombosis, occlusion, catheter dysfunction, or unplanned hospital readmissions. The patient reported satisfaction with the treatment experience and the ability to maintain daily activities throughout treatment. Conclusions: This study describes and clinically contextualises an APN-led multidisciplinary vascular access care pathway for patients with cystic fibrosis requiring prolonged intravenous therapy. The illustrative patient demonstrated the feasibility of applying the pathway in routine clinical practice. Further prospective multicentre studies are required to evaluate its effectiveness, safety, reproducibility, and broader applicability. Full article