Search Results (8,025)

Background: Micronutrient deficiencies (MD) are highly prevalent among candidates for bariatric surgery (BS) and are associated with adverse perioperative and postoperative outcomes. Although guidelines recommend systematic preoperative screening and correction, conventional targeted supplementation (CTS) often requires multiple products, potentially limiting adherence and delaying surgical readiness. Bariatric-specific multivitamins (BSM) may simplify nutritional management, but their real-world effectiveness for preoperative correction of multiple MD remains insufficiently investigated. Objective: To compare the effectiveness, efficiency, and adherence of a BSM versus CTS for preoperative correction of multiple MD in BS candidates. Methods: This retrospective multicenter cohort study included 1560 adults with obesity evaluated for BS between 2020 and 2024 across three Italian bariatric centers. The primary efficacy analysis was restricted to patients presenting with ≥3 laboratory-confirmed MD at baseline. Patients treated between 2020 and 2022 received individualized CTS using multiple products, whereas those treated between 2023 and 2024 received a single BSM. Biochemical follow-up was scheduled at 4 and 8 weeks. The primary outcome was the achievement of complete biochemical correction of all baseline deficiencies at the predefined 4-week follow-up assessment (composite endpoint). Secondary outcomes included supplementation burden and self-reported adherence. Early correction rates were compared using absolute risk differences and risk ratios; adjusted associations were evaluated using multivariable regression models including center and baseline deficiency burden. As a supplementary analysis, the patient-level proportion of baseline deficiencies corrected at 4 weeks was also evaluated. Results: Among patients with ≥3 baseline deficiencies (n = 216), complete biochemical correction at 4 weeks was achieved in 55/134 patients (41.0%) in the BSM group and in 13/82 patients (15.9%) in the CTS group, corresponding to an absolute risk difference of 25.2 percentage points (95% CI 7.8–40.0) and a risk ratio of 2.59 (95% CI 1.51–4.44). In adjusted analyses accounting for center and baseline deficiency pattern, BSM use remained independently associated with early complete correction (adjusted absolute risk difference 26.3 percentage points; adjusted risk ratio 2.69). Sensitivity analyses restricting follow-up timing and excluding early calendar periods yielded consistent results. The mean proportion of baseline deficiencies corrected per patient at 4 weeks was higher in the BSM group compared with CTS (0.74 ± 0.25 vs. 0.54 ± 0.30). Compared with CTS, BSM was associated with lower supplementation burden (1 vs. 3.5 supplements on average) and higher adherence (92% vs. 70%). Conclusions: In a real-world multicenter cohort of BS candidates with ≥3 baseline MD, a simplified preoperative supplementation strategy based on a BSM was associated with a significantly higher probability of complete biochemical correction at 4 weeks, lower supplementation burden, and higher reported adherence compared with CTS. Although complete correction was not universal at 4 weeks, BSM significantly increased the likelihood of achieving early multi-deficiency normalization. Given the non-concurrent observational design, these findings should be interpreted as hypothesis-generating and warrant confirmation in prospective studies with concurrent cohorts. Full article

The growing demand for high-fidelity, multi-parameter, distributed sensing in critical domains such as structural health monitoring, oil and gas exploration, and secure perimeter surveillance is pushing traditional optical fiber sensors (OFS) to their performance limits. Although conventional multiplexing techniques such as time-division and wavelength-division multiplexing (TDM, WDM) have been commercially successful, they are rapidly approaching fundamental bottlenecks in sensor density, spatial resolution, and data capacity. This review argues that the synergistic convergence of space-division multiplexing (SDM) and artificial intelligence (AI) represents a paradigm shift, enabling a new generation of intelligent, high-dimensional sensing networks. We comprehensively survey the state of the art in SDM-based OFS, detailing the operating principles and applications of multi-core fibers (MCFs) for ultra-dense sensor arrays and 3D shape sensing, as well as few-mode fibers (FMFs) for mode-division multiplexing and enhanced multi-parameter discrimination. However, the unprecedented spatial parallelism provided by SDM introduces significant challenges, including inter-channel crosstalk, complex signal demultiplexing, and massive data volumes. This paper systematically explores how AI, particularly machine learning (ML) and deep learning (DL), is being leveraged not merely as a tool but as an indispensable core technology to mitigate these impairments. We critically analyze AI’s role in digital crosstalk suppression, intelligent mode demultiplexing, signal denoising, and solving complex inverse problems for parameter estimation. Furthermore, we highlight how this AI–SDM synergy enables capabilities beyond the reach of either technology alone, such as super-resolution sensing and predictive analytics. The discussion is extended to include the critical supporting pillars of this ecosystem, such as advanced interrogation techniques and the associated data management challenges. Finally, we provide a forward-looking perspective on the trajectory of the field, outlining a path toward cognitive sensing networks that are self-calibrating, adaptive, and capable of autonomous decision-making. This review is intended to serve as a foundational reference for researchers and engineers at the intersection of photonics and intelligent systems, illuminating the pathway toward tomorrow’s intelligent sensing infrastructure. Full article

Background/Objectives: Wound management presents a substantial clinical challenge due to the rising incidence of chronic wounds, infections, and the limitations of conventional dressings in creating an ideal healing microenvironment. This review aims to provide a comprehensive overview of advanced smart hydrogel platforms designed to improve wound healing outcomes, focusing on their capacity to respond adaptively to physiological and external stimuli. Methods: This article analyzes the core characteristics of smart hydrogels, specifically examining stimuli-responsive systems (pH, temperature, enzyme, light, and electricity). The review evaluates advanced configurations—including injectable, self-healing, and 3D-printable systems—and functionalized hydrogels integrated with antimicrobials, drugs, and nanocomposites. Additionally, essential characterization methodologies, biological assessments, and regulatory considerations for clinical translation are synthesized. Results: The literature, which is predominantly preclinical in nature, indicates that functionalized hydrogels significantly enhance tissue regeneration, angiogenesis, and infection control compared to traditional methods. Conductive hydrogels utilizing bioelectrical signals show particular promise in accelerating the healing process. While current clinical applications and commercial products demonstrate efficacy, significant barriers remain regarding large-scale manufacturing and regulatory approval. Conclusions: Smart hydrogels represent a transformative approach to precision wound management, offering superior adaptability and therapeutic delivery. To achieve widespread clinical adoption, future research must address manufacturing scalability and focus on emerging trends, such as the integration of biosensors and AI-powered monitoring systems, to create fully intelligent wound care solutions. Full article

Against the backdrop of dietary structure evolution and the “big food concept” strategy, there has been a shift from the traditional grain-centric perspective toward a diversified supply system. Taking Hubei Province—a major grain-producing region in China—as a case study, this research establishes a multi-criteria evaluation system and conducts analysis using statistical yearbooks and land survey data. By integrating natural conditions, economic benefits, and production capacity, the suitability of cultivated land for growing grain crops, cash crops, and forage crops is assessed. Concurrently, landscape pattern indices were applied to quantify the degree of farmland fragmentation. Employing a self-organizing mapping (SOM) neural network model, we synthesized suitability and fragmentation data to delineate differentiated farmland conservation zones. The results revealed significant spatial heterogeneity in crop suitability and fragmentation levels. High-suitability zones for grain crops were concentrated in the Jianghan Plain, while forage crops exhibited higher suitability in northeastern and southeastern Hubei. Farmland fragmentation showed a spatial pattern of lower levels in central Jianghan Plain, gradually increasing toward surrounding hilly and mountainous areas. SOM clustering effectively partitioned farmland into six functional zones: multifunctional agricultural zones, mixed farming zones, grain crop zones, cash crop zones, forage crop zones, and production improvement zones. This multi-source geographic and statistical data-driven zoning framework provides scientific basis for targeted policy interventions. It enables the quantitative management, quality enhancement, and spatial optimization of farmland resources, thereby operationalizing the big food concept to strengthen regional food security. Full article

This article is about the concept of external psychological control (having a sense of psychological control over the environment). This article examines the construct of external psychological control and differentiates it from similar concepts, showing its unique attributes and how it can help understand a diverse array of psychological phenomena. Of note, external psychological control differs from internal psychological control, which is about maintaining internal psychological equilibrium or being grounded. The term psychological control is similar to terms, but we show that it differs from them and is unique in how it is presently defined. Some of these terms include distress tolerance, self-efficacy, and many variations in terms of control as part of the terminology. Another term examined is related to psychological reserve, the depletion of which affects psychological control. The article presents an original questionnaire that could be used to research external psychological control. The article concludes with a formal mathematical representation of the interaction between psychological control and psychological reserve, and with simulation research that serves as a proof of concept of the constructs proposed. The concepts of psychological control and psychological reserve can help in understanding psychotherapeutic change mechanisms. The concepts of psychological control and psychological reserve are relatively novel terms that can help understand reactions to stress and consequent stress management. Full article

This research examines the potential of Battlefield Tourism as a strategic tool for rural development, focusing on the cultural heritage of Extremadura, Spain. Given the specific nature of the regional tourism offer, this paper is presented as a case study to analyze how military historical resources can be integrated into sustainable tourism models. The study employs a mixed-methodology approach, combining a quantitative cross-sectional survey with complementary qualitative analysis of open-ended responses. A sample of 149 municipal managers was analyzed to evaluate their institutional perceptions of military cultural tourism and its potential integration into regional strategic initiatives. Results, supported by χ² tests and Cronbach’s α reliability analysis, suggest that the use of specific terminology associated with cultural heritage, rather than ‘war’ or ‘dark’ tourism, is perceived by local stakeholders as more socially and politically acceptable for rural development plans. Given the sample size and self-selection bias, these perception-based findings highlight the importance of terminological sensitivity for local leaders exploring new tourism offerings. The study concludes that, from an institutional standpoint, framing Battlefield Tourism through professional heritage protocols may facilitate its acceptance as a potential tool for economic diversification in inland destinations facing challenges of depopulation. Full article

Background/Objectives: Temporomandibular disorders (TMD) are common in pediatric patients, yet limited data exist on orthodontists’ knowledge, confidence, and clinical practices related to pediatric TMD. This cross-sectional study aimed to characterize orthodontists’ perceived knowledge, confidence, training, and practice patterns, and examine associations between routine screening behaviors and perceived confidence. Methods: A 34-item anonymous survey was distributed to orthodontists and orthodontic residents enrolled in or graduated from U.S. Commission on Dental Accreditation (CODA)-accredited programs. The survey assessed perceived knowledge, confidence in screening, diagnosis, and management of pediatric TMD, adequacy of residency training (on 0–10 numerical rating scale), frequency of routine TMD screening and examination practices, and referral patterns. Respondents were compared in study outcomes according to years of clinical practice with ANOVA. Respondents were categorized according to frequency of TMD screening (always/some of the time vs. sometimes/never) and compared in study outcomes using independent t-tests. Results: Out of 83 respondents, perceived knowledge (56.8 ± 26.9), confidence with screening (62.0 ± 30.5), diagnosis (59.4 ± 29.8), and management (50.8 ± 30.9) of pediatric TMD were moderate. Less than half of respondents (45.8%) reported routinely screening pediatric patients using standardized screening questions. Orthodontists who reported routine screening demonstrated significantly greater perceived knowledge and confidence in screening, diagnosis, and management compared with those who screened less frequently (all p’s ≤ 0.018, effect size between 0.57 and 0.78). Greater use of specific history-taking and clinical examination components was also associated with higher perceived confidence (all p’s between 0.001 and 0.046, effect size between 0.53 and 1.01). Confidence differed by years in practice, with lower scores reported among residents and mid-career practitioners (p < 0.05). Conclusions: Variability exists in orthodontists’ perceived knowledge, confidence, and clinical practices regarding pediatric TMD. Routine screening was associated with greater perceived competence. These findings highlight potential alignment between structured screening behaviors and self-reported confidence and may inform educational strategies in orthodontic training. Full article

Safety monitoring in container hoisting operations within rail-road intermodal logistics parks is a critical task in industrial safety management. Such scenarios are characterized by complex environments, large variations in target scales, deformable object shapes, and frequent occlusions, which pose significant challenges to visual perception systems. Conventional single-task models suffer from inherent limitations in handling low recall rates for distant small targets and insufficient adaptability to geometric deformations, making them inadequate for high-precision, real-time safety warning applications. To address these challenges, this study proposes a unified visual analysis framework that integrates semantic segmentation and object detection to enhance the recognition performance of small and deformable targets in complex operational environments, enabling real-time perception and safety warning of key objects and hazardous regions within container yards. Specifically, we introduce FSD-YOLO, a fusion-based architecture composed of the following key components. First, a SegFormer-based semantic segmentation module is employed to achieve pixel-level delineation of different operational regions. Second, an improved object detection network is developed based on the YOLOv8n architecture, incorporating: (1) the integration of C2f modules in the shallow layers of the backbone to enhance high-resolution feature extraction; (2) the embedding of C2fDCN modules within the detection head to improve modeling capability for deformable objects via deformable convolution; (3) the adoption of CARAFE upsampling operators to optimize multi-scale feature fusion; and (4) a dynamic loss-weighting strategy for small objects, where loss weights are adaptively adjusted according to target area to increase training emphasis on small-scale targets. Finally, a decision-level fusion strategy is applied to combine segmentation and detection outputs, enabling real-time safety judgment based on semantic rules. Experimental results on a self-constructed container yard dataset demonstrate that the proposed detection model achieves an mAP50-95 of 0.6433 and an mAP50 of 0.9565, significantly outperforming the baseline YOLOv8n model (mAP50-95: 0.5394, mAP50: 0.8435), thereby validating the effectiveness of the proposed framework. Full article

The operation of the gas–steam–electricity multi-energy coupling system in iron and steel enterprises faces critical challenges: conflicts between energy efficiency and economic objectives, insufficient scheduling accuracy, and low energy utilization caused by source–load fluctuations. To address these issues, this paper proposes a hybrid scheduling model based on condition awareness and multi-objective optimization. The model integrates three key components. First, an energy fluctuation prediction technology based on working condition changes is developed. By acquiring real-time production signals and gas flow data, combined with a condition definition management module, it enables automatic identification and tracking of equipment operation status. A working condition sample curve superposition method is used to calculate energy medium imbalances, generating visual prediction curves for key parameters such as blast furnace, coke oven, and converter gas holder levels, achieving an average prediction accuracy of ≥95%. Second, a peak-shifting and valley-filling scheduling model for gas holders is designed, leveraging time-of-use electricity prices. During valley price periods, power purchases are increased and surplus gas is stored; during peak price periods, gas power generation is increased to reduce purchased electricity. A nonlinear model capturing the load–efficiency relationship of boilers and generators is established to dynamically optimize scheduling strategies. This reduces the proportion of peak hour power purchases by 10.3%, energy costs by 3.12%, and system energy consumption by 2.16%. Third, a multi-period and multi-medium energy optimization scheduling model is formulated as a mixed-integer nonlinear programming (MINLP) problem, with dual objectives of minimizing operating cost and energy consumption. Constraints include energy supply–demand balance, equipment operating limits, gas holder capacity, and generator ramp rates. The Pareto optimal solution set is obtained using the AUGMECON2 method and efficiently computed with the IPOPT solver. Application results demonstrate that the model achieves zero gas emissions, a dispatching instruction accuracy of 95%, and a 0.8% increase in the proportion of peak–valley-level self-generated power, outperforming comparable technologies. It provides technical support for the safe, efficient, and economic operation of multi-energy systems in iron and steel enterprises. Full article

Transplanting status is a significant indicator for rice cultivation, and is essential for field management, food security and agricultural production. However, traditional characterization cannot detect the transplanting status in a timely and effective manner; manual seedling replanting is labor-intensive, has a high cost and is inefficient. This study proposed a detection method for floating seedlings and missed transplanting. The method employed a self-built improved YOLO, namely HGV-YOLO. We leverage a HorBlock module to achieve the splitting of the morphological features of rice seedlings in different dimensions of the backbone network of YOLOv8n, which enabled the network to further enhance the classification and recognition ability of rice seedlings. Furthermore, Grouped Spatial Convolution (GSConv) replaces convolution, and the VOV-GSCSP replaces the C2f modules, reducing the number of parameters and improving the model’s inference speed. To improve the model’s bounding box precision, the WIoU loss function was also incorporated. Finally, we use the least squares method to predict the center point of the rice seedlings. The experimental results indicate that HGV-YOLO achieves a precision of 93.7%, a recall of 83.1%, and an mAP@0.5 of 91.1%. Compared to YOLOv8n, HGV-YOLO reduces Params by 3.1% and GFLOPs by 1.2%, respectively, while improving mAP@0.5 by 2.3%. Compared to YOLOv3-tinyYOLOv5 and YOLOv6, HGV-YOLO achieves increases in mAP@0.5 of 4.6 %, 3.1%, and 2.8%, respectively. In summary, the HGV-YOLO model exhibits a strong performance and provides valuable insights for advancing the autonomous navigation of rice transplanting robotics. Full article

Background: The Mediterranean diet (MedDiet) has been associated with anti-inflammatory effects and potential benefits in several chronic conditions. However, adherence to the MedDiet and its relationship with lifestyle factors and disease severity across different rheumatological diseases remain poorly characterized. Objectives: This study aimed to evaluate differences in MedDiet adherence among patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and fibromyalgia (FM), and to explore its association with cardiovascular comorbidities, bowel habits, and disease-related outcomes. Methods: In this monocentric cross-sectional study, adherence to the MedDiet was assessed using the 14-item PREDIMED questionnaire. Self-reported data on sociodemographic characteristics, cardiovascular comorbidities, bowel habits, and dietary behaviors were collected through questionnaires. Disease activity and severity were assessed using validated disease-specific measures. Differences in MedDiet adherence across diagnostic groups were evaluated using non-parametric tests. Multivariable models were performed to examine associations between MedDiet adherence and cardiovascular comorbidities or disease outcomes, adjusting for potential confounders including age, sex, BMI, smoking status, and educational level. Results: A total of 422 participants were included (RA n = 165, PsA n = 85, FM n = 172). Significant differences in MedDiet adherence were observed across diagnostic groups (p < 0.001), with the highest adherence in RA, intermediate values in PsA, and the lowest in FM. Compared with the other groups, a higher proportion of FM participants reported food intolerances (46.5%) and restrictive diets, including lactose-free (34.9%) and gluten-free (15.1%) diets. In the FM group, high adherence to the MedDiet was significantly associated with lower FIQR scores (β = −16.9; 95% CI −32.1 to −1.7; p = 0.01) and lower PDS scores (β = −4.34; 95% CI −7.81 to −0.86; p = 0.01). Sensitivity analyses using the continuous PREDIMED score confirmed these associations. Conclusions: Adherence to the MedDiet differs across rheumatological diseases, with the lowest adherence observed in FM. Higher adherence was associated with lower disease severity and impact in FM. These findings highlight the potential relevance of nutritional counselling in rheumatological diseases and support the need for longitudinal and interventional studies evaluating the role of the MedDiet within multidisciplinary disease management. Full article

Self-regulated learning (SRL) is a fundamental competence for academic transition and success in higher education, especially in health sciences, where autonomy and learning management are essential. This systematic review analyzed the relationship between SRL, academic performance, and student well-being among undergraduate health sciences students. Following the PRISMA protocol, 39 articles published between 2015 and 2025 on Web of Science, Scopus, and PubMed databases were selected. The consolidated sample consisted of 24,835 participants. The methodological quality of the selected studies was assessed using the Newcastle–Ottawa scale (NOS). A predominantly positive association was found between high levels of SRL and academic performance (GPA) (with correlation coefficients ranging from r = 0.11 to r = 0.55 in the primary studies). Furthermore, evidence from standardized self-report questionnaires in the reviewed literature indicates that several studies report female students showed higher levels of organization and planning, but these findings were not consistently observed across all studies. SRL acts as a key protective factor against stress, anxiety, and academic burnout. However, a “stagnation paradox” was identified: SRL skills do not always evolve linearly, often showing regression or stagnation in advanced clinical years due to the high cognitive load and insufficient support structure in those environments. Regarding sociodemographic variables, female students reported higher levels of planning and responsibility. SRL does not develop spontaneously with academic progress. Therefore, higher-education institutions must implement systematic and intentional pedagogical strategies from the early years of training to foster student well-being and the development of resilient professionals. Full article

Background: While mobile health (mHealth) interventions show promise for type 2 diabetes management, mechanisms linking user experience to clinical outcomes remain poorly understood. We hypothesized that perceived usability may mediate associations between patient characteristics and short-term clinical changes, with implications for health equity in digital interventions. Methods: Secondary analysis of the intervention arm from a randomized controlled trial in urban Mexican primary care (ClinicalTrials.gov NCT05924516). Participants used a diabetes self-management mobile application for 90 days. We assessed usability with the validated Computer System Usability Questionnaire (CSUQ; 16 items, 7-point scale) and measured clinical changes in body mass index (BMI), systolic blood pressure (SBP), and HbA1c. Bayesian mediation analysis (literature-informed priors) examined interface quality as a mediator of age-related clinical effects. Item-level analysis identified educational disparities in specific usability dimensions using independent t-tests adjusted for multiple comparisons. Results: Mean overall usability was 5.20/7 (SD = 0.89, 74th percentile). Interface quality mediated 39% of the age–SBP association. Participants experiencing high usability (≥6) versus low usability showed BMI reduction −0.78 vs. −0.21 kg/m² (Cohen’s d = 0.56) and SBP reduction −7.3 vs. −1.2 mmHg (Cohen’s d = 0.51). No mediation effect was observed for HbA1c change. Users with ≤primary education (41% of sample) scored 1.9 points lower on error messages (3.2 vs. 5.1, p < 0.01) and 1.4 points lower on help documentation (3.6 vs. 5.0, p < 0.03). These disparities persisted after controlling for age and baseline severity. Conclusions: Perceived usability was associated with a potential mechanistic pathway linking user experience to clinical outcomes. Higher usability scores were associated with clinically meaningful improvements in cardiometabolic parameters. Educational disparities in understanding error messages and helping documentation represent modifiable design barriers. Implementing contextual error explanations with visual examples and plain-language help content may enhance both clinical effectiveness and equity in digital diabetes interventions. Full article

Background: Dental adhesive materials are important for achieving adequate adhesion results; however, they are not the only factor contributing to final bond strength, as improper operatory field isolation and contamination also significantly influence clinical outcomes. Objectives: This narrative review aims to provide a clinical perspective, supported by evidence-based arguments, to identify clinical procedures for optimizing adhesive protocols, including the execution of absolute isolation with a rubber dam, appropriate cleaning and preparation of the dental substrate, and protocols applicable to total-etch and self-etch techniques. Methods: The literature included in this review was selected through a structured search in PubMed, Scopus, and Web of Science, prioritizing systematic reviews, meta-analyses, long-term clinical studies, and foundational experimental investigations related to adhesive systems and substrate management. Results: A well-established clinical protocol that integrates proper adhesive selection, contamination-free operative field control, and adequate substrate preparation is essential for achieving predictable outcomes in adhesive dentistry. Conclusions: Although simplified adhesive systems offer acceptable bond strength results, established techniques continue to demonstrate consistent reliability, contributing to restorative longevity. Full article

Background/Objectives: Head and neck cancer survivors experience many late toxicities following radiation therapy. This study aims to identify symptom clusters of late toxicities and their related factors in head and neck cancer survivors. Methods: A cross-sectional study was conducted with 83 survivors (pharyngeal or laryngeal cancer) who had received radiation therapy at least one year earlier. Nine late toxicities were assessed using the Japanese version of the Patient Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) and a custom questionnaire. Quality of life (QoL) and related factors were evaluated with the European Organization for Research and Treatment of Cancer (EORTC QLQ-C 30), Hospital Anxiety and Depression Scale (HADS), UCLA Loneliness Scale, and Liebowitz Social Anxiety Scale (LSAS). Exploratory factor analyses and multiple regression analyses were performed. Results: All participants reported at least one symptom. Dry mouth (90.4%) and difficulty swallowing (72.3%) were particularly prevalent. Exploratory factor analysis (EFA) identified two symptom clusters (SCs): an oropharyngeal dysfunction cluster (pain, trismus, taste changes, difficulty swallowing, hoarseness) and a dry mouth cluster (dry mouth, sticky saliva). Regression analysis indicated that higher scores in both clusters were significantly associated with lower global QoL (oropharyngeal dysfunction SC: β = −0.427, p < 0.001; dry mouth SC: β = −0.268, p = 0.009). Chemoradiotherapy (CRT) was also significantly associated with higher cluster scores (oropharyngeal dysfunction SC: β = 0.233, p = 0.020; dry mouth SC: β = 0.343, p = 0.001). Conclusions: Late toxicities following radiation therapy include two clusters: oropharyngeal dysfunction cluster and dry mouth cluster. Head and neck cancer survivors with higher SC scores had lower global QoL scores and had undergone CRT. These findings may aid in the assessment and self-management support of head and neck cancer survivors after radiation therapy. Full article