Search Results (118)

Background: Capturing the healthfulness of mixed dishes per serving can be a challenge. Objectives: To develop a Nutrient Density Calculator (NDC) for mixed dishes to guide recipe innovation and reformulation. Methods: Recipe files and nutrient composition data for mixed dishes came from the US Department of Agriculture Food and Nutrient Database for Dietary Studies (FNDDS 2021–2023). Included were mixed dishes with meat, poultry, seafood, grains, vegetables or legumes as their main ingredient, Asian and Mexican dishes, pizza, sandwiches, burgers, and nuts and seeds (n = 1570). Observed servings as consumed came from the National Health and Nutrition Examination Survey data (NHANES 2017–2020/2021 –2023). The NDC version 643 had three components: NR6 based on six nutrients to encourage (protein, fiber, calcium, iron, potassium, vitamin D); MP4 based on ingredients (fruits and vegetables, whole grains, pulses, nuts and seeds); and LIM based on three nutrients to limit (saturated fat, added or total sugar, sodium). An abbreviated version, NDC343, used NR3 (protein, fiber, calcium). Alternative NDC models tested different component weights. Nutrient density was calculated per serving. Results: Both NDC643 and NDC343 gave higher scores to vegetables, pulses, and nuts and lower scores to meat-based dishes. Equal weighting of the three components produced NDC scores that were correlated with Nutri-Score (r = −0.64 for NDC343 and −0.70 for NDC643) and Health Star Rating values (r = −0.74 for NDC343 and −0.75 for NDC643). Correlations with energy density were −0.25 for NDC343 and −0.33 for NDC643. The NDC643 model was sensitive to recipe improvements for a variety of mixed dishes—more so than the Nutri-Score or the Health Star Rating. Conclusion: The three-component NDC model, combining both nutrients and ingredients, successfully captured nutrient density of mixed dishes and was sensitive to recipe improvements. Full article

Background: Nurse–patient communication is a nurse-associated, interprofessionally delivered care-process indicator captured by the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), but its hospital-level association with hospital-wide readmission after structural and case-mix adjustment remains incompletely characterized. Methods: We conducted a cross-sectional secondary analysis of publicly available Centers for Medicare and Medicaid Services (CMS) Hospital Compare data. The exposure was the HCAHPS nurse communication composite (April 2024–March 2025), and the outcome was the Hybrid Hospital-Wide All-Cause 30-day Readmission measure (July 2023–June 2024). The primary model adjusted for ownership and US Census region. Robustness was assessed using a six-model hierarchy, including linkage to Provider of Services and HCRIS data to account for teaching intensity, staffing density, and Disproportionate Share Hospital percentage. Additional sensitivity analyses examined survey weighting, survey-volume restriction, lagged HCAHPS scores, HCAHPS-domain specificity, CMS star-rating adjustment, non-linearity, regional interaction, health-system clustering, and alternative functional forms. Findings are interpreted as cross-sectional ecological associations, not causal or predictive effects. Results: Among 2844 acute care hospitals, each 10-percentage-point higher patient-perceived nurse communication score was associated with a 0.289 percentage-point lower 30-day readmission rate (95% CI −0.341 to −0.236; p < 0.001) in the primary model. The association was consistent across sensitivity analyses, although it was attenuated after additional adjustment for linked structural hospital characteristics. Among HCAHPS domains, discharge information showed the largest association with readmission. These findings indicate a modest but consistent hospital-level association rather than evidence of causality. Conclusions: Hospitals with higher patient-perceived nurse communication tended to have lower 30-day readmission rates, although the association was attenuated after adjustment for structural hospital characteristics. Patient-perceived nurse communication may therefore be a useful nurse-associated process indicator for readmission-related benchmarking, although it reflects interprofessional care and residual organizational confounding remains plausible. Longitudinal or interventional studies are needed to determine whether improving nurse communication can reduce readmissions. Full article

Purpose: There is limited literature on the functional outcomes of robotics-assisted (RA) superior transverse atraumatic reconstruction approach (STAR) in total hip arthroplasty (THA). This study compares the early functional outcomes, patient satisfaction, expectation fulfilment and complication rates between STAR RA-THA and direct anterior approach (DAA) RA-THA. Methods: We retrospectively analyzed all primary RA-THA performed between January 2022 and December 2024 at a high-volume tertiary centre. Patients undergoing either the DAA or STAR THA with available 6-month outcomes were included. There was a total of 123 patients (74 DAA and 49 STAR). Propensity score matching was used to account for baseline differences, generating 49 matched pairs based on age, sex, body mass index (BMI), and American Society of Anesthesiologists (ASA) grade. Postoperative patient-reported outcome measures (PROMs) and the proportion achieving minimum clinically important difference (MCID) were compared between groups. PROMs included were the Oxford Hip Score (OHS), Western Ontario and McMaster University Arthritic Index (WOMAC), Short-Form 36 Health Survey (SF-36) subscale, patient satisfaction score and expectation fulfilment score. Results: The DAA group demonstrated significantly better postoperative day one (POD1) ambulation distance (p = 0.00390). No differences in PROMs, MCID, patient satisfaction and expectation fulfilment scores were noted at last follow-up. The RA-DAA group had a higher incidence of meralgia paresthetica (p = 0.00260). Conclusions: The STAR RA-THA demonstrated early functional recovery comparable to DAA RA-THA. Although POD1 ambulation distance was greater in the DAA group, at six months, both approaches had similar functional outcomes, patient satisfaction and low complication rates. Full article

Background/Objectives: Dietary behaviors among young adults in Japan have become increasingly polarized, highlighting the limitations of traditional knowledge-based health education. Behavioral science-based approaches such as nudging and gamification may offer alternative strategies. This study aimed to develop and examine a Theory of Planned Behavior (TPB)-based path model of healthy dietary choice behavior among young Japanese adults and to examine patterns associated with a star-rating gamification feature embedded in a nutrition management mobile application. Methods: A total of 188 participants aged 18–39 years completed an online survey assessing TPB constructs and normative factors. Participants used either a star-rating or non-rating version of the FoodLog Athl application. Composite-score-based path analysis and conditional process analyses were conducted to examine relational patterns among constructs. Results: Intention and self-efficacy jointly explained 48% of the variance in dietary behavior, with self-efficacy emerging as the strongest predictor. Several moderation patterns were observed, including those of gender, university year, diet app use, awareness of consequences, and ascription of responsibility. Compared with users of the non-rating version, star-rating users were observed to show higher nutrient scores but lower self-efficacy and dietary behavior scores, along with greater awareness of dietary consequences. These post-intervention findings are exploratory. Conclusions: Self-efficacy plays a central role in healthy dietary choice behavior among young adults, and its association with behavior appears to be shaped by perceived consequences and responsibility. By applying a composite-score-based path analysis within an SEM framework, this study clarifies the structural relationships among TPB components in everyday dietary choice behavior among Japanese young adults. Star-rating feedback may enhance reflective awareness and shows potential as a gamified nudging tool but further research is needed to clarify its effects. Full article

The rise in seasonal lifestyle tourism, characterized by winter-escape health and wellness stays and long-term leisure residence, has intensified peak–off-peak imbalances and pressures on the allocation of tourism service supply in tropical island destinations. However, existing research lacks a systematic comparison of seasonal fluctuations and long-term evolution for this subgroup at the city/county level. Therefore, this study aims to characterize the seasonal pattern, long-term trend features, and typological differentiation of seasonal lifestyle tourism at the county level, and to compare differences across types. Using monthly data on seasonal lifestyle tourism for 18 cities/counties in Hainan from 2021 to 2024, we apply TRAMO/SEATS decomposition to identify seasonal structures and measure seasonal amplitude and employ the Hodrick–Prescott (HP) filter to extract trend components and determine their directions of change. We further construct five development types by integrating trend categories and changes in seasonal amplitude and test between-type differences using one-way analysis of variance (ANOVA). Results show that Hainan exhibits a stable “winter–spring peak and summer–autumn trough” pattern (peaks concentrated in January–March and December, with the off-season typically spanning May–October), with strong seasonality and pronounced spatial heterogeneity. The four-year mean seasonal range at the county level is 215.01, with high values clustered in southern Hainan; Haikou remains relatively low, while Wenchang shows an upward trend. Long-term trends are clearly differentiated: 13 counties show sustained growth, 2 show decline, and 3 display a U-shaped recovery (decline followed by rebound). Growth rates also vary substantially, with Qionghai increasing at roughly 27 times the rate of Qiongzhong. Integrating seasonal and trend characteristics yields five types, of which the Robust Development type accounts for the largest share (50%). Between-type differences are mainly reflected in tourism service supply capacity: the number of star-rated hotels (p = 0.033, η² = 0.530) and overnight visitors (p = 0.004, η² = 0.676) differ significantly across types, whereas differences in natural-environment conditions are not significant. This study provides a scientific basis for zoning management and optimizing low-season strategies in Hainan. Full article

The rapid digitalization of healthcare has led to the widespread availability of mobile health (mHealth) applications, including those aimed at mental health and well-being. The present study followed the PRISMA guidelines and systematically reviewed English and/or German mental health apps available in the Google Play Store to evaluate their functional quality and behavior-change potential. It utilized the Mobile App Rating Scale (MARS) to assess app quality, including engagement, functionality, esthetics, and information quality, and the App Behavior Change Scale (ABACUS) to evaluate the potential for behavior change by inclusion of behavior change techniques (BCTs). A total of 77 apps were reviewed, with findings indicating an average functional quality and moderate behavior-change potential, as the reviewed apps only utilized a limited amount of BCTs. Notably, only a small fraction of apps had been evaluated in randomized controlled trials (RCTs). Further analysis showed that MARS and ABACUS scores had limited predictive power regarding app popularity as measured by stars awarded by users and number of user ratings in the Google Play Store. The study highlights the need for more rigorous testing of mHealth apps and suggests that factors beyond those measured by MARS and ABACUS may influence app popularity. In addition to the scientific value, this review provides insights for both users interested in mental health support via apps and developers aiming to enhance the quality and impact of mental health applications. Full article

Women of reproductive age, especially those with polycystic ovarian syndrome (PCOS), often use glucagon-like peptide-1 receptor agonists (GLP-1RAs) to improve their metabolic functions. A growing body of evidence suggests that GLP-1R signaling may directly affect ovarian physiology, influencing granulosa cell proliferation, survival pathways, and steroidogenic production, in addition to its systemic metabolic effects. Nonetheless, there is a limited comprehension of the molecular mechanisms that regulate these activities and their correlation with menstrual function, reproductive potential, and assisted reproduction. This comprehensive review focuses on ovarian biology, granulosa cell signaling networks, steroidogenesis, and translational fertility outcomes, integrating clinical, in vivo, and in vitro information to elucidate the effects of GLP-1 receptor agonists on reproductive health. We conducted a thorough search of PubMed, Scopus, and Web of Science for randomized trials, prospective studies, animal models, and cellular experiments evaluating the effects of GLP-1RA on reproductive or ovarian outcomes, in accordance with PRISMA criteria. The retrieved data included metabolic changes, androgen levels, monthly regularity, ovarian structure, granulosa cell growth and death, FOXO1 signaling, FSH-cAMP-BMP pathway activity, and fertility or IVF results. Clinical trials shown that GLP-1 receptor agonists improve menstrual regularity, decrease body weight and central adiposity, increase sex hormone-binding globulin levels, and lower free testosterone in overweight and obese women with PCOS. Liraglutide, when combined with metformin, significantly improved IVF pregnancy rates, whereas exenatide increased natural conception rates. Mechanistic studies demonstrate that GLP-1R activation affects FOXO1 phosphorylation, hence promoting granulosa cell proliferation and anti-apoptotic processes. Incretin signaling altered steroidogenesis by reducing the levels of StAR, P450scc, and 3β-HSD, so inhibiting FSH-induced progesterone synthesis, while simultaneously enhancing BMP-Smad signaling. Animal studies demonstrated both beneficial (enhanced follicular growth, anti-apoptotic effects) and detrimental results (oxidative stress, granulosa cell death, uterine inflammation), indicating a context- and dose-dependent response. GLP-1 receptor agonists influence female reproductive biology by altering overall physiological processes and specifically impacting the ovaries via FOXO1 regulation, steroidogenic enzyme expression, and BMP-mediated FSH signaling. Preliminary clinical data indicate improved reproductive function in PCOS, as seen by increased pregnancy rates in both natural and IVF cycles; nevertheless, animal studies reveal a potential risk of ovarian and endometrial damage. These results highlight the need for controlled human research to clarify reproductive safety, molecular pathways, and optimum therapy timing, particularly in non-PCOS patients and IVF settings. Full article

This study examines how psycholinguistic features of online reviews relate to guest satisfaction in Bali’s spa hotel market. Using LIWC-22 category rates from Google Maps reviews, a corpus of 15,560 quality-filtered reviews from ten leading spa hotels was analyzed. Exploratory factor analysis yielded four interpretable dimensions—Social, Health and Wellness, Emotional Tone, and Lifestyle. In regressions predicting review star ratings (satisfaction), Social (β = 0.028) and Health and Wellness (β = 0.023) showed small but statistically detectable positive associations, whereas Emotional Tone (β = 0.006, t = 0.727) and Lifestyle (β = 0.004, t = 0.476) were not significant. The model’s explained variance is negligible (R² = 0.001; F = 5.283, p < 0.05), reflecting the many influences on ratings beyond review language; findings are interpreted as directional associations rather than predictive effects. Practically, the results point to prioritizing interpersonal service cues and wellness/treatment assurances, with tone monitoring being used for service-recovery signals. The design favors interpretability (validated, word-based categories; full-history snapshot) over black-box complexity, and transferability is Bali-specific and conditional on comparable market features. Future work should add contextual covariates (e.g., price and location), apply explicit temporal segmentation, extend to multilingual corpora, and triangulate text analytics with brief questionnaires and qualitative inquiry to strengthen validity and explanatory power. Full article

Background: Veterinary antibiotics are widely used in food-producing animals, raising public health concerns due to drug residues and the risk of antimicrobial resistance. Rapid and reliable detection systems are critical to ensure food safety and regulatory compliance. Colloidal gold immunoassay (CGIA)-based antigen–antibody test cards are widely used in food safety for the rapid screening of veterinary antibiotic residues. However, manual interpretation of test cards remains inefficient and inconsistent. Methods: To address this, we propose a complete AI-based detection system for veterinary antibiotic residues. The system is built on the Rockchip RK3568 platform and integrates a five-megapixel OV5640 autofocus USB camera (60° field of view) with a COB LED strip (6000 K, rated 5 W/m). It enables high-throughput, automated interpretation of colloidal gold test cards and can generate structured detection reports for regulatory documentation and quality control. The core challenge lies in achieving accurate and fast inference on resource-constrained embedded devices, where traditional detection networks often struggle to balance model size and performance. To this end, we propose VetStar, a lightweight detection algorithm specifically optimized for this task. VetStar integrates StarBlock, a shallow feature extractor, and Depthwise Separable-Reparameterization Detection Head (DR-head), a compact, partially decoupled detection head that accelerates inference while preserving accuracy. Results: Despite its compact size, with only 0.04 M parameters and 0.3 GFLOPs, VetStar maintains strong performance after distillation with the Bridging Cross-task Protocol Inconsistency Knowledge Distillation (BCKD) method. For our custom Veterinary Drug Residue Rapid Test Card (VDR-RTC) dataset, it achieves an mAP50 of 97.4 and anmAP50-95of 89.5. When deployed on the RK3568 device, it delivers results in just 5.4 s—substantially faster than comparable models. Conclusions: These results highlight the system’s strong potential for high-throughput, cost-effective, and rapid veterinary antibiotic residue screening, supporting food safety surveillance efforts. Full article

Background: The majority of Australian children exceed the World Health Organization’s recommended dietary intake of free sugar, particularly through the consumption of sugar-sweetened beverages. Front-of-pack nutrition labels increase perceived risk and deter the consumption of sugar-sweetened beverages. However, past studies of young children have focused almost exclusively on a parent’s choice of beverage for children. This study investigated the influence of four label designs (text-based warning, tooth decay pictorial, teaspoons of sugar, and Health Star Rating) on the beverage choices of N = 1229 Australian children (aged 4–11 years) and their parents. Methods: In an online vending machine scenario, parent–child dyads were separately asked to select which beverage they would choose for themselves before and after being randomised to one label condition. The beverages displayed included 100% fruit juice, soft drink, soft drink with a non-nutritive sweetener, flavoured milk, plain milk and bottled water. Beverage healthiness was determined by a 1–10 rating based on a review by a panel of experts (10 dietitians and nutritionists). Results: Mixed-model ANOVAs showed that for parents, each label design performed comparably; however, for children, small but significant differences were seen in the effectiveness of different label designs, with the teaspoons of sugar label, text-based warning, and tooth decay pictorial found to be more impactful in promoting healthier drink choices than the Health Star Rating. Conclusions: These findings can inform public health advocacy efforts to improve food labelling and could be incorporated into educational resources to help children understand the nutritional profiles of different sugary drinks. Full article

Puerto Rico has faced significant damage from natural disasters and the COVID-19 pandemic, disrupting clinical services and scientific research logistics. In response, the RCMI-CCRHD Program at the UPR-MSC organized a retreat with the objective of understanding the challenges faced by its research network during the pandemic and strategies to overcome them. The retreat featured presentations on COVID-19 supplemental projects and included a discussion group. Twenty attendees identified the challenges they encountered and the strategies developed through an open-ended question and a satisfaction survey, implementing a mixed-method approach. We performed a content analysis on the open-ended survey questions and used descriptive statistics for the satisfaction survey. Key challenges included remote work implementation, recruitment difficulties, and mental health concerns. Attendees shared actions taken to address these issues, such as modifying protocols for remote planning and using digital platforms for improving communication. They also recognized opportunities that arose from remote work, which allowed them to focus on publishing and adapting mental health support tools. The retreat received positive feedback, with 93.8% of attendees giving a five-star rating. By reflecting on these experiences, investigators can refine strategies and implement effective solutions. Recommendations include flexible IRB protocols, improved digital tools, community involvement, and robust emergency preparedness plans. Full article

Background: The health benefits associated with the consumption of nuts and seeds are well established, yet this food group is known to be the furthest from the recommended intake; therefore, actions aiming to increase nut intake are needed. The main front-of-pack communication device in Australia, the Health Star Rating (HSR), inadvertently penalises nuts with negative points associated with energy and saturated fat content. Methods: This study aims to suggest options to policy makers by (i) examining how the HSR rates a sample of 82 nuts, seeds and products containing them and (ii) testing three sets of moderate adjustments of the HSR algorithm on the sampled products: discounting the energy from nuts and seeds (S1), discounting the saturated fat from nuts and seeds (S2) and applying an adapted algorithm based on that for ‘oils and spreads’ for foods with ≥50% nuts and seeds (S3). Results: All three scenarios improved the Spearman correlation between the HSR score and the nut and seed content (−0.80, −0.75 and −0.71 for S1, S2 and S3, respectively) compared to the original HSR (−0.66). Products with more than 50% of their weight being nuts and seeds benefited much more from these adjustments than those below 50%. For all scenarios, but most clearly for S3, the products that had a lower HSR score than the original HSR (the healthier products) benefited more from the changes brought about by the adjusted algorithms than those of lower nutritional quality. The HSR of foods that contained no nuts or seeds remained unchanged. Conclusions: With minor changes to the HSR algorithm, nut and seed products could be brought into alignment with the current evidence, encouraging their regular inclusion in dietary patterns, which could help guide consumers at the supermarket shelf. Full article

Background/Objectives: Nursing staff turnover can adversely affect nursing home (NH) performance. To address staffing shortages, NHs are increasingly turning to agency nursing staff as a solution. This study examined the relationship between the use of agency nursing staff and turnover rates among NH permanent nursing staff. Methods: This retrospective, observational study used secondary data from several sources, including the Payroll-Based Journal, the Care Compare: Five Star Quality Rating System, and Area Health Resource Files (n: =35,200, years: 2021–2023). The dependent variable was turnover rates among registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs). The independent variable was the classification of NHs based on their level of agency nursing staff utilization. Facilities were classified as “high utilizers” (the top 25% in agency nursing staff use) and “low utilizers” (the remaining 75%). This classification was informed by prior research indicating that the impact of agency nursing staff on NH performance is most pronounced at higher levels of utilization. A two-way fixed-effects regression model (facility and year) was used, with appropriate control variables. Results: NHs identified as high utilizers had significantly higher turnover rates among permanent RNs (7%) and CNAs (1.9%) compared to facilities that had low utilization of agency nurses (p < 0.001). No significant association was found between agency LPN utilization and LPN turnover. Conclusions: Greater reliance on agency nursing staff was associated with increased turnover, with the strongest effect observed for RNs. NH administrators should consider strategies to balance agency staff utilization with efforts to retain permanent staff, emphasizing long-term workforce stability. Full article

Background/Objectives: The incidence of pedestrian traffic injuries is an escalating concern for public health worldwide. Particularly in fast-developing nations, such as Saudi Arabia, these injuries form a significant portion of trauma-related healthcare challenges. This study aims to explore age-specific differences in trends, seasonal variations, and the overall impact of pedestrian traffic injuries in Riyadh, Saudi Arabia, with a focus on injury characteristics and clinical outcomes. Methods: The study conducted a retrospective analysis using data from the Saudi Trauma Registry (STAR) covering the period between August 2017 and December 2022. It employed descriptive statistics, chi-square tests, and multivariable linear regression analyses to explore demographic trends, characteristics of injuries, and hospital-based outcomes. Results: This study analyzed data from 1062 pedestrian injury cases, revealing key demographic and clinical patterns. Most incidents occurred on weekdays (71.9%) and during nighttime hours (63.3%), with seasonal peaks observed from April to June (30.4%). The lower extremities (27.5%) and head (21.3%) were the most frequently injured body regions. ICU admissions were more common among individuals aged 30–40, females, and those with head or chest trauma, while higher in-hospital mortality was associated with patients over 60 years old, transport by private or police vehicles, and extended ICU and hospital stays. Approximately 25.6% of cases required ICU care, with an overall in-hospital mortality rate of 4.9%. Conclusions: This study provides an in-depth analysis of pedestrian traffic injuries treated at a trauma center in Riyadh, highlighting significant demographic, temporal, and clinical patterns. Understanding these trends is essential for optimizing resource allocation and improving emergency care outcomes. Furthermore, the identified age-specific risk factors and seasonal variations underscore the critical need for targeted interventions and policy enhancements to improve road safety and reduce the burden of pedestrian injuries. Full article

Open source software (OSS) projects rely on voluntary contributions, but their long-term survivability depends on sustained community engagement and effective problem-solving. Survivability, critical for maintaining project quality and trustworthiness, is closely linked to issue activity, as unresolved issues reflect a decline in maintenance capacity and problem-solving ability. Thus, analyzing issue retention rates provides valuable insights into a project’s health. This study evaluates OSS survivability by identifying the features that influence issue activity and analyzing their relationships with survivability. Kaplan–Meier survival analysis is employed to quantify issue activity and visualize trends in unresolved issue rates, providing a measure of project maintenance dynamics. A random forest model is used to examine the relationships between project features—such as popularity metrics, community engagement, code complexity, and project age—and issue retention rates. The results show that stars significantly reduce issue retention rates, with rates dropping from 0.62 to 0.52 as stars increase to 4000, while larger codebases, higher cyclomatic complexity, and older project age are associated with unresolved issue rates, rising by up to 15%. Forks also have a nonlinear impact, initially stabilizing retention rates but increasing unresolved issues as contributions became unmanageable. By identifying these critical factors and quantifying their impacts, this research offers actionable insights for OSS project managers to enhance project survivability and address key maintenance challenges, ensuring sustainable long-term success. Full article