Search Results (3,822)

Background/Objectives: Substance use disorders (SUD) pose a significant public health challenge, with 47.7 million people nationwide struggling to end their addiction. Individuals in recovery from SUDs are at an elevated risk of relapses, even after an extended period of abstinence from substances. While the importance of social relationships in addiction recovery has been extensively researched, the specific ways addiction recovery differs between sex/gender within Oxford House (OH) settings needs further research. Some evidence suggests males and females experience SUD differently and respond distinctively to recovery. Methods: We recruited 229 participants from 42 OH recovery homes, with 55.5% (n = 127) male participants. Moderated mediation model seven by Andrew F. Hayes was used to determine the relationship between quality of life, length of stay, sense of community, and sex/gender. Results: Length of stay was a significant predictor of sense of community, with longer stays associated with stronger perceived community ties. Additionally, quality of life had a robust direct effect on sense of community. We found that there is a small indirect effect of quality of life on sense of community through length of stay for females. Conclusions: These findings suggest that while quality of life and length of stay both independently contribute to individuals’ sense of community, the mediating role of length of stay appears to be more pronounced among females. Further research is needed to understand and address sex/gender-specific recovery experiences. Full article

This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It applies a multi-nominal logit (MNL) model to examine factors influencing travel mode choices and utilizes structural equation modeling (SEM) to assess travel satisfaction—a composite metric derived from residents’ subjective evaluations of convenience, cost, time, and comfort. Findings indicate that private cars and public transportation are the primary travel modes. The MNL model reveals that age and destination accessibility significantly influence travel choices. SEM path analysis further shows that annual household income has a direct positive effect on satisfaction, while age exerts an indirect negative influence through mediating variables. Female satisfaction levels were significantly lower than those of males. Both road density and perceived infrastructure quality significantly enhanced satisfaction, while destination accessibility may exert a slight negative indirect effect by increasing travel expectations. The study theoretically enriches research on rural travel patterns and provides practical insights into rural transportation planning and infrastructure development. Full article

Background/Objectives: Adolescents aged 13–18 are exposed to traumatic content even without direct experience, owing to the increasing media coverage of disasters. Such indirect exposure can result in post-traumatic stress symptoms, including intrusion, avoidance, and hyperarousal, as well as associated emotions such as sadness, anger, and guilt. These effects may persist for months, reflecting the vulnerability of adolescents during cognitive and emotional development. This study examined resilience and social support as protective predictors against indirect trauma. Methods: A cross-sectional correlational design was employed, with middle- and high-school students aged 13–18 years in Seoul, South Korea, as participants. Indirect trauma, resilience, and perceived social support were assessed using validated self-report instruments. Correlation analyses were conducted, followed by stepwise regression. Owing to multicollinearity, resilience was retained as the sole predictor in the final model. Results: The average indirect trauma score was 1.20 out of 4, and 59.2% of participants exhibited partial or full post-traumatic stress disorder. The mean resilience and social support scores were 3.47 and 3.82 out of 5, respectively. Resilience was positively correlated with social support (r = 0.60, p = 0.001). The regression analysis indicated that resilience significantly predicted indirect trauma (β = 0.82, p < 0.001), accounting for 66.4% of the variance, whereas social support showed no direct effect. Conclusions: Resilience emerged as a key predictor of indirect trauma, underscoring its importance in mitigating distress. Although social support did not directly predict trauma, its positive correlation with resilience suggests potential indirect effects. These findings highlight the need to strengthen resilience and expand school-based counseling and support systems to help adolescents deal with indirect trauma. Full article

Gut microbiota has increasingly been shown to exert effects beyond the gastrointestinal tract, some of which are mediated through its metabolites, such as trimethylamine N-oxide (TMAO)—a compound converted by gut bacteria from dietary choline found predominantly in animal products that is associated with cardiovascular disease (CVD). However, a significant gap persists in human clinical trials assessing its potential causal role. This narrative review aims to present the current understanding of the gut microbiome, TMAO, and their relationship with CVD, while proposing future directions that may support the use of TMAO as a biomarker and guide potential interventions to reduce its harmful impact. Both animal and human studies have demonstrated a link between TMAO and CVD, with animal studies also indicating a causal effect—showing increased cardiovascular risk following TMAO administration and reduced risk when TMAO is eliminated. While direct extrapolation from animal models to humans is limited due to biological differences, these findings offer a foundation for the development of well-designed clinical trials in human populations. Although direct approaches to target TMAO—such as trimethylamine (TMA) lyase inhibitors and antisense oligonucleotide (ASO) therapy—have shown promising results in animal studies, they have yet to be investigated in human trials, leaving indirect strategies such as dietary changes and probiotics as the only currently available options. Full article

Minority stress appears to be consistently associated with a heightened risk of developing eating disorders. There is limited data investigating the role of witnessed heterosexist experiences (vicarious trauma), such as discrimination, harassment, or violence happening to other LGBTQ+ people. The present study aims to examine the association between vicarious trauma and eating disorder risk while surveying the mediating role of emotional dysregulation, self-esteem, and shame. An anonymous online survey was conducted involving 376 LGBTQ+ people from Italy. Participants completed self-report questionnaires regarding heterosexist experiences and factors associated with eating behavior. Descriptive, bivariate, and mediation analyses were conducted using the “PROCESS” macro. Statistically significant positive associations were found between all the main variables in bivariate analyses. Mediation analyses highlighted a direct effect of vicarious trauma on eating disorder risk and indirect effects of vicarious trauma on eating disorder risk through low self-esteem and emotion dysregulation. The indirect effect through shame was nonsignificant. Vicarious trauma appears to have a significant direct effect on eating disorder risk and small but significant indirect effects through emotional dysregulation and low self-esteem. Health promotion contexts would benefit from policies at the institutional, organizational, and social levels to prevent minority stress and reduce observed health disparities. Full article

Understanding trait relationships is fundamental in soybean breeding because the goal is to maximize simultaneous gains. Standard multi-trait genome-wide association studies (MT-GWAS) identify variants linked to multiple traits but fail to capture phenotypic structures or interrelations. Structural Equation Models (SEM) account for covariances and recursion, enabling the decomposition of single nucleotide polymorphism (SNP) effects into direct or indirect components and identifying pleiotropic regions. We applied SEM to analyze morphology (pod thickness, PT) and yield traits (number of pods, NP; number of grains, NG; hundred-grain weight, HGW). The dataset comprised 96 soybean individuals genotyped with 4070 SNP markers. The phenotypic network was constructed using the hill-climbing algorithm, a class of score-based methods commonly applied to learn the structure of Bayesian networks, and structural coefficients were estimated with SEM. According to coefficient signs, we identified negative interrelationships between NG and HGW, and positive ones between NP and NG, and HGW and PT. NG, HGW, and PT showed indirect SNP effects. We also found loci jointly controlling traits. In total, 46 candidate genes were identified: 7 associated exclusively with NP and 4 associated with NG. An additional 15 genes were common to NP and NG, 3 were common to NP and HGW, 6 were common to NG and HGW, and 11 were common to NP, NG, and HGW. In summary, SEM-GWAS revealed novel relationships among soybean traits, including PT, supporting breeding programs. Full article

Per- and polyfluoroalkyl substances (PFASs) are highly chemically stable synthetic compounds. They are widely used in industrial and commercial sectors due to their ability to repel water and oil, thermal stability, and surfactant properties. However, this stability results in environmental persistence and bioaccumulation, posing significant health risks as PFASs eventually find their way into environmental media. Key PFAS compounds, including PerFluoroOctanoic Acid (PFOA), PerFluoroOctane Sulfonic acid (PFOS), and PerFluoroHexane Sulfonic acid (PFHxS), have been linked to hepatotoxicity, immunotoxicity, neurotoxicity, and endocrine disruption. In response to the health threats these substances pose, global regulatory measures, such as the Stockholm Convention restrictions and national drinking water standards, have been implemented to reduce PFAS exposure. Despite these efforts, a lack of universally accepted definitions or comprehensive inventories of PFAS compounds hampers the effective management of these substances. As definitions differ across regulatory bodies, research and policy integration have become complicated. PFASs are broadly categorized as either perfluoroalkyl acids (PFAAs), precursors, or other fluorinated substances; however, PFASs encompass over 5000 distinct compounds, many of which are poorly characterized. PFAS contamination arises from direct industrial emissions and indirect environmental formation, these substances have been detected in water, soil, and even air samples from all over the globe, including from remote regions like Antarctica. Analytical methods, such as primarily liquid and gas chromatography coupled with tandem mass spectrometry, have advanced PFAS detection. However, standardized monitoring protocols remain inadequate. Future management requires unified definitions, expanded monitoring efforts, and standardized methodologies to address the persistent environmental and health impacts of PFAS. This review underscores the need for improved regulatory frameworks and further research. Full article

Heat stress (HS) is an environmental variable challenging pig production worldwide. It may alter carcass composition by increasing fat deposition but the mechanisms are poorly understood. Betaine is a metabolic modifier able to decrease carcass fat in pigs, but the effects of betaine on lipolysis under high temperatures are not known. Our goal was to determine a potential effect of betaine on lipolysis in the fat tissue of Iberian pigs under thermoneutral (TN) or HS conditions. Eight pigs (89 kg BW) were used to obtain explants from dorsal subcutaneous adipose tissue. Explants were cultivated under TN (37 °C) or HS conditions (41.5 °C) for 1.5 h to study direct effects of HS on acute lipolysis. Treatments included control and betaine addition (200 µM). Indirect effects of HS were examined using the culture medium amended with 1 μM isoproterenol ±10 nM insulin in the presence or absence of betaine and HS. Media glycerol was measured at the end of the incubations as a proxy of lipolysis. HS decreased basal lipolysis (−47%; p < 0.001) but increased isoproterenol-stimulated (a β-agonist) lipolysis (+31%; p < 0.01). Betaine increased non-stimulated lipolysis both under TN and HS conditions (73%; p < 0.001). As expected, isoproterenol augmented lipolysis both in TN (2714%; p < 0.001) and HS (3589%; p < 0.001) conditions. The addition of insulin to lipolysis-stimulated explants analogously diminished glycerol release in TN (−39%; p < 0.001) and HS (−50%; p < 0.001) conditions. In conclusion, HS reduced non-stimulated lipolysis in Iberian pigs in line with increased adipose tissue accretion, while betaine partly increased lipolysis, counteracting the effects of HS. Betaine supplementation could be a strategy to counteract HS-induced fattening in pigs. Full article

This study investigates the effectiveness of integrating explicit learning-strategy instruction into gatekeeper mathematics courses to foster a math growth mindset, self-regulated learning (SRL), and improved academic performance among underrepresented minority students. The intervention was implemented across four key courses—College Algebra I/II and Calculus I/II—and incorporated evidence-based cognitive, metacognitive, and behavioral learning strategies through course materials, class discussions, and reflective assignments. Grounded in a conceptual framework linking learning-strategy instruction, growth mindset, SRL, and performance—while accounting for students’ social identities—the study explores both direct and indirect effects of the intervention. Using an explanatory sequential mixed-methods design, we first collected quantitative data via pre- and post-surveys/tests and analyzed performance outcomes, followed by qualitative focus groups to contextualize the findings. Results showed no significant effects of the intervention on growth mindset or SRL, nor evidence of mediation through these constructs. The direct effect of the intervention on performance was negative, though baseline mindset, SRL, and pre-course preparedness strongly predicted outcomes. No moderation effects were detected by student identities. The findings suggest that while explicit learning-strategy instruction may not independently shift mindset or SRL in the short term, pre-existing differences in these areas are consequential for performance. Qualitative findings provided further context for understanding how students engaged with the strategies and how instructor implementation shaped outcomes. These insights inform how learning strategies might be more effectively embedded in introductory math to support success and equity in STEM pathways, particularly in post-COVID educational contexts. Full article

This study examines the impact of Environmentally Specific Servant Leadership (ESSL) on employees’ pro-environmental behavior (PEB) by proposing a serial mediation model that incorporates green psychological empowerment and green creativity as central mechanisms. Guided by social exchange theory (SET), survey data from managers in Saudi Arabia were analyzed using PROCESS Model 6 with bootstrapping to test direct, indirect, and serial mediation effects. The results show that ESSL has a significant positive influence on PEB, with both psychological empowerment and green creativity acting as partial mediators. Moreover, the serial mediation analysis confirms that empowerment enhances creativity, which in turn drives employees’ pro-environmental actions. The findings support the social exchange theory, SET, in the contextual environmental settings of the rapidly developing economy of Saudi Arabia. These findings highlight the critical role of psychological empowerment and creativity in translating leadership values into sustainable behaviors. Practically, the study suggests that organizations can advance sustainability goals by fostering servant leadership practices, empowering employees with autonomy and resources, and encouraging innovative solutions for environmental challenges. Within the context of Saudi Vision 2030, the findings provide valuable insights for aligning leadership development with national sustainability objectives. Full article

Periodontitis is a prevalent condition that leads to the destruction of periodontal tissue, making the regeneration of the periodontium a key focus in dental research. In this context, periodontal ligament cells (PDLCs) are particularly interesting due to their stem cell-like properties, including the ability to differentiate into various cell types and further contribute to tissue repair. This study aimed to isolate and characterize primary human PDLCs and examine the effects of both indirect and direct treatment with the blood concentrate platelet-rich fibrin (PRF), with particular focus on how PRF influences cell proliferation and differentiation. PDLCs were treated with PRF prepared using a low relative centrifugal force (600 rpm) either directly through a conditioned medium or indirectly using trans-well filter systems. The impact of PRF on PDLC proliferation and differentiation was assessed through viability assays, alkaline phosphatase assays, gene and protein expression analyses, and immunofluorescence. PDLCs exhibited cellular markers characteristic of stem cell-like cells. In addition, PRF treatment was found to suppress cell proliferation while concurrently promoting osteogenic differentiation and increase factors important for tissue regeneration. These effects were more pronounced when the cells were directly treated with PRF-conditioned medium compared to indirect treatment. Our findings support the hypothesis that PRF serves as a biologically active reservoir of growth factors that modulate PDLC behavior and might create a microenvironment favorable for periodontal repair. Full article

This study aims to explore whether and how data elements affect the green total factor productivity (GTFP) of China’s logistics industry, and conducts empirical tests using the super-efficiency SBM model, Malmquist exponential model, and spatial Dubin model. Based on the relevant data of 30 provinces in China from 2013 to 2021, we employ the Super-efficiency SBM model and the Malmquist dynamic index model to calculate the green total factor productivity of the logistics sector. We then establish a three-tier evaluation framework for data elements, employ the entropy method to determine the weighting of each indicator, and utilize linear weighting to calculate the comprehensive evaluation value of data elements. By incorporating appropriate control variables and employing the spatial Durbin model, this study examines the impact of data elements on the GTFP of the logistics industry. It is found that data elements have a contributing effect on improving GTFP of the logistics industry in the local region as well as a positive spillover effect on the neighboring regions, and this is achieved by improving the level of technical progress. In addition, the coefficients are decomposed into direct, indirect, and total effects by partial differentiation, again verifying the above conclusions. This study investigates the impact of data elements on GTFP in the logistics industry from theoretical mechanisms and empirical tests, and analyzes the dual impact of data elements and other factors on the local region and neighboring regions. The findings of this study can provide references for better empowering the development of the logistics industry with data elements. Full article

Objectives: This study examined whether skeletal muscle mass mediates the relationship between sedentary behavior, physical activity, and cardiometabolic health, and if this relationship differs by genders. Methods: Secondary analysis was conducted using data from the 2022–2023 Korean National Health and Nutrition Examination Survey (n = 5956). Cardiometabolic abnormalities were defined as having one or more of the five metabolic syndrome (MS) criteria, while MS was defined as having three or more. Muscle mass relative to body weight was measured by bioelectrical impedance analysis. Sedentary time and recommended moderate-to-vigorous physical activity (MVPA) levels at work, for transportation, and for recreation (≥600 Mets), and strength training (≥2 times/week), were assessed using the Global Physical Activity Questionnaire. Results: Higher MVPA (p < 0.001) and less sedentary time (p < 0.01) were significantly correlated with greater muscle mass in middle-aged and elderly men and women. Mediation analyses, which controlled for MS risk factors, revealed gender differences. In men, the indirect effects of sedentary time, MVPA, and strength training on both cardiometabolic abnormalities (b = 0.007, CI [0.003, 0.013]; b = −0.066, CI [−0.110, −0.033]; b = −0.074, CI [−0.110, −0.033]) and MS (b = 0.007, CI [0.003, 0.011]; b = −0.060, CI [−0.095, −0.032]; b = −0.065, CI [−0.100, −0.035]) were significant, indicating mediation by muscle mass. In women, the indirect effects of these three behaviors on cardiometabolic abnormalities were also mediated by muscle mass (b = 0.003, CI [0.001, 0.006]; b = −0.014, CI [−0.031, −0.002]; b = −0.023, CI [−0.050, −0.003]). However, for MS, sedentary time (b = 0.057, p < 0.001) and MVPA (b = −0.222, p < 0.05) had only direct effects, with no mediation by muscle mass. Furthermore, strength training showed no significant effects. Conclusions: These findings suggest that promoting MVPA and strength training, while reducing sedentary time, can improve cardiometabolic health by increasing muscle mass, though the mediating role of muscle mass for MS differs by gender. Full article

Background: Depression is a significant public health concern, with working mothers at greater risk due to combined biological and psychosocial stressors. Recent evidence suggests that inner strength may play a mediating role in the link between biological risks and depression. Objectives: The primary objective was to determine whether inner strength mediates the relationship between biological risk factors (hormonal fluctuations, smoking, alcohol use, family psychiatric history, and physical diseases) and depressive symptoms among Chinese working mothers. A secondary objective was to assess the prevalence of depressive symptoms in this population, measured with the OI-Depression subscale (Outcome Inventory-21). Methods: A cross-sectional online survey was conducted with 330 Chinese working mothers aged 30–45 years, using validated instruments to measure depression, inner strength, and parental stress. Mediation analysis evaluated the indirect effect of inner strength, while covariate-adjusted regression analyses explored associated factors. Results: Biological risk factors showed a significant direct effect (β = 0.584, p < 0.001) and an indirect effect through inner strength (indirect effect = 0.623, 95% CI [0.294, 0.962]. The Sobel test indicated that the indirect effect of biological risk factors on depressive symptoms through inner strength was statistically significant (z = 3.67, p < 0.001). The prevalence of clinically significant depressive symptoms was 38.2%. Conclusions: Biological factors significantly contribute to depressive symptoms, but inner strength partially mediates this relationship, suggesting that interventions to enhance inner strength may help reduce depression risk in working mothers. Further research should investigate strategies to build inner resilience in this population. Full article

Artificial intelligence (AI) adoption in strategic sectors such as energy is often framed in optimistic narratives, yet its actual economic contribution remains under-quantified. This study proposes a novel, multi-stage methodology at the intersection of machine learning, statistics, and big data analytics to bridge this gap. First, we construct a media-derived AI Adoption Score using natural language processing (NLP) techniques, including dictionary-based keyword extraction, sentiment analysis, and zero-shot classification, applied to a large corpus of firm-related news and scientific publications. To enhance reliability, we introduce a Misinformation Bias Score (MBS)—developed via zero-shot classification and named entity recognition—to penalise speculative or biased reporting, yielding a credibility-adjusted adoption metric. Using these scores, we classify firms and apply a Fixed Effects Difference-in-Differences (FE DiD) econometric model to estimate the causal effect of AI adoption on turnover. Finally, we scale firm-level results to the macroeconomic level via a Leontief Input–Output model, quantifying direct, indirect, and induced contributions to GDP and employment. Results show that AI adoption in Romania’s energy sector accounts for up to 42.8% of adopter turnover, contributing 3.54% to national GDP in 2023 and yielding a net employment gain of over 65,000 jobs, despite direct labour displacement. By integrating machine learning-based text analytics, statistical causal inference, and big data-driven macroeconomic modelling, this study delivers a replicable framework for measuring credible AI adoption and its economy-wide impacts, offering valuable insights for policymakers and researchers in digital transformation, energy economics, and sustainable development. Full article