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Prevalence and associated factors of suicidal behavior among adolescents in Bahir Dar City, Northwest Ethiopia
Background Suicide is a significant public health issue worldwide and the third leading cause of death among 15–19-year-olds. In Ethiopia, while suicidal behaviors among adolescents have a considerable impact, there is limited information on these behaviors, especially in community settings. The study aimed to assess the prevalence and associated factors of suicidal behavior among adolescents in Bahir Dar City. Methods A community-based cross-sectional study involving 692 adolescents was conducted in Bahir Dar City, Northwest Ethiopia, in May 2021. Participants were selected through a multistage sampling technique. Semi-structured and standardized questionnaires were employed to gather data via face-to-face interviews. Suicidal behavior was evaluated using the six questions of the Mini International Neuropsychiatric Interview. Epi-Data version 3.1 was utilized for data entry, whereas Statistical Package for Social Science version 24 was employed for analysis. Logistic regression with an adjusted odds ratio determined the relationship between outcome and factor variables. A p-value of < 0.05 was considered statistically significant. Results The prevalence of suicidal behavior was found to be 19.8%, with a 95% CI (16.6, 22.8). Regarding predictive variables, low social support (AOR 12.42, 95% CI 5.95 to 25.95), expressed more anger (AOR 7.30, 95% CI 2.51 to 21.22), negative childhood experiences (AOR 7.11, 95% CI 3.56 to 14.20), family history of suicidal attempts (AOR 5.66, 95% CI 2.44 to 13.10), having no good relationship with parents (AOR 5.59, 95% CI 2.59 to 12.08), depression (AOR 5.32, 95% CI 2.64 to 10.70), stressful life events (AOR 2.91, 95% CI 1.45 to 4.91), and interpersonal stress (AOR 2.17, 95% CI 1.07 to 4.40) were significantly increased odds of suicidal behavior among respondents. Conclusion Suicidal behavior was prevalent in the study area, and factors such as depression, stressful life events, poor parental relationships, negative childhood experiences, high anger expression, low social support, and a family history of suicidal attempts were the significant contributors. Mental health interventions have to emphasize psychosocial support for adolescents, improve the parent-adolescent relationship by increasing parental knowledge about adolescents’ mental health, and integrate youth-friendly health services that foster mental well-being. Policymakers can also propose mandating mental health guidance in schools.
Scene-dependent sound event detection based on multitask learning with deformable large kernel attention convolution
Sound event detection (SED) and acoustic scene classification (ASC) are closely related tasks in environmental sound analysis. Given the interrelationship between sound events and scenes, some previous studies have proposed using the multitask learning (MTL) method to jointly analyze SED and ASC. However, these multitask learning methods are generally based on hard parameter-sharing, which exchange sound event and scene features only through the low-level network. Such approaches are difficult to balance the complex interrelationships between SED and ASC, and limits the feature sharing and information flow between tasks during the training. To address these challenges, this study proposes a novel multitask network based on residual multi-level feature extraction (R-MFE) framework, which aims to jointly analyze SED and ASC tasks, and utilize scene information to improve the performance of sound event detection. In addition, this study designs the D-LKAC attention module, which combines the advantages of self-attention mechanisms and convolution to capture global and local features. To further enhance SED performance, this study introduces the MS-conv module, which captures audio details from multiple dimensions. The proposed MTL method is evaluated on the TUT Acoustic Scenes 2016/2017 and TUT Sound Events 2016/2017 datasets. Experimental results indicate that our approach outperforms state-of-the-art techniques, improving the F-scores by 6.44%.
The effect of location in mining or borderland areas on HIV incidence among people who use drugs attending a harm reduction programme in Myanmar, 2014–2021: A retrospective cohort study
Background High HIV prevalence has been documented among people who inject drugs in Myanmar particularly in mining and borderland areas. We estimated incidence of HIV among people using drugs (via injecting and other routes) and examine associations between location in mining or borderland areas and risk of infection. Methods and findings Analysis of data among clients registered at harm reduction programmes across Sagaing region, Kachin, and Northern Shan States between 2014–2021. Data on sociodemographic, drug use characteristics and clinic-level data on borderland or mining locations were collected at time of registration. Characteristics, repeat HIV testing and HIV seroconversion were analysed using a cohort approach. We use Poisson regression models to examine associations between location in a borderland or mining area and incidence of HIV, adjusting for confounders. Data were available for 85,093 clients, 52,526 reported HIV tests and 20.0% were seropositive. 38,670 clients had no or only one recorded HIV result. The median time between HIV tests was 1.1 years. Among 13,359 clients with 2 or more HIV tests the HIV seroconversion rate was 3.8 per 100 person years (pyrs) (95% CI 3.6–4.0). Incidence among those who injected drugs was 6.8 per 100/pyrs, 8.9 among those aged ≤ 25 years, 2.3 among women, 2.3 among those who had migrated, 5.6 among those located in border areas, and 3.7 among those in mining areas. After adjusting for confounders, HIV incidence remained higher for people located in borderland areas (Incidence Rate Ratio 1.67 95% CI 1.13–2.45) but there was no evidence of association between location in a mining area and HIV seroconversion. Conclusions Findings highlight the need to intensify harm reduction interventions with a focus on cross-border interventions. Increasing uptake of HIV testing alongside the scale up of evidenced based interventions is urgently needed to curb the high rates of HIV transmission associated with drug use, particularly among young people.
Determinants of tea planters’ purchasing behavior of planting insurance: SEM analysis
This study explores the influence of government support and risk cognition on tea planters’ purchasing behavior regarding planting insurance, with a particular emphasis on the mediating roles of perceived value and environmental concern. Data were collected from 550 tea planters in Guizhou Province, China, using a structured questionnaire and convenience sampling method. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were conducted using AMOS 28.0 to analyze the data. The results indicate that both government support and risk cognition significantly and positively impact the perceived value of planting insurance. To promote the uptake of planting insurance among tea farmers, government agencies should strengthen policy advocacy and provide business guidance. Such efforts would help tea farmers recognize the value and psychological significance of planting insurance, thereby better safeguarding their agricultural interests. This study enhances the understanding of how government support and risk cognition can facilitate the adoption of planting insurance among tea farmers.
Effects of perspective-taking training based on relational frame theory for cognitive empathy and emotional empathy: Differences in perspective-taking according to various theoretical approaches
Perspective-taking has garnered considerable attention across various psychological domains and is often conceptualized as cognitive empathy within the organizational model of empathy. Relational frame theory, a theoretical framework elucidating human behavior and language, addresses perspective-taking and offers corresponding training protocols. However, previous studies have not examined the relationship between training and perspective-taking, defined as cognitive empathy in the organizational model of empathy. This study investigated the impact of perspective-taking training rooted in the relational frame theory on perspective-taking, as conceptualized by the organizational model of empathy. To this end, 43 participants underwent a training regimen and completed pre- and post-training assessments using questionnaires that measure organizational empathy. The post-training scores for the subscales measuring cognitive empathy increased significantly (p = 0.031); however, The increase in the score remained significant trend after adjusting for training performance. The scores for some subscales of emotional empathy also increased after training. The limitations of this study include a bias in the sample and discrepancies in the results between scales measuring the same concept. Nonetheless, these results provide scope for debate regarding the impact of perspective-taking training under relational frame theory on perspective-taking within the organizational model of empathy. While considering the limitations of the obtained results, this study discusses the relationship between perspective taking based on relational frame theory and the organizational model of empathy, including emotional empathy.
A protocol for high-dose quadrivalent influenza vaccine effectiveness in the community and long-term care facilities using electronic health records
Since the 2022–2023 season in Portugal, a high-dose quadrivalent influenza vaccine is freely available for individuals living in long-term care facilities (LTCF). In 2024–2025, vaccination was extended to community-dwelling individuals aged ≥85 years. Given the scarcity of reported high-dose influenza vaccine effectiveness (IVE) estimates for this population, this study aims to estimate the high-dose relative and absolute IVE. A retrospective cohort study using data from electronic health records databases (EHR) will be implemented, using two cohorts, one of individuals vaccinated with influenza vaccine (to estimate relative IVE) and another of individuals eligible for the high-dose quadrivalent influenza vaccine (to estimate absolute IVE). We will consider two subgroups for both cohorts: individuals living in LTCF and community-dwelling individuals aged ≥85. We will use a fixed cohort approach, defining the eligible population by age at the vaccination campaign(s) start and living status. The outcomes are based on the primary cause of hospital admission. The reference population database will be defined by linking EHR on vaccination, comorbidities, and hospitalisations using a unique identifier through a deterministic data linkage procedure, and influenza vaccination status will be assessed retrospectively. We will use Cox proportional hazards regression models to estimate the hazard ratio (HR), considering as event the first hospitalisation due to influenza-like-illness and as exposure the vaccination status. IVE will be estimated as one minus the confounder-adjusted HR of vaccinated with the high-dose quadrivalent influenza vaccine vs vaccinated with standard dose (to estimate relative IVE) or unvaccinated (to estimate absolute IVE). While challenges such as EHR constraints and potential reporting bias pose limitations, using routinely collected data has successfully estimated COVID-19 VE and enables precise monitoring of VE with higher representativeness. The results of this study will inform the Health Ministry on the future influenza vaccine programme in Portugal.
Study on measurement and prediction of agricultural product supply chain resilience based on improved EW-TOPSIS and GM (1,1)-Markov models under public emergencies
The COVID-19 pandemic, African Swine Fever, and other major public health emergencies have affected the agricultural product supply chain in recent years. It appeared in various chain breakdown and blocking issues, in which the resilience was drastically reduced and food security and social stability were greatly disrupted. This dissertation adopted an improved EW-TOPSIS method to evaluate resilience and determined the significance of influence factors of the agricultural product supply chain in China, showing that adjustment capability was closely connected to resilience. Through the empirical research on top listed enterprises (NHL, SQF, DBN, YILI, HTGF), it was found that the resilience of the industry was generally lower in 2020–2021 than in 2015–2019, and recovered and peaked in 2022. An improved Markov-modified GM (1,1) forecasting method was adopted to construct a resilience-predicting model. It was found that there would be a decline of resilience in 2024–2025, while a general growth with fluctuations trend was shown during the thirteen years before and after the breakout of the COVID-19 pandemic. In addition, this dissertation uses independent samples T-test and Solomon sensitivity analysis methods to verify the feasibility of the empirical results. Accordant enhancement mechanisms were proposed based on the empirical findings and results, which were expected to improve the risk-resistant capability of the domestic agricultural product supply chain under potential public emergency scenarios in the future. Our research findings can serve as a valuable reference for scientific decision-making and policy formulation to encourage the establishment of a robust agricultural product supply chain resilience system.
Spatial layout characteristics of Northern Wei Luoyang: A spatial humanities analysis of the “Record of the Monasteries of Luoyang”
This paper explores the urban spatial structure and social stratification of Northern Wei Dynasty Luoyang City, based on Record of the Monasteries of Luoyang. Adopting a spatial humanities approach, the study integrates quantitative approaches, including the application of geographic information systems (GIS) for spatial analysis and complex network analysis. The findings indicate that the spatial organization of Northern Wei Luoyang was primarily concentrated within and around the inner city. People of different social classes and statuses occupied distinct spaces, forming socially stratified groups. As one moves outward from the city’s center, the social rank of these groups decreases. The city’s layout is characterized by a single central axis, with multiple spatial divisions, and the west side being associated with higher-status groups. This spatial arrangement was shaped by factors such as geography, urban development, Central Plains rituals, traditional customs, and ethnic diversity. This study enhances our understanding of the spatial layout characteristics of Northern Wei Luoyang. It provides innovative insights and methods for understanding the city’s structure and its implications for other underground historical cities. Furthermore, it provides valuable data and visualizations that could support future preservation and planning efforts for the city.
An analysis of adolescent leisure activity structure based on subjective well-being: Focusing on social network analysis
This study examines how adolescent leisure activity networks relate to subjective well-being (SWB) using Statistics Korea’s 2019 Time Use Survey. The analysis includes 241 high-SWB and 241 low-SWB adolescents, assessing network density, inclusiveness, average distance, isolated nodes, degree centrality, and cohesion through NetMiner 4.0, with descriptive statistics processed in SPSS ver. 25.0. The results show clear differences in leisure activity networks. High-SWB adolescents engaged in more social activities and sports, while low-SWB adolescents participated in fewer, more solitary activities. High-SWB networks were diverse and well-connected, whereas low-SWB networks were more fragmented. Screen-based activities also played different roles: supporting social connections in high-SWB adolescents but reinforcing isolation in low-SWB adolescents. This study visually highlights that leisure participation varies by SWB level. The findings suggest that promoting diverse and interactive leisure activities can improve adolescent well-being, offering insights for policy and intervention programs.
Study on axial compressive behavior and mesoscopic structural evolution of FRP confined coal gangue concrete
To address the environmental hazards caused by coal gangue waste, coal gangue concrete (CGC) has been proposed as a solution. However, due to its porosity and low strength, CGC faces numerous challenges in practical applications. To further improve its performance, fiber reinforced polymer (FRP) material was introduced to confine it. In this study, the PFC3D-FLAC3D coupling analysis method was employed to simulate the uniaxial compression test of FRP confined coal gangue concrete specimens. The influence of different FRP types (GFRP, CFRP, BFRP) and coal gangue replacement rates (0%, 50%, 100%) on the axial compression performance of coal gangue concrete columns was analyzed. Based on the indoor uniaxial compression test of glass fiber reinforced polymer (GFRP) confined coal gangue concrete, the modeling and calibration of coal gangue concrete columns confined by different FRP sheets were conducted. The strength variation and microstructure evolution mechanism of coal gangue concrete specimens confined by three kinds of FRP were discussed. The results indicated that the numerical model is highly accurate and consistent with existing experiments. The type of FRP significantly influences the confinement effect on coal gangue concrete specimens. As the coal gangue replacement rate increases, both the strength and elastic modulus of the specimens decrease. The difference of the spatial distribution of strong contact number and strong contact force reflect the microscopic manifestation of the macroscopic strength. The crack evolution of FRP confined coal gangue concrete went through three stages during uniaxial compression. This study is of great significance for selecting the appropriate type of FRP confinement for concrete under different coal gangue replacement rates.
TempO-seq and RNA-seq gene expression levels are highly correlated for most genes: A comparison using 39 human cell lines
Recent advances in transcriptomics technologies allow for whole transcriptome gene expression profiling using targeted sequencing techniques, which is becoming increasingly popular due to logistical ease of data acquisition and analysis. As data from these targeted sequencing platforms accumulates, it is important to evaluate their similarity to traditional whole transcriptome RNA-seq. Thus, we evaluated the comparability of TempO-seq data from cell lysates to traditional RNA-Seq from purified RNA using baseline gene expression profiles. First, two TempO-seq data sets that were generated several months apart at different read depths were compared for six human cell lines. The average Pearson correlation was 0.93 (95% CI: 0.90–0.96) and principal component analysis (PCA) showed that these two TempO-seq data sets were highly reproducible and could be combined. Next, TempO-seq data was compared to RNA-Seq data for 39 human cell lines. The log2 normalized expression data for 19,290 genes within both platforms were well correlated between TempO-seq and RNA-seq (Pearson correlation 0.77, 95% CI: 0.76–0.78), and the majority of genes (15,480 genes, 80%) had concordant gene expression levels. PCA showed a platform divergence, but this was readily resolved by calculating relative log2 expression (RLE) of genes compared to the average expression across cell lines in each platform. Application of gene ontology analysis revealed that ontologies associated with histone and ribosomal functions were enriched for the 20% of genes with non-concordant expression levels (3,810 genes). On the other hand, gene ontologies annotated to cellular structure functions were enriched for genes with concordant expression levels between the platforms. In conclusion, we found TempO-seq baseline expression data to be reproducible at different read depths and found TempO-seq RLE data from lysed cells to be comparable to RNA-seq RLE data from purified RNA across 39 cell lines, even though the datasets were generated by different laboratories using different cell stocks.
Direct evidence for processing Isatis tinctoria L., a non-nutritional plant, 32–34,000 years ago
Recovering evidence for the intentional use of plants in the Palaeolithic is challenging due to their perishable nature as, unlike chipped stone or bone artefacts, plant remains are rarely preserved. This has created a paradigm for the Palaeolithic in which plants seldom feature, resulting in a partial and skewed perspective; in fact, plants were as essential to human life then as they are today. Here, we combine morphological and spectroscopic analyses (µ-Raman, µ-FTIR) to provide robust multiscale physical and biomolecular evidence for the deliberate pounding and grinding of Isatis tinctoria L. leaves 34–32,000 years ago. The leaf epidermis fragments were found entrapped in the topography of the used surface of unmodified pebbles, in association with use-wear traces. Although their bitter taste renders them essentially inedible, the leaves have well-recognised medicinal properties and contain indigotin precursors, the chromophore responsible for the blue colour of woad, a plant-based dye that is insoluble in water. We used a stringent approach to contamination control and biomolecular analysis to provide evidence for a new perspective on human behaviour, and the applied technical and ecological knowledge that is likely to have prevailed in the Upper Palaeolithic. Whether this plant was used as a colourant, as medicine, or indeed for both remains unknown, but offers a new perspective on the fascinating possibilities of non-edible plant use.
Scoping review of methods of monitoring acute changes in lower body neuromuscular function via force plates
Force plates are amongst the most utilised technological apparatus for monitoring acute changes in neuromuscular function in sports. Practitioners apply monitoring strategies to manage neuromuscular fatigue and physical preparedness with valid, reliable, and sensitive measures. The aim of this scoping review was to identify, map, and describe the variety of monitoring procedures which have been previously applied in research (e.g., test and metric selection, data collection, study design, and data analysis procedures). Searches were completed by 24th June 2024. One thousand, nine hundred, and seventy-eight studies were identified across four databases (PubMed, EBSCO, Clarivate web of science, and Ovid). After removing duplicates, applying the inclusion criteria, and scouring the reference lists of remaining studies, a final total of thirty studies of within-group repeated measures design were used in this review. Major differences were identified across all aspects of studies methodologies, such as in subject demographics (e.g., sex, sport, and competitive level), data collection protocols (e.g., force plate hardware utilised, test and metric selection, verbal cues, and provision of information regarding testing surface, familiarisation and warm-up provided, the process of zeroing force plates between trials, and weighing of subjects during trials), and study design (e.g., reference physical activity investigated, time of season, testing timepoints, and training load determination). A general lack of reporting and uniformity in metric definitions, metric calculations, and phase terminology was identified across studies. For example, two separate calculations were reported for “peak force” across studies, as either “the maximum force achieved throughout the entirety of the trial”, or as “the maximum force achieved during the propulsion phase”. The latter calculation was also utilised for “peak concentric force” in a separate study. Thus, an accurate comparison of results across studies (e.g., via meta-analysis) and forming any generalized conclusions about the application of specific tests and metrics for monitoring acute changes in neuromuscular function using force plates was premature at this time. The information presented in this review will contribute towards forming a rationale for the data collection, study design, and data analysis protocols for future research on monitoring acute changes in neuromuscular function using force plates.
MiR-129-5p alleviates depression and anxiety by increasing astrocyte ATP production partly through targeting deubiquitinase Mysm1
Major depressive disorder (MDD) is a major global mental concern that severely affects quality of life, yet current pharmacological treatments remain limited in their effectiveness. Long-term chronic stress has been shown to increase the incidence of depression and anxiety. Micro RNAs (miRNAs) have been revealed to participate in the pathological process of depression and represent promising therapeutic targets. In this study, we found that microRNA-129-5p (miR-129-5p) was significantly decreased in the brains of depressive mice. Overexpression of miR-129-5p in the hippocampus effectively alleviated depressive-like behaviors and reduced the activation of microglial cells and astrocytes. In addition, ATP levels in depressive mice were significantly increased following miR-129-5p overexpression. The antidepressant effects of miR-129-5p were reversed when ATP function was blocked with the non-specific P2 receptor antagonist suramin. In vitro experiments revealed that miR-129-5p overexpression enhanced ATP production in astrocytes. Furthermore, using a dual-luciferase reporter assay, we found that miR-129-5p directly targeted Mysm1. When overexpressed in astrocytes, miR-129-5p significantly suppressed Mysm1 expression, promoted phosphorylation of p53 and AMPK, and enhanced the expression of PGC1α, factors previously associated with ATP production. Our findings highlight the crucial role of miR-129-5p in regulating depression, suggesting that miR-129-5p overexpression may serve as an effective strategy for antidepressant treatment.
Seasonality of medically attended norovirus gastroenteritis and its association with climatic factors within an US integrated healthcare system, 2016–2019
Background While acute gastroenteritis (AGE) occurs year-round, norovirus has a winter seasonality in the United States. Objective We analyzed norovirus seasonality within a US integrated healthcare delivery system from 2016–2019. Methods Electronic medical records were collected for acute gastroenteritis (AGE) encounters with specific ICD-9/10 codes or clinical stool testing. Norovirus percent positivity was calculated as the 8-week centered rolling average. Temperature and absolute humidity data were measured via weather station. The relationship between these factors and weekly norovirus episodes were modeled via negative binomial models. Results From 2016–2019, there were 198,181 AGE episodes reported; among the 18,998 episodes tested, 892 (5%) were norovirus positive. Norovirus percent positivity peaked in epidemiologic week 7 at 9%. Two negative binomial models showed significant inverse relationships between weekly number of norovirus episodes and both temperature and absolute humidity. Conclusion Norovirus AGE exhibited winter seasonality from 2016–2019, associated with lower temperatures and humidity. Understanding this seasonality may help predict peak transmission periods and their impact on healthcare resources.
Generative artificial intelligence in secondary education: Applications and effects on students’ innovation skills and digital literacy
As generative artificial intelligence (AI) rapidly transforms educational landscapes, understanding its impact on students’ core competencies has become increasingly critical for educators and policymakers. Despite growing integration of AI technologies in classrooms, there remains a significant knowledge gap regarding how these tools influence the development of essential 21st-century skills in secondary education contexts. This study addresses this gap by investigating the relationships between generative AI applications and two critical student outcomes: innovation capability and digital literacy. Through structural equation modeling analysis of data collected from 500 students across grades 7–12, the research reveals three key findings: Firstly, generative AI applications demonstrate a substantial positive effect on students’ innovation capability (β = 0.862, p < .001), enhancing critical thinking, creative problem-solving, and adaptive learning processes. Secondly, AI integration significantly improves digital literacy (β = 0.835, p < .001) by facilitating sophisticated information processing and active technological engagement. Thirdly, a strong bidirectional relationship exists between innovation capability and digital literacy (β = 0.791, p < .001), suggesting these competencies mutually reinforce each other in AI-enhanced learning environments. The model demonstrates robust explanatory power with excellent fit indices. By integrating the Technology Acceptance Model with Diffusion of Innovations theory, this study advances theoretical understanding of AI’s educational impact while providing practical guidelines for educators. The findings underscore the importance of strategic AI integration in educational curricula and suggest specific pathways for developing critical student competencies in the digital age.
LBA-YOLO: A novel lightweight approach for detecting micro-cracks in building structures
Developing an efficient and accurate algorithm for detecting building cracks, especially micro-cracks, is essential for ensuring structural integrity and safety. The identification and precise localization of cracks remain challenging due to varying crack sizes and the inconsistency in available datasets. To address these issues, this study introduces an innovative crack detection model based on YOLOv8n. The proposed method incorporates two novel components: AC-LayeringNetV2, a hierarchical backbone network that optimizes feature extraction by integrating local, peripheral, and global contextual information, and RAK-Conv, a convolutional module that combines an attention mechanism with irregular convolution operations to enhance the model’s ability to handle complex backgrounds. These innovations significantly improve semantic segmentation accuracy while reducing computational overhead. Experimental results on a benchmark dataset demonstrate a 2.20% improvement in precision, a 3.50% increase in recall, and a 1.90% rise in mAP@50 compared to the baseline model. Additionally, the model achieves a 6.55% reduction in size and a 0.03% decrease in computational complexity. These results highlight the practical applicability and efficiency of the proposed approach for automatic crack detection in building structures, emphasizing the novel integration of feature fusion and attention mechanisms to address challenges in real-time and high-accuracy detection of micro-cracks in complex environments.
Evolving demographics of eligible patient population can impact enrollment of a biomarker clinical study
In a prospective clinical study to better understand how biological markers can improve diagnosis of and prognosis for asthmatic and atopic conditions, we contacted over 3500 eligible patients and observed noticeable differences in the range of their likelihood to enroll based on gender (3.8–13.4%), race and ethnicity (4.8–29.8%), and distance to study site (1.1–29.2%). Both the eligible patients and enrolled participants exhibited a more diverse racial and ethnic composition compared to local population demographics. Based on the eligible patients that the study team contacted (“eligible patients”, n = 3648) and those who agreed to enroll (“enrolled participants”, n = 454), we analyzed the gender, age, race and ethnicity composition of the groups, together with their proximity to the study site. Living close to the study site was the largest contributor to a patient's decision to enroll for both adults (odds ratio OR: 2.26, 95% confidence interval CI: 1.64–3.15, p < 0.001) and children (OR: 2.59, 95% CI: 1.67–4.41, p < 0.001). We also observed that patients from White and non-Hispanic racial and ethnic background were more likely to participate in the study among both pediatric (OR: 1.51, CI: 0.92–2.62, p = 0.122) and adult patients (OR: 1.81, CI: 1.18–2.89, p = 0.009). Eligible patients of female gender were also more likely to enroll in both adult (OR: 1.53, CI: 1.16–2.05, p = 0.003) and pediatric groups (OR: 2.14, CI: 1.42–3.22, p < 0.001). Overall, the pediatric patients (18 years old or younger) were much less willing to participate in the clinical biomarker study. Nonetheless, as they age, the enrollment likelihood increased accordingly (5 years OR: 1.71, CI, 1.32–2.21, p < 0.001). The eligible patient population of the study reflected the evolving demographics and different disease prevalence for asthma and other allergic diseases in adult and pediatric groups. These factors in turn influenced the composition of the enrolled participants.
Predictors of alcohol use disorder risk in young adults: Direct and indirect psychological paths through binge drinking
Alcohol-use disorders (AUD) risk is highly prevalent in university students, and is associated with both intraindividual (e.g., metacognitions, personality traits) and interindividual (e.g., social motives, drinking identity, drinking norms) psychological factors. Binge drinking (BD) also constitutes a widespread drinking pattern in youth, distinct from AUD risk and mainly predicted by interindividual factors. As BD is itself a risk factor for AUD, we tested a dual psychological path model to AUD risk, combining a direct path (including intra/interindividual factors independent from BD) with an indirect path (where interindividual factors increase AUD risk through BD). We assessed a large range of psychological factors predicting BD and AUD risk in an online survey among 2026 university students (Mage = 20.46; SD = 2.82; 67.42% of women). We tested the direct and indirect (via BD) effects of these psychological factors on three subdimensions of AUDIT (alcohol intake, dependence symptoms, and alcohol-related problems) through a multivariate mediation model using percentile bootstrapped estimates. Support for the dual-path model to risk of AUD emerged from the results, comprising a direct path mainly influenced by intra-individual factors unrelated to BD (e.g., coping motives, depression symptoms, and uncontrollability beliefs), and an indirect BD-mediated path mainly influenced by inter-individual factors (e.g., social motives, enhancement motives, drinking norms) through BD. This new dual-path conceptualization combining direct/intra-individual and indirect/inter-individual risk factors identifies key psychological determinants of AUD risk in youth and offers new prevention avenues for AUD risk.
Translation and validation of Malay version of NIOSH worker well-being questionnaire (WellBQ)
The NIOSH Worker Well-Being Questionnaire (WellBQ) offers a comprehensive framework to evaluate worker well-being across five domains: work evaluation, workplace policies, physical environment and safety, health status, and home/community influences. In Malaysia, traditional occupational safety and health (OSH) initiatives have primarily focused on workplace hazards, often neglecting broader psychosocial and organizational factors. To address this gap, this study adapted and validated the Malay version of the WellBQ for healthcare workers, ensuring cultural and contextual relevance. A rigorous translation process, including forward and backward translation, expert panel reviews, and pilot testing, was conducted to retain the original framework while addressing local nuances. Psychometric evaluation involved 366 healthcare workers from Hospital Universiti Sains Malaysia, employing Confirmatory Factor Analysis (CFA) to assess model fit, internal consistency, and construct validity. The Malay WellBQ demonstrated robust psychometric properties, with a Content Validity Index (CVI) of 0.92 and a Face Validity Index (FVI) of 0.98, reflecting high relevance and clarity. CFA confirmed an acceptable model fit (RMSEA = 0.050, CFI = 0.887, TLI = 0.877) and strong internal consistency (CR > 0.7). Convergent validity was observed across most subdomains, although some Average Variance Extracted (AVE) scores fell below 0.5, highlighting areas for refinement. Discriminant validity was achieved within domains but revealed overlaps between some domains, suggesting interconnected constructs. The Malay WellBQ is a reliable and culturally relevant tool for assessing worker well-being, offering actionable insights for workplace policy and intervention development. Further refinements are recommended to enhance construct validity across domains.