Frontiers in Public Health最新文献

Background: Artificial intelligence (AI) is reshaping healthcare from clinical care and diagnostics to operations and public health and has been accelerated by recent advances in large language models (LLMs), such as ChatGPT. Because healthcare directly concerns human life and well-being, the use of AI must be approached with care. As AI systems are ultimately designed, implemented, and trusted by people, identifying the factors that shape medical students' attitudes toward AI is critical for safe and effective integration.

Methods: In this study, attitudes toward AI were measured with the General Attitudes toward AI Scale (GAAIS), and personality traits were measured with the Big Five Inventory-2 (BFI-2). Along with demographic information, all these data were collected via an online platform from five-year clinical medicine students in Beijing, Shanghai, and Chengdu. Correlation and linear regression were conducted.

Results: Analyses indicated that openness and agreeableness were associated with higher scores of positive attitudes toward AI, whereas conscientiousness was associated with lower scores of positive attitudes toward AI. For negative attitudes toward AI, openness and agreeableness were associated with its higher scores, whereas neuroticism was associated with its lower scores.

Conclusion: These results suggest that students with greater openness and agreeableness not only view AI more favorably but are also more tolerant of its limitations. In contrast, those high in conscientiousness report fewer positive views, and those high in neuroticism are less tolerant of AI shortcomings. To our knowledge, this is the first study to examine the associations between personality traits and attitudes toward AI in medical students in China, highlighting the need for targeted educational interventions that reflect diverse personality profiles.

Objectives: The prevalence of human immunodeficiency virus (HIV) remains a severe public health issue, especially among young people. To determine whether family functioning and self-monitoring influence HIV/acquired immunodeficiency syndrome (AIDS)-related preventive behaviors among young students with sexual experience, we conducted a cross-sectional exploratory study.

Methods: This study, which used a convenience sampling method, was conducted in Fuzhou, China. The questionnaires used for this research included the Adaptation-Partnership-Growth-Affection-Resolve (APGAR) scale, the Self-Monitoring Scale, and questions concerning HIV/AIDS-related preventive behaviors. Binary logistic regression, multiple linear regression, and the Karlson-Holm-Breen method were employed to assess the relationship between family functioning and HIV/AIDS-related preventive behavior and to identify the mediating role of self-monitoring in this context.

Results: A total of 29,038 students participated in the survey, of whom 2,510 had sexual experience. Family functioning had positive effects on students' attitudes toward HIV testing [odds ratio (OR): 1.763; p < 0.01], reading/hearing HIV/AIDS news (OR: 2.776; p < 0.001), seeking online information (OR: 2.815; p < 0.001), and engaging in discussions about HIV/AIDS with others (OR: 2.686; p < 0.001). Moreover, the results of the mediation analysis revealed that self-monitoring played a mediating role in the relationship between family functioning and HIV/AIDS-related preventive behaviors.

Conclusion: Family functioning was mediated by self-monitoring and indirectly affected HIV/AIDS-related preventive behaviors. It is essential to promote family functioning education in public health programs and to develop family intervention tools. Practical activities pertaining to the prevention of HIV/AIDS should be added to the self-management content of sex education courses for young students.

Introduction: Accurately predicting cross-regional spread of infectious diseases and designing cost-effective interventions is challenging due to population mobility, multi-pathogen circulation, and spatiotemporal heterogeneity. This study aims to build a unified framework that improves multi-disease forecasting, enhances interpretability of transmission pathways, and enables data-driven optimization of public-health interventions.

Methods: We develop a spatiotemporal graph attention network (ST-GAT) that integrates surveillance, meteorological, healthcare, and NPI data on a dynamic multi-relational graph combining geographic adjacency and origin-destination mobility. Spatial and temporal attention with a distribution-aware NB/ZINB decoder generates calibrated 1-4-week probabilistic forecasts, and the model is embedded in a multi-objective optimization engine to evaluate vaccine allocation and mobility restriction strategies under cost, fairness, and feasibility constraints.

Results: Using ILI, HFMD, dengue, and RSV data, ST-GAT reduces MAE (34% vs ARIMAX, 27% vs Prophet, 15% vs LSTM/GRU) and improves WIS/CRPS across diseases. Spatial attention identifies high-weight transmission corridors, temporal attention highlights short lags of 1-4 weeks, and optimization shows a vaccine-first strategy achieves the best cost-effectiveness and stability.

Discussion: The framework provides an integrated, interpretable, and generalizable solution for real-time epidemic prediction and equitable public-health decision-making.

Purpose: This study aims to explore the correlation between Fundamental Movement Skills (FMS) and Aquatic Competence (AC) acquisition in preschool children aged 4-6 years.

Methods: A total of 120 preschool children aged 4-6 years with no swimming learning experience (60 boys and 60 girls) were recruited in Beijing. All subjects were stratified and randomly divided into an experimental group and a control group (30 boys and 30 girls). Before and after a 6-week (twice a week, total of 12 sessions) aquatic movement skills course in the experimental group, all children underwent FMS and AC testing. Descriptive statistics were performed on the results of the two tests, and the Mann-Whitney U test was used to compare the ΔAC of the two groups of subjects. Analysis of covariance (ANCOVA) and rank-transformed ANCOVA were used for inter-group difference analysis. Spearman rank correlation analysis was used to explore the correlation between FMS and AC acquisition.

Results: The locomotor skills, object control, and FMS scores of the experimental group and the control group in the post-test were all higher than those in the pre-test, and the AC post-test score of the experimental group was higher than the pre-test. The improvement levels of locomotor skills (F = 18.98, p < 0.01, η² = 0.14), object control (F = 32.19, p < 0.01, η² = 0.22), FMS (F = 45.85, p < 0.01, η² = 0.28), and AC (F = 1663.96, p < 0.01, η² = 0.93) in the experimental group were significantly better than those in the control group. At the same time, the improvement level of Aquatic Competence (ΔAC) in the experimental group was significantly higher than that of the control group (Z = -9.48, p < 0.01). Correlation analysis indicates that the acquisition of AC in boys is significantly positively correlated with object control skills (r = 0.419, p = 0.021) and FMS (r = 0.388, p = 0.034).

Conclusion: Learning aquatic movement skills can significantly enhance the fundamental movement skills and aquatic competence of preschool children aged 4-6 years. The control skills of boys are related to their aquatic competence acquisition. Therefore, during the preschool stage, focusing on and cultivating children's fundamental movement skills, especially object control abilities, is of great significance for their effective development of future aquatic competence.

Background and aims: Endoscopic visualization for the diagnosis of Helicobacter pylori (HP) infection status is highly important for helping endoscopists quickly understand the status of gastric background mucosa and assisting in subsequent diagnosis and treatment. In this study, a deep learning algorithm was designed to construct a three-class classification model of HP infection status, providing a new approach to address the subjectivity in the interpretation of endoscopic features.

Methods: The clinical data of patients who completed gastroscopy were collected, and 16 endoscopic features were evaluated and recorded. On the basis of the status of HP infection, the patients were classified into three groups: the current HP infection group (CI), the previous HP infection group (PI), and the negative HP infection group (NI), with 1,000 patients screened in each group. In this study, an HP infection classification model based on the transformer network was constructed, which uses a self-attention mechanism to capture feature associations for the task of HP infection classification and recognition. Model interpretability was achieved by screening key features through SHapley Additive exPlanations (SHAP) value analysis.

Results: A total of 3,000 subjects were included in the study, and comparative analysis revealed that the 1D-transformer model demonstrated superior performance in the HP recognition task. The accuracy, specificity, sensitivity, and F1_scores produced by the model were 98.9 ± 0.28, 98.8 ± 0.14, 99.4 ± 0.27, and 98.9 ± 0.28, respectively. In addition, it has better performance than other algorithms and models. In terms of model interpretability, this study highlights the importance rankings of different features in model decision-making and the directions of their influence. The results show that map redness (SHAP value of 0.220), xanxoma (SHAP value of 0.101), atrophy (SHAP value of 0.065), and intestinal metaplasia (SHAP value of 0.008) are key features for identifying the PI. Diffuse redness (SHAP 0.186), thickened folds (SHAP 0.126), mucus coverage (SHAP 0.094), and nodular changes (SHAP 0.043) are key features for identifying CI. The presence of RAC (SHAP 0.262) and ridge redness (SHAP 0.026) are key features for identifying NI.

Conclusion: This study applies a 1D-transformer model to the task of classifying HP infection status, and compared with other models, it can precisely screen out populations with three different HP infection statuses, with higher performance and reliability.

Background: Children living in low socioeconomic status (SES) environments are more likely to develop behavior problems. Breastfeeding is one behavior that has been positively linked to mental health throughout childhood. We investigated whether breastfeeding modifies the association between low SES and behavior problems.

Methods: We studied a subset of the Canadian CHILD cohort (N = 2,342). Lower SES (n = 592) was defined as one or more of: (1) low income based on family size, (2) single parenthood, or (3) maternal education below a post-secondary degree. Breastfeeding was reported by caregivers from birth to 2 years. The Child Behavior Checklist (mean 50, SD (10), comprising internalizing, externalizing, and total behavior scores) was administered at 5 years. We tested main effects and interactions between SES and breastfeeding on child behavior, adjusting for several maternal and child characteristics.

Results: Lower SES was related to higher (worse) behavior scores (B = 2.06 [95%CI: 1.06, 3.07] for total behavior scores), while longer and more exclusive breastfeeding was related to lower (better) behavior scores (B = -2.43 [95% CI: -3.74, -1.11] for exclusive breastfeeding at 6 months, compared to no breastfeeding, for total behavior scores). We observed significant interactions between longer and more exclusive breastfeeding and family SES on internalizing and total behavior scores, indicating that the "socioeconomic gap" in behavior scores becomes smaller with more exclusive and longer breastfeeding.

Conclusion: This study provides new evidence that breastfeeding may be one factor that can help reduce socioeconomic inequities in child behavior scores.

Background: Physical exercise (PE) is important for health. Girls are reported to participate less compared to boys. Multiple factors influence participation and non-participation, including neighborhood, socioeconomic status, social support, and disability. Factors may combine and form paths to participation or non-participation, yet these paths are unknown. To our knowledge, this is the first study to combine cluster analysis with a configurational comparative method to explore paths to participation and non-participation in PE among adolescents.

Methods: Data from 178 Swedish 15-18-year-olds revealed two exercise-related clusters: Not exercising and Sporting & Exercising. Girls and boys in these clusters were analyzed separately by coincidence analysis to identify paths leading to membership in each cluster. The initial analysis included 41 questions aggregated into 24 variables.

Results: Not having quick access to pocket money is a path by itself to Not exercising among girls and part of the path to Sporting & Exercising. The paths to Not exercising are more complex for boys. Participation in adult-led activities differs between boys in the Not exercising and Sporting & Exercising clusters. Having a disability is only a difference-making factor among boys when combined with "not avoiding anyone in the neighborhood" and "sometimes meeting friends in person."

Conclusion: Multiple distinct paths lead to Sporting & Exercising and Not exercising, and these differ between girls and boys. Paths to exercising and non-exercising can be multi-factorial in nature, where several factors must be jointly present to explain membership in a particular exercise-related cluster. Future research may wish to adopt a similar configurational approach to explore other high-priority activities in which adolescents do or do not participate to improve interventions and policies aimed at increasing adolescent participation in PE.

Background: Sanitation workers are exposed to heavy metals due to improper disposal of waste. This study analyzes heavy metal concentrations in the serum, urine, and blood of sanitation workers exposed to improperly disposed e-waste and industrial residues, and examines how protective measures affect these levels.

Methods: This study examines heavy metal levels in 102 sanitation workers (22 operators, 37 drivers, and 43 sanitary workers) versus a control group of 50 unrelated workers. Samples were pre-treated with 0.5% nitric acid and Triton X-100 for serum and blood, and 0.5% nitric acid with 200 μg/L gold for urine. ICP-MS in KED mode was used to measure concentrations of 10 heavy metals (Cr, Mn, Co, Ni, As, Cd, Sn, Sb, Hg, and Pb) in the samples.

Results: Long working hours, working at disposal and hand injury were associated with higher concentrations of Cd, Sb, and Hg in human blood. Elevated serum levels of Mn (2.46 μg/L), Cd (0.14 μg/L), Sn (1.19 μg/L), and Sb (9.99 μg/L) were observed in sanitation workers. Among drivers, increased serum concentrations were noted for Mn (2.67 μg/L), Cd (0.15 μg/L), Sn (1.18 μg/L), and Hg (0.57 μg/L). Serum Sb (10.10 μg/L) was particularly elevated in the sanitary workers. Sanitation workers exhibited heightened urine levels of Cr (1.91 μg/L), Co (0.35 μg/L), Ni (2.79 μg/L), Cd (0.92 μg/L), Sn (6.43 μg/L), and Sb (0.14 μg/L). Operators demonstrated an increased concentration of Cr (2.37 μg/L). Drivers showed elevated levels of As (95.29 μg/L), Cd (1.34 μg/L), Sb (0.14 μg/L), and Hg (0.31 μg/L). Sanitary workers exhibited higher concentrations of Co (0.41 μg/L), Ni (3.54 μg/L), and Sn (6.79 μg/L). Blood concentration levels of As (8.70 μg/L), Cd (3.62 μg/L), Hg (3.82 μg/L), and Pb (16.71 μg/L) were highest in drivers' group followed by operators, while lowest in sanitary workers. The median concentrations were all below the BEI (ACGIH, GBZ, WS/T).

Conclusion: Sanitation workers face an elevated risk of exposure to heavy metals, may posing significant threats to their occupational health. There is a critical need for comprehensive prevention and intervention strategies to mitigate heavy metal exposure among sanitation workers.