Objective: To explore the experiences of obesity among junior high school students, and reveal its core themes and essential features, so as to provide evidence for health promotion. Methods: From March to August 2025, semi structured in depth interviews were conducted with 22 obese junior high school students (15 boys,7 girls) aged 13-16 years from two junior high schools in Beijing and one junior high school in Shenyang.Each interview lasted about 40 minutes, and the outline of the interview mainly involved three dimensions: obesity experience, obesity life experience, suggestions and future expectations. Data were analyzed using Moustakas phenomenological method. Results: A total of 4 core themes and 13 sub themes were identified: health experiences (external discipline, health conflicts, perceptual tension), exercise experiences (restricted activity, weight loss expectations, psychological catharsis, physical education test pressure), emotional experiences (appearance anxiety, self soothing, generalized impact), and social experiences (social devaluation, external support, covert suppression). Conclusions Obesity is a complex experience co-constructed by body awareness, physiological indicators, and sociocultural factors. Interventions should enhance students’ body awareness, facilitate a shift from external discipline to internal motivation, and form a collaborative health promotion pathway involving families, schools, and society.

Objective: To explore the longitudinal association between weight trajectories and physical fitness test composite scores among primary school students, so as to provide empirical evidence for school based weight management and physical health promotion. Methods: A total of 2 112 students from a primary school in Beijing who participated in physical fitness assessments annually from 2008 to 2023 were included and classified into different body weight trajectory groups based on body mass index (BMI) threshold: "normal/overweight-obese". Group based trajectory model was used to identify distinct weight trajectories. Generalized estimating equation and Cox regression were used to analyze the associations between weight trajectories and changes in physical fitness test scores, as well as event risks. Robustness checks were conducted. Results: The prevalence of overweight and obesity among primary school students was 26.50%. BMI showed a significant negative correlation with physical fitness composite scores ( r=-0.19, P <0.01). Four types of weight trajectories were identified: persistent normal group (64.5%, 1 362), persistent overweight- obese group (18.2%, 385), normal to overweight-obese group (14.0%, 296), and overweight-obese to normal group (3.3%, 69). Compared to the persistent normal group, both the normal to overweight-obese and persistent overweight-obese groups showed significantly higher risks of failing the physical fitness test ( HR =4.23, 4.60), and the speed of achieving excellent was slower ( HR = 0.52, 0.40) (all P <0.05). Robustness tests confirmed the stability of the findings. Conclusions Body weight trajectories have a long term impact on physical fitness performance among primary school students. Students with persistent or progressive overweight-obese trajectories have limited score improvement and a higher risk of failure; primary school students with persistent or progressive overweight and obesity should be a key focus.

Objective: To explore the interrelationships between mental vulnerability, cognitive emotion regulation strategies, and positive psychological capital in medical postgraduates, so as to provide precise intervention targets for mental health services in universities. Methods: From April to June 2025, a convenience sampling method was used to select 1 461 medical postgraduates from three colleges in Hubei Province. Participants were assessed using the Mental Vulnerability Questionnaire (MVQ), the Cognitive Emotion Regulation Questionnaire-Chinese Version (CERQ-C) and the Positive Psychological Capital Questionnaire (PPQ). The network analysis model was constructed using a Gaussian graphical model. Results: The network analysis revealed that the edge connection between somatic symptoms and mental symptoms was the strongest, followed by the connection between refocus on planning and positive reappraisal within cognitive emotion regulation, with edge weights of 0.69 and 0.59, respectively. Interpersonal problems within psychological vulnerability exhibited the highest expected influence( EI =1.27), serving as the core node of the network. Rumination within cognitive emotion regulation demonstrated the highest bridge expected influence( BEI =0.33), playing a critical connecting role among psychological vulnerability, cognitive emotion regulation, and positive psychological capital. Conclusion In the mental health network of medical postgraduates, mental vulnerability, cognitive emotion regulation, and positive psychological capital interact through their respective key dimensions, jointly affect overall mental health.

Objective: To develop and compare multiple machine learning models for identifying high-risk college students exhibiting phubbing behavior and to determine key predictive factors, so as to provide evidence for precise screening and early intervention strategies. Methods: In December 2025, 1 828 undergraduate students, selected from three universities in Wuhan by using convenience sampling method, were surveyed via online qustionnaire for sociodemographic characteristics, phubbing behavior, family cohesion index, mature happiness, fear of negative evaluation, multidimensional state boredom, and psychological vulnerability. Four machine learning algorithms, including multilayer perceptron (MLP), extreme gradient booting (XGBoost), K-nearest neighbors (KNN), and gradient boosting decision tree (GBDT), were applied. The dataset was randomly split into a training set and a test set at a ratio of 7∶3. Model performance was evaluated using accuracy, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The best performing model was further interpreted using shapley additive explanation (SHAP) analysis to assess feature importance. Results: In the training set,955 participants were classified as having low level phubbing behavior, and 325 participants were classified as having high level phubbing behavior. Significant differences were observed in psychological vulnerability, multidimensional state boredom, family cohesion index, and mature happiness between groups ( Z =-10.29, -11.72, -8.17, -7.83, all P <0.05). Significant differences were also found in the detection rate of high level phubbing behavior according to family residence, family status, left behind experience,interpersonal relationships,exercise frequency,physical flexibility,and sleep status ( χ 2=12.22, 38.93, 16.90, 44.64, 58.17, 82.14, 37.89, all P <0.05). Among the four machine learning models (MLP, KNN, GBDT, XGBoost),all showed good discrimination ability, with XGBoost performing best (accuracy 79%, recall 71%, F1-score=0.70, AUC=0.78), while GBDT achieved the highest precision (78%). Feature importance analysis showed that multidimensional state boredom was the most important predictor of phubbing behavior, followed by psychological vulnerability, family cohesion, mature happiness, and fear of negative evaluation. SHAP analysis indicated that multidimensional state boredom, psychological vulnerability, and fear of negative evaluation had positive risk effects, while family cohesion and hedonic well being had protective effects for high risk of phubbing behavior. Conclusions Multidimensional state boredom is the core predictor of phubbing behavior among college students. The XGBoost model demonstrates good predictive performance and can provide a reference for identifying high risk individuals and implementing targeted interventions.

The ultimate goal of enhanced recovery after surgery (ERAS) is to achieve risk-free and pain-free care. It is necessary in establishing perioperative comfort-oriented wards for medical technology advancement and economic development. This article discusses the clinical practices of comfort-oriented wards at the Lung Cancer Center of West China Hospital, Sichuan University and focuses on the following aspects: concept, framework, and team-building; current clinical application status, challenges, and implementation strategies; analysis of related construction models and plans; and clinical outcomes and future prospects. This work aims to promote a shift in the ERAS evaluation system toward a patient-centered concept and the application of comfort-oriented wards.

To investigate the genetic relatedness between carbapenem-resistant Klebsiella pneumoniae(CRKP) strains isolated from intestinal colonization and subsequent bloodstream infections.

Objective: To analyze the influencing factors of aggressive behaviors in high school students, rank the importance of relevant variables with visual presentation, so as to provide new references for developing intervention strategies. Methods: In December 2024, a convenience sampling method was used to select 5 330 students from 5 high schools in Wuhan for an online questionnaire survey. The survey included the Buss-Perry Aggression Questionnaire (BPAQ), Interaction Anxiety Scale (IAS), Emotion Regulation Ability Scale, Inventory of Parent and Peer Attachment (IPPA), and a self designed general information questionnaire. Variables were screened using LASSO regression, followed by multivariate Logistic regression analysis. The Random Forest model was then employed to rank and visualize variable importance. Results: Univariate analysis and LASSO regression results indicated that gender, emotion regulation capability, paternal attachment quality, maternal attachment quality, maternal parenting style, paternal parenting style, parenting consistency, monthly household income per capita, school climate, relationship with classmates, interaction anxiety, and academic ranking were all significant variables (all P <0.01). Multivariate Logistic regression analysis identified the following as influencing factors of aggressive behaviors in high school students: emotional management ability ( OR=0.38, 95%CI =0.34-0.43), gender ( OR=0.83, 95%CI =0.75-0.93), mother attachment quality ( OR=0.89, 95%CI = 0.74 -1.07), father attachment quality ( OR=0.76, 95%CI = 0.66- 0.87), interaction anxiousness ( OR=1.58, 95%CI =1.40- 1.78 ), consistency of parenting styles of parents ( OR=1.40, 95%CI =1.21-1.62), school atmosphere ( OR=1.50, 95%CI =1.14-1.98), academic performance ranking (upper middle: OR=0.76, 95%CI =0.61-0.93; middle: OR=0.70, 95%CI =0.57-0.86) were the influencing factors of aggressive behavior in high school students (all P <0.05). The results of Random Forest showed that emotional management ability was the most important factor affecting aggressive behavior in high school students. Conclusion Emotion regulation capability is identified as the core predictor of adolescent aggressive behaviors, which can significantly reduce the incidence of aggressive behaviors through enhanced emotion management.

Objective: To investigate the association between 24 hour activity behavior and body composition among primary and secondary school students using compositional data analysis method, so as to provide scientific guidance for optimizing daily activity allocation and improving physical health. Methods: In June 2021, following the principle of random cluster sampling, 349 primary and middle school students were selected by lottery method from Taiyuan City, Shanxi Province. Compositional multiple regression analysis was conducted to examine the relationship between different 24 hour activity behaviors and body composition indicators. The isotemporal substitution model was adopted to examine the quantitative effects of substituting 10 or 20 minutes among activity behaviors on body composition. Results: In girls, sedentary behavior (SB) time was negatively correlated with fat free mass (FFM) ( β =-4.81); in boys, moderate to vigorous physical activity (MVPA) time was positively correlated with FFM ( β =7.01), while light physical activity (LPA) time was negatively correlated with FFM ( β =-9.26) and positively correlated with body fat percentage (FAT%) ( β =0.09) (all P <0.01). Isocaloric substitution analysis revealed that replacing the same duration of MVPA with SB, sleep (SL), or LPA for 10 or 20 minutes produced significantly greater adverse effects compared to the beneficial effects of MVPA substitution. Replacing MVPA with LPA for 10 minutes resulted in 1.01% increase in FAT% and 0.91% decrease in reverse substitution for boys; replacing MVPA with SB or SL for 10 minutes resulted in a decrease of 1.10 kg and 1.16 kg in FFM for boys, 0.81 kg and 0.74 kg for girls, and reverse substitution increased by 0.92 and 0.97 kg, 0.65 and 0.58 kg, respectively (all P < 0.05 ). When LPA, SB or SL were replaced with MVPA for 20 minutes, the trend of change were basically consistent (all P <0.05). Conclusions Activity behaviors of 24 hour are associated with body composition among primary and secondary school students. MVPA is the primary influential component.

Objective: To analyze the factors associated with high level fear of negative evaluation (FNE) among junior high school students and to construct a nomogram risk prediction model, so as to provide scientific tools for psychological health intervention for junior high school students. Methods: A convenience sampling combined with cluster random sampling method was used to select 5 485 junior high school students from 4 cities (Wuhan, Huanggang, Xianning and Xiaogan) for an online questionnaire survey in March 2025. The total sample was randomly split into a training set ( n =3 839) and a validation set ( n =1 646). Univariate analysis was performed in the training set using Chi-square test and t-test. Variables with statistical significance were subsequently included in multivariate Logistic regression to identify independent predictors and to construct a nomogram based risk prediction model. The discriminative ability and clinical utility of the model were evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: There were 1 649 junior high school students with low level FNE and 2 190 with high level FNE in the training set. The self control ability of junior high school students with lowlevel and high level FNE showed a statistically significant difference (23.96±3.96, 21.48±3.37, t=25.15, P < 0.01 ). Statistically significant differences in the detection rate of high level FNE were observed among junior high school students with different genders, family types, parenting styles, academic rankings, psychological flexibility, mobile phone addiction tendencies, emotional management training, exercise frequency, left behind experiences, and places of origin ( χ 2=82.01- 1 126.68 , all P <0.01). The results of Logistic regression analysis revealed that, the following factors were identified as significant factors influencing high level FNE among junior high school students:exercise frequency ( OR=0.21, 95%CI =0.17-0.26); parenting style ( OR=0.48, 95%CI =0.40-0.58); left behind experience ( OR=3.88, 95%CI =3.27-4.61); smartphone addiction proneness ( OR=2.19, 95%CI =0.89-0.93); self-control ability ( OR=0.91, 95%CI =0.89-0.93); and psychological flexibility ( OR=0.16, 95%CI =0.10-0.28) (all P <0.05). The AUC for the training and validation set were 0.88 (95% CI =0.87-0.89) and 0.87 (95% CI =0.85-0.89), respectively. The Hosmer-Lemeshow goodness of fit test yielded χ 2=8.57, 15.20 (both P >0.05). Conclusion The risk prediction model with high level FNE demonstrates good accuracy and can assist educators and parents in timely screening of junior high school students with high level FNE, thereby providing a basis for implementing targeted interventions.

Objective: To explore the association between physical activity, anxiety symptoms and academic performance among junior high school students, so as to provide data support for optimizing school physical education and health work and formulating physical activity guidelines. Methods: From September to December 2022, a convenience cluster sampling method was used to survey 2 800 junior high school students in a middle school from Anqing City, Anhui Province. Data were collected on the students anxiety symptoms, academic performance, 24 hour physical activity [moderate to vigorous intensity physical activity(MVPA), light intensity physical activity(LPA), sedentary behavior(SB), and sleep(SLP) duration] as well as demographic characteristics. Compositional data analysis was used to explore the associations between 24 hour physical activity, anxiety symptoms and academic performance among junior high school students, and to predict the optimal time use combination pattern. Results: Among the junior high school students, 16.0% (447 students) reported anxiety symptoms, and 42.0% (1 175 students) achieved excellent or good academic performance. Compositional data analysis showed that increased SLP duration was associated with both reduced anxiety symptoms ( β =-0.18) and decreased academic performance ( β =-0.03) among junior high school students; increased MVPA duration was correlated with fewer anxiety symptoms ( β =-0.02) and lower academic performance ( β =-0.13); in contrast, increased SB duration was linked to more anxiety symptoms ( β =0.09) and higher academic performance ( β =0.09) (all P <0.01). LPA duration exhibited a non linear relationship with anxiety symptoms and academic performance in junior high school students (all P >0.05). The time use combination pattern corresponding to the lowest anxiety symptoms and highest academic performance (top 5%) in adolescents was 611 (520-640) minutes of SLP, 258 (230-320) minutes of SB, 454 (280-610) minutes of LPA, and 117 (20-200) minutes of MVPA per day. Conclusions The 24 hour physical activity of junior high school students is associated with anxiety symptoms and academic performance. Therefore, it is recommended to increase the time spent on SB, MVPA, and LPA for junior high school students, while reducing SB.