To analyze the design flaws and statistical issues present in medical papers submitted to core domestic journals, and to explore strategies for improving the quality of medical papers and submission acceptance rates.

A questionnaire survey was conducted to collect data on submissions to domestic core medical journals between January 2021 and December 2023. Quantitative empirical and qualitative analyses were performed.

A total of 306 clinical medicine research papers and 328 basic medicine research papers were included in the analysis. There was a statistically significant difference in the acceptance rates between these two categories (P<0.001), while no significant difference was found concerning the acceptance rates of papers supported by different levels of funding (P>0.05). Observational studies constituted 71.40% of all submissions; however, their acceptance rate was lower than that of experimental studies (43.75% vs. 53.66%, P<0.05). Various deficiencies were identified in the methodological design and statistical analysis reporting of the manuscripts. The main issues included unclear description of study design types, inadequate matching between groups, insufficient modeling and validation, neglect of sample size calculation, and errors in result reporting.

Significant flaws exist in the research design and statistical analysis reporting of medical manuscripts, with a considerable gap compared to internationally recognized medical reporting standards. Hospitals and medical schools should strengthen training in the latest medical research standards and statistical knowledge to improve the quality of academic papers and enhance research outcomes.

To evaluate the effectiveness of case study-modularized teaching design method in undergraduate nursing students.

Undergraduate nursing students in the class of 2020 of a medical university were selected as research subjects, and a parallel controlled trial was designed with case study-modularized teaching in the intervention group and traditional teaching methods in the control group, and the evaluation of teaching effectiveness was conducted by anonymous questionnaires and final grades.

The scores, learning attitudes, course cognition, teaching satisfaction, and self-learning effect evaluation of students in the intervention group were better than those in the control group (P<0.05), and the teaching method was especially effective in improving students’ comprehensive application ability.

The case study modularized teaching method used in the teaching of medical statistics is popular among students, with high course satisfaction and self-learning effect evaluation, which can improve the comprehensive application ability of students, and the teaching effect is remarkable.

To analyze the relationship between the ratio of glycated albumin to glycated hemoglobin (GA/HbA1c)and all-cause mortality in adults with metabolic syndrome MetS.

This study is a retrospective cohort study utilizing data from the National Health and Nutrition Examination Survey (NHANES) and the National Death Index (NDI) from 1999 to 2004. A total of 1 497 eligible participants were included and followed up until December 31, 2019. The relationship between the GA/HbA1c ratio and all-cause mortality in MetS patients was assessed using Kaplan-Meier survival curves, multivariable weighted Cox regression, and restricted cubic splines.

Among a weighted population of 55 224 898 eligible individuals with a median follow-up of 16.3 years, there were 501 cases of all-cause mortality. Participants were divided into three groups(T1, T2, T3) based on weighted tertiles of the GA/HbA1c ratio. After adjusting for covariates, a higher GA/HbA1c ratio (T3) was associated with an increased risk of all-cause mortality in MetS patients compared to the lowest tertile (T1) (HR=1.335, 95%CI:1.010-1.772). The restricted cubic spline analysis also revealed a non-linear “S” shaped relationship between the GA/HbA1c ratio and all-cause mortality (non-linear P<0.05). Subgroup analyses (all interaction P>0.05) and sensitivity analyses (HR=1.344, 95%CI: 1.014-1.783) showed similar results.

There is a non-linear association between the GA/HbA1c ratio and all-cause mortality in patients with metabolic syndrome, with higher GA/HbA1c ratios linked to an increased risk of all-cause mortality in these patients.

To explore the association between the Sleep Regularity Index (SRI) and central obesity, as well as the differences among different age and gender groups, to provide a reference for research on sleep regularity and central obesity in the population.

A questionnaire survey and objective sleep monitoring were conducted among individuals aged 40 to 65 who underwent health check-ups at the First People’s Hospital of Fuquan city from March to November 2022, ultimately including 522 participants with complete data. The association between SRI and the risk of central obesity was assessed using a non-conditional binary logistic regression model and restricted cubic splines, along with subgroup analyses based on gender and age.

Among the participants included in the study, 331 individuals (64.41%) were classified as having central obesity. After adjusting for confounding variables, the results from the restricted cubic splines indicated that when the SRI score exceeded 72.67, the risk of central obesity gradually decreased with increasing SRI scores. The non-conditional binary logistic regression model revealed that individuals with more regular sleep patterns had a lower risk of central obesity compared to those with severely irregular sleep patterns. Compared to the lowest SRI quartile (Q1), the odds ratios (OR) for Q3 and Q4 were 0.56(95%CI: 0.32-0.99) and 0.51 (95%CI: 0.29-0.90), respectively. Subgroup analyses showed that in male participants and those aged 50 and above, the risk of central obesity decreased with more regular sleep patterns. In males, compared to Q1, the OR for Q3 was 0.41 (95%CI: 0.19-0.91) and for Q4 was 0.37 (95%CI: 0.16-0.86). In the population aged ≥50, the OR for Q3 was 0.41(95%CI: 0.19-0.89) and for Q4 was 0.31 (95%CI: 0.14-0.71). Sensitivity analyses yielded consistent results.

There is a certain association between sleep regularity, as assessed by the SRI and central obesity. Higher SRI scores are associated with a lower risk of developing central obesity, particularly in males and individuals aged 50 and above.

To verify the reliability and validity of the Simplified Coping Style Questionnaire (SCSQ) among firefighters in the Aba Tibetan and Qiang Autonomous Prefecture (referred to as “Aba Prefecture”) of Sichuan Province, and to make necessary revisions.

A total of 726 active firefighters from various fire brigades in Aba Prefecture were surveyed, and their demographic data were collected. The reliability and validity of the SCSQ was evaluated. The sample was randomly split into two halves, and both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to explore the scale structure of this study and compare it with the original scale structure. The reliability was tested using Cronbach α coefficient and Spearman-Brown coefficient.

EFA extracted two common factors with 19 items, accounting for a cumulative variance contribution rate of 56.53%, with factor loadings ranging from 0.523 to 0.827. CFA results indicated that the structural validity of the revised SCSQ was satisfactory. The total Cronbach α coefficient for the revised scale was 0.884, while the Cronbach α coefficients for the two dimensions were 0.927 and 0.860, respectively, with odd-even split reliability coefficients of 0.905 and 0.820.

The revised Simplified Coping Style Questionnaire demonstrates good reliability and validity, making it an effective tool for assessing the coping style tendencies of firefighters in the Aba Tibetan and Qiang Autonomous Prefecture of Sichuan Province.

To investigate the chain mediating effects of sedentary behavior and smoking on the relationship between screen exposure and visceral fat index in adult men.

Data were collected from the 2020 Chronic Disease Risk Factor Survey in Guizhou Province, focusing on male participants. A health behavior questionnaire was employed to gather information on electronic screen exposure time, sedentary behavior, and smoking quantity. Laboratory indicators were used to assess blood lipid levels, while physical measurements provided data on height, weight, and waist circumference. A correlation coefficient matrix was constructed to analyze the relationships among variables, and a multiple mediation model was developed to explore the mediating pathways of sedentary time and smoking in the relationship between screen exposure and visceral fat index. The PROCESS plugin in SPSS was used to test the chain mediation effects via the bootstrap method, and the mediation pathways were illustrated using Amos.

A total of 1 174 subjects were included in the study. After controlling for age, urban/rural status, education level, marital status, and occupation, regression results indicated a significant direct effect of screen exposure on the visceral fat index in men (β=0.232, 95%CI: 0.915-0.270). Sedentary time (β=0.046, 95%CI: 0.038-0.055) and smoking quantity(β=0.031, 95%CI: 0.004-0.059) were also found to significantly influence the visceral fat index. The mediation analysis revealed that the simple mediating effects of sedentary time and smoking between screen exposure and the visceral fat index were 0.018(95%CI: 0.020-0.033) and 0.056 (95%CI: 0.042-0.072), respectively, while the chain mediation effect was 0.009 (95%CI:0.003-0.014).

Sedentary behavior and smoking exhibit mediating effects in the relationship between screen exposure and visceral fat index in men. As screen exposure is a prevalent lifestyle factor, it is crucial for men to reduce smoking and sedentary behaviors during screen time to mitigate the occurrence of visceral obesity.

To provide a new perspective for exploring the influencing factors of depression symptoms in individuals aged 45 and older in China, helping reveal the complex relationships among potential influencing factors.

Using data from the China Health and Retirement Longitudinal Study (CHARLS) 2018, independent variables were determined based on the five dimensions of the health ecological model. A total of 8 485 individuals aged 45 and older were included. The LASSO algorithm was employed for variable selection, and the Apriorism algorithm from association rules was utilized to mine the causal association rules of depression symptoms among the elderly in China from multiple dimensions.

The detection rate of depression symptoms among middle-aged and elderly individuals in China was 38.42%. The variables selected by LASSO regression included gender from the personal traits layer, self-rated health, life satisfaction, disability, number of chronic diseases, visual impairment, hearing impairment, and nighttime sleep duration from the behavioral traits layer, as well as household registration type and education level from the living and working conditions layer. The Apriorism algorithm identified 21 strong association rules, with the highest support of 20.71%, maximum confidence of 68.40%, and the highest lift of 1.78. Key association factors for depression symptoms among the elderly included living in rural areas, having two or more chronic diseases, nighttime sleep duration of less than 6 hours, being female, having a disability, poor self-rated health, and being relatively satisfied with life, with primary school education. Compared to those with excessive nighttime sleep duration, individuals with insufficient nighttime sleep duration exhibited a higher risk of depression symptoms. The factor of rural residence was highly correlated with nighttime sleep duration of less than 6 hours and having two or more chronic diseases.

This study suggests considering depression issues from three dimensions: personal traits, behavioral traits, and living and working conditions, emphasizing the need to pay special attention to rural populations and patients with comorbid chronic diseases during depression symptom screening.

To analyze relevant data on the burden of appendicitis among individuals aged 70 and above in China from 1990 to 2019, describe its current status and epidemiological trends, and provide scientific evidence for exploring prevention and treatment strategies for appendicitis in the elderly population in China.

Utilizing the 2019 Global Burden of Disease data, this study analyzed the incidence, mortality, and disability-adjusted life years (DALY) of appendicitis in individuals aged 70 and above in China from 1990 to 2019. The Join point regression model was used to calculate the average annual percentage change (AAPC).

From 1990 to 2019, the incidence of appendicitis among individuals aged 70 and above in China exhibited a year-on-year increasing trend, with the most significant rise occurring between 2000 and 2005. In contrast, both the mortality rate and DALY rate showed a declining trend during the same period, with a substantial decrease starting in 2004. However, the decline rate has slowed down since 2008. Among different gender and age group compositions, the highest incidence was observed in the 70-74 age group, with a higher incidence in females compared to males. Conversely, the highest mortality and DALY rates were found in the 85-89 age group, with both rates being higher in males than in females.

Since 1990, the burden of mortality and DALY due to appendicitis among individuals aged 70 and above in China has gradually decreased, yet the incidence remains at a relatively high level. Therefore, it is essential for China to adopt various prevention and treatment strategies for the elderly population to reduce the disease burden of appendicitis in those aged 70 and above.

To introduce the application of the time series generalized regression neural network (GRNN) model in predicting the incidence of viral hepatitis in China and to evaluate its fitting and predictive accuracy.

Monthly incidence data of viral hepatitis from 2004 to 2019 were collected to construct time series. Data from January 2004 to June 2019 were used as training data, while data from July to December 2019 served as testing data. Both GRNN and SARIMA models were established to predict the incidence from July to December 2019, and the predictions were compared with the testing data. The mean absolute percentage error (MAPE) was employed to assess the model’s fitting and predictive performance.

The fitting MAPE for the GRNN model across various types of hepatitis ranged from 1.67% to 21.22%, while the predictive MAPE ranged from 2.26% to 17.17%. In comparison, the SARIMA model’s fitting MAPE for various types of hepatitis ranged from 3.84% to 7.87%, with a predictive MAPE ranging from 2.54% to 48.89%. Notably, the predictive MAPE for hepatitis A was 48.89%, indicating a significant prediction error.

The GRNN model outperformed the SARIMA model in predicting the monthly incidence of viral hepatitis in China, suggesting its suitability for broader application.

To investigate the correlation between the comorbidity of chronic diseases and concurrent depression symptoms with increased disability risk among older adults in China.

Utilizing data from the 2020 China Health and Retirement Longitudinal Study (CHARLS), we analyzed health-related data, including basic information, chronic diseases, depression symptoms, and disability among individuals aged 60 and above. A chi-square test χ² was employed for preliminary analysis of the association between various factors and disability risk, followed by calibration of a binary logistic regression model. The odds ratios (OR) were estimated to reflect the increased disability risk of respondents with comorbidity and depression symptoms compared to other respondents.

A total of 8 762 respondents were included, with a balanced gender distribution and an average age of 68.10 years. Among the respondents, 41.35% exhibited depression symptoms, and 15.10% had comorbid conditions, with a comorbidity and depression symptom co-occurrence rate of 8.38%. The results indicated that respondents with comorbidity and depression symptoms had a 550% (OR=6.50, 95%CI: 4.98-8.47) increased risk of impairment in Basic Activities of Daily Living (BADL) and a 389% (OR=4.89, 95%CI: 4.07-5.87) increased risk of impairment in Instrumental Activities of Daily Living (IADL), along with a significant increase in the risk of impairment in Activities of Daily Living(ADL) (OR=4.98, 95%CI: 4.16-5.96).

There is a significant correlation between the comorbidity of chronic diseases and concurrent depression symptoms with increased disability risk among older adults in China. This poses a serious threat to the health and quality of life of the elderly, highlighting the need for early screening and intervention, as well as enhanced health education and psychological support to effectively reduce disability risk.