Objective:To develop a scale for assessing science popularization competency in traditional Chinese medicine (TCM) and to evaluate its reliability and validity.Methods:Based on Lasswell's "5W" communication theory, the scale was constructed through literature review, expert consultation, and a pilot survey. Using convenient sampling, 450 TCM-related professionals were selected from two ClassⅢ Grade ATCM hospitals and their affiliated medical alliance community health institutions in Hunan Province. A total of 450 questionnaires were distributed and 446 valid responses were collected (valid response rate: 99.11%). Of these, 222 questionnaires were used for item analysis, reliability testing, and exploratory factor analysis (EFA) ; the remaining 224 were used for confirmatory factor analysis (CFA) .Results:The final TCM Science Popularization Competency Scale comprised 26 items under 6 dimensions: namely popular science cognition; science content creation ability; communication ability; professional values and personality traits; quality of science communication products; evaluation and feedback of communication effectiveness. EFA extracted six common factors, explaining 86.85% of total variance, with all item factor loadings > 0.500. The overall Cronbach's α coefficient for the scale was 0.972, with subscale values all > 0.800. Split-half reliability was 0.948. CFA showed good model fit across indices, indicating high reliability and validity.Conclusions:The TCM Science Popularization Competency Scale demonstrates good psychometric properties and can be used to assess the science popularization competency of TCM professionals. It offers a scientific tool to support the dissemination of TCM knowledge and contribute to the goals of the Healthy China initiative.

AIM: To screen and analyze the influencing factors of myopia among primary and secondary school students and establish a predictive model to provide ideas for the prevention and control measures of myopia among children and adolescents.METHODS:A total of 1 759 primary and secondary school students from 2 primary schools, 2 junior high schools, 2 senior high schools and 1 vocational high school in the urban area of Qingdao were sampled by means of stratified cluster sampling in September 2023. Vision screening and a questionnaire survey on influencing factors were carried out based on machine learning algorithms. The screening and determination were mainly conducted in accordance with the Standard Logarithmic Visual Acuity Chart(GB/T11533-2011)and the Specifications for Screening Myopia in Children and Adolescents. The influencing factors of myopia were analyzed and a prediction model was developed based on the machine learning algorithms LASSO in combination with XGBoost, and visualization was achieved through an interactive Nomogram. Statistical analysis was performed using R statistical software version 4.3.3.RESULTS:The screening prevalence of myopia among primary and secondary school students in the urban area of Qingdao was 70.61%(1 242 cases). The optimal predictive variables for screening were grade, gender, whether parents were myopic, daily indoor sedentary time, appropriate distance between eyes and books during reading and writing, daily sleep time, distance between eyes and TV screen when watching TV/playing video games exceeding 3 meters, the playground during breaks, total duration of tutorial classes, how often eyes are rested during near work, daily computer usage time, and average daily homework time after school, totaling 12 influencing factors. The AUCs of the training set and test set were 0.770(95%CI:0.751-0.789)and 0.732(95%CI:0.714-0.750), respectively.CONCLUSION: A machine learning-based prediction model was developed and validated to predict the risk of myopia onset in primary and secondary school students, accompanied by effective visualization techniques.

Objective:To develop a scale for assessing science popularization competency in traditional Chinese medicine (TCM) and to evaluate its reliability and validity.Methods:Based on Lasswell's "5W" communication theory, the scale was constructed through literature review, expert consultation, and a pilot survey. Using convenient sampling, 450 TCM-related professionals were selected from two ClassⅢ Grade ATCM hospitals and their affiliated medical alliance community health institutions in Hunan Province. A total of 450 questionnaires were distributed and 446 valid responses were collected (valid response rate: 99.11%). Of these, 222 questionnaires were used for item analysis, reliability testing, and exploratory factor analysis (EFA) ; the remaining 224 were used for confirmatory factor analysis (CFA) .Results:The final TCM Science Popularization Competency Scale comprised 26 items under 6 dimensions: namely popular science cognition; science content creation ability; communication ability; professional values and personality traits; quality of science communication products; evaluation and feedback of communication effectiveness. EFA extracted six common factors, explaining 86.85% of total variance, with all item factor loadings > 0.500. The overall Cronbach's α coefficient for the scale was 0.972, with subscale values all > 0.800. Split-half reliability was 0.948. CFA showed good model fit across indices, indicating high reliability and validity.Conclusions:The TCM Science Popularization Competency Scale demonstrates good psychometric properties and can be used to assess the science popularization competency of TCM professionals. It offers a scientific tool to support the dissemination of TCM knowledge and contribute to the goals of the Healthy China initiative.