RÉSUMÉ
Objective To identify the eye movement characteristics that can distinguish reading interest and comprehensibilityin order to provide reference for prediction of reading interest and comprehensibility based on eye movement.Methods Tobii Glasses 3 was used to collect eye tracking data from 11 participants who read 12 texts on different topics.After reading all the texts,the participants marked each sentence with theirlevels of interest and comprehensibility.Then,Python R and excel software were used to preprocess and analyze the data,and the differences in eye movementamid the four combinations of reading interest(interested or not)and comprehensibility(levels of difficulty)were studiedat overall and individual levels.Results At the overall level,there were statistically significant differences in eye movement between the easy comprehension group and the difficult comprehensiongroup where interest was concerned,but there was little difference between the interested group and the disinterested groupwhen it came to comprehensibility.There were differences in eye movement behavior between individuals,and some of the statistically significant differences in eye movement were consistent across most of the participants.In addition,some of the eye movement characteristicswere oppositeacross different individuals or could not distinguish between the interested and disinterested at the overall level,but could be distinguished within individuals.Conclusion At the overall level,it is relatively easy to determine comprehensibility through eye movement,but it is more difficult to distinguish whether the participant is interested in the sentence or not,especially when the text is easily comprehensible.At the individual level,eye movement behavior varies widely between individuals,and individuals manifest different characteristics in distinguishing reading interest and comprehensibility.
RÉSUMÉ
Objective:To investigate the common disease spectrum of grass-root troops, to provide a basis for meeting the needs for military medical support among officers and soldiers, and to improve targeted training of military general practitioners in grass-root troops.Methods:With reference to International Classification of Diseases (9th edition), a questionnaire survey was conducted to investigate 146 types of diseases among the military doctors in grass-root troops. SPSS 23.0 was used to determine the score of the common degree of each disease, and the mean score of each disease was ranked. At the same time, the Kendell consistency test was used to compare the scores of doctors between different altitudes and troops.Results:Most grass-root military doctors were male graduates aged 20-39 years, among whom 109 (51.90%) did not receive continuing education, and there were 140 doctors (66.67%) belonging to the health company, 11 (5.24%) belonging to the health platoon, 35 (16.67%) belonging to the health clinic, and 24 (11.42%) belonging to the health team. As for the location of the troops, there were 42 doctors (20.00%) in the temperate zone, 56 (26.67%) in the subtropical zone, 57 (27.14%) in the alpine region, 37 (17.62%) in the plains, and 18 (8.57%) on the islands. There were 173 patients with an age of 20-29 years, accounting for 82.38%. The Kendell consistency test showed Kendell's W=0.968 ( χ 2=711.51, P<0.001), suggesting a consistent evaluation of 146 diseases by grass-roots doctors from different altitudes. Conclusion:With reference to the investigation of disease spectrum, it is necessary to formulate characteristic training objectives and contents for the training of military general practitioners, explore the training models and methods for military general practitioners in grass-root troops, promote the construction of military general practitioners during the new military reform, and improve the post competency of military doctors.
RÉSUMÉ
Objective:To construct a practical education training quality evaluation system that can monitor the entire training process for the master of public health, and to provide a basis for improving the public health education system.Methods:Based on the survey of the current status of the master of public health, combined with the literature survey, the focus group discussion and the expert forum, an evaluation system was established, and the weight coefficient of each index was determined by the analytic hierarchy process (AHP). All data were entered by Excel double-person, and matlabR2018a was used to calculate the weight, and determine the maximum characteristic root of the matrix, consistency index and consistency ratio.Results:The evaluation index system consisted of 7 first-level indicators and 24 second-level indicators. The average authority coefficient of 32 experts was 0.791. The top three items with the highest weight in the first-level indicators were mentor guidance (0.213), professional practice (0.157) and scientific research topics (0.149). The weight coefficient consistency ratio ( CR) was 0.040, showing that the consistency test passed ( CR<0.1). Conclusion:The educational quality evaluation system of the master of public health constructed by the institute is scientific, and the weight of the evaluation index reflects the focus of the postgraduate training process of the master of public health, which can provide a reference for improving the quality of public health professionals.
RÉSUMÉ
To discuss the latent variable growth curve model of longitudinal data and give its implementation method in Mplus.The application of Mplus software has been used to deal with the longitudinal data of mental health status of college students in an university.Results show that the model can process the longitudinal data with latent variables,which can compare the differences of the overall development trend and individual development,also taking a covariate into the model to improve the effect of model fitting.Using Mplus software to process the longitudinal data with latent variables,the program is simple and easy to operate.This study provides the latent variable growth curve model of longitudinal data and its procedure of implementation in Mplus,and the statistical methodology guidance and reference for practical applications of epidemiological cohort study.
RÉSUMÉ
To discuss the latent variable growth curve model of longitudinal data and give its implementation method in Mplus.The application of Mplus software has been used to deal with the longitudinal data of mental health status of college students in an university.Results show that the model can process the longitudinal data with latent variables,which can compare the differences of the overall development trend and individual development,also taking a covariate into the model to improve the effect of model fitting.Using Mplus software to process the longitudinal data with latent variables,the program is simple and easy to operate.This study provides the latent variable growth curve model of longitudinal data and its procedure of implementation in Mplus,and the statistical methodology guidance and reference for practical applications of epidemiological cohort study.