Lovro Tacol: Interactions among physical development, motor skills and executive functions in children
TSJ Dashboard enables interactive and real-time analysis of the users’ questions and counsellors’ answers in the online counselling service This is me, which is maintained by the National Institute of public health RS. Also, the data from Google Analytics can be analyzed in TSJ Dashboard. The tool is designed as a web application. This means that it can be used on any computer with a web browser and internet access. TSJ Dashboard offers different kinds of data analysis and visualizations. Partial analysis (aggregated data, tables) can be exported in .csv format (can be easily opened with MS Excel). Also, all microdata can be exported for further statistical analysis.
The scientific monography is based on the survey done in the Spring of 2012. The main research question relates to the needs of the integration of sex education in Slovenian high schools education programs, the knowledge of sexually transmitted diseases and contraception among students. The results are comparable with the previous studies. They indicate the need to include the contents related to sexuality in the educational process. The results also show a low level of knowledge of sexually transmitted diseases among students and highlight the importance of the public media in the imparting the contents related to sexuality.
The 100 pages long automatic generated report outlines the basic descriptive statistics related to the operation of the This is me online counselling service in a given period. The current structure of the document was designed in cooperation with the This is me editorial office. The hottest topics and statistics in which they want to have a better insight were selected. However, there are still possibilities of adding any supplements at any time. The computer program used to generate the automatic generated report is written in Sweave, which combines the programming language for statistical analysis, namely R, and Latex, the document mark-up language. The input is the entire forum database, and the output is the document in PDF format.
The evaluation of the web counselling service This is me combines: (i) the analysis of data collected with Google Analytics; (ii) the analysis of the adolescents’ questions and counsellors’ answers; (iii) the analysis of the web survey data; and (iv) the analysis of qualitative interviews among the users of the web counselling service. Analyses have shown that most users who have posted at least one question in the web counselling service are females aged 15 to 17 years old. Most questions are related to relationships, sexuality and sexual health, physical health and mental health. The users recognized the service as a precious and easily accessible communication channel with the professionals from the fields of mental and physical health. The web counselling service was ranked among the most highly rated web sites in its category, according to the ACSI.
The project aimed to identify cancer-related messages in the online healthcare community MedOverNet among approx. 3 million messages posted between 2015 and 2019. Different machine learning algorithms (naive Bayes classification, support vector machine, decision trees and random forests) were used on lematized text with removed stop-words. The most efficient was the random forest model with 92% sensitivity and 89% specificity. Around 0.6% messages were about cancer – 2.9% within health consulting discussions, 1.9% within social support discussions and 0.5% within socializing discussions. The identified messages were considered in the sampling procedure to analyze the quality of cancer-related information in the online healthcare community MedOverNet.
All questions posted between 2001 and 2021 in the Web counselling service were analyzed. The characteristics of the questions (e.g., age, gender and content of questions) have been determined by hand since 2012. These were used to determine the content of the remaining questions posted before 2012 (supervised machine learning algorithms were used). Overall, the physical, mental, and sexual health questions are equally represented. However, the number of questions about physical health decreased in the later years while the number of questions about mental health remained unchanged. According to gender: questions about drugs, addiction and sexuality, are more common among boys, while questions about mental health, relationships and body are more commonly asked by girls.
The package provides functions to compute the values of different modifications of the Rand and Wallace indices. The indices are used to measure the stability or similarity of two partitions obtained on two different sets of units with a non-empty intercept. Splitting and merging of clusters can (depends on the selected index) have a different effect on the value of the indices.
The package provides functions for multivariate analysis (e.g., factor analysis and discriminant analysis). It is primarily written for the course Multivariate analysis and for the course Computer intensive methods at the master's program of Applied Statistics at the University of Ljubljana.