Mental Health and Work: Impact, Issues and Good Practices

[From Introduction] There is growing evidence of the global impact of mental illness. Mental health problems are among the most important contributors to the burden of disease and disability worldwide. Five of the 10 leading causes of disability worldwide are mental health problems. They are as relevant in low-income countries as they are in rich ones, cutting across age, gender and social strata. Furthermore, all predictions indicate that the future will see a dramatic increase in mental health problems

Mining health knowledge graph for health risk prediction

Nowadays classification models have been widely adopted in healthcare, aiming at supporting practitioners for disease diagnosis and human error reduction. The challenge is utilising effective methods to mine real-world data in the medical domain, as many different models have been proposed with varying results. A large number of researchers focus on the diversity problem of real-time data sets in classification models. Some previous works developed methods comprising of homogeneous graphs for knowledge representation and then knowledge discovery. However, such approaches are weak in discovering different relationships among elements. In this paper, we propose an innovative classification model for knowledge discovery from patients’ personal health repositories. The model discovers medical domain knowledge from the massive data in the National Health and Nutrition Examination Survey (NHANES). The knowledge is conceptualised in a heterogeneous knowledge graph. On the basis of the model, an innovative method is developed to help uncover potential diseases suffered by people and, furthermore, to classify patients’ health risk. The proposed model is evaluated by comparison to a baseline model also built on the NHANES data set in an empirical experiment. The performance of proposed model is promising. The paper makes significant contributions to the advancement of knowledge in data mining with an innovative classification model specifically crafted for domain-based data. In addition, by accessing the patterns of various observations, the research contributes to the work of practitioners by providing a multifaceted understanding of individual and public health

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Difference Knowledge Aftergiven Health Education About Rubing Dental with Video Modeling

Background: Knowledge is the result of considering a case, including recall events that never happened either intentionally or unintentionally. Lack of knowledge about brushing teeth is very influential in personal hygiene as brushing teeth include routines that must be done every day. Results of a preliminary study that researchers do in SDS Kartini in 2013, showed that after the interview about the importance of brushing your teeth, 3 out of 10 children can answer questions correctly and 7 children can not answer the question correctly. It can be concluded that there is still a lack of knowledge of the students at SDS Kartini. In improving the knowledge to do with one of the health education video modeling. This study want to analyze different knowledge between before and after giving health education. Methods: This study used a pre-experimental research design with the approach of one group pretest-posttest design. The population in this study were children aged 6-12 years in SDS Kartini. The sampling technique in this research is simple random sampling with a sample size of 32 people. Data collection is done at the time before and after health education using a questionnaire of 25 questions. Analysis of statistical data used is dependent t test. Results: The results obtained from this study is the knowledge before intervention (pretest) is 50.84 and knowledge after intervention (posttest) is 89.22 with p value (sig) of 0.000. Conclusion: Based on the results, there are significant differences in the level of knowledge before and after being given health education

Towards a possibility-theoretic approach to uncertainty in medical data interpretation for text generation

Many real-world applications that reason about events obtained from raw data must deal with the problem of temporal uncertainty, which arises due to error or inaccuracy in data. Uncertainty also compromises reasoning where relationships between events need to be inferred. This paper discusses an approach to dealing with uncertainty in temporal and causal relations using Possibility Theory, focusing on a family of medical decision support systems that aim to generate textual summaries from raw patient data in a Neonatal Intensive Care Unit. We describe a framework to capture temporal uncertainty and to express it in generated texts by mean of linguistic modifiers. These modifiers have been chosen based on a human experiment testing the association between subjective certainty about a proposition and the participants’ way of verbalising it.peer-reviewe

Effect of Health Education on Knowledge and Attitudes of Pregnant Women at Kalijaga Community Health Center, Cirebon, West Java

Background: Health education is all activities that enhance knowledge, attitude, good practice of individuals, groups or communities, in maintaining and improving their own health. Health education may be more effective in improving knowledge and attitude of pregnant women if delivered with suitable media. This study aimed to analyze the effects of health education with media assistance to knowledge and attitudes about health in pregnant women. Subjects and Method: This study was a randomized controlled trial carried out at Kalijaga community health center, Cirebon City, West Java. A sample of 30 pregnant women was divided into 3 groups by randomization: (1) 10 pregnant women who received health education about pregnancy using flipchart, (2) 10 pregnant women who received health education about pregnancy using multimedia, and (3) 10 pregnant women who received health education about pregnancy using music box. Data were collected by questionnaire and analyzed by Kruskal-Wallis to test the differences between the three groups, followed by the Mann Whitney to test group pairs. Results: The knowledge scores in the multimedia group and the music box group were higher than the flipchart group, with p= 0.001. Attitude score on the multimedia group and music box group was higher than flipchart group, with p= 0.023. The score of knowledge in the multimedia group was about equal to the music box group, with p= 0.342. Attitude score on the multimedia group was about equal to the music box group, with p= 0.517. Conclusion: Health education using multimedia or music box is more effective than a flipchart to improve knowledge and attitudes about the health of pregnant women. Health education using multimedia or music box shows comparable effectiveness. Keywords: health education, knowledge, attitude, multimedia, music box, flipchart, pregnant wome

Evaluating health visitors’ existing knowledge of Down syndrome and the effect of a training workshop

© 2018 The Authors. Journal of Policy and Practice in Intellectual Disabilities published by International Association for the Scientific Study of Intellectual and Developmental Disabilities and Wiley Periodicals, Inc.Children with Down syndrome are at an increased risk of health and development issues in early childhood, therefore monitoring their development and identifying health conditions as early as possible is critical. Health professionals may not always have the training and knowledge to effectively support families of children with disabilities, including Down syndrome. In the UK, health visitors conduct health and development reviews for children under 5 years, therefore they have a key role to play in monitoring and identifying health issues in young children with Down syndrome. However there has been no research on health visitors' knowledge and training needs regarding Down syndrome. This study aimed to assess health visitors' existing knowledge of Down syndrome and evaluate a pilot Down syndrome training session for health visitors. Twenty-six health visitors from two NHS Trusts in England participated in 1 of 5 group training workshops. Pretraining and posttraining questionnaires assessed knowledge about Down syndrome, and feedback on the training session. Knowledge about Down syndrome was low prior to the training and increased significantly following the training session. Health visitors rated the training workshop very highly and would recommend it to a colleague. Health visitors identified a need for training to enable them to increase their knowledge about Down syndrome and better support families. In summary, a pilot training session about Down syndrome received positive feedback from health visitors, and led to improvements in knowledge and understanding about Down syndrome. This has the potential to improve health outcomes for children with Down syndrome.Peer reviewe