Comparison of Machine Learning Algorithms in the Prediction of Hospitalized Patients with Schizophrenia.

New computational methods have emerged through science and technology to support the diagnosis of mental health disorders. Predictive models developed from machine learning algorithms can identify disorders such as schizophrenia and support clinical decision making. This research aims to compare the performance of machine learning algorithms: Decision Tree, AdaBoost, Random Forest, Naïve Bayes, Support Vector Machine, and k-Nearest Neighbor in the prediction of hospitalized patients with schizophrenia. The data set used in the study contains a total of 11,884 electronic admission records corresponding to 6933 patients with various mental health disorders; these records belong to the acute units of 11 public hospitals in a region of Spain. Of the total, 5968 records correspond to patients diagnosed with schizophrenia (3002 patients) and 5916 records correspond to patients with other mental health disorders (3931 patients). The results recommend Random Forest with the best accuracy of 72.7%. Furthermore, this algorithm presents 79.6%, 72.8%, 72.7%, and 72.7% for AUC, precision, F1-Score, and recall, respectively. The results obtained suggest that the use of machine learning algorithms can classify hospitalized patients with schizophrenia in this population and help in the hospital management of this type of disorder, to reduce the costs associated with hospitalization.

Usability Analysis of a System for Cognitive Rehabilitation, "Gradior", in a Spanish Region.

Objective: The main aim of our research is to assess the use, satisfaction, and pedagogy of software for neuropsychological rehabilitation by computer, called "Gradior™," to obtain relevant information on the impact of information and communications technology on people with severe and prolonged mental illness. Methods: To evaluate the usability and satisfaction standards, the questionnaire "Usability survey on the use of the cognitive rehabilitation and assessment program by computer" was completed by 83 patients of the Rodríguez Chamorro Hospital. Results: The results of the study show that Gradior has 81.2% acceptance and 83.7% general assessment. This indicates that those who responded to the survey consider that the Gradior program improves cognitive functions and abilities in patients with severe and prolonged mental illness and therefore their quality of life. Conclusion: This research is oriented toward professionals of the Health Area and Systems Engineers, who develop software for neuropsychological rehabilitation with neurocognitive deficit. The purpose is to make the learning process more effective among the people who use it and to improve usability for specific groups. We hope that the reading of the work contributes to the activities, techniques and materials planned are in accordance with the needs of the population affected with cognitive disorders.

Social Robots for People with Aging and Dementia: A Systematic Review of Literature.

Background: Social robots are currently a form of assistive technology for the elderly, healthy, or with cognitive impairment, helping to maintain their independence and improve their well-being. Objective: The main aim of this article is to present a review of the existing research in the literature, referring to the use of social robots for people with dementia and/or aging. Methods: Academic databases that were used to perform the searches are IEEE Xplore, PubMed, Science Direct, and Google Scholar, taking into account as date of publication the last 10 years, from 2007 to the present. Several search criteria were established such as "robot" AND "dementia," "robot" AND "cognitive impairment," "robot" AND "social" AND "aging," and so on., selecting the articles of greatest interest regarding the use of social robots in elderly people with or without dementia. Results: This search found a total of 96 articles on social robots in healthy people and with dementia, of which 38 have been identified as relevant work. Many of the articles show the acceptance of older people toward social robots. Conclusion: From the review of the research articles analyzed, it can be said that use of social robots in elderly people without cognitive impairment and with dementia, help in a positive way to work independently in basic activities and mobility, provide security, and reduce stress.

Analysis of Mental Health Disease Trends Using BeGraph Software in Spanish Health Care Centers: Case Study.

BACKGROUND: In the era of big data, networks are becoming a popular factor in the field of data analysis. Networks are part of the main structure of BeGraph software, which is a 3D visualization application dedicated to the analysis of complex networks. OBJECTIVE: The main objective of this research was to visually analyze tendencies of mental health diseases in a region of Spain, using the BeGraph software, in order to make the most appropriate health-related decisions in each case. METHODS: For the study, a database was used with 13,531 records of patients with mental health disorders in three acute medical units from different health care complexes in a region of Spain. For the analysis, BeGraph software was applied. It is a web-based 3D visualization tool that allows the exploration and analysis of data through complex networks. RESULTS: The results obtained with the BeGraph software allowed us to determine the main disease in each of the health care complexes evaluated. We noted 6.50% (463/7118) of admissions involving unspecified paranoid schizophrenia at the University Clinic of Valladolid, 9.62% (397/4128) of admissions involving chronic paranoid schizophrenia with acute exacerbation at the Zamora Hospital, and 8.84% (202/2285) of admissions involving dysthymic disorder at the Rio Hortega Hospital in Valladolid. CONCLUSIONS: The data analysis allowed us to focus on the main diseases detected in the health care complexes evaluated in order to analyze the behavior of disorders and help in diagnosis and treatment.

Health Care Management Models for the Evolution of Hospitalization in Acute Inpatient Psychiatry Units: Comparative Quantitative Study.

BACKGROUND: Mental health disorders are a problem that affects patients, their families, and the professionals who treat them. Hospital admissions play an important role in caring for people with these diseases due to their effect on quality of life and the high associated costs. In Spain, at the Healthcare Complex of Zamora, a new disease management model is being implemented, consisting of not admitting patients with mental diseases to the hospital. Instead, they are supervised in sheltered apartments or centers for patients with these types of disorders. OBJECTIVE: The main goal of this research is to evaluate the evolution of hospital days of stay of patients with mental disorders in different hospitals in a region of Spain, to analyze the impact of the new hospital management model. METHODS: For the development of this study, a database of patients with mental disorders was used, taking into account the acute inpatient psychiatry unit of 11 hospitals in a region of Spain. SPSS Statistics for Windows, version 23.0 (IBM Corp), was used to calculate statistical values related to hospital days of stay of patients. The data included are from the periods of 2005-2011 and 2012-2015. RESULTS: After analyzing the results, regarding the days of stay in the different health care complexes for the period between 2005 and 2015, we observed that since 2012 at the Healthcare Complex of Zamora, the total number of days of stay were reduced by 64.69%. This trend is due to the implementation of a new hospital management model in this health complex. CONCLUSIONS: With the application of a new hospital management model at the Healthcare Complex of Zamora, the number of days of stay of patients with mental diseases as well as the associated hospital costs were considerably reduced.

Usability evaluation of the eHealth Long Lasting Memories program in Spanish elderly people.

In recent years, there has been a great development of software technology in the field of psychogeriatric research, helping to improve the quality of life of the elderly and preventing cognitive deterioration associated with aging, and thus decrease the possible dependence. The main objective of the present study is to evaluate the usability of the Long Lasting Memories program in elderly people with or without cognitive impairment in a region of Spain. For the study, users were classified into three groups: subjects with no cognitive impairment, with mild cognitive impairment and mild dementia, and they were given a usability questionnaire covering different variables. Of the 157 Spanish participants in the study, 84.1 percent answered the usability questionnaire, obtaining wide acceptance in all study groups regarding the usability of the Long Lasting Memories program. Current research begins to mark a new perspective that recognizes the need to establish a preventive strategy for degenerative diseases.