Measures for the assessment of stressful life events in the Spanish adult population: A systematic review

Objetivo: Este estudio pretende identificar y analizar los instrumentos de evaluación de los eventos vitales estresantes creados/adaptados para su uso con población española adulta, publicados en la literatura nacional e internacional, con especial atención en sus propiedades psicométricas y en su asociación con medidas de problemas de salud. Métodos: Se llevó a cabo una revisión sistemática de la literatura de todos los instrumentos publicados a través de los buscadores MEDLINE; ProQuest Health y Medical Complete ProQuest Psychology Journals PsycARTICLES PsycINFO Psicodoc OpenSIGLE desde la fecha de inicio hasta el 31 de enero de 2016. Dos investigadores independientes evaluaron la elegibilidad de todos los artículos, extrajeron los datos y evaluaron sus propiedades psicométricas. Resultados: Se seleccionaron 12 instrumentos que cumplían los criterios de inclusión en el estudio. Las medidas presentaron una gran heterogeneidad. La mayoría no incluían información sobre sus propiedades psicométricas o necesitaban aportar más datos, ya que eran pocas los que evaluaban su estabilidad test-retest y/o su estructura interna. Los cuestionarios creados o adaptados por González de Rivera y Morena (1983), Sandín y Chorot (1987), Fernández y Mielgo (1992), Gracia y Herrero (2004) y Motrico et al. (2013) mostraron asociaciones significativas con variables de problemas de salud. Discusión: Se requieren más estudios sobre la asociación de los instrumentos con variables de problemas de salud mental y física, lo que facilitaría su aplicación clínica. Estos resultados tienen una gran utilidad a la hora de seleccionar un instrumento de evaluación de eventos vitales estresantes en el ámbito clínico y de investigación en España

Redes neuronales y algoritmos genéticos en la docencia en las escuelas de ingenieros: Un problema práctico de diseño de pantallas acústicas

[EN] In this paper we develop a technique based on neural networks and genetic algorithms for constructing a mathematical tool for the design of adapted acoustic screens. In order to do this, we use the information of a company specialized in the construction of these devices. Actually, we solve the following problem: if we want to attenuate the noise in a certain point, which is the best screen for doing it?[ES] En este trabajo desarrollamos una técnica basada en redes neuronales y algoritmos genéticos para construir un instrumento matemático para el diseño de pantallas acústicas adaptadas. Para hacer esto, usamos la información de una empresa especializada en la construcción de estos dispositivos. En realidad, solucionamos el problema siguiente: si se quiere atenuar el ruido en un cierto punto, ¿cuál es la mejor pantalla para hacerlo?Capdevila, JF.; Ruiz, JM.; Salinas, JL.; Sánchez Pérez, EA. (2010). Redes neuronales y algoritmos genéticos en la docencia en las escuelas de ingenieros: Un problema práctico de diseño de pantallas acústicas. Modelling in Science Education and Learning. 3:17-27. doi:10.4995/msel.2010.3107SWORD17273Barro, Senén y Mira, José. Computación Neuronal. Ed. Servicio de Publicaciones e Intercambio Científico (Campus Universitario Sur), Univ. de Compostela, 1995Isasi Vi-uela, Pedro y Galván León, Inés M. Redes de neuronas artificiales: un enfoque práctico. Ed. Pearson Prentice Hall, 2004Russell, Stuart y Norvig, Peter. Inteligencia artificial: Un enfoque moderno. Ed. Pearson Prentice Hall, 200

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning

Background: Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. Methods: We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. Results: The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). Conclusions: This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice

Gender differences in psychological well-being and health problems among European health professionals : analysis of psychological basic needs and job satisfaction

Background: The aim was to examine the mediating role of basic psychological needs and job satisfaction in the relationship between the gender effect on health problems and psychological well-being for health professionals in Europe in 2015. Methods: Two multiple partial mediation analyses were conducted in order to test the partial mediation of both basic needs and job satisfaction, with gender as the independent variable and health problems or well-being, respectively, as the dependent variables, with a sample of health professionals. Results: Women reported lower psychological well-being and more health problems than men. The total effect of gender on both well-being and health problems was found to be significant. Regarding multiple mediation analyses: (a) the effect of gender on well-being was fully mediated by global basic need satisfaction and job satisfaction, such that gender did not present a significant direct effect and (b) the effect of gender on health problems was partially mediated by global basic need satisfaction and job satisfaction, such that the direct effect remained significant. Conclusions: The fulfillment of basic needs for autonomy, competence, and relatedness, as postulated within self-determination theory, was hypothesized to play a mediating role in the relationship between gender and well-being. Since significant gender differences in basic need satisfaction were observed, such a mediator should be controlled in order to achieve a significant relationship between gender and well-being when basic needs comes into play. The current study adds to the research emphasizing the need for satisfaction as a promising mechanism underlying for female health professionals’ well-being

Modelling mental healthcare improvement in highly integrated care systems: the case of the Basque Country (Spain)

Currently there is growing interest in providing integrated mental health care between hospital (acute residential care) and community-based services (… and other health systems). Mental health systems are complex due to the high disorder prevalence, socio-economic burden, stigma associated, and high gap of unmet population needs. Mental health can be considered an ecosystem related to, at least, physical health and social services ones. Decision support systems are robust tools for guiding and improving planning and management of health ecosystems by integrating methods like Bayesian networks. These models identify critical variables, domains and constructs and their corresponding causal relationships. The objective of this research is to design an integrated and integral theoretical Bayesian network for guiding mental health planning and management, and in consequence, improving mental health care delivery

The Impact of Socio-Economic Status on Self-Rated Health: Study of 29 Countries Using European Social Surveys (2002–2008)

Studies show that the association between socio-economic status (SES) and self-rated health (SRH) varies in different countries, however there are not many country comparisons that examine this relationship over time. The objective of the present study is to determine the effect of three SES measures on SRH in 29 countries according to findings in European Social Surveys (2002–2008), in order to study how socio-economic inequalities can vary our subjective state of health. In line with previous studies, income inequalities seem to be greater not only in Anglo Saxon and Scandinavian countries, but especially in Eastern European countries. The impact of education is greater in Southern countries, and this effect is similar in Eastern and Scandinavian countries, although occupational status does not produce significant differences in southern countries. This study shows the general relevance of socio educational factors on SRH. Individual economic conditions are obviously a basic factor contributing to a good state of health, but education could be even more relevant to preserve it. In this sense, policies should not only aim at reducing income inequalities, but should also further the education of people who are in risk of social exclusion

Identification and location of hot and cold spots of treated prevalence of depression in Catalonia (Spain)

Abstract Background Spatial analysis is a relevant set of tools for studying the geographical distribution of diseases, although its methods and techniques for analysis may yield very different results. A new hybrid approach has been applied to the spatial analysis of treated prevalence of depression in Catalonia (Spain) according to the following descriptive hypotheses: 1) spatial clusters of treated prevalence of depression (hot and cold spots) exist and, 2) these clusters are related to the administrative divisions of mental health care (catchment areas) in this region. Methods In this ecological study, morbidity data per municipality have been extracted from the regional outpatient mental health database (CMBD-SMA) for the year 2009. The second level of analysis mapped small mental health catchment areas or groups of municipalities covered by a single mental health community centre. Spatial analysis has been performed using a Multi-Objective Evolutionary Algorithm (MOEA) which identified geographical clusters (hot spots and cold spots) of depression through the optimization of its treated prevalence. Catchment areas, where hot and cold spots are located, have been described by four domains: urbanicity, availability, accessibility and adequacy of provision of mental health care. Results MOEA has identified 6 hot spots and 4 cold spots of depression in Catalonia. Our results show a clear spatial pattern where one cold spot contributed to define the exact location, shape and borders of three hot spots. Analysing the corresponding domain values for the identified hot and cold spots no common pattern has been detected. Conclusions MOEA has effectively identified hot/cold spots of depression in Catalonia. However these hot/cold spots comprised municipalities from different catchment areas and we could not relate them to the administrative distribution of mental care in the region. By combining the analysis of hot/cold spots, a better statistical and operational-based visual representation of the geographical distribution is obtained. This technology may be incorporated into Decision Support Systems to enhance local evidence-informed policy in health system research.</p

A Semiautomated Classification System for Producing Service Directories in Social and Health Care (DESDE-AND): Maturity Assessment Study

Background: DESDE-LTC (Description and Evaluation of Services and DirectoriEs for Long-Term Care) is an international classification system that allows standardized coding and comparisons between different territories and care sectors, such as health and social care, in defined geographic areas. We adapted DESDE-LTC into a computer tool (DESDE-AND) for compiling a directory of care services in Andalucia, Spain. Objective: The aim of this study was to evaluate the maturity of DESDE-AND. A secondary objective of this study is to show the practicality of a new combined set of standard evaluation tools for measuring the maturity of health technology products. Methods: A system for semiautomated coding of service provision has been co-designed. A panel of 23 domain experts and a group of 68 end users participated in its maturity assessment that included its technology readiness level (TRL), usability, validity, adoption (Adoption Impact Ladder [AIL]), and overall degree of maturity [implementation maturity model [IMM]). We piloted the prototype in an urban environment (Seville, Spain). Results: The prototype was demonstrated in an operational environment (TRL 7). Sixty-eight different care services were coded, generating fact sheets for each service and its geolocation map. The observed agreement was 90%, with moderate reliability. The tool was partially adopted by the regional government of Andalucia (Spain), reaching a level 5 in adoption (AIL) and a level 4 in maturity (IMM) and is ready for full implementation. Conclusions: DESDE-AND is a usable and manageable system for coding and compiling service directories and it can be used as a core module of decision support systems to guide planning in complex cross-sectoral areas such as combined social and health care