Benefits of a dance group intervention on institutionalized elder people: A Bayesian network approach

2018

[EN] The present study aims to explore the effects of an adapted classical dance intervention on the psychological and functional status of institutionalized elder people using a Bayesian network. All participants were assessed at baseline and after the 9 weeks period of the intervention. Measures included balance and gait, psychological well-being, depression, and emotional distress. According to the Bayesian network obtained, the dance intervention increased the likelihood of presenting better psychological well-being, balance, and gait. Besides, it also decreased the probabilities of presenting emotional distress and depression. These findings demonstrate that dancing has functional and …

Frailty and Comorbidities. Frailty in Women

2017

Frailty and multimorbidity: Two related yet different concepts.

2016

The extension of life expectancy is a global phenomenon. The growth in the ageing population has created a new health scenario in which there is a higher prevalence of frailty and multimorbidity. The attention received by both conditions derives from their strong association with disability, hospitalization, and death. The aim of the present paper is to conceptualize and differentiate these terms and to discuss their interrelations. We conclude that, yet related, they represent two different clinical conditions. Frailty identifies the increased vulnerability to stressors due to a dynamic, non-linear, and multidimensional depletion of physiological reserve and redundancy, whereas multimorbid…

A happiness degree predictor using the conceptual data structure for deep learning architectures

2017

Abstract Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed …