Search

The increasing isolation of the elderly both in their own homes and in care homes has made the problem of caring for elderly people who live alone an urgent priority. This article presents a proposed design for a heterogeneous multirobot system consisting of (i) a small mobile robot to monitor the well-being of elderly people who live alone and suggest activities to keep them positive and active and (ii) a domestic mobile manipulating robot that helps to perform household tasks. The entire system is integrated in an automated home environment (AAL), which also includes a set of low-cost automation sensors, a medical monitoring bracelet and an Android application to propose emotional coaching activities to the person who lives alone. The heterogeneous system uses ROS, IoT technologies, such as Node-RED, and the Home Assistant Platform. Both platforms with the home automation system have been tested over a long period of time and integrated in a real test environment, with good results. The semantic segmentation of the navigation and planning environment in the mobile manipulator for navigation and movement in the manipulation area facilitated the tasks of the later planners. Results about the interactions of users with the applications are presented and the use of artificial intelligence to predict mood is discussed. The experiments support the conclusion that the assistance robot correctly proposes activities, such as calling a relative, exercising, etc., during the day, according to the user's detected emotional state, making this is an innovative proposal aimed at empowering the elderly so that they can be autonomous in their homes and have a good quality of life., Funding agency:Fundacion Seneca 19895/GERM/15

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot’s autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot's autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought., Funding agencies:Spanish Ministerio de Ciencia, Innovacion y Univesidades, Agencia Estatal de Investigacion (AEI) RTI2018-095599-A-C22Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Some of the components of perfectionism produce a variety of problems, such as interpersonal hypersensitivity and hostility, that may be associated with aggression behavior during adolescence. This study aims to identify classes of adolescents depending on their levels of Perfectionistic Strivings (PS) and Perfectionistic Concerns (PC) as well as to examine whether there are significant differences in the manifestations of the four components of aggression behavior (i.e., anger, hostility, physical aggression, and verbal aggression) between them. A total of 1,074 high school students from various educational centers participated in this study (M = 14.78, SD = 1.84). The Child-Adolescent Perfectionism Scale and the Aggression Questionnaire short form were used. The Latent Class Analysis identified three classes of adolescent perfectionism: (a) Non-Perfectionists (low PS and PC), (b) Maladaptive Perfectionists (high PS and PC), and (c) Adaptive Perfectionists (moderate PS and PC). Results revealed significant differences between classes regarding the different manifestations of aggression. Maladaptive Perfectionists and Adaptive Perfectionists reported, respectively, the highest and lowest levels of aggression behavior. This study assists in educational programs to prevent conflicts related to school violence through emotional adjustment.

El acoso entre iguales es una realidad en las enseñanzas superiores. Las nuevas tecnologías suponen un vehículo para la aparición y propagación del fenómeno. El objetivo de este estudio fue analizar la validez y fiabilidad del Cuestionario sobre Acoso entre Estudiantes Universitarios (QAEU), herramienta diseñada para su detección. Se trata de una prueba psicométrica compuesta por tres escalas: objeto, agente y observador. En el estudio participaron 765 estudiantes de Grado y Máster de diversas titulaciones de una universidad del sureste español con una media de edad de 23.27 (DT = .81), siendo el 72.7% mujeres. Los resultados mostraron una fiabilidad Alfa de Cronbach de .970. Los análisis estructurales, para confirmar la existencia de constructos en el cuestionario (tipo de acoso, vías por las que se produce, momento), presentaron un modelo robusto, tanto para las escalas de víctima, agresor o como observador. En conclusión, el QAEU es un instrumento con alta consistencia interna y válido para su uso en investigación, situaciones prácticas y en ámbitos de innovación., Harassment among peers is a reality framed in higher education. In addition, new technologies can be a vehicle for the appearance and propagation of the phenomenon. The main objective in this research was to analyse the validity and reliability of the Questionnaire on Harassment among University Students (QAEU in Spanish), a tool designed for its detection. It is a psychometric tool composed by three scales: object, agent and bystander. There were 765 students of Degree and Master from a university of the Spanish southeast with an average age of 23.27 (SD = .81), with 72.7% women. The results showed a reliability by Cronbach’ Alpha of .970. The structural equations model, analyses for confirming the constructs of the questionnaire (forms of aggression, ways and moment of aggression), presented robust model for victim scale, aggressor scale and even for bystanders scale. In conclusion, the QAEU is a tool with a high internal consistency and is valid for being used in research, practical situations and innovation areas.

The rise of technology has increased risks such as problematic internet use or cyberbullying. Data show that there is problematic use of the internet, which has important repercussions academically, personally, socially and for health. The objective of this study was to identify different profiles that vary according to intra- and interpersonal conflicts related to internet use. In addition, this study aimed to examine whether there are significant differences in bullying and cyberbullying among adolescents with a conflict related to internet use. The study participants were 810 students of Compulsory Secondary Education (M = 13.99, SD = 1.32). The Questionnaire on School Violence and the Questionnaire of Experiences Related to Internet was use. The latent profile analysis identified four different types of conflicts related to internet use: (a) high levels in intra- and interpersonal conflicts; (b) low levels intra- and interpersonal conflicts; (c) moderate intra- and interpersonal conflicts and (d) very high levels in intra- and interpersonal conflicts. The results of the study indicated that there were significant differences in the manifestations of school violence between the profiles. This study assists in educational programs to prevent conflicts related to internet use and school violence through emotional adjustment.

The use of mobile phones has great benefits for communication. However, evidence has shown that problematic use, such as cyberbullying, can also be associated with mobile phones. In this sense, emotional regulation plays an important role. The objective of this study was to identify different groups that varied in terms of conflicts related to problematic mobile phone use (namely, maladaptive communication and emotional patterns). Furthermore, the study aimed to examine whether there were significant differences in the dimensions of emotional intelligence and cyberbullying between adolescents with a mobile phone use problem. The study participants were 810 students aged between 12 and 16 years. The Emotional Coefficient Inventory questionnaire about cyberbullying and a questionnaire on experiences related to mobile phones were used. The cluster analysis identified three different types of mobile phone use: A group displaying no problematic use, a group displaying moderately problematic use, and a group displaying problematic use. The study results motivate carrying out stress management programs, emotional re-education, and other actions that reinforce emotional intelligence.

Burnout is a reality in the teaching profession. Specifically, teaching staff usually have higher burnout rates. The present study aims to analyze the different burnout profiles and to verify if there were differences between burnout profiles in depressive symptomatology and in the self-esteem of the teachers at school. The total number of participants was 210 teachers from 30 to 65 years. The first scale was the Maslach burnout inventory, the second scale was the Self-Rating depression scale and the third scale was the Rosenberg Self-Esteem Scale . The latent class analysis identified three burnout profiles: the first group with a high level of emotional exhaustion, low personal accomplishment and depersonalization (high burnout); the second group with low emotional exhaustion, low depersonalization and high personal accomplishment (low burnout) and the third group with low depersonalization, low emotional exhaustion and low personal accomplishment (moderate burnout). The results revealed that there were differences in depressive symptomatology (group 1 obtained higher scores than group 2 and group 3) and self-esteem (group 2 obtained higher scores than group 1). The psychological balance and health of teachers depend on preventing the factors that have been associated with this syndrome.

Burnout syndrome is has been associated with mental health problems such as depression, anxiety, and stress. Given this fact, some teachers implement various coping strategies for emotional control that are not always functional to mitigate such difficulties. Accordingly, this study aimed to identify different burnout profiles that vary in the levels of the three underlying dimensions: depersonalization (DE), emotional exhaustion (EE), and personal accomplishment (PA). Further, this study aimed to examine whether there are significant differences in depressive symptomatology, coping strategies, and the quality of interpersonal relationships at school between teachers with varying burnout profiles. The Maslach Burnout Inventory (MBI), Zung Self-Rating Depression Scale (SDS), Coping with Stress Questionnaire, and a questionnaire that measured sociodemographic characteristics were administered to 215 teachers (men: 42.8%) who were recruited from various secondary schools. Cluster analysis identified three different burnout profiles: groups of teachers with a predominance of (a) low levels of EE and high levels of PA, (b) high levels of EE and DE, and (c) low levels of DE and PA. The results revealed that there were significant differences in coping strategies, depressive symptomatology, and the quality of interpersonal relationships at school between teachers with different burnout profiles. These results have important implications for educational professionals. Specifically, the findings underscore the need for prevention and intervention programs that enhance teachers’ emotional skills, especially their ability to cope with exhaustion. These skills will alleviate their depression and consequently offer both teachers and students a conducive learning environment.