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Data mining is a technique that aims to explain large data sets through patterns of behavior, associations, changes, or significant structures in the data. The main goal of this study was to analyze information about beliefs and attitudes towards hypnosis, evaluated by the Valencia Scale of Attitudes and Beliefs Toward Hypnosis, Client version (VSABTH-C) in two temporal moments with a total of 444 participants; developing decision trees in order to discover any sociodemographic factors influencing these variables. The results indicate some influence of gender, education level, and profession on the scores in the scale factors, thus women tended to get higher scores on factors such as Control and Fear; people with a higher educational level tended to get higher scores on factors that denote more positive attitudes and beliefs towards hypnosis; in addition, the psychologist participants showed more positive attitudes and beliefs regarding hypnosis. Considering these results, it would be interesting to carry out similar studies, increasing the size of the sample and also adding some new variables, in order to deepen this relationship and implement changes that would lead people to have more positive attitudes and beliefs regarding hypnosis.
María Franquelo; Jose Pastrana-Brincones; Rafael Reigal; Juan Morillo-Baro; Juan Vázquez-Diz; Antonio Hernández-Mendo; Verónica Morales-Sánchez. Data Mining for Attitudinal and Belief Profiles Determination towards Hypnosis. Sustainability 2021, 13, 7721 .
AMA StyleMaría Franquelo, Jose Pastrana-Brincones, Rafael Reigal, Juan Morillo-Baro, Juan Vázquez-Diz, Antonio Hernández-Mendo, Verónica Morales-Sánchez. Data Mining for Attitudinal and Belief Profiles Determination towards Hypnosis. Sustainability. 2021; 13 (14):7721.
Chicago/Turabian StyleMaría Franquelo; Jose Pastrana-Brincones; Rafael Reigal; Juan Morillo-Baro; Juan Vázquez-Diz; Antonio Hernández-Mendo; Verónica Morales-Sánchez. 2021. "Data Mining for Attitudinal and Belief Profiles Determination towards Hypnosis." Sustainability 13, no. 14: 7721.
The main goal of this research is to study the relationships between physical activity, mood states and self-rated health in the Spanish lockdown (March 2020–April 2020) due to the state of alarm caused by COVID-19. The participants were 328 people aged between 19 and 59 years (M = 37.06; SD = 10.82). Females comprised 63.70% of the participants, and 36.30% were male. An associative, comparative and predictive design was used in this research. The International Physical Activity Questionnaire (IPAQ), the Profile of Mood State (POMS), the state anxiety scale of the State-Trait Anxiety Questionnaire (STAI) and the General Health Questionnaire GHQ−12 were applied in order to measure the study variables. Both correlation and linear regression analyses were performed, showing that physical activity is positively related to health perception and mood. Similarly, data have shown that moderate physical practice predicts better health perceptions and positive mood states than vigorous physical activity. Specifically, moderate physical activity is the only variable that predicts the anxiety state (R = 0.22; R 2 adjusted = 0.05; F = 15.51; p < 0.001). In addition, it has been detected that mood is related to the perception of the state of health. Outcomes suggest that practicing moderate physical activity during these types of situations could amortize its negative effects on psychological health and benefit a more positive mental state. Future studies should consider the employment status of the sample to detect possible differences based on this variable.
Rafael Reigal; José Páez-Maldonado; José Pastrana-Brincones; Juan Morillo-Baro; Antonio Hernández-Mendo; Verónica Morales-Sánchez. Physical Activity Is Related to Mood States, Anxiety State and Self-Rated Health in COVID-19 Lockdown. Sustainability 2021, 13, 5444 .
AMA StyleRafael Reigal, José Páez-Maldonado, José Pastrana-Brincones, Juan Morillo-Baro, Antonio Hernández-Mendo, Verónica Morales-Sánchez. Physical Activity Is Related to Mood States, Anxiety State and Self-Rated Health in COVID-19 Lockdown. Sustainability. 2021; 13 (10):5444.
Chicago/Turabian StyleRafael Reigal; José Páez-Maldonado; José Pastrana-Brincones; Juan Morillo-Baro; Antonio Hernández-Mendo; Verónica Morales-Sánchez. 2021. "Physical Activity Is Related to Mood States, Anxiety State and Self-Rated Health in COVID-19 Lockdown." Sustainability 13, no. 10: 5444.
MenPas is a psychosocial assessment platform1 developed by the University of Malaga in 2008. There has been a significant increase in data traffic during the period of confinement by COVID-19 (March and April ’20) compared to the same period in the previous year. The main goal to achieve in this work is to determine the patterns of use of this platform on both period of time. So, we want to respond to the following question: So, we the following question: Has the COVID-19 Pandemic changed the pattern of the Menpas users? In order to respond it, cluster analysis techniques (Data Mining) have been used to classify people taking surveys into quotient sets (cluster). This is a multivariate technique for dividing data into sets to that are as homogeneous as possible within themselves and heterogeneous among themselves. Specifically, the K-Means algorithm has been used for this analysis, which is based on the evaluation of the distance between data and the average of each variable. So, it is recommended to discover patterns or relationships among the data. Specifically, the use of the following questionnaires has been analyzed: Competitive State Anxiety Inventory-2 (CSAI-2), State Trait Anxiety Inventory (STAI), Profile of Mood State (POMS), Resilience Scale (RS), Sport Performance Psychological Inventory (IPED), Maslach Burnout Inventory (MBI) and Self-concept Form-5 (AF-5). The analyses have shown changes in cluster formation between 2019 and 2020 based on the variables gender, age, marital status or physical practice. Therefore, the analyses carried out have been sensitive to determine several profiles of people using the MenPas platform because there are changes in the characteristics of the user groups that have carried out the analyzed tests.
Rafael E. Reigal; Jose Luis Pastrana; Sergio Luis González-Ruiz; Antonio Hernández-Mendo; Juan Pablo Morillo-Baro; Verónica Morales-Sánchez. Use of Data Mining to Determine Usage Patterns of an Online Evaluation Platform During the COVID-19 Pandemic. Frontiers in Psychology 2020, 11, 1 .
AMA StyleRafael E. Reigal, Jose Luis Pastrana, Sergio Luis González-Ruiz, Antonio Hernández-Mendo, Juan Pablo Morillo-Baro, Verónica Morales-Sánchez. Use of Data Mining to Determine Usage Patterns of an Online Evaluation Platform During the COVID-19 Pandemic. Frontiers in Psychology. 2020; 11 ():1.
Chicago/Turabian StyleRafael E. Reigal; Jose Luis Pastrana; Sergio Luis González-Ruiz; Antonio Hernández-Mendo; Juan Pablo Morillo-Baro; Verónica Morales-Sánchez. 2020. "Use of Data Mining to Determine Usage Patterns of an Online Evaluation Platform During the COVID-19 Pandemic." Frontiers in Psychology 11, no. : 1.
Attention is one skill related to processes such as memory or learning, so, its evaluation is very interesting in areas such as clinical, educational or sports. The aim of this paper is to analyze the reliability and generalizability of one online computerized tool, named MenPas Mondrian Color, that has been developed for the visual attention span assessing and training. In addition, it has been intended to determine any existing relationships among the different parameters of the tasks performed in order to check the coherence of the results obtained in the executions. In 11,540 analyzed executions of 1064 users from different American, African and European countries, 6543 of them were performed by women (56.70%) and 4997 by men (43.30%). The age distribution showed that all of the participants were aged 18–55 years, with an average of 25.50 ± 8.91 years. The analyzed tool is called MenPas Mondrian Color which is included in the MENPAS 1.0 platform. Reliability (Cronbach’s Alpha), variance components and generalizability analyses were carried out in order to analyze the quality of the data gathered by this tool. The obtained results indicated optimal scores in the analyses performed, suggesting that the data gathered are reliable, precise and statistically generalizable to a larger population. Likewise, correlation analyses indicated that the difficulty of the task is related to the effectiveness in its executions, indicating that this is a highly sensitive tool.
Rafael Reigal; Fernando González-Guirval; José Pastrana-Brincones; Sergio González-Ruiz; Antonio Hernández-Mendo; Verónica Morales-Sánchez. Analysis of Reliability and Generalizability of One Instrument for Assessing Visual Attention Span: MenPas Mondrian Color. Sustainability 2020, 12, 7655 .
AMA StyleRafael Reigal, Fernando González-Guirval, José Pastrana-Brincones, Sergio González-Ruiz, Antonio Hernández-Mendo, Verónica Morales-Sánchez. Analysis of Reliability and Generalizability of One Instrument for Assessing Visual Attention Span: MenPas Mondrian Color. Sustainability. 2020; 12 (18):7655.
Chicago/Turabian StyleRafael Reigal; Fernando González-Guirval; José Pastrana-Brincones; Sergio González-Ruiz; Antonio Hernández-Mendo; Verónica Morales-Sánchez. 2020. "Analysis of Reliability and Generalizability of One Instrument for Assessing Visual Attention Span: MenPas Mondrian Color." Sustainability 12, no. 18: 7655.
The main goal of this study was to analyze the relationships among physical fitness, selective attention and concentration in a group of 210 teenagers (43.81% male, 56.19% female) from the city of Málaga (Spain), aged between 11 and 15 years old (M = 13.27, SD = 1.80) that participated in the study. D2 attention test was used in order to analyze selective attention and concentration. Physical fitness was evaluated using the horizontal jump test, the Course Navette test and the 5 × 10 meters speed test. The analysis taken indicated a significant relationship among the physical fitness level, the attention and the concentration, as in the general sample as looking at gender. Linear regression tests performed showed that oxygen consumption is the best predictor of attentional parameters. Cluster analysis shows two groups characterized by a greater or lower physical fitness level. So, the highest physical fitness level group scores better in the attention (e.g., boys: p < 0.001, d’ Cohen = 1.01, 95% CI [0.57, 1.44]; girls: p < 0.01, d’ Cohen = 0.61, 95% CI [0.24, 0.98]) and the concentration tests (e.g., boys: p < 0.001, d’ Cohen = 0.89, 95% CI [0.46, 1.32]; girls: p < 0.01, d’ Cohen = 0.58, 95% CI [0.21, 0.95]). Results indicate that physical fitness analysis can be used as a tool for observing differences in the attention and concentration level of the analyzed adolescents, suggesting that a physical performance improvement could be an adequate procedure to develop some cognitive functions during adolescence.
Rafael E. Reigal; Luna Moral-Campillo; Rocío Juárez-Ruiz De Mier; Juan P. Morillo-Baro; Verónica Odilia Morales Sánchez; Jose Luis Pastrana; Antonio Hernández-Mendo. Physical Fitness Level Is Related to Attention and Concentration in Adolescents. Frontiers in Psychology 2020, 11, 110 .
AMA StyleRafael E. Reigal, Luna Moral-Campillo, Rocío Juárez-Ruiz De Mier, Juan P. Morillo-Baro, Verónica Odilia Morales Sánchez, Jose Luis Pastrana, Antonio Hernández-Mendo. Physical Fitness Level Is Related to Attention and Concentration in Adolescents. Frontiers in Psychology. 2020; 11 ():110.
Chicago/Turabian StyleRafael E. Reigal; Luna Moral-Campillo; Rocío Juárez-Ruiz De Mier; Juan P. Morillo-Baro; Verónica Odilia Morales Sánchez; Jose Luis Pastrana; Antonio Hernández-Mendo. 2020. "Physical Fitness Level Is Related to Attention and Concentration in Adolescents." Frontiers in Psychology 11, no. : 110.
Data mining is seen as a set of techniques and technologies allowing to extract, automatically or semi-automatically, a lot of useful information, models, and tendencies from a big set of data. Techniques like “clustering,” “classification,” “association,” and “regression”; statistics and Bayesian calculations; or intelligent artificial algorithms like neural networks will be used to extract patterns from data, and the main goal to achieve those patterns will be to explain and to predict their behavior. So, data are the source that becomes relevant information. Research data are gathered as numbers (quantitative data) as well as symbolic values (qualitative data). Useful knowledge is extracted (mined) from a huge amount of data. Such kind of knowledge will allow setting relationships among attributes or data sets, clustering similar data, classifying attribute relationships, and showing information that could be hidden or lost in a vast quantity of data when data mining is not used. Combination of quantitative and qualitative data is the essence of mixed methods: on one hand, a coherent integration of result data interpretation starting from separate analysis, and on the other hand, making data transformation from qualitative to quantitative and 1 vice versa. A study developed shows how data mining techniques can be a very interesting complement to mixed methods, because such techniques can work with qualitative and quantitative data together, obtaining numeric analysis from qualitative data based on Bayesian probability calculation or transforming quantitative into qualitative data using discretization techniques. As a study case, the Psychological Inventory of Sports Performance (IPED) has been mined and decision trees have been developed in order to check any relationships among the “Self-confidence” (AC), “Negative Coping Control” (CAN), “Attention Control” (CAT), “Visuoimaginative Control” (CVI), “Motivational Level” (NM), “Positive Coping Control” (CAP), and “Attitudinal Control” (CACT) factors against gender and age of athletes. These decision trees can also be used for future data predictions or assumptions.
José L. Pastrana; Rafael E. Reigal; Verónica Odilia Morales Sánchez; Juan P. Morillo-Baro; Rocío Juárez-Ruiz De Mier; José Alves; Antonio Hernández-Mendo. Data Mining in the Mixed Methods: Application to the Study of the Psychological Profiles of Athletes. Frontiers in Psychology 2019, 10, 2675 .
AMA StyleJosé L. Pastrana, Rafael E. Reigal, Verónica Odilia Morales Sánchez, Juan P. Morillo-Baro, Rocío Juárez-Ruiz De Mier, José Alves, Antonio Hernández-Mendo. Data Mining in the Mixed Methods: Application to the Study of the Psychological Profiles of Athletes. Frontiers in Psychology. 2019; 10 ():2675.
Chicago/Turabian StyleJosé L. Pastrana; Rafael E. Reigal; Verónica Odilia Morales Sánchez; Juan P. Morillo-Baro; Rocío Juárez-Ruiz De Mier; José Alves; Antonio Hernández-Mendo. 2019. "Data Mining in the Mixed Methods: Application to the Study of the Psychological Profiles of Athletes." Frontiers in Psychology 10, no. : 2675.
J.L. Pastrana; Ernesto Pimentel; M. Katrib. QoS-enabled and self-adaptive connectors for Web Services composition and coordination. Computer Languages, Systems & Structures 2011, 37, 2 -23.
AMA StyleJ.L. Pastrana, Ernesto Pimentel, M. Katrib. QoS-enabled and self-adaptive connectors for Web Services composition and coordination. Computer Languages, Systems & Structures. 2011; 37 (1):2-23.
Chicago/Turabian StyleJ.L. Pastrana; Ernesto Pimentel; M. Katrib. 2011. "QoS-enabled and self-adaptive connectors for Web Services composition and coordination." Computer Languages, Systems & Structures 37, no. 1: 2-23.
Software systems grow each day in size and complexity. In an effort to manage increasing complexity and to maximize the reuse of code, the software engineering community has, in recent years, put considerable effort into the design and development of component-based software methodologies and tools. Inspired by the notion of connector (Allen and Garlan (1994) Formal connectors. Technical report CMU-CS-94-115, Carnegie Mellon University, PA, USA) in software architecture and the ‘Design by Contract’ metaphor proposed by Meyer ((2000) Object-Oriented Software Construction. Prentice Hall, USA), this paper presents a methodology for component composition, coordination and dynamic adaptation. Our proposal is based on connectors enriched with contracts, making software architecture more explicit at the implementation level. Those connectors will be components in our system. Therefore, we can use subtyping techniques for connectors development and we could offer a set of generic connectors implementing standard behavior patterns. In addition, the connectors will use semantic web techniques and a Prolog machine to solve functional adaptation problems, such us name or parameters mismatching of a service, at run-time.
J.L. Pastrana; Ernesto Pimentel; M. Katrib. Composition of Self-Adapting Components for Customizable Systems. The Computer Journal 2007, 51, 481 -496.
AMA StyleJ.L. Pastrana, Ernesto Pimentel, M. Katrib. Composition of Self-Adapting Components for Customizable Systems. The Computer Journal. 2007; 51 (4):481-496.
Chicago/Turabian StyleJ.L. Pastrana; Ernesto Pimentel; M. Katrib. 2007. "Composition of Self-Adapting Components for Customizable Systems." The Computer Journal 51, no. 4: 481-496.
The ESPUMA project is a university project directed to the improvement of teaching in first-year subjects of programming. The ESPUMA project was born three years ago with the main aim of improving the quality of teaching and motivating the student to learn the foundations of programming. This project involves both the use of the new technologies in the classroom and the development of attractive graphical environments aimed at helping the student to study the topics of the subjects. In this paper we present the ESPUMA project and evaluate its three-year application by showing main results in terms of academic results and acceptance from the student’s point of view.
M.V. Belmonte; C. Cotta; A.J. Fernández; I. Gomez; J.L Pastrana; J.A. Pedreira; F. Rus; E. Soler. Foundations of Programming: a Teaching Improvement. Computers and Education 2006, 81 -91.
AMA StyleM.V. Belmonte, C. Cotta, A.J. Fernández, I. Gomez, J.L Pastrana, J.A. Pedreira, F. Rus, E. Soler. Foundations of Programming: a Teaching Improvement. Computers and Education. 2006; ():81-91.
Chicago/Turabian StyleM.V. Belmonte; C. Cotta; A.J. Fernández; I. Gomez; J.L Pastrana; J.A. Pedreira; F. Rus; E. Soler. 2006. "Foundations of Programming: a Teaching Improvement." Computers and Education , no. : 81-91.