Search

School anxiety depends on multiple factors that occur directly or indirectly in the teaching-learning process, such as going to the blackboard in class or reporting low grades at home. Other factors that influence school climate are social skills and coping strategies. That said, the aim of this research was to analyze the sources of school anxiety, coping strategies, and social skills in Italian secondary school students through an artificial neural network. For this purpose, a quantitative and ex post facto design was used in which the Inventory of School Anxiety (IAES), the Coping Scale for Children (EAN), and the Questionnaire for the Evaluation of Social Skills student version (EHS-A) were administered. The results showed that cognitive avoidance and behavioral avoidance coping strategies, together with the lack of social skills in students, are the variables that contributed the most to school anxiety scores in the artificial neural network. The conclusions revolve around the need to develop primary prevention programs.

Suicidal behavior among young people has become an increasingly relevant topic after the COVID-19 pandemic and constitutes a public health problem. This study aimed to examine the variables associated with suicide risk and determine their predictive capacity. The specific objectives were: (1) to analyze the relationship between suicide risk and model variables and (2) to design an artificial neural network (ANN) with predictive capacity for suicide risk. The sample comprised 337 youths aged 18-33 years. An ex post facto design was used. The results showed that emotional attention, followed by problem solving and perfectionism, were variables that contributed the most to the ANN's predictive capacity. The ANN achieved a hit rate of 85.7%, which is much higher than chance, and with only 14.3% of incorrect cases. This study extracted relevant information on suicide risk and the related risk and protective factors via artificial intelligence. These data will be useful for diagnosis as well as for psycho-educational guidance and prevention. This study was one of the first to apply this innovative methodology based on an ANN design to study these variables.

Mathematics and statistical skills are crucial to daily life. However, many students found mathematics difficult to learn and understand. This research aimed to find relationships between mathematics and statistical attitudes and emotional dimensions, such as anxiety or self-efficacy. The sample consisted of two groups: the first group was formed by 276 Spanish students (75.7% female with an average age of 19.92 years) from different degrees at the University of Granada and the second one by agroup of 19 secondary school students from of a Secondary School in Granada, Spain (57.9% male students between 14 and 16 years of age from a public school). The instruments applied were a scale of attitude toward mathematics, a scale of attitude toward statistics, a scale to assess mathematical anxiety, and a scale to assess self-efficacy. An artificial neural network for the backpropagation algorithm was designed using dependent variable. The results showed a negative impact of anxiety on those attitudes, while self-efficacy had a positive impact on those mentioned attitudes. Therefore, emotional education is important in the well-being, and teaching in mathematics. The usefulness of the innovative neural network analysis in predicting the constructs evaluated in this study can be highlighted., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer CR declared a shared affiliation with the authors JM-R to the handling editor at the time of review., (Copyright © 2023 Hernández de la Hera, Morales-Rodríguez, Rodríguez-Gobiet and Martínez-Ramón.)

Affective-sexual and gender diversity is an increasingly distinctive and extended reality and should be acknowledged and respected. From a psychosocial and educational point of view, it is appropriate to review young people's attitudes and knowledge regarding this, relating them to aspects such as empathy, violence, or bullying, to implement quality education in the early stages of primary education. The main objective of this study was to analyze the relationship between empathy levels, attitudes toward transsexuality, and bullying among Spanish university students. The sample consisted of 247 students. Instruments were administered to evaluate negative attitudes toward transsexual people, gender ideology, transphobia, bullying, and empathy. Inverse relationships were found between transphobia and empathy. Regression analysis demonstrated the predictive ability of empathy on attitudes toward transsexual people. The results of this study are expected to increase awareness in society and encourage appropriate, satisfactory, or tolerable coexistence, in which all individuals can be free to live and express themselves. While the results indicated that the quality of life of transgender people has comparatively improved, there is still a long way to go.

Artificial intelligence (AI) is a useful predictive tool for a wide variety of fields of knowledge. Despite this, the educational field is still an environment that lacks a variety of studies that use this type of predictive tools. In parallel, it is postulated that the levels of self-esteem in the university environment may be related to the strategies implemented to solve problems. For these reasons, the aim of this study was to analyze the levels of self-esteem presented by teaching staff and students at university ( N  = 290, 73.1% female) and to design an algorithm capable of predicting these levels on the basis of their coping strategies, resilience, and sociodemographic variables. For this purpose, the Rosenberg Self-Esteem Scale (RSES), the Perceived Stress Scale (PSS), and the Brief Resilience Scale were administered. The results showed a relevant role of resilience and stress perceived in predicting participants' self-esteem levels. The findings highlight the usefulness of artificial neural networks for predicting psychological variables in education., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Martínez-Ramón, Morales-Rodríguez, Ruiz-Esteban and Méndez.)

The COVID-19 global health emergency has greatly impacted the educational field. Faced with unprecedented stress situations, professors, students, and families have employed various coping and resilience strategies throughout the confinement period. High and persistent stress levels are associated with other pathologies; hence, their detection and prevention are needed. Consequently, this study aimed to design a predictive model of stress in the educational field based on artificial intelligence that included certain sociodemographic variables, coping strategies, and resilience capacity, and to study the relationship between them. The non-probabilistic snowball sampling method was used, involving 337 people (73% women) from the university education community in south-eastern Spain. The Perceived Stress Scale, Stress Management Questionnaire, and Brief Resilience Scale were administered. The Statistical Package for the Social Sciences (version 24) was used to design the architecture of artificial neural networks. The results found that stress levels could be predicted by the synaptic weights of coping strategies and timing of the epidemic (before and after the implementation of isolation measures), with a predictive capacity of over 80% found in the neural network model. Additionally, direct and significant associations were identified between the use of certain coping strategies, stress levels, and resilience. The conclusions of this research are essential for effective stress detection, and therefore, early intervention in the field of educational psychology, by discussing the influence of resilience or lack thereof on the prediction of stress levels. Identifying the variables that maintain a greater predictive power in stress levels is an effective strategy to design more adjusted prevention programs and to anticipate the needs of the community., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Morales-Rodríguez, Martínez-Ramón, Méndez and Ruiz-Esteban.)

The present study aims analyze the risk factors that lead to high levels of burnout among nurses and physicians and the protective factors that prevent them. Thus, it is also intended to explore the possible correlation between physical and verbal violence produced at work and the symptoms derived from burnout. Methods: The search was carried out on the Scopus, PubMed and Web of Science databases between 2000 and 2019 (on which date the bibliographic search ends). Descriptive studies estimating the prevalence of workplace violence and risk and protective factors and burnout were included. An adapted version of the Downs and Black quality checklist was used for article selection. 89.6 percent of the studies analysed were in the health sector. There is a significant correlation between burnout symptoms and physical violence at work. On the one hand, the risk factors that moderate this correlation were of structural/organisational type (social support, quality of the working environment, authoritarian leadership, little autonomy or long working days, etc.) and personal type (age, gender, nationality or academic degree, etc.). On the other hand, protective factors were the quality of the working environment, mutual support networks or coping strategies. The results were analysed in-depth and intervention strategies were proposed.

Students with psychosis in school within the ordinary education system are a reality in the classroom. To study their correct adaptation at school, it is necessary to consider numerous factors such as the personal characteristics of the student, environmental variables, educational measures put in place as well as emotional and cognitive aspects. The aim of this research was to monitor the teaching-learning process of a student diagnosed with psychosis and enrolled in a public school at the secondary level in the ordinary modality with support during an academic year, with the usual resources provided by a guidance department to assess the impact of the educational measures and plans on his emotional and academic fields. This was a single case study in which both qualitative and quantitative information was collected ( N = 1). The participant was a student with special needs at the secondary level. An analysis of the results of psychometric tests, plan for diversity, observational analysis, academic file, scholastic history, and multiple interviews were carried out. The findings show how the educational curriculum can be adapted to improve the competences of a student with psychosis by encouraging an increase in social abilities and potential cognitive abilities through the counseling department. The conclusions of this research can provide a guideline for comparison of different educational systems, paying greater attention to the development of emotional aspects, and opting for inclusive measures. In this line, this study shows that students with psychosis can share classrooms and studies with their peers, thus fulfilling the principle of educational inclusion.

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.

Bullying and cyberbullying are important global issues with negative consequences for physical and mental health in education. The objective of this study was to analyze to what extent some dimensions of emotional intelligence predict certain manifestations of bullying and cyberbullying in adolescents. The total number of subjects recruited in compulsory secondary education schools, was 309 (53.1% female). Their ages ranged from 12 to 16 ( M = 14.17, SD = 1.4). The used instruments were the school violence questionnaire and the emotional coefficient inventory; the study design was cross-sectional. Results showed that the score increases on some scales (adaptability, stress management, and interpersonal) involved a greater risk of increasing the likelihood of social perception the different manifestations of school violence. However, in the general mood, the increase in this variable score implied lower perceiving in likelihood of violent behavior. It is important to take into account preventive actions aimed at improving school life and, above all, to alleviate difficulties in managing stress, adaptability, and interpersonal relationships.

Each of sixty Rasa aragonesa ewes received two embryos on Days 2-3 of the estrous cycle (Day 0=estrus) from 27 donors of the same breed that were superovulated with pFSH. The influence of several variables on fertility and prolificacy after transfer was studied by discriminant analysis. Our results showed that the main variables contributing to higher fertility were: in the donor-recipient couple, degree of estrus synchrony between them (better if donors were in estrus before recipients); in recipients, interval from FGA withdrawal to estrus onset, prolificacy in the previous lambing, age (all, better if inferior to the mean) and interval from the previous lambing (better if superior to the mean); in donors, ovulation rate (better if lower than the mean); and in embryos, developmental stage (better if superior to the mean). Likewise, the main variables contributing to higher prolificacy were: in donors, body condition score (better if higher than the mean) and weight (better if inferior to the mean); and in recipients, plasma progesterone concentration at transfer (better if inferior to the mean). The percentage of ewes correctly classified as lambing or not was 71.7% (P<0.01), and 72.5% of the ewes were correctly classified as having one or two lambs (P<0.05). Whether the criteria we have found for optimum results after transfer are applicable or not to conditions other than ours will need to be confirmed.

The application of pGH (porcine Growth Hormone) to superovulated ewes was studied with the aim of improving the embryo yield. Thirty-seven ewes were superovulated with pFSH for 3 d and 18 of them were cotreated the third day with 0.50 mg of pGH. Embryos were surgically recovered on Day 7 after sponge withdrawal. Then, 102 morphologically healthy embryos were immediately transferred in pairs to 51 synchronized recipient ewes. The GH treatment did not significantly affect the percentage of ewes in estrus, the time of estrus onset or the ovulation rate. However, it improved synchronization by grouping estrus in a narrower range (12 h) in comparison to the control group (24 h); (16 to 28 h after sponge withdrawal vs 12 to 36 h; P < 0.05). The total amount of LH released during the preovulatory surge was lower in the GH than in the control group (P < 0.05). No differences were found between groups for other LH-related parameters such as basal levels, peak values or peak time from sponge removal. The proportions of unfertilized oocytes and degenerate embryos recovered were lower in the GH cotreated group (P < 0.05 and P < 0.01, respectively). This resulted in higher rates of transferable embryos and lambs born per donor ewe in the GH than in the untreated group (3.9 vs 1.7 and 2.28 vs 0.84, respectively; both, P < 0.05). These beneficial effects of GH would likely be due either to a direct action on oocyte maturation or to an indirect action on the oviductal environment.

Rasa Aragonesa ewes (n = 89) received 2 embryos on Day 6 of the estrous cycle (Day 0 = estrus) from 46 donors of the same breed that had been superovulated with FSH-p. The influence of several variables on fertility and prolificacy after transfer was studied by discriminant analysis. Our results showed that the main variables that contributed to a high fertility rate were the degree of synchrony (better outcome if donors come into estrus later than the recipients); Fluorogestone acetate (FGA) to estrus interval and interval from previous lambing in the recipients, ovulation rate of the donors and recipients (better if superior to the mean); prolificacy of recipients in the previous lambing; and difference in developmental stage of the pair of transferred embryos (better if inferior to the mean). The main variables affecting prolificacy were the ovulation rate and weight of the donors and progesterone concentrations of the recipients (better if lower than the mean); age of the donors and difference in progesterone concentrations between donors minus those of the recipients (better if higher than the mean). The percentage of ewes correctly classified into lambing or not lambing status was 73% (P < 0.001) and that of the ewes correctly classified as lambing 1 or 2 lambs was 81.8% (P < 0.001). Whether or not the criteria we have established for optimum transfer results are applicable to conditions other than our own still needs to be confirmed.