Addressing medical student burnout through informal peer-assisted learning: a correlational analysis.

BACKGROUND: Despite the recognized advantages of Peer-Assisted Learning (PAL) in academic settings, there is a notable absence of research analyzing its effects on students' Academic Burnout. This study aims to cover this gap by assessing the underlying effectiveness of Informal Peer-Assisted Learning (IPAL) as a cooperative learning method, focusing on its potential to mitigate academic burnout among medical students. METHODS: In 2022, a cross-sectional study was conducted at the School of Medicine, Universidad Central del Caribe, in Puerto Rico. The research team gathered data from 151 participants, 49.19% of 307 total student body. This cohort included 76 female students, 71 male students, and 4 individuals saying other. The School Burnout Inventory questionnaire (SBI-9) was employed to assess Academic Burnout, along with an added query about self-reported IPAL. The SBI-9 underwent validation processes to ascertain its reliability and validity, incorporating the Exploratory Factor Analysis and Confirmatory Factor Analysis. Following this, the investigators conducted an analysis to determine the correlation between academic burnout levels and involvement in IPAL. RESULTS: The validation process of the questionnaire affirmed its alignment with an eight-item inventory, encapsulating two principal factors that elucidate academic burnout. The first factor pertains to exhaustion, while the second encompasses the combined subscales of cynicism and inadequacy. The questionnaire shows high reliability (Cronbach's alpha = 0.829) and good fit indices (Comparative Fit Index = 0.934; Tucker-Lewis Index = 0.902; Standardized Root Mean Squared Residual = 0.0495; Root Mean Squared Error of Approximation = 0.09791; p-value < 0.001). The factors proven in the selected model were used to evaluate the correlation between Academic Burnout and IPAL. Students engaged in IPAL showed significantly lower academic burnout prevalence compared to those who never participated in such practices, with a mean academic burnout score of 44.75% (SD 18.50) for IPAL engaged students versus 54.89% (SD 23.71) for those who never engaged in such practices (p-value < 0.013). Furthermore, within the group engaged in IPAL, students displayed lower levels of cynicism/inadequacy 41.98% (SD 23.41) compared to exhaustion 52.25% (SD 22.42) with a p-value < 0.001. CONCLUSIONS: The results of this study underscore a notable issue of academic burnout among medical students within the surveyed cohort. The investigation reveals a significant correlation between Academic Burnout and IPAL, suggesting that incorporating IPAL strategies may be beneficial in addressing burnout in medical education settings. However, further research is needed to explore potential causal mechanisms.

Exploratory investigation of theoretical predictors of nomophobia using the Mobile Phone Involvement Questionnaire (MPIQ).

Despite the advantages that the development of new technologies has brought to our lives, it is also true that the problematic use of technology can have negative effects on some people, as the prevalence of nomophobia, defined as the fear and anxiety of being unreachable via one's mobile phone. While some authors are beginning to study the relationship of nomophobia with variables such as age, no investigation has yet been carried out into psychological variables. Our study contributes to the literature by looking at personality, self-esteem, gender and age as predictors of nomophobia, evaluated by the Mobile Phone Involvement Questionnaire (MPIQ). The study comprised 242 Spanish students (46.7% men and 53.3% women; 49.2% studying for a high school certificate and 50.8% for a university degree). Multiple regressions were conducted, finding that self-esteem, extraversion, conscientiousness and emotional stability predict nomophobia. Finally, we discuss these results and provide suggestions for future research.

Microparticle dynamics in upper-ocean turbulence: Dataset for analysis, modeling & prediction.

Plastic particle pollution has threatened the well-being of seawater ecosystems over the past decades. Therefore, understanding, modeling and (potentially) predicting the dynamics of microplastics and biogenic particles in ocean turbulence is of utmost importance to help develop mitigation strategies and propose technological solutions ultimately aimed at safeguarding global water systems. This is particularly significant for microplastics in the upper-ocean layer. To that end, this work presents a comprehensive and openly accessible dataset carefully designed to explore the interplay between the flow physics of particle-laden turbulence and the physicochemical effects of biofilm stickiness. The dataset comprises nine point-particle direct numerical simulations of fluid flow featuring microplastic and biogenic debris within a periodic three-dimensional flow domain. In all cases, the chosen turbulent intensity and microparticle properties represent conditions observed in the upper-ocean layer. This data repository aims to facilitate in-depth exploration, modeling and prediction of the intricate flow physics observed in marine microplastics, particularly regarding their distribution and aggregation.

Personality and Nomophobia: The Role of Dysfunctional Obsessive Beliefs.

BACKGROUND: The development of new technologies (ICTs), and specifically the invention of smartphones, has offered users enormous benefits. However, the use of this technology is sometimes problematic and can negatively affect people's lives. Nomophobia has been defined as the fear of being unreachable by means of a smartphone and is considered a disorder of the modern world. The present study aims to provide additional evidence of the relationship between personality traits and nomophobia. Moreover, this research explores dysfunctional obsessive beliefs as another possible antecedent. Finally, this study also examines the effect of the combination of these antecedents on nomophobia. METHOD: The study sample was comprised of Spanish workers (males: 44.54%; females: 55.46%) in the city of Tarragona and its surroundings. RESULTS: Our results showed that nomophobia is directly related to personality traits such as extraversion, and that dysfunctional obsessive beliefs play a role in the development of nomophobia. Moreover, our study confirms that the combination of personality traits and dysfunctional obsessive beliefs can affect the degree of nomophobia experienced. DISCUSSION AND CONCLUSIONS: Our study contributes to the body of literature that examines how psychological variables of personality can be predictors of nomophobia. Additional research is needed to better understand the determinants of nomophobia.

Optimal design of water reuse networks in cities through decision support tool development and testing.

Water scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic approaches are still common practice for planning both drinking and reclaimed water distribution networks. This work illustrates a decision support tool that, based on open data sources and graph theory coupled to greedy optimization algorithms, is able to automatically compute the optimal reclaimed water network for a given scenario. The tool provides not only the maximum amount of served reclaimed water per unit of invested cost, but also the length and diameters of the pipes required, the location and size of storage tanks, the population served, and the construction costs, i.e., everything under the same architecture. The usefulness of the tool is illustrated in two different but complementary cities in terms of size, density, and topography. The construction cost of the optimal water reclaimed network for a city of approximately 100,000 inhabitants is estimated to be in the range of €0.17-0.22/m3 (for a payback period of 30 years).

Health and safety at work in the transport industry (TRANS-18): factorial structure, reliability and validity.

In this article, we study the psychometric properties of a short scale (TRANS-18) which was designed to detect safe behaviors (personal and vehicle-related) and psychophysiological disorders. 244 drivers participated in the study, including drivers of freight transport vehicles (regular, dangerous and special), cranes, and passenger transport (regular transport and chartered coaches), ambulances and taxis. After carrying out an exploratory factor analysis of the scale, the findings show a structure comprised of three factors related to psychophysiological disorders, and to both personal and vehicle-related safety behaviors. Furthermore, these three factors had adequate reliability and all three also showed validity with regard to burnout, fatigue and job tension. In short, this scale may be ideally suited for adequately identifying the safety behaviors and safety problems of transport drivers. Future research could use the TRANS-18 as a screening tool in combination with other instruments.

Variables that predict burnout in professional drivers.

Objectives. Stress maintained over time leads to a state of exhaustion known as burnout syndrome. This syndrome constitutes an occupational health problem, leading to high absenteeism. It can also mean that workers come to the workplace feeling unwell, which increases occupational collisions and injuries at work. In this study, we developed a predictive model of burnout in professional drivers using the following indicators: age, hours worked, seniority, educational level, fatigue, personality, attitudes toward driving, safety behaviors in the vehicle, and work characteristics and content. Method. A total of 523 professional drivers from different transport sectors, obtained through non-probability sampling, participated in the study. We used SPSS version 25.0 to analyze the data. Results. We determined the predictive capacity of certain variables that affect drivers and cause burnout. Exhaustion can be predicted with fatigue (48.8%), professional efficiency with emotional stability (39.8%) and cynicism with lack of motivation (28%) as the best predictors. Conclusions. The results contribute to a better knowledge of those factors that cause burnout in professional drivers. It is important to design individual interventions to reduce burnout, which would help reduce sick leave and possible collisions, in addition to providing greater well-being for drivers.

Influence that job characteristics, personality and burnout have on fatigue in professional drivers.

Objectives. Professional drivers drive for many hours without rest. This factor, in addition to the characteristics of the job, the vehicle, the environment and the driver, causes driver fatigue. Fatigue is one of the most common risk factors when driving because it causes drowsiness, decreases drivers' attention and may make them fall asleep at the wheel. In this article we propose a predictive model for professional drivers using the following variables: age, number of children, time spent at work, time spent inside the vehicle, personality, job characteristics (JDS), job content (JCQ) and burnout. Method. Participants were 509 professional drivers from various transport sectors recruited by non-probabilistic sampling. SPSS version 25.0 was used for statistical analysis. Results. The predictive capacity of variables that cause driver fatigue was determined. Exhaustion best predicts fatigue positively, while openness to experience best predicts it negatively. Burnout and certain personality characteristics are good predictors, whereas other variables, such as JCQ and JDS, are weak predictors. Conclusions. This study extends our knowledge of the factors that cause fatigue in professional drivers and underlines the importance of designing interventions aimed at reducing the incidence of fatigue, promoting greater driver well-being and lowering the incidence of accidents.

Personality and impulsivity as antecedents of occupational health in the construction industry.

Objectives. In health and safety at work, two main groups of causes of occupational accidents have been identified: unsafe conditions or technical factors; and the causes related to safe behavior or the human factor. The objective of this study is to analyze the predictive variables (emotional intelligence, personality, impulsivity and safety of the work environment) for three factors of the CONS-32 scale (criterion variables: use of protections, personal risk behavior and personal physical workload) in the construction sector. Methods. Using a sample of 256 Spanish workers from this sector, we analyzed the significant correlations between the three criterion variables and a set of variables extracted from various instruments, as well as the regression models that explain most of the variance. Results. The results show that the main predictive variables that explain the three factors are those related to responsibility as a personality trait, impulsivity and safety of the work environment. Conclusions. Based on the empirical evidence found, the most explanatory factor in all cases is safety climate in the work environment.

Age, gender, personality, burnout, job characteristics and job content as predictors of driver fatigue.

Objectives. Several studies have shown that one of the most common causes of collision is driver fatigue since fatigue causes drowsiness while driving and this decreases the driver's ability to maneuver the vehicle and increases the probability of their nodding off and falling asleep at the wheel. This may be due to a variety of personal reasons and specific factors connected to working conditions. In the present work we therefore intend to develop a predictive model for fatigue in professional drivers using the following indicators: age, gender, personality, burnout, characteristics and job content. Method. The participants were 516 professional drivers from different transport sectors, obtained through non-probabilistic sampling. SPSS version 25.0 was used for data analysis. Results. The predictive capacity of a number of variables that affect drivers by causing fatigue is determined. Fatigue can be predicted through certain variables, with the best predictor being exhaustion (48.8%). Conclusions. This research contributes to a greater knowledge of the factors that produce fatigue in professional drivers. It highlights the importance of designing interventions to reduce the incidence of fatigue, resulting in greater well-being for the driver and a lower incidence of collisions.

Impact of Techno-Creators and Techno-Inhibitors on Techno-Stress Manifestations in Chilean Kindergarten Directors in the Context of the COVID-19 Pandemic and Teleworking.

The research objective was to predict the impact of techno-creators and techno-inhibitors on the different manifestations of technostress in kindergarten directors in the context of the COVID-19 pandemic and telework. The participants were INTEGRA Foundation kindergarten directors, from a sample of 567 kindergartens in Chile. To measure the technostress manifestations, the RED-TIC questionnaire was used as an instrument, and concerning techno-creators and techno-inhibitors, those established in previous research were considered. The partial least squares structural equation modeling (PLS-SEM) methodology was used, and the model estimation was performed using SmartPLS version 3.0 software. It was obtained that techno-creators correlate positively and significantly with the technostress manifestations. A negative correlation was found between techno-inhibitors and technostress manifestations and techno-creators, but not significant for skepticism and inefficacy manifestations. Therefore, it is concluded that techno-creators lead to technostress manifestations, however, techno-inhibitors did not show a significant effect in reducing these manifestations in the sample studied.

DF-8: a specific scale for assessing work fatigue in professional drivers.

The study objective is to create a scale specifically for measuring driver fatigue and to analyze the scale's psychometric properties. The participants were 518 Spanish drivers. We carried out an exploratory factor analysis (EFA) and the first subsample obtained a single-item solution (eight items). We then performed a confirmatory factor analysis (CFA) with a second subsample. The results were root mean square error of approximation (rmsea) = 0.05, comparative fit index (CFI) = 0.94 and Tucker-Lewis index (TLI) = 0.92, which corroborates the previous results and maintains the same number of elements. The resulting dimension shows good reliability. The scale scores were then related to several external correlates and other scales, and showed good convergence and criteria validity. The results indicate that the scale for assessing work fatigue specifically in professional drivers - driver fatigue (DF-8) - is a reliable and valid instrument.

Analyzing the evolution of technostress: A science mapping approach.

This paper analyzes the scientific map of technostress and the scientific production on this topic between 1982 and 2017, highlighting its structure, evolution, and trends in this field. A literature review based on bibliometric analysis of 246 records indexed in Scopus database was conducted. These publications were analyzed according to bibliometric indicators and through science maps with SciMAT. Co-occurrence of terms by grouping techniques was implemented. In addition, elaboration of maps of science and performance analysis for periods was executed. The main contribution of this work is to provide the first scientific map of technostress and a detailed understanding of the scientific production that predicts the directions of future research. The bibliometric analyses permit an overview of the growth, extent and distribution of the scientific literature related to the technostress and the study of the scientific production of an institution, country, author or research group.

Spanish Adaptation of the Organizational Culture Assessment Instrument: Reflection on the Difficulty in Transferring the ad hoc Factor.

The Organizational Culture Assessment Instrument is a common instrument for measuring organizational culture in English-speaking countries based on four factors: Clan, ad hoc, Market and Hierarchy. However, to date, there is no proper translation of the scale into Spanish. In this study, we describe the translation and adaptation of the instrument through Exploratory Factor Analysis with a Spanish sample (n 1 = 246; 69.9% men and 30.1% women) and Confirmatory Factor Analysis with a Peruvian sample (n 2 = 510; 70.4% men and 29.6% women). The result reduces the four-factor internal structure to a three-factor structure that retains the Clan, Market and Hierarchy factors, but completely excludes the ad hoc factor. Confirmatory Factor Analysis shows acceptable indicators, reliabilities are good and indication of validity is also confirmed. In conclusion, this study has given rise to the instrument in Spanish, called OCAI-12, which is suitable for evaluating organizational culture.

Technostress of Chilean Teachers in the Context of the COVID-19 Pandemic and Teleworking.

This article shows the levels of technostress in primary and secondary education teachers in Chile, in the context of educational telework that Chile has adopted in connection with the health crisis by COVID-19. The information has been collected with the use of the RED-TIC scale, previously used in this country, whose validity and reliability of the instrument has been treated, for this case, with confirmatory factorial analysis (CFA) with a national coverage sample of 3006 teachers. The results show that 11% of teachers reveal techno anxiety and 7.2%, techno fatigue. Combining both manifestations, we find that 6.8% of teachers are techno stressed. Finally, fatigue and anxiety factors are higher for female teachers.

Work addiction as a predictor of anxiety and depression.

BACKGROUND: A worker's work habits can affect their health, both physically and psychologically. Negative results have been associated with work demands (stress, anxiety and depression). OBJECTIVE: In the present research we carried out a predictive study of work addiction by applying three questionnaires on depression and anxiety. METHODS: In this study, the participants were 332 workers, obtained through non-probabilistic sampling. The FACTOR (version 7.2) and SPSS 23.0 programs were used. RESULTS: The results of the correlation analysis show both positive and negative associations with the variables studied. We conclude that work addiction variables can predict anxiety and depression because we found that two variables predict 18.3% of depression and 20.3% of anxiety, which are feelings generated by work and excessive work. CONCLUSION: It can be concluded that feelings generated by work and excessive work predict anxiety and depression, thus the present research helps to broaden knowledge on work addiction, promoting a healthy lifestyle and prevent absenteeism.

Optimal selection of monitoring sites in cities for SARS-CoV-2 surveillance in sewage networks.

Selecting sampling points to monitor traces of SARS-CoV-2 in sewage at the intra-urban scale is no trivial task given the complexity of the networks and the multiple technical, economic and socio-environmental constraints involved. This paper proposes two algorithms for the automatic selection of sampling locations in sewage networks. The first algorithm, is for the optimal selection of a predefined number of sampling locations ensuring maximum coverage of inhabitants and minimum overlapping amongst selected sites (static approach). The second is for establishing a strategy of iterations of sample&analysis to identify patient zero and hot spots of COVID-19 infected inhabitants in cities (dynamic approach). The algorithms are based on graph-theory and are coupled to a greedy optimization algorithm. The usefulness of the algorithms is illustrated in the case study of Girona (NE Iberian Peninsula, 148,504 inhabitants). The results show that the algorithms are able to automatically propose locations for a given number of stations. In the case of Girona, always covering more than 60% of the manholes and with less than 3% of them overlapping amongst stations. Deploying 5, 6 or 7 stations results in more than 80% coverage in manholes and more than 85% of the inhabitants. For the dynamic sensor placement, we demonstrate that assigning infection probabilities to each manhole as a function of the number of inhabitants connected reduces the number of iterations required to detect the zero patient and the hot spot areas.

Predictive power of selected factors over driver stress at work.

Professional drivers are considered prone to health risks. For this reason we have conducted a predictive study to analyze variables that may be predictors of stress in driving. Participating in this study were 372 drivers (93.4% men, 6.6% women) recruited through non-probabilistic sampling. The aim of the study is to develop a prediction model for job stress in professional drivers using the following indicators: personality, impulsiveness, hardy personality, job, age, seat comfort, seat suspension, lumbar support and driving hours. We found that the variables with predictive power over driving stress were: commitment over relaxed driving (ΔR2 = 0.101; ß = 0.135), danger prevention (ΔR2 = 0.139; ß = 0.342) and fatigue and anxiety (ΔR2 = 0.063; ß = -0.227); control over alertness and vigilance (ΔR2 = 0.069; ß = 0.278); agreeableness over sensation-seeking (ΔR2 = 0.047; ß = -0.268). In conclusion, driver stress can be predicted by certain variables. This study contributes to better understanding of driver stress and promotes safety at the wheel, thus helping to prevent traffic accidents.

Teacher Technostress in the Chilean School System.

The expanded use of information technology in education has led to the emergence of technostress due to a lack of adaptation to the technological environment. The purpose of this study is to identify the levels of technostress in primary and secondary education in 428 teachers using a RED-TIC questionnaire, of which skepticism, fatigue, anxiety, and inefficiency are the main components. For the empirical analysis of the data, principal component analysis (PCA) and confirmatory factor analysis (CFA) were used. The results show that 12% of Chilean teachers participating in the study feel techno-fatigued, 13% feel techno-anxious, and 11% present both conditions. Male teachers show a higher incidence of techno-anxiety and techno-fatigue than their female peers. It can be concluded that the questionnaire used is a reliable tool to evaluate the presence of technostress, and it manifests itself importantly in its components of techno-anxiety and techno-fatigue in Chilean teachers.

The Influence of Gender Inequality in the Development of Job Insecurity: Differences Between Women and Men.

Job insecurity is an indicator of precarious work that refers to the fear of losing one's job. It is a relevant source of stress, with negative consequences on people's mental health. The main objective and contribution of this study is to identify how gender inequality and job insecurity are related, responding to the lack of consensus found in scientific literature in this field of study. To do so, a predictive study of job insecurity, broken down by gender, is developed, considering sociodemographic and labor variables as antecedents. The sample included 1,005 employees (420 men and 585 women) aged between 18 and 65, and a linear regression was conducted for each group. Results show that women perceive greater insecurity under precarious working conditions (temporary work, informal work, salary cuts, tenure), whereas in the case of men variables related to their professional careers (job category, education) and household incomes were relevant predictors. It is concluded that job insecurity affects both gender groups, but the conditions in which this perception grows are significantly impacted by gender inequality. These findings will allow for holistic and effective actions to decrease the effects of precarious work.