Albert Sesé

Relationships between negative affectivity, emotion regulation, anxiety, and depressive symptoms in adolescents as examined through structural equation modeling

The relationship between negative affectivity (NA) and emotion regulation (ER) in determining anxiety and depressive symptomatology was examined in a large (n=1441) sample of adolescents (12-17 years old). Two models, diverging only as to inclusion or exclusion of a path from NA to negative ER, were analyzed through structural equation modeling; the goal was to explore the mediational or non-mediational role of ER in determining anxiety symptoms. The models yielded similar adequate fit to data, indicating that both NA and negative ER contribute to anxiety symptoms which, in turn, significantly determine depressive symptomatology. The mediational model better captures the relationships revealed in the data, with NA determining negative ER to a great extent. Additionally, most individuals scoring highly in NA also tend to score highly in negative ER, indicating that adolescents with heightened NA are prone to a dysfunctional style of ER.

Occupational safety and health in Spain

Occupational Health and Safety in Spain has improved considerably over the last decade, most likely due to a new concept where an overall concept of safety culture is defined. Important changes in industrial safety, hygiene, and psychosocial factors present an optimistic panorama for the future of Spain. Despite this general improvement, according to the European Convergence Program, Spanish statistics still offer far from good safety results. In fact, according to 1997 official statistics, Spain had the highest incidence rate for nonfatal occupational accidents of all European Union (EU) countries, and occupied third place for fatal accidents. This paper summarizes the organizational structure of the Spanish National System of Health & Safety at Work, its effective health and safety laws, and statistics on the Spanish work environment obtained from III Spanish National Survey on Work Conditions (1997). The researchers hope that the findings of this work will have an impact on Spanish industry that will subsequently bring about improvements in work conditions and develop assessment and intervention models in occupational health and safety, from a theoretical position integrating environmental, human, and organizational factors.

Mental disorders, chronic conditions and psychological factors: a path analysis model for healthcare consumption in general practice.

To explore potential individual determinants of healthcare utilization in primary care (PC) using a structural equation modelling approach. Atotal of 638 patients from five PC units were randomly selected. Mental disorders, psychological distress and other psychological factors were assessed with the 28-item General Health Questionnaire (GHQ-28) and the Schedules for Clinical Assessment in Neuropsychiatry (SCAN). Medical records and ICD-10 diagnosis were used to measure somatic morbidity. There is a negative relationship between the presence of mental disorders and psychological well-being (−0.74), and a negative relationship with use of health services (−0.25). Age has a positive and significant relationship with the presence of chronic diseases (0.49), which has a positive and significant relationship with limitation of daily activities (0.18). This limitation has a positive relationship with poor perception of health (0.57) and with psychological well-being (0.03). Findings confirm the existence of specific pathways in PC health use. Health service use depends on the patients psychological well-being and on the presence of chronic medical conditions. Healthcare professionals need to pay attention to the comorbidity of mental disorders and chronic medical conditions in order to identify frequent attenders and to decrease the inappropriate use of healthcare services.

Dimensionality Reduction in Data Mining Using Artificial Neural Networks

The use of classic dimension reduction techniques can be considered customary practice within the context of data mining (DM). Nevertheless, although artificial neural networks (ANNs) are one of the most important DM techniques, specific ANN architectures for dimensionality reduction, such as the principal components analysis ANN (PCA-ANN) and the linear auto-associative ANN (LA-ANN), are used on far fewer occasions. In this study, categorical principal component analysis (CATPCA) and the two ANN procedures are studied and compared searching for uniqueness in an applied context relative to personality variables and drug consumption. A sample of 7,030 adolescents completed a personality test made up of 20 dichotomous items with a hypothesized four-factor latent model. Results point out that both ANN factor solutions converge to those obtained using CATPCA. Nevertheless, possible drawbacks of the ANN techniques lie in their relatively complex application, as well as in the need to use visual graphic analysi...

Psychometric Measurement Models and Artificial Neural Networks.

The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the use of neural networks as a dimensionality reduction tool applied to psychometrics is totally nonexistent in the literature. The work presented here is devoted to the description of Neural Networks Principal Components Analysis (NNPCA) and the comparison of its results with performance of classical PCA by means of a computer simulation study. Results indicate very important convergence between neural and classical PCA, even with simulated diffuse latent structures. NNPCA is performed under principles of neurobiologic plausibility (learning neural architecture), useful to analyze latent psychometric structures adding more psychological significance. This new tool could be considered as another complementary way to assess measurement models, together with classical approaches. The pioneer character of this work also requires the development of further empirical evidence that allows advancement in the use of the NNPCA in the study of psychometric measurement models.

Effects of organizational complexity and resources on construction site risk

INTRODUCTION Our research is aimed at studying the relationship between risk level and organizational complexity and resources on constructions sites. Our general hypothesis is that site complexity increases risk, whereas more resources of the structure decrease risk. A Structural Equation Model (SEM) approach was adopted to validate our theoretical model. METHOD To develop our study, 957 building sites in Spain were visited and assessed in 2003-2009. All needed data were obtained using a specific tool developed by the authors to assess site risk, structure and resources (Construction Sites Risk Assessment Tool, or CONSRAT). This tool operationalizes the variables to fit our model, specifically, via a site risk index (SRI) and 10 organizational variables. Our random sample is composed largely of small building sites with general high levels of risk, moderate complexity, and low resources on site. CONCLUSIONS The model obtained adequate fit, and results showed empirical evidence that the factors of complexity and resources can be considered predictors of site risk level. PRACTICAL APPLICATIONS Consequently, these results can help companies, managers of construction and regulators to identify which organizational aspects should be improved to prevent risks on sites and consequently accidents.

Recommendations for the use of statistics in Clinical and Health Psychology

The generation of scientific knowledge in Psychology has made significant headway over the last decades, as the number of articles published in high impact journals has risen substantially. Breakthroughs in our understanding of the phenomena under study demand a better theoretical elaboration of work hypotheses, efficient application of research designs, and special rigour concerning the use of statistical methodology. Anyway, a rise in productivity does not always mean the achievement of high scientific standards. On the whole, statistical use may entail a source of negative effects on the quality of research, both due to (1) the degree of difficulty inherent to some methods to be understood and applied and (2) the commission of a series of errors and mainly the omission of key information needed to assess the adequacy of the analyses carried out. Despite the existence of noteworthy studies in the literature aimed at criticising these misuses (published specifically as improvement guides), the occurrence of statistical malpractice has to be overcome. Given the growing complexity of theories put forward in Psychology in general and in Clinical and Health Psychology in particular, the likelihood of these errors has increased. Therefore, the primary aim of this work is to provide a set of key statistical recommendations for authors to apply appropriate standards of methodological rigour, and for reviewers to be firm when it comes to demanding a series of sine qua non conditions for the publication of papers.

Can Attitudes toward Statistics and Statistics Anxiety Explain Students’ Performance? // ¿Pueden las actitudes hacia la estadística y la ansiedad estadística explicar el rendimiento de los estudiantes?

The aim of this study was to investigate the relationships between math background, trait anxiety, test anxiety, statistics anxiety, attitudes toward statistics and statistics performance in a sample of 472 university students enrolled in statistics courses of Health Sciences majors. A Structural Equation Modeling (SEM) approach showed the attitudes as the stronger direct predictor of performance, and played a full mediating role on the relationship between statistics anxiety and performance. Contrary to hypothesized, the direct contribution of math background, trait anxiety, and test anxiety to performance was non-significant. A final model posited that performance was positively and directly affected by attitudes, and in turn attitudes were positively influenced by math background and negatively affected by anxiety. Math background also appeared as negative predictor of anxiety. Finally, test anxiety was a positively direct predictor of statistics anxiety.