Software Estadístico de Libre Acceso en Psicología. Una Librería de Módulos para elSistema ViSta

En este trabajo describimos las capacidades y funcionalidad de una serie de módulos de análisis estadísticos integrables al sistema ViSta. Estos módulos se han creado con la finalidad de ampliar las capacidades de este programa en áreas de potencial interés para el investigador en Psicología, entre las que se cuentan: técnicas para el análisis de ítems, métodos de Análisis Factorial y métodos de estimaciones del tamaño del efecto. Esperamos que el trabajo contribuya a una mayor difusión del software libre y facilite el acceso a las tecnologías necesarias para el trabajo de investigación en psicología

Manipulating the alpha level cannot cure significance testing

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, and implications for applications. To boil all this down to a binary decision based on a p-value threshold of 0.05, 0.01, 0.005, or anything else, is not acceptable

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Adjective Checklist to Assess the Big Five Personality Factors in the Argentine Population

The aim of this work was to develop an adjective checklist to assess the Big Five personality factors in the Argentine population. The new instrument was administered to pilot (n= 112), validation (n= 372), and replication (n= 309) samples. The final version of the checklist included 67 adjectives encompassing its 5 dimensions. Factor analysis results were consistent with the Five-factor model. Internal consistency of scales was very good and convergent correlations with the Big Five Inventory (BFI; John, Donahue, & Kentle, 1991) were substantial. Face validity, as evaluated by 2 independent raters, was good. Preliminary evidence of validity for the checklist is presented. Finally, the Adjective Checklist for Personality Assessment and BFI are compared, taking into consideration their psychometric properties in our cultural context. Study limitations and future research are discussed

Adjective Checklist to Assess the Big Five Personality Factors in the Argentine Population

The aim of this work was to develop an adjective checklist to assess the Big Five personality factors in the Argentine population. The new instrument was administered to pilot (n= 112), validation (n= 372), and replication (n= 309) samples. The final version of the checklist included 67 adjectives encompassing its 5 dimensions. Factor analysis results were consistent with the Five-factor model. Internal consistency of scales was very good and convergent correlations with the Big Five Inventory (BFI; John, Donahue, & Kentle, 1991) were substantial. Face validity, as evaluated by 2 independent raters, was good. Preliminary evidence of validity for the checklist is presented. Finally, the Adjective Checklist for Personality Assessment and BFI are compared, taking into consideration their psychometric properties in our cultural context. Study limitations and future research are discussed

Focus Article The History of ViSta: The Visual Statistics System

ViSta is a project that focuses on dynamic and interactive graphics for statistics and was initiated by the late Forrest W. Young at the beginning of the 1990s. For over approximately 20 years, Forrest and other collaborators, including the authors of this article, have used ViSta for experimenting with these kinds of graphics in different settings, applying them to different scenarios of data and statistical analysis, searching to develop the right combination of features most appropriate in each case. In this time, ViSta evolved quite considerably, going through what we reckon were three different stages, namely: the initial one setting forth the foundations of ViSta; the second period where versions 5 and 6 of ViSta were released; and the consolidation period when a book summarizing the lessons learnt in the project was published. This book was titled ‘Visual Statistics: Seeing your data with interactive and dynamic graphics ’ and was completed in the last days of life of Forrest, who continued to work enthusiastically in the project even though his health was seriously deteriorating during that time. This article is a tribute to this work, but also describes the innovative features of ViSta, many of which are still relevant today. © 2012 Wiley Periodicals, Inc. How to cite this article

Psicología del tránsito: logros y desafíos de la investigación

Este trabajo ofrece una descripción de la psicología del tránsito atendiendo tanto a las características distintivas y aspectos consolidados del área como a los temas pendientes y desafíos de cara al futuro. Se revisan y discuten las necesidades prácticas que orientan la producción científica, los principales temas de estudio y las metodologías para su abordaje. Destacamos la necesidad de promover líneas de investigación que (a) acompañen las nuevas tendencias y demandas en materia de tránsito (e.g., alcanzar formas de movilidad más sustentables); (b) se ocupen de las formas menos hegemónicas de movilidad y de los grupos más vulnerables de usuarios, como peatones y ciclistas; y (c) atiendan las necesidades y particularidades propias del tránsito y el transporte en los países de la región.This paper brings a description of traffic psychology, including its distinctive features, consolidated issues, pending topics, and future challenges. We revise and discuss the practical needs that guide research, the mainstream subjects of study, and the research methods used. We highlight the need to promote research lines that (a) take into account new traffic trends and requirements (e.g., reach more sustainable ways of mobility); (b) deal with alternative ways of mobility and vulnerable road users (e.g., cyclists and pedestrians); and (c) address the specific transport and traffic needs from Latin-American countries

Predicting road safety behavior with the implicit attitudes and the Theory of Planned Behavior

Introduction The Theory of Planned Behavior (TPB) is one of the most widely used psychological models when it comes to explaining road safety behaviors. Recently, studies have also been conducted from the perspective of dual-process models. However, the present is the first study on road safety behaviors that integrates both perspectives. The study evaluates the roles of both implicit attitudes and TPB constructs in the prediction of seatbelt use. Method A sample of 100 drivers completed: (1) a self-reporting instrument on seatbelt use, (2) a questionnaire addressing TPB constructs, (3) an indirect measure of attitudes (Implicit Association Test), and (4) a social desirability scale. Results Results suggest that both types of attitudes make a significant and quite similar contribution to the explanation of seatbelt use. Interestingly, implicit attitudes were a better predictor than explicit attitudes among participants reporting inconsistent seatbelt use. In addition, path analysis models suggested that implicit attitudes appear to be relatively independent of TPB constructs and have a direct effect on seatbelt use. Conclusion The findings advance the idea of adding implicit attitudes to variables from the TPB model in order to increase the explanatory power of models used to predict road safety behaviors. Practical applications Potential use of implicit attitude measures in the education and training of drivers are discussed