Ecological validity and cultural sensitivity for outcome research: Issues for the cultural adaptation and development of psychosocial treatments with Hispanics

This article has two objectives. The first is to provide a culturally sensitive perspective to treatment outcome research as a resource to augment the ecological validity of treatment research. The relationships between external validity, ecological validity, and culturally sensitive research are reviewed. The second objective is to present a preliminary framework for culturally sensitive interventions that strengthen ecological validity for treatment outcome research. The framework, consisting of eight dimensions of treatment interventions (language, persons, metaphors, content, concepts, goals, methods, and context) can serve as a guide for developing culturally sensitive treatments and adapting existing psychosocial treatments to specific ethnic minority groups. Examples of culturally sensitive elements for each dimension of the intervention are offered. Although the focus of the article is on Hispanic populations, the framework may be valuable to other ethnic and minority groups.     

“Everything Is Interrelated”

The COVID-19 pandemic has shown that “everything is interrelated,” especially in relation to health, ecology, economy, and climate change, as various authors have stated. The motto is the leitmotif of Pope Francis’ encyclical Laudato si’ and leads to his proposal of an integral ecology. This article deepens the implications of the latter in the encyclical and in other works and shows how the Catholic Synod of Bishops for the Pan-Amazon Region is an example of the reception and application of integral ecology in a given context. Based on this, the article proposes some conclusions, taking into account the theme of the next assembly of the World Council of Churches in 2022.     

An Introduction to Everyday Aesthetics in Education

Studies in Philosophy and Education - The purpose of this paper is to introduce everyday aesthetics in education. First, it presents everyday aesthetics as a subdiscipline within philosophical...     

Development and validation of the Granada Burnout Questionnaire in Spanish police

The goal of the present study is to develop a questionnaire, with proper psychometric properties and current norms, to evaluate the burnout syndrome in Spain. The operative definition of burnout proposed by Maslach and Jackson is used to define three dimensions (Emotional exhaustion, Depersonalization and Personal accomplishment). A total of 2,403 national Spanish police participated. Evidence of construct validity was checked through cross validation (showing a good fit of the three factors model to the data). Using the MBI, NEO-FII and CECAD evidence of convergent validity and criteria validity were developed (showing that the relations are similar to the ones that appear in other research). The discrimination, mean, standard deviation, and typical error of the average of the items composing the various dimensions were analyzed. Both the Cronbach's alpha coefficient and the conditional standard error of measurement (CSEM) were calculated for each of the dimensions. The results showed good internal consistency (all α values > .85). Finally, the questionnaire was scaled using T scores. The psychometrical properties reported here support the use of this new questionnaire for the burnout evaluation in Spanish police.     

Stratified Belief Bases Revision with Argumentative Inference

We propose a revision operator on a stratified belief base, i.e., a belief base that stores beliefs in different strata corresponding to the value an agent assigns to these beliefs. Furthermore, the operator will be defined as to perform the revision in such a way that information is never lost upon revision but stored in a stratum or layer containing information perceived as having a lower value. In this manner, if the revision of one layer leads to the rejection of some information to maintain consistency, instead of being withdrawn it will be kept and introduced in a different layer with lower value. Throughout this development we will follow the principle of minimal change, being one of the important principles proposed in belief change theory, particularly emphasized in the AGM model. Regarding the reasoning part from the stratified belief base, the agent will obtain the inferences using an argumentative formalism. Thus, the argumentation framework will decide which information prevails when sentences of different layers are used for entailing conflicting beliefs. We will also illustrate how inferences are changed and how the status of arguments can be modified after a revision process.     

Effects of Modeling the Heterogeneity on Inferences Drawn from Multilevel Designs

This article uses Monte Carlo techniques to examine the effect of heterogeneity of variance in multilevel analyses in terms of relative bias, coverage probability, and root mean square error (RMSE). For all simulated data sets, the parameters were estimated using the restricted maximum-likelihood (REML) method both assuming homogeneity and incorporating heterogeneity into multilevel models. We find that (a) the estimates for the fixed parameters are unbiased, but the associated standard errors are frequently biased when heterogeneity is ignored; by contrast, the standard errors of the fixed effects are almost always accurate when heterogeneity is considered; (b) the estimates for the random parameters are slightly overestimated; (c) both the homogeneous and heterogeneous models produce standard errors of the variance component estimates that are underestimated; however, taking heterogeneity into account, the REML-estimations give correct estimates of the standard errors at the lowest level and lead to less underestimated standard errors at the highest level; and (d) from the RMSE point of view, REML accounting for heterogeneity outperforms REML assuming homogeneity; a considerable improvement has been particularly detected for the fixed parameters. Based on this, we conclude that the solution presented can be uniformly adopted. We illustrate the process using a real dataset.