The probability of simple versus complex causal models in causal analyses

What does a population-level mediation reveal about individual people?

Mediation analysis investigates the covariation of variables in a population of interest. In contrast, the resolution level of psychological theory, at its core, aims to reach all the way to the behaviors, mental processes, and relationships of individual persons. It would be a logical error to presume that the population-level pattern of behavior revealed by a mediation analysis directly describes all, or even many, individual members of the population. Instead, to reconcile collective covariation with theoretical claims about individual behavior, one needs to look beyond abstract aggregate trends. Taking data quality as a given and a mediation model's estimated parameters as accurate population-level depictions, what can one say about the number of people properly described by the linkages in that mediation analysis? How many individuals are exceptions to that pattern or pathway? How can we bridge the gap between psychological theory and analytic method? We provide a simple framework for understanding how many people actually align with the pattern of relationships revealed by a population-level mediation. Additionally, for those individuals who are exceptions to that pattern, we tabulate how many people mismatch which features of the mediation pattern. Consistent with the person-oriented research paradigm, understanding the distribution of alignment and mismatches goes beyond the realm of traditional variable-level mediation analysis. Yet, such a tabulation is key to designing potential interventions. It provides the basis for predicting how many people stand to either benefit from, or be disadvantaged by, which type of intervention.

Are complex causal models less likely to be true than simple ones? A critical comment on Trafimow (2017)

Trafimow (2017) used probabilistic reasoning to argue that more complex causal models are less likely to be true than simpler ones, and that researchers should be skeptical of causal models involving more than a handful of variables (or even a single correlation coefficient) [Trafimow, D. (2017). The probability of simple versus complex causal models in causal analyses. Behavior Research Methods, 49, 739-746]. In this comment, I point out that Trafimow's argument is misleading, and reduces to the observation that more informative models (that make definite statements about certain causal relations) are less likely to be true than less informative models (that remain silent about those relations, by omitting some variables from consideration). This correct but trivial statement does not deliver the epistemological leverage promised in the paper. When complexity is evaluated with reasonable criteria (such as the number of nonzero effects in alternative models involving the same variables), more complex models can be more, less, or equally likely to be true compared with simpler ones. I also discuss Trafimow's claim that, if a model is unlikely to be true a priori, researchers will seldom be able to gather evidence of sufficient quality to support it; in practice, even low-probability models can receive strong support without the need for extraordinary evidence. Researchers should evaluate the plausibility of causal models on a case-by-case basis, and be skeptical of overblown claims about the dangers of complex theories.

Comparative study of trait emotional intelligence and executive functioning among youth

This study investigated the relationship between trait emotional intelligence (TEI) and executive skills (ESs), and the differences between TEI and ESs among Malaysian and Iranian youths. In this study, 226 Malaysians and 248 Iranians completed the TEIQue-SF and Executive Skills Questionnaire. Hypotheses were tested with Partial Least Squares-Structural Equation Modeling (PLS-SEM). Findings indicated that TEI had significant predictions on ESs, depending on cultural contexts. Significant differences were found in the effects of TEI on ESs, including emotional control, metacognition, goal-directed persistence, response inhibition, planning/prioritization, sustained attention, stress tolerance, task initiation, and working memory among Malaysian and Iranian youth. No significant difference was found in the effects of TEI on ESs, including flexibility, organization, and time management across both groups. This study makes a unique contribution to emotional intelligence and executive functioning research literature by considering several ESs at the same time for personal development and promoting healthier lives. Comparison of the effect of TEI on ESs in the Malaysian and Iranian contexts using advanced analysis methods is one of the most important methodological contributions of the study.

The Importance of Emotional Intelligence and Cognitive Style in Institutionalized Older Adults' Quality of Life

Despite previous evidence showing a positive relationship between emotional intelligence (EI) and quality of life (QoL), associating older adults' emotional processing with several health indicators, few studies have explored both the IE and the a mechanisms through which they affect QoL. This cross-sectional study analyzes the mediator role of optimistic and pessimistic cognitive styles in the relationship between perceived EI (PEI) and QoL in 115 institutionalized older adults from Southern Spain. Regression analyses showed, after controlling for cognitive style, that PEI predicted a significant percentage of variance in: Health (β = .25, p < .01), Functional abilities (β = .20, p < .05), Activity and leisure (β = .17, p < .05) and Life satisfaction (β = .21, p < .05). Additionally, multiple mediation analysis revealed that cognitive style partially mediated the relationship between PEI and Health, Activity and leisure and Life satisfaction. Thus, PEI could promote personal but not external or environmental QoL aspects, highlighting the importance of developing emotional skills for healthy aging.

The impact of economic recessions on depression and individual and social well-being: the case of Spain (2006-2013)

PURPOSE

Although there is abundant evidence about the impact of economic crises on depression and other mental health problems, little is known about the protective role of variables linked to positive functioning (i.e., psychological well-being).

METHODS

We analyzed data from Spain, one of the European countries most affected by the 2008-2013 economic recession, collected in Round 3 (R3, 2006) and Round 6 (R6, 2013) of the European Social Survey interviews. Both surveys included measures of psychological well-being, social well-being and depression. Both samples were nationally representative of the general population (R3: 1877 participants, 49.2% men; R6: 1889 participants, 48.9% men).

RESULTS

Data from the R6 survey showed that, compared to data gathered in R3 (i.e., before the onset of the recession) Spanish citizens showed significantly less life satisfaction (95% CIs 0.37-0.63), less personal optimism (95% CIs 0.03-0.15), less social optimism (95% CIs 0.75-0.85), and higher levels of depressive symptoms (95% CIs - 0.74 to - 0.19). Structural equation modeling revealed that protective factors for depression changed in both rounds. In R3 (2006), close relationships, social optimism and social trust were significant mediators between well-being and depression. However, social optimism and social trust were no longer significant in R6 (2013), whereas close relationships remained a partial mediator of the effects of psychological well-being on depression.

CONCLUSIONS

Economic crises are associated with a significant increase in depressive symptoms. Furthermore, financial crises seem to have a corrosive impact on mental health by reducing the mediating effects of positive beliefs regarding the good nature of society.