Executive functions are crucial for complex learning in addition to prior knowledge. In this article, we argue that executive functions can moderate the effectiveness of instructional approaches that ...vary with respect to the demand on these functions. In addition, we suggest that engagement in complex activity contexts rather than specific cognitive training paradigms may enhance executive functions and yield practically relevant transfer effects to other cognitive abilities. We develop several hypotheses and principles for how to improve executive functions in these contexts. For future research, we suggest to systematically investigate the moderating role of executive functions in learning environments with varying degrees of instructional support and varying context characteristics. We identify potential factors influencing the improvement of executive functions to be considered in a systematic research program.
Context and objective Shared decision making is especially advocated for preference‐sensitive decisions. We investigated whether physicians’ recommendations pull patients away from their preferred ...treatment option when making a preference‐sensitive decision.
Design, participants and methods Inpatients (N = 102 with schizophrenia, N = 101 with multiple sclerosis) were presented with a hypothetical scenario (the choice between two drugs). They were first asked about their preferences concerning the two drugs and then they received a (fictitious) clinician’s recommendation that was contrary to their preferences. Subsequently they made a final choice between the two drugs.
Main outcome measures The main outcome measure was whether the patient followed the physician’s advice in the hypothetical scenario. Thereby patient’s (pre‐recommendation) preferences served as a baseline.
Results In the decision scenario, about 48% of the patients with schizophrenia and 26% of the patients with multiple sclerosis followed the advice of their physician and thus chose the treatment option that went against their initial preferences. Patients who followed their physician’s advice were less satisfied with their decision than patients not following their physician’s advice (schizophrenia: t = 2.61, P = 0.01; multiple sclerosis: t = 2.67, P = 0.009).
Discussion and conclusions When sharing decisions with patients, physicians should be aware that their advice might influence patients’ decisions away from their preferred treatment option. They should encourage their patients to identify their own preferences and help to find the treatment option most consistent with them.
The relationship between working memory, intelligence and problem-solving is explored. Wittmann and Süß showed that working memory shares unique variance with problem-solving beyond intelligence. The ...authors used measures of visuo-spatial intelligence (Gv) and working memory to predict performance in the simulation-based problem-solving test MultiFlux in a sample of N = 144 undergraduate students. SEM analyses showed that while there was no unique contribution of Gv, working memory was a significant predictor of MultiFlux rule knowledge and rule application. This result is not in line with findings by Wittmann and Süß. It is discussed that task content (verbal, figural, numerical) might play an important role in explaining the relationship between intelligence and problem-solving. (Verlag).
The impact of symmetry Zech, Alexandra; Bühner, Markus; Kröner, Stephan ...
Journal of intelligence,
05/2017, Volume:
5, Issue:
2
Journal Article
Peer reviewed
Open access
Findings of studies on the unique effects of reasoning and working memory regarding complex problem solving are inconsistent. To find out if these inconsistencies are due to a lack of symmetry ...between the studies, we reconsidered the findings of three published studies on this issue, which resulted in conflicting conclusions regarding the inter-relations between reasoning, working memory, and complex problem solving. This was achieved by analysing so far unpublished problem solving data from the study of Bühner, Krumm, Ziegler, and Plücken (2006) (N= 124). One of the three published studies indicated unique effects of working memory and reasoning on complex problem solving using aggregated scores, a second study found no unique contribution of working memory using only figural scores, and a third study reported a unique influence only for reasoning using only numerical scores. Our data featured an evaluation of differences across content facets and levels of aggregation of the working memory scores. Path models showed that the results of the first study could not be replicated using content aggregated scores; the results of the second study could be replicated if only figural scores were used, and the results of the third study could be obtained by using only numerical scores. For verbal content, none of the published results could be replicated. This leads to the assumption that not only symmetry is an issue when correlating non-symmetrical data, but that content also has to be taken into account when comparing different studies on the same topic. (Orig.).
Studies on the interface between cognitive ability (intelligence) and personality in the prediction of academic performance have yielded mixed results so far. Especially an interaction between ...conscientiousness (and its facet achievement striving) and intelligence has been investigated. The hypothesis is that conscientiousness enhances the impact of intelligence on performance. Based on findings supporting the idea of a non-linear relationship between conscientiousness and performance the present study aimed at a clarification of the mixed results. Given such a non-linear relationship, studies investigating a possible moderating effect should pay attention to the performance level. A sample of
N
=
271 students completed a conscientiousness and an intelligence measure. Moderated regression analyses revealed a moderation for conscientiousness but not its facet achievement striving in the total sample. However, splitting the sample into a low and a high performer group revealed an enhancing effect of achievement striving for low performers and a buffering effect for high performer. Practical as well as theoretical implications are discussed.
This study explored predictors of multitasking performance. Based on cognitive psychology research, attention and working memory were assumed to be predictors. Fluid intelligence, polychronicity (as ...the preference for multitasking and the belief that their preference is the best way to handle things), and Extraversion were argued to be additional predictors. Multitasking performance was measured with the scenario "Simultaneous capacity/Multi-tasking (SIMKAP)" (n = 122). Hierarchical multiple regression analyses revealed that working memory was the most important predictor in addition to attention and fluid intelligence. The latter two constructs contributed significantly to the explained variance, but to a lesser extent. Polychronicity was not a significant predictor, nor was Extraversion. Implications for personnel selection and for time management are discussed.
Determining the number of factors in exploratory factor analysis is probably the most crucial decision when conducting the analysis as it clearly influences the meaningfulness of the results (i.e., ...factorial validity). A new method called the Factor Forest that combines data simulation and machine learning has been developed recently. This method based on simulated data reached very high accuracy for multivariate normal data, but it has not yet been tested with ordinal data. Hence, in this simulation study, we evaluated the Factor Forest with ordinal data based on different numbers of categories (2–6 categories) and compared it to common factor retention criteria. It showed higher overall accuracy for all types of ordinal data than all common factor retention criteria that were used for comparison (Parallel Analysis, Comparison Data, the Empirical Kaiser Criterion and the Kaiser Guttman Rule). The results indicate that the Factor Forest is applicable to ordinal data with at least five categories (typical scale in questionnaire research) in the majority of conditions and to binary or ordinal data based on items with less categories when the sample size is large.
Replicability has become a highly discussed topic in psychological research. The debates focus mainly on significance testing and confirmatory analyses, whereas exploratory analyses such as ...exploratory factor analysis are more or less ignored, although hardly any analysis has a comparable impact on entire research areas. Determining the correct number of factors for this analysis is probably the most crucial, yet ambiguous decision—especially since factor structures have often been not replicable. Hence, an approach based on bootstrapping the factor retention process is proposed to evaluate the robustness of factor retention criteria against sampling error and to predict whether a particular factor solution may be replicable. We used three samples of the “Big Five Structure Inventory” and four samples of the “10 Item Big Five Inventory” to illustrate the relationship between stable factor solutions across bootstrap samples and their replicability. In addition, we compared four factor retention criteria and an information criterion in terms of their stability on the one hand and their replicability on the other. Based on this study, we want to encourage researchers to make use of bootstrapping to assess the stability of the factor retention criteria they use and to compare these criteria with regard to this stability as a proxy for possible replicability.
The 20-item Toronto Alexithymia Scale (TAS-20) is the most widely used instrument for measuring alexithymia. However, different studies did not always yield identical factor structures of this scale. ...The present study aims at clarifying some discrepant results.
Maximum likelihood confirmatory factor analyses of a German version of the TAS-20 were conducted on data from a clinical sample (
N=204) and a sample of normal adults (
N=224). Five different models with one to four factors were compared.
A four-factor model with factors (F1) “Difficulty identifying feelings” (F2), “Difficulty describing feelings” (F3), “Low importance of emotion” and (F4) “Pragmatic thinking” and a three-factor model with the combined factor “Difficulties in identifying and describing feelings” described the data best. Factors related to “externally oriented thinking” provided no acceptable level of reliability.
Results from the present and other studies indicate that the factorial structure of the TAS-20 may vary across samples. Whether factor structures different from the common three-factor structure are an exception in some mainly clinical populations or a common phenomenon outside student populations has still to be determined. For a further exploration of the factor structure of the TAS-20 in different populations, it would be important not only to test the fit of the common three-factor model, but also to consider other competing solutions like the models of the present study.
Being able to work on several tasks at the same time (multitasking) is an important performance aspect of many jobs. Recent research findings pointed out the important role of working memory for ...multitasking performance in general. To understand more about the role of working memory in predicting the speed and the error aspect of multitasking performance, this research was based on a newly developed and well-elaborated multidimensional model of working memory (Oberauer, Süß, Wilhelm, & Wittmann, 2003). Its 3 dimensions are storage in the context of processing, coordination, and supervision. In addition, attention and reasoning were controlled when predicting multitasking speed and error. A multitasking scenario, a battery of working memory tests, a battery of reasoning tests, and 2 attention tests were administered to 135 participants. As expected working memory was the best predictor of multitasking performance, followed by reasoning and attention. Working memory components showed a differential validity when predicting multitasking speed and multitasking error: Multitasking speed was predicted mainly by coordination, and multitasking error mainly by storage in the context of processing. Thus, this study provided a deeper insight into the relevant abilities of multitasking. Implications for personnel selection are discussed.
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