Hundred Days of Cognitive Training Enhance Broad Cognitive Abilities in Adulthood: Findings from the COGITO Study

We examined whether positive transfer of cognitive training, which so far has been observed for individual tests only, also generalizes to cognitive abilities, thereby carrying greater promise for improving everyday intellectual competence in adulthood and old age. In the COGITO Study, 101 younger and 103 older adults practiced six tests of perceptual speed (PS), three tests of working memory (WM), and three tests of episodic memory (EM) for over 100 daily 1-h sessions. Transfer assessment included multiple tests of PS, WM, EM, and reasoning. In both age groups, reliable positive transfer was found not only for individual tests but also for cognitive abilities, represented as latent factors. Furthermore, the pattern of correlations between latent change factors of practiced and latent change factors of transfer tasks indicates systematic relations at the level of broad abilities, making the interpretation of effects as resulting from unspecific increases in motivation or self-concept less likely

Within-person structures of daily cognitive performance cannot be inferred from between-person structures of cognitive abilities

First published online: 09 June 2020Over a century of research on between-person differences has resulted in the consensus that human cognitive abilities are hierarchically organized, with a general factor, termed general intelligence or "g," uppermost. Surprisingly, it is unknown whether this body of evidence is informative about how cognition is structured within individuals. Using data from 101 young adults performing nine cognitive tasks on 100 occasions distributed over six months, we find that the structures of individuals' cognitive abilities vary among each other, and deviate greatly from the modal between-person structure. Working memory contributes the largest share of common variance to both between- and within-person structures, but the g factor is much less prominent within than between persons. We conclude that between-person structures of cognitive abilities cannot serve as a surrogate for within-person structures. To reveal the development and organization of human intelligence, individuals need to be studied over time

Studying within-person variation and within-person couplings in intensive longitudinal data. Lessons learned and to be learned

Intensive longitudinal designs (e.g., experience sampling methods, daily diary studies, or ambulatory assessments) continue to gain importance in sychological aging research. Empirical research using these designs has greatly facilitated our understanding of short-term within-person processes and has started to approach the question how these processes shape long-term development across the life span. The aim of this viewpoint article is to point out four key issues in intensive longitudinal designs that in our opinion require more attention than they are currently given: (a) improvement in measurement reliability, (b) the necessity to investigate inter-individual differences in short-term dynamics, (c) considerations of the time scale across which dynamic effects unfold, and (d) targeting causality by incorporating experimental methods in intensive longitudinal designs. We illustrate these four key issues by referring to a prominent example of within-person dynamics in prior empirical research: the within-person coupling of stressor occurrence and well-being stress reactivity). (DIPF/Orig.

Vampires and nurses are rated differently by younger and older adults - age-comparative norms of imageability and emotionality for about 2500 German nouns

Imageability and emotionality ratings for 2592 German nouns (3-10 letters, one to three phonological syllables) were obtained from younger adults (21-31 years) and older adults (70-86 years). Valid ratings were obtained on average from 20 younger and 23 older adults per word for imageability, and from 18 younger and 19 older adults per word for emotionality. The internal consistency (Cronbach's α) and retest rank-order stability of the ratings were high for both age groups (α and r ≥ .97). Also, the validity of our ratings was found to be high, as compared to previously published ratings (r ≥ .86). The ratings showed substantial rank-order stability across younger and older adults (imageability, r = .94; emotionality, r = .85). At the same time, systematic differences between age groups were found in the mean levels of ratings (imageability, d = 0.38; emotionality, d = 0.20) and in the extent to which the rating scales were used (imageability, SD = 24 vs. 19, scale of 0 to 100; emotionality, SD = 26 vs. 31, scale of -100 to 100). At the descriptive level, our data hint at systematically different evaluations of semantic categories regarding imageability and emotionality across younger and older adults. Given that imageability and emotionality have been reported, for instance, as important determinants for the recognition and recall of words, our findings highlight the importance of considering age-specific information in age-comparative cognitive (neuroscience) experimental studies using word materials. The age-specific imageability and emotionality ratings for the 2592 German nouns can be found in the electronic supplementary material 1

Experiments in the wild. Introducing the within-person encouragement design

The within-person encouragement design introduced here combines methodological approaches from three research traditions: (a) the analysis of within-person couplings using multilevel models, (b) the experimental manipulation of a treatment variable at the within-person level, and (c) the use of random encouragements as instrumental variables to induce exogenous experimental variation when strict treatment adherence is unrealistic. The proposed combination of these approaches opens up new possibilities to study treatment effects of a broad range of behavioral variables in realistic everyday contexts. We introduce this new research design together with a corresponding data analysis framework: instrumental variable estimation with two-level structural equation models. Using simulations, we show that the approach is applicable with feasible design dimensions regarding numbers of measurement occasions and participants and realistic assumptions about adherence to the encouragement conditions. Possible applications and extensions, as well as potential problems and limitations are discussed. (DIPF/Orig.

Do higher educated people feel better in everyday life? Insights from a day reconstruction method study

Past research has shown a positive association between education and well-being. Much of this research has focused on the cognitive component of well-being (i.e., life satisfaction) as outcome. On the other hand, the affective component, that is, how often and intensively people experience positive affect (PA) and negative affect (NA) in their everyday lives, has received far less attention. Therefore, we examined the association between education and PA and NA in everyday life, with a particular focus on affective experiences at the sub-facet level (based on a structure of NA with multiple factors). We used data from a nationally representative sample (N = 1647) of the German Socioeconomic Panel Innovation Sample (SOEP-IS), employing the Day Reconstruction Method (DRM) to capture affective experiences of everyday activities. Multilevel structural equation models revealed that (1) education was not related to PA, but (2) was positively associated with two sub-facets of NA (mourning/worries and loneliness/boredom); (3) income might in part explain the association between education and NA; (4) education does not particularly seem to serve as a resource in times of unemployment or retirement (i.e., there were no interactions between education and unemployment/retirement regarding well-being) In essence, higher educated people reported fewer negative emotions in everyday life than their lower educated counterparts, but not more positive emotions. The findings underline that different facets of NA, in addition to life satisfaction, are relevant variables related to education and should receive more attention in order to gain a more comprehensive understanding of non-monetary correlates of education. (DIPF/Orig.

Developing personalized education. A dynamic framework

Personalized education—the systematic adaptation of instruction to individual learners—has been a long-striven goal. We review research on personalized education that has been conducted in the laboratory, in the classroom, and in digital learning environments. Across all learning environments, we find that personalization is most successful when relevant learner characteristics are measured repeatedly during the learning process and when these data are used to adapt instruction in a systematic way. Building on these observations, we propose a novel, dynamic framework of personalization that conceptualizes learners as dynamic entities that change during and in interaction with the instructional process. As these dynamics manifest on different timescales, so do the opportunities for instructional adaptations—ranging from setting appropriate learning goals at the macroscale to reacting to affective-motivational fluctuations at the microscale. We argue that instructional design needs to take these dynamics into account in order to adapt to a specific learner at a specific point in time. Finally, we provide some examples of successful, dynamic adaptations and discuss future directions that arise from a dynamic conceptualization of personalization. (DIPF/Orig.

Integrating state dynamics and trait change

Recent theoretical accounts on the causes of trait change emphasize the potential relevance of states. In the same vein, reactions to daily stress have been shown to prospectively predict change in well-being, speaking for the proposition that state dynamics can be a precursor to long-term change in more stable individual-differences characteristics. A common analysis approach towards linking state dynamics such as stress reactivity and change in some more stable individual differences characteristic has been a two-step approach, modeling state dynamics and trait change separately. In this paper, we elaborate on one-step procedures to simultaneously model state dynamics and trait change, realized in the multilevel structural equation modeling framework. We highlight three distinct advantages over the two-step approach which pre-exists in the methodological literature, and we disseminate these advantages to a larger audience. We target a readership of substantive researchers interested in the relationships between state dynamics and traits or trait change, and we provide them with a tutorial style paper on state-of-the-art methods on these topics.Deutsche Forschungsgemeinschafthttps://doi.org/10.13039/501100001659Peer Reviewe

Affective states contribute to trait reports of affective well-being

Asking people to provide global judgments, or trait reports, of their affective experience is a standard method for assessing trait affective well-being, with countless applications in the social sciences. Trait reports reflect numerous influences that generally go unnoticed. Although state affect is a highly plausible candidate for such influences, this source of unwanted variance does not receive much attention and is usually not controlled for in empirical studies. Using 100-day data from the COGITO study, we provide direct and strong evidence that trait reports of affect depend on how people feel at the time they provide the evaluations (i.e., their affective state). For example, participants experiencing more positive affect on a specific day relative to their individual mean also provide more positive ratings of their global affective experience. Furthermore, we found that current affect influences trait ratings in a surprisingly differentiated way—those particular facets of affect that are more/less prevalent at a certain moment are believed to occur more/less often in general. We stress the need for repeated observations within individuals to estimate state contributions to standard assessments of trait affect, to distinguish between state and trait in psychological assessment, and to achieve good indicators of affective experiences in the social and medical sciences