The Use of Digital Technologies at School and Cognitive Learning Outcomes : A Population-Based Study in Finland

Recently, the use of information and communications technology (ICT) at school has been extensively increased in Finland. This study investigated whether the use of ICT at school is linked to students 'learning outcomes in Finland. We used the Finnish PISA 2015 data (N=5037). Cognitive learning outcomes (i.e. science, mathematics, reading, collaborative problem-solving) were evaluated with computer-based tests. ICT use at school, ICT availability at school, and students' perceived ICT competence were assessed with self-rating questionnaires. Frequent ICT use at school predicted students' weaker performance in all the cognitive learning outcomes, when adjusted for age, gender, parental socioeconomic status, students' ICT competence, and ICT availability at school. Further, the effect of ICT use on learning outcomes was more negative in students with higher than lower ICT skills. Frequent use of ICT at school appears to be linked to weaker cognitive learning outcomes in Finland. This may be explained by working memory overload and task-switching during the use of digital technologies. This finding also suggests that even though students with ICT skills are good at mechanical use of digital device, they may not have abilities for a goal-oriented and self-directed use of digital technologies that could promote their learning.Peer reviewe

Somatic complaints in early adulthood predict the developmental course of compassion into middle age

Objective: The aim of the present study was to investigate (i) whether somatic complaints predict the developmental course of compassion in adulthood, and (ii) whether this association depends on alexithymic features. Methods: The participants came from the population-based Young Finns study (N = 471-1037). Somatic complaints (headache, stomachache, chest pain, backache, fatigue, exhaustion, dizziness, heartburn, heartbeat, and tension) were evaluated with a self-rating questionnaire in 1986 when participants were aged between 18 and 24 years. Compassion was assessed with the Compassion Scale of the Temperament and Character Inventory (TCI) in 1997, 2001, and 2012. The data were analyzed using growth curve models. Results: We obtained a significant compassion-age interaction (B = -0.137, p =.02) and a compassion -age squared interaction (B = 0.007, p =.006), when predicting the course of somatic complaints. Specifically, in participants without frequent somatic complaints, compassion steadily increased with age in adulthood. In participants with frequent somatic complaints, however, compassion remained at a lower level until the age of 40 years, then started to increase, and achieved the normal level of compassion approximately at the age of 50 years. The association between somatic complaints and compassion over age was found to be independent of alexithymic features. The analyses were adjusted for a variety of covariates (age, gender, use of health care in childhood, depression in childhood, parental socioeconomic factors, parental care-giving practices, stressful life events, parental alcohol intoxication, and participants' socioeconomic factors in adulthood). Conclusion: Frequent somatic complaints may predict delayed development of compassion in adulthood. This association was found to be independent of alexithymic features.Peer reviewe

Does Compassion Predict Blood Pressure and Hypertension? The Modifying Role of Familial Risk for Hypertension

Background This study investigated (i) whether compassion is associated with blood pressure or hypertension in adulthood and (ii) whether familial risk for hypertension modifies these associations. Method The participants (N = 1112-1293) came from the prospective Young Finns Study. Parental hypertension was assessed in 1983-2007; participants' blood pressure in 2001, 2007, and 2011; hypertension in 2007 and 2011 (participants were aged 30-49 years in 2007-2011); and compassion in 2001. Results High compassion predicted lower levels of diastolic and systolic blood pressure in adulthood. Additionally, high compassion was related to lower risk for hypertension in adulthood among individuals with no familial risk for hypertension (independently of age, sex, participants' and their parents' socioeconomic factors, and participants' health behaviors). Compassion was not related to hypertension in adulthood among individuals with familial risk for hypertension. Conclusion High compassion predicts lower diastolic and systolic blood pressure in adulthood. Moreover, high compassion may protect against hypertension among individuals without familial risk for hypertension. As our sample consisted of comparatively young participants, our findings provide novel implications for especially early-onset hypertension.Peer reviewe

The relationship of dispositional compassion with well-being : a study with a 15-year prospective follow-up

We investigated the associations of individual's compassion for others with his/her affective and cognitive well-being over a long-term follow-up. We used data from the prospective Young Finns Study (N = 1312-1699) between 1997-2012. High compassion was related to higher indicators of affective well-being: higher positive affect (B = 0.221, p <.001), lower negative affect (B = -0.358, p <.001), and total score of affective well-being (the relationship of positive versus negative affect) (B = 0.345, p <.001). Moreover, high compassion was associated with higher indicators of cognitive well-being: higher social support (B = 0.194, p <.001), life satisfaction (B = 0.149, p <.001), subjective health (B = 0.094, p <.001), optimism (B = 0.307, p <.001), and total score of cognitive well-being (B = 0.265, p <.001). Longitudinal analyses showed that high compassion predicted higher affective well-being over a 15-year follow-up (B = 0.361, p <.001) and higher social support over a 10-year follow-up (B = 0.230, p <.001). Finally, compassion was more likely to predict well-being (B = [-0.076; 0.090]) than vice versa, even though the predictive relationships were rather modest by magnitude.Peer reviewe

Structural and functional alterations in the brain gray matter among first-degree relatives of schizophrenia patients : A multimodal meta-analysis of fMRI and VBM studies

Objective: We conducted a multimodal coordinate-based meta-analysis (CBMA) to investigate structural and functional brain alterations in first-degree relatives of schizophrenia patients (FRs). Methods: We conducted a systematic literature search from electronic databases to find studies that examined differences between FRs and healthy controls using whole-brain functional magnetic resonance imaging (fMRI) or voxel-based morphometry (VBM). A CBMA of 30 fMRI (754 FRs; 959 controls) and 11 VBM (885 FRs; 775 controls) datasets were conducted using the anisotropic effect-size version of signed differential mapping. Further, we conducted separate meta-analyses about functional alterations in different cognitive tasks: social cognition, executive functioning, working memory, and inhibitory control. Results: FRs showed higher fMRI activation in the right frontal gyrus during cognitive tasks than healthy controls. In VBM studies, there were no differences in gray matter density between FRs and healthy controls. Furthermore, multi-modal meta-analysis obtained no differences between FRs and healthy controls. By utilizing the BrainMap database, we showed that the brain region which showed functional alterations in FRs (i) overlapped only slightly with the brain regions that were affected in the meta-analysis of schizophrenia patients and (ii) correlated positively with the brain regions that exhibited increased activity during cognitive tasks in healthy individuals. Conclusions: Based on this meta-analysis, FRs may exhibit only minor functional alterations in the brain during cognitive tasks, and the alterations are much more restricted and only slightly overlapping with the regions that are affected in schizophrenia patients. The familial risk did not relate to structural alterations in the gray matter. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe

Does Compassion Predict Blood Pressure and Hypertension? The Modifying Role of Familial Risk for Hypertension

Background This study investigated (i) whether compassion is associated with blood pressure or hypertension in adulthood and (ii) whether familial risk for hypertension modifies these associations. Method The participants (N = 1112-1293) came from the prospective Young Finns Study. Parental hypertension was assessed in 1983-2007; participants' blood pressure in 2001, 2007, and 2011; hypertension in 2007 and 2011 (participants were aged 30-49 years in 2007-2011); and compassion in 2001. Results High compassion predicted lower levels of diastolic and systolic blood pressure in adulthood. Additionally, high compassion was related to lower risk for hypertension in adulthood among individuals with no familial risk for hypertension (independently of age, sex, participants' and their parents' socioeconomic factors, and participants' health behaviors). Compassion was not related to hypertension in adulthood among individuals with familial risk for hypertension. Conclusion High compassion predicts lower diastolic and systolic blood pressure in adulthood. Moreover, high compassion may protect against hypertension among individuals without familial risk for hypertension. As our sample consisted of comparatively young participants, our findings provide novel implications for especially early-onset hypertension

A Longitudinal Multilevel Study of the "Social" Genotype and Diversity of the Phenotype

Sociability and social domain-related behaviors have been associated with better well-being and endogenous oxytocin levels. Inspection of the literature, however, reveals that the effects between sociability and health outcomes, or between sociability and genotype, are often weak or inconsistent. In the field of personality psychology, the social phenotype is often measured by error-prone assessments based on different theoretical frameworks, which can partly explain the inconsistency of the previous findings. In this study, we evaluated the generalizability of "sociability" measures by partitioning the population variance in adulthood sociability using five indicators from three personality inventories and assessed in two to four follow-ups over a 15-year period (n = 1,573 participants, 28,323 person-observations; age range 20-50 years). Furthermore, we tested whether this variance partition would shed more light to the inconsistencies surrounding the "social" genotype, by using four genetic variants (rs1042778, rs2254298, rs53576, rs3796863) previously associated with a wide range of human social functions. Based on our results, trait (between-individual) variance explained 23% of the variance in overall sociability, differences between sociability indicators explained 41%, state (within-individual) variance explained 5% and measurement errors explained 32%. The genotype was associated only with the sociability indicator variance, suggesting it has specific effects on sentimentality and emotional sharing instead of reflecting general sociability

Evolution of genetic networks for human creativity

The genetic basis for the emergence of creativity in modern humans remains a mystery despite sequencing the genomes of chimpanzees and Neanderthals, our closest hominid relatives. Data-driven methods allowed us to uncover networks of genes distinguishing the three major systems of modern human personality and adaptability: emotional reactivity, self-control, and self-awareness. Now we have identified which of these genes are present in chimpanzees and Neanderthals. We replicated our findings in separate analyses of three high-coverage genomes of Neanderthals. We found that Neanderthals had nearly the same genes for emotional reactivity as chimpanzees, and they were intermediate between modern humans and chimpanzees in their numbers of genes for both self-control and self-awareness. 95% of the 267 genes we found only in modern humans were not protein-coding, including many long-non-coding RNAs in the self-awareness network. These genes may have arisen by positive selection for the characteristics of human well-being and behavioral modernity, including creativity, prosocial behavior, and healthy longevity. The genes that cluster in association with those found only in modern humans are over-expressed in brain regions involved in human self-awareness and creativity, including late-myelinating and phylogenetically recent regions of neocortex for autobiographical memory in frontal, parietal, and temporal regions, as well as related components of cortico-thalamo-ponto-cerebellar-cortical and cortico-striato-cortical loops. We conclude that modern humans have more than 200 unique non-protein-coding genes regulating co-expression of many more protein-coding genes in coordinated networks that underlie their capacities for self-awareness, creativity, prosocial behavior, and healthy longevity, which are not found in chimpanzees or Neanderthals.Peer reviewe

Finding reliable subgraphs from large probabilistic graphs

Reliable subgraphs can be used, for example, to find and rank nontrivial links between given vertices, to concisely visualize large graphs, or to reduce the size of input for computationally demanding graph algorithms. We propose two new heuristics for solving the most reliable subgraph extraction problem on large, undirected probabilistic graphs. Such a problem is specified by a probabilistic graph G subject to random edge failures, a set of terminal vertices, and an integer K. The objective is to remove K edges from G such that the probability of connecting the terminals in the remaining subgraph is maximized. We provide some technical details and a rough analysis of the proposed algorithms. The practical performance of the methods is evaluated on real probabilistic graphs from the biological domain. The results indicate that the methods scale much better to large input graphs, both computationally and in terms of the quality of the result.Reliable subgraphs can be used, for example, to find and rank nontrivial links between given vertices, to concisely visualize large graphs, or to reduce the size of input for computationally demanding graph algorithms. We propose two new heuristics for solving the most reliable subgraph extraction problem on large, undirected probabilistic graphs. Such a problem is specified by a probabilistic graph G subject to random edge failures, a set of terminal vertices, and an integer K. The objective is to remove K edges from G such that the probability of connecting the terminals in the remaining subgraph is maximized. We provide some technical details and a rough analysis of the proposed algorithms. The practical performance of the methods is evaluated on real probabilistic graphs from the biological domain. The results indicate that the methods scale much better to large input graphs, both computationally and in terms of the quality of the result.Reliable subgraphs can be used, for example, to find and rank nontrivial links between given vertices, to concisely visualize large graphs, or to reduce the size of input for computationally demanding graph algorithms. We propose two new heuristics for solving the most reliable subgraph extraction problem on large, undirected probabilistic graphs. Such a problem is specified by a probabilistic graph G subject to random edge failures, a set of terminal vertices, and an integer K. The objective is to remove K edges from G such that the probability of connecting the terminals in the remaining subgraph is maximized. We provide some technical details and a rough analysis of the proposed algorithms. The practical performance of the methods is evaluated on real probabilistic graphs from the biological domain. The results indicate that the methods scale much better to large input graphs, both computationally and in terms of the quality of the result.Peer reviewe