Integration and Visualization of Time Series Expression Data of Gene Regulatory Networks.

Time series expression experiments are used to measure the expression of thousands of genes at a time under certain conditions, such as disease or drug treatment. By evaluating the large amounts of data, scientists gather valuable knowledge on various biological questions. An important problem addressed by the study of time series experiments is the discovery of gene function, since it is still unknown for a large set of genes. A web application- Expression Data Visualiser (EDVis), that enables the integration, visualization and evaluation of time series expression data, was developed and evaluated in the course of the thesis. EDVis provides several methods for comparison of time courses: Euclidean distance, Pearson and Spearman correlation and Dynamic Time Warping algorithm. Thus, one can identify highly correlated curves which in turn determine a possible similar function. Furthermore, the tool can be used to construct user-defined regulatory networks which are essential for the study of celullar processes

Do Tangible User Interfaces promote social behaviour during free play? A comparison of autistic and typically-developing children playing with passive and digital construction toys

Background. Little is known about the extent to which embodied digital mediation may support social engagement between children with or without autism (ASD) in free play settings. This study draws on Affordance theory and Sociocultural theory to investigate social play behaviours associated with use of a Tangible User Interface (TUI) during free play. Method. The study used a detailed observational and descriptive design. Two groups of children with ASD and two groups of typically developing (TD) children were filmed during a 20-minute play session with either a passive toy, or a digital toy with a TUI. Behaviours were coded according to a scheme based on Parten’s Play States. Data were described in terms of duration, frequency and the likelihood of transition to another state, given the current state. Results. For TD children, Parallel and Associative were the most frequently observed Play States across both conditions. For those with ASD, Parallel Play and Non-Play-Related Conversation were the most frequent states in the passive condition, while Parallel and Associative Play were the most common in the TUI condition. This group demonstrated a longer duration of co-operative play with the TUI toy compared to TD children. Both groups showed higher frequencies of social play in the TUI condition. Conclusions. Social play states can be effectively mediated by TUIs for both TD and ASD groups. For the ASD group, repetitive behaviour with a TUI may not be inhibitory to social engagement. Practitioners may consider making TUI enabled toys available during free play opportunities.LEGO Foundatio

Exploring the Relationship between Social Class and Quality of Life: the Mediating Role of Power and Status

Funder: Universität zu Köln (1017)AbstractWhy does social class affect Quality of Life? We simultaneously investigated two novel possible explanations: Because a high social class is associated with increased control over resources (i.e., power) or because a high social class is associated with higher respect and esteem in the eyes of others (i.e., status). To test these explanations, we collected data from 384 US-based individuals. We measured their social class, power, status, and four facets of Quality of Life (physical, mental, social, and environmental). For each facet, we calculated the correlation with social class. Next, we tested whether the relationship between social class and the specific facet was mediated by power, status, or both. Social class correlated significantly with all facets of Quality of Life (physical, mental, social, and environmental). Using parallel mediation models, we found that this positive relationship was mediated by status, but not by power. For some facets of Quality of Life (physical, environmental), power even had a negative indirect effect. These results suggest that upper-class individuals indeed have a higher Quality of Life. However, this seems to be mostly due to the increased status of upper-class individuals, whereas power was less important or even had detrimental effects on Quality of Life. Researchers and policymakers aiming to address class-based Quality of Life inequality could thus benefit from focusing on status as an important mediator. Moreover, our work demonstrates the importance of considering power and status as distinct constructs, in order to fully unravel the relationship between social class and Quality of Life.</jats:p

The Mental Wellbeing of Child and Adolescent Mental Health Service (CAMHS) Workers in England: A Cross-Sectional Descriptive Study Reporting Levels of Burnout, Wellbeing and Job Satisfaction

In the UK, there has been a notable increase in referrals to specialist children’s mental health services. This, coupled with shortages of qualified staff, has raised concerns about the escalating occupational stress experienced by staff in this sector. In this brief report, we present cross-sectional quantitative data from 97 staff members working in one Child and Adolescent Mental Health Service (CAMHS) in the UK during spring 2023, reporting on their wellbeing, job satisfaction, and burnout. Our findings reveal that over a third of CAMHS staff experienced moderate or high levels of work-related burnout; 39% reported moderate or high levels of personal burnout, but levels of client-related burnout were much lower (13%). Both work- and client-related burnout showed a robust negative relationship with job satisfaction, with higher burnout predicting lower levels of job satisfaction. Only a small proportion of respondents reported high levels of wellbeing, with about a quarter experiencing levels of wellbeing that can be considered indicative of mild or clinical depressive symptoms. Whilst these results are from a small sample in one area of the UK, they present an important snapshot of CAMHS staff wellbeing and are discussed in the context of similar trends reported in the wider NHS sector

Bridging brain and cognition: a multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role 'between' brain and behavior. We discuss implications and possible avenues for future studies.Stress and Psychopatholog

The general fault in our fault lines

Pervading global narratives suggest that political polarization is increasing, yet the accuracy of such group meta-perceptions has been drawn into question. A recent US study suggests that these beliefs are inaccurate and drive polarized beliefs about out-groups. However, it also found that informing people of inaccuracies reduces those negative beliefs. In this work, we explore whether these results generalize to other countries. To achieve this, we replicate two of the original experiments with 10,207 participants across 26 countries. We focus on local group divisions, which we refer to as fault lines. We find broad generalizability for both inaccurate meta-perceptions and reduced negative motive attribution through a simple disclosure intervention. We conclude that inaccurate and negative group meta-perceptions are exhibited in myriad contexts and that informing individuals of their misperceptions can yield positive benefits for intergroup relations. Such generalizability highlights a robust phenomenon with implications for political discourse worldwide

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions 1, with behavioural science increasingly part of this process 2. In April 2020, an influential paper 3 proposed 19 policy recommendations (‘claims’) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms ‘physical distancing’ and ‘social distancing’. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization

A synthesis of evidence for policy from behavioural science during COVID-19

Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization