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Online communities are virtual spaces for users to share interests, support others, and to exchange knowledge and information. Understanding user behavior is valuable to organizations and has applications from marketing to security, for instance, identifying leaders within a community or predicting future behavior. In the present research, we seek to understand the various roles that users adopt in online communities–for instance, who leads the conversation? Who are the supporters? We examine user role changes over time and the pathways that users follow. This allows us to explore the differences between users who progress to leadership positions and users who fail to develop influence. We also reflect on how user role proportions impact the overall health of the community. Here, we examine two online ideological communities, RevLeft and Islamic Awakening (N = 1631; N = 849), and provide a novel approach to identify various types of users. Finally, we study user role trajectories over time and identify community “leaders” from meta-data alone. Study One examined both communities using K-MEANS cluster analysis of behavioral meta-data, which revealed seven user roles. We then mapped these roles against Preece and Schneiderman’s (2009) Reader-to-Leader Framework (RtLF). Both communities aligned with the RtLF, where most users were “contributors”, many were “collaborators”, and few were “leaders”. Study Two looked at one community over a two-year period and found that, despite a high churn rate of users, roles were stable over time. We built a model of user role transitions over the two years. This can be used to predict user role changes in the future, which will have implications for community managers and security focused contexts (e.g., analyzing behavioral meta-data from forums and websites known to be associated with illicit activity). [ABSTRACT FROM AUTHOR]

As the challenge of mental health problems such as anxiety and depression increasing today, more convenient, objective, real-time assessing techniques of mental state are in need. The Microsoft Kinect camera is a possible option for contactlessly capturing human gait, which could reflect the walkers’ mental state. So we tried to propose a novel method for monitoring individual’s anxiety and depression based on the Kinect-recorded gait pattern. In this study, after finishing the 7-item Generalized Anxiety Disorder Scale (GAD-7) and the 9-item Patient Health Questionnaire (PHQ-9), 179 participants were required to walked on the footpath naturally while shot by the Kinect cameras. Fast Fourier Transforms (FFT) were conducted to extract features from the Kinect-captured gait data after preprocessing, and different machine learning algorithms were used to train the regression models recognizing anxiety and depression levels, and the classification models detecting the cases with specific depressive symptoms. The predictive accuracies of the regression models achieved medium to large level: The correlation coefficient between predicted and questionnaire scores reached 0.51 on anxiety (by epsilon-Support Vector Regression, e-SVR) and 0.51 on depression (by Gaussian Processes, GP). The predictive accuracies could be even higher, 0.74 on anxiety (by GP) and 0.64 on depression (by GP), while training and testing the models on the female sample. The classification models also showed effectiveness on detecting the cases with some symptoms. These results demonstrate the possibility to recognize individual’s questionnaire measured anxiety/depression levels and some depressive symptoms based on Kinect-recorded gait data through machine learning method. This approach shows the potential to develop non-intrusive, low-cost methods for monitoring individuals’ mental health in real time. [ABSTRACT FROM AUTHOR]

The activity of neural populations in the brains of humans and animals can exhibit vastly different spatial patterns when faced with different tasks or environmental stimuli. The degrees of similarity between these neural activity patterns in response to different events are used to characterize the representational structure of cognitive states in a neural population. The dominant methods of investigating this similarity structure first estimate neural activity patterns from noisy neural imaging data using linear regression, and then examine the similarity between the estimated patterns. Here, we show that this approach introduces spurious bias structure in the resulting similarity matrix, in particular when applied to fMRI data. This problem is especially severe when the signal-to-noise ratio is low and in cases where experimental conditions cannot be fully randomized in a task. We propose Bayesian Representational Similarity Analysis (BRSA), an alternative method for computing representational similarity, in which we treat the covariance structure of neural activity patterns as a hyper-parameter in a generative model of the neural data. By marginalizing over the unknown activity patterns, we can directly estimate this covariance structure from imaging data. This method offers significant reductions in bias and allows estimation of neural representational similarity with previously unattained levels of precision at low signal-to-noise ratio, without losing the possibility of deriving an interpretable distance measure from the estimated similarity. The method is closely related to Pattern Component Model (PCM), but instead of modeling the estimated neural patterns as in PCM, BRSA models the imaging data directly and is suited for analyzing data in which the order of task conditions is not fully counterbalanced. The probabilistic framework allows for jointly analyzing data from a group of participants. The method can also simultaneously estimate a signal-to-noise ratio map that shows where the learned representational structure is supported more strongly. Both this map and the learned covariance matrix can be used as a structured prior for maximum a posteriori estimation of neural activity patterns, which can be further used for fMRI decoding. Our method therefore paves the way towards a more unified and principled analysis of neural representations underlying fMRI signals. We make our tool freely available in Brain Imaging Analysis Kit (BrainIAK). [ABSTRACT FROM AUTHOR]

Purpose: To assess the effectiveness of Home Fire Safety (HFS) interventions versus other interventions/no interventions/controls on HFS knowledge and behaviour at short-, intermediate- and long-term follow ups. Design: Systematic review and meta-analysis of randomized controlled trials. Data sources: MEDLINE, EMBASE and PubMed databases were searched from January 1998 to July 2018, and studies retrieved. Participants: Toddlers, children (primary or secondary school), teenagers or adults. Interventions/Comparison: HFS interventions compared to other interventions / no interventions / controls. Outcomes: HFS knowledge and behaviour. Results: 10 studies were identified (8 RCTs and 2 prospective cohort). Two studies assessed the effects of HFS interventions vs no interventions on HFS knowledge at up to 4 months follow up in school children and demonstrated significant difference between groups (very low quality, 2 RCTs, 535 participants, SMD 0.38, 95% CI: 0.21 to 0.55, p < 0.001). One study examined the effects of different modes of HFS interventions (computer-based vs instructor-led) on HFS knowledge and behaviour immediately post-intervention in adults and displayed no significant difference between groups (HFS knowledge; very low quality, 1 RCT, 68 participants, SMD -0.02, 95% CI: -0.50 to 0.45, p = 0.92) and (HFS behaviour; very low quality, 1 RCT, 68 participants, SMD 0.06, 95% CI: -0.41 to 0.54, p = 0.79) respectively. Conclusion: The limited evidence supports the use of HFS interventions to improve HFS knowledge and behaviour in children, families with children and adults. [ABSTRACT FROM AUTHOR]

We report a systematic review and meta-analysis of research using animal models of chemotherapy-induced peripheral neuropathy (CIPN). We systematically searched 5 online databases in September 2012 and updated the search in November 2015 using machine learning and text mining to reduce the screening for inclusion workload and improve accuracy. For each comparison, we calculated a standardised mean difference (SMD) effect size, and then combined effects in a random-effects meta-analysis. We assessed the impact of study design factors and reporting of measures to reduce risks of bias. We present power analyses for the most frequently reported behavioural tests; 337 publications were included. Most studies (84%) used male animals only. The most frequently reported outcome measure was evoked limb withdrawal in response to mechanical monofilaments. There was modest reporting of measures to reduce risks of bias. The number of animals required to obtain 80% power with a significance level of 0.05 varied substantially across behavioural tests. In this comprehensive summary of the use of animal models of CIPN, we have identified areas in which the value of preclinical CIPN studies might be increased. Using both sexes of animals in the modelling of CIPN, ensuring that outcome measures align with those most relevant in the clinic, and the animal’s pain contextualised ethology will likely improve external validity. Measures to reduce risk of bias should be employed to increase the internal validity of studies. Different outcome measures have different statistical power, and this can refine our approaches in the modelling of CIPN. [ABSTRACT FROM AUTHOR]

Background: The Best Possible Self is a Positive Psychology Intervention which asks participants to write down about themselves in their best possible future. Previous studies have shown its efficacy to enhance wellbeing, but the mechanisms that underlie its efficacy are still unknown. Objective: The aim of this study was to analyze the content of the essays of the BPS intervention and to examine how this content was related to the efficacy of the intervention to increase positive affect. Method: Participants (N = 78) were randomized to either the Best Possible Self condition, or one of two variants of the intervention: one’s best self in the present, and one’s best self in the past. Qualitative analyses of the texts were carried out to explore the main themes and features of the essays. Then, a mixed-methods approach with quantitative and qualitative data was followed, in order to analyze the relationship between the content of the texts and the change in positive affect produced by the interventions. Results: Significant differences between conditions were found in the content of the compositions. Regression analyses showed that different variables predicted the change in positive affect depending on the condition. Mediation analyses also found differences among conditions. Conclusions: These findings suggest that these interventions respond to different underlying mechanisms which influence their efficacy. This study contributed to a better understanding of how Positive Psychology Interventions work, and how to increment their efficacy. [ABSTRACT FROM AUTHOR]

Success in different soccer skills like kicking depends on motor abilities achieved. Kicking is a soccer fundamental, which depends on many different and complex factors (technique, foot-ball interaction, ball flight, etc.). Therefore, it is important to identify players that are able to perform faster kicks using both dominant and non-dominant leg. The current study investigated some basic variables of different soccer kicking speed and their relevance to success in youth soccer academy. 119 players from the first and the second division participated to this study. They were randomly divided into age groups (U-15, U-17, and U19) and team status (first team, reserves). The diagnostic ability of the different ball kicking speed tests in capturing differences between first team players and reserves among different age categories were computed using the receiver operating characteristics analysis. Results demonstrated that first team players achieved better results when comparing to reserves in each category. In addition, differences were greater in the U-15 and the U-17 than in the U-19 age group. In conclusion, ball kicking speed could be one of the possible identification tools to evaluate players' success in youth soccer. [ABSTRACT FROM AUTHOR]

Representations of the body and peripersonal space can be distorted for people with some chronic pain conditions. Experimental pain induction can give rise to similar, but transient distortions in healthy individuals. However, spatial and bodily representations are dynamic, and constantly update as we interact with objects in our environment. It is unclear whether induced pain disrupts the mechanisms involved in updating these representations. In the present study, we sought to investigate the effect of induced pain on the updating of peripersonal space and body representations during and following tool-use. We compared performance under three conditions (pain, active placebo, neutral) on a visuotactile crossmodal congruency task and a tactile distance judgement task to measure updating of peripersonal space and body representations, respectively. Consistent with previous findings, the difference in crossmodal interference from visual distractors in the same compared to opposite visual field to the tactile target was less when tools were crossed than uncrossed. This suggests an extension of peripersonal space to incorporate the tips of the tools. Also consistent with previous findings, estimates of the felt tactile distance judgements decreased after active tool-use. In contrast to our predictions, however, we found no evidence that pain interfered with performance on either task when compared to the control conditions. Our findings suggest that the updating of peripersonal space and body representations is not disrupted by induced pain. That is, experiencing acute pain does not give rise to distorted representations of the body and peripersonal space that can be present in people with chronic pain conditions. [ABSTRACT FROM AUTHOR]

Background: Critical care intensity is known to vary across regions and centers, yet the mechanisms remain unidentified. Physician behaviors have been implicated in the variability of intensive care near the end of life, but physician characteristics that may underlie this association have not been determined. Purpose: We sought to identify behavioral attributes that vary among intensivists to generate hypotheses for mechanisms of intensivist-attributable variation in critical care delivery. Methods: We administered a questionnaire to intensivists who participated in a prior cohort study in which intensivists made prognostic estimates. We evaluated the degree to which scores on six attribute measures varied across intensivists. Measures were selected for their relevance to preference-sensitive critical care: a modified End-of-Life Preferences (EOLP) scale, Life Orientation Test–Revised (LOT-R), Jefferson Scale of Empathy (JSE), Physicians' Reactions to Uncertainty (PRU) scale, Collett-Lester Fear of Death (CLFOD) scale, and a test of omission bias. We conducted regression analyses assessing relationships between intensivists’ attribute scores and their prognostic accuracy, as physicians’ prognostic accuracy may influence preference-sensitive decisions. Results: 20 of 25 eligible intensivists (80%) completed the questionnaire. Intensivists’ scores on the EOLP, LOT-R, PRU, CLFOD, and omission bias measures varied considerably, while their responses on the JSE scale did not. There were no consistent associations between attribute scores and prognostic accuracy. Conclusions: Intensivists vary in feasibly measurable attributes relevant to preference-sensitive critical care delivery. These attributes represent candidates for future research aimed at identifying mechanisms of clinician-attributable variation in critical care and developing effective interventions to reduce undue variation. [ABSTRACT FROM AUTHOR]

How do echo chambers operate? Why does social propagation of information become trapped within the boundaries of social groups? Previous studies of these questions have identified informational and structural factors which hinder information exchange across group boundaries; these factors constitute “chambers” in which information flows are confined and transformed into “echoes.” However, empirical evidence has indicated that these factors may not sufficiently explain the mechanism of echo chambers. Hence, the present study investigated whether the insular flow of information emerges and endures without the chambers. A randomized controlled experiment was conducted in which participants, who were classified into two political groups, exchanged randomly selected articles with the same number of ingroup and outgroup neighbors. The experiment manipulated the directionality of incoming information flow by varying the number of articles sent from ingroup neighbors across two conditions. Analyses revealed that the ingroup-slanted inflow induced ingroup-slanted outflow, suppressing transmission toward neighbors in a different social group. The biased inflow also promoted positive reactions to information exchanges and reduced negative evaluations on the exchanged information. Furthermore, the ingroup-slanted inflow increased false perceptions of ingroup majority, which is known to encourage information dissemination by a social group. The present study suggests two self-reinforcing mechanisms of ingroup-biased flows that generate echoes even without the chambers. These mechanisms may enable a small group of strategic actors to exacerbate polarization within a large population by manipulating directions of information flow. [ABSTRACT FROM AUTHOR]

Lane change violations are a major cause of traffic conflicts and accidents at urban intersections and one of many road-safety issues in China. This study aims to explore the socio-psychological factors underlying drivers’ motivation for lane change violation behavior at urban intersections and examines how these factors predict this violation behavior. A self-reported questionnaire is designed by applying the construct of the theory of planned behavior (TPB) to collect data. Five hundred-six valid responses are received from the questionnaire survey conducted on the Internet in China. The data are then analyzed using structural equation modeling (SEM). The results of the analysis show that behavioral intention is the strongest predictor of self-reported lane change violation behavior at urban intersections. Perceived behavioral control has both direct and indirect effects on self-reported lane change violation behavior. Furthermore, attitude, subjective norms and perceived behavioral control are found to have significant correlations with drivers’ intention of lane change violations at urban intersections. The results of this study could provide a reference for designing more effective interventions to modify drivers’ lane change violation behavior at urban intersections. [ABSTRACT FROM AUTHOR]

We present a study of the dimensionality and factorial invariance of religiosity for 26 countries with a Christian heritage, based on the 1998 and 2008 rounds of the International Social Survey Programme (ISSP) Religion survey, using both exploratory and multi-group confirmatory factor analyses. The results of the exploratory factor analysis showed that three factors, common to Christian and religiously unaffiliated respondents, could be extracted from our initially selected items and suggested the testing of four different three-factor models using multi-group confirmatory factor analysis. For the model with the best fit and measurement invariance properties, we labeled the three resulting factors as “Beliefs in afterlife and miracles”, “Belief and importance of God” and “Religious involvement.” The first factor is measured by four items related to the Supernatural Beliefs Scale (SBS-6); the second by three items related to belief in God and God’s perceived roles as a supernatural agent; and the third one by three items with the same structure found in previous cross-cultural analyses of religiosity using the European Values Survey (ESS) and also by belief in God. Unexpectedly, we found that one item, belief in God, cross-loaded on to the second and third factors. We discussed possible interpretations for this finding, together with the potential limitations of the ISSP Religion questionnaire for revealing the structure of religiosity. Our tests of measurement invariance across gender, age, educational degree and religious (un)affiliation led to acceptance of the hypotheses of metric- and scalar-invariance for these groupings (units of analysis). However, in the measurement invariance tests across the countries, the criteria for metric invariance were met for twenty-three countries only, and partial scalar invariance was accepted for fourteen countries only. The present work shows that the exploration of large multinational and cross-cultural datasets for studying the dimensionality and invariance of social constructs (in our case, religiosity) yields useful results for cross-cultural comparisons, but is also limited by the structure of these datasets and the way specific items are coded. [ABSTRACT FROM AUTHOR]

How the brain makes sense of a complicated environment is an important question, and a first step is to be able to reconstruct the stimulus that give rise to an observed brain response. Neural coding relates neurobiological observations to external stimuli using computational methods. Encoding refers to how a stimulus affects the neuronal output, and entails constructing a neural model and parameter estimation. Decoding refers to reconstruction of the stimulus that led to a given neuronal output. Existing decoding methods rarely explain neuronal responses to complicated stimuli in a principled way. Here we perform neural decoding for a mixture of multiple stimuli using the leaky integrate-and-fire model describing neural spike trains, under the visual attention hypothesis of probability mixing in which the neuron only attends to a single stimulus at any given time. We assume either a parallel or serial processing visual search mechanism when decoding multiple simultaneous neurons. We consider one or multiple stochastic stimuli following Ornstein-Uhlenbeck processes, and dynamic neuronal attention that switches following discrete Markov processes. To decode stimuli in such situations, we develop various sequential Monte Carlo particle methods in different settings. The likelihood of the observed spike trains is obtained through the first-passage time probabilities obtained by solving the Fokker-Planck equations. We show that the stochastic stimuli can be successfully decoded by sequential Monte Carlo, and different particle methods perform differently considering the number of observed spike trains, the number of stimuli, model complexity, etc. The proposed novel decoding methods, which analyze the neural data through psychological visual attention theories, provide new perspectives to understand the brain. [ABSTRACT FROM AUTHOR]

Involving patients in research broadens a researcher’s field of influence and may generate novel ideas. Preclinical research is integral to the progression of innovative healthcare. These are not patient-facing disciplines and implementing meaningful public and patient involvement (PPI) can be a challenge. A discussion forum and thematic analysis identified key challenges of implementing public and patient involvement for preclinical researchers. In response we developed a “PPI Ready” planning canvas. For contemporaneous evaluation of public and patient involvement, a psychometric questionnaire and an open source tool for its evaluation were developed. The questionnaire measures information, procedural and quality assessment. Combined with the open source evaluation tool, researchers are notified if public and patient involvement is unsatisfactory in any of these areas. The tool is easy to use and adapts a psychometric test into a format familiar to preclinical scientists. Designed to be used iteratively across a research project, it provides a simple reporting grade to document satisfaction trend over the research lifecycle. [ABSTRACT FROM AUTHOR]

Introduction: Only a few, large population-based studies, have reported on whiplash-associated disorder (WAD). However, none of them have investigated the influence of crash severity on WAD outcome. In the present study, we aimed to determine whether crash severity predicts outcomes among patients with no-fault government insurance for acute WAD. Methods: We utilized data from a compulsory, no-fault government automobile liability insurance agency in Japan. Individuals involved in a car accident between April 2001 and June 2015 with residual disabilities reported at the end of the treatment between October 2014 and September 2015 were included. Crash severity was assessed based on property damage costs, size of the other vehicle (large car, medium car, small car, or two-wheeled vehicles), and collision types (rear-end collision, contact with vehicle moving in the same direction, or in the opposite direction). Outcomes included the time to claim closure and the number of treatment visits. Results: We analyzed data for a total of 52,251 individuals (28,571 male and 23,680 female) with a median age of 44 years (range: 2–95 years). The median time to claim closure was 220 days (range: 1–4,938 days), and the median number of treatment visits was 102 (range: 1–2,492). There was no significant association between outcomes and property damage costs or size of the other vehicle. Collision types exhibited no consistent association with outcomes. However, older age and affected body parts, in addition to the neck, were independent risk factors for delayed claim closure and a large number of visits, although, all odds ratios were low (often less than 2.0). Conclusions: There was no obvious association of outcomes with property damage costs, size of the other vehicle, or collision types in acute WAD patients. Further studies should investigate the influence of psychological factors, compensation systems, and cultural conditions. [ABSTRACT FROM AUTHOR]

Humans exert a great deal of control over our local environments–selecting and arranging the many objects around us on the basis of conflicting task-demands, aesthetic preferences, and habitual convenience. Because routine behaviour necessitates that we regularly find and access these objects, the particular arrangements we choose can influence the likelihood and difficulty of engaging in different tasks and actions. Despite this importance, relatively little research has directly examined human organizational behaviours and tendencies. Here we investigate how objects in a computer-based search task are freely and dynamically arranged by participants over time, while manipulating the statistics of the target sequence. We report common organizational behaviours including reduction of distance between targets as well as separation of target subsets with high community. However, the extent of these behaviours and their relationship to individual differences in performance varies as a function of the target sequence structure. In particular, tasks composed of a larger number of smaller groups of targets lead to better organizational and performance outcomes than tasks composed of fewer larger groups. [ABSTRACT FROM AUTHOR]

In an online Qualtrics panel survey experiment (N = 1620), we found that scientists posting self-portraits (“selfies”) to Instagram from the science lab/field were perceived as significantly warmer and more trustworthy, and no less competent, than scientists posting photos of only their work. Participants who viewed scientist selfies, especially posts containing the face of a female scientist, perceived scientists as significantly warmer than did participants who saw science-only images or control images. Participants who viewed selfies also perceived less symbolic threat from scientists. Most encouragingly, participants viewing selfies, either of male or female scientists, did not perceive scientists as any less competent than did participants viewing science-only or control images. Subjects who viewed female scientist selfies also perceived science as less exclusively male. Our findings suggest that self-portraiture by STEM professionals on social media can mitigate negative attitudes toward scientists. [ABSTRACT FROM AUTHOR]

Audiovisual educational material has been used effectively as a knowledge translation strategy in patient education. Given the need to impact maternal mortality rates, 12 video clips related to maternal and neonatal health information were designed based on the results of a previous systematic review (SR). The content was formulated based on clinical practice guideline recommendations and validated following a formal consensus methodology. This study evaluated the effectiveness of knowledge transfer from the 12 video clips in terms of attention, emotional response, and recall by using neuroscience tools. In a randomized cross-over trial, 155 subjects (pregnant women, non-pregnant women, and men) received random sequences of 13 video clips, including a control video clip. Participants’ attention levels were evaluated through eye tracking, their emotional reactions were monitored by electrodermal activity and pupillary diameter, and their recall was tested via a questionnaire. An analysis was performed to evaluate differences in the groups and between the video clips and the control clip using variance analysis models that considered period, sequence, and carry-over effects. Results revealed that fixation length was greater in women than in men, while the greatest emotional effects occurred in men. All three groups had good recall results, without any significant differences between them. Although the sequencing did influence attentional processes, no carry-over effect was demonstrated. However, a differential effect was noted among video clips in all three outcomes, that is, when adjusted for group, level of education, and having had children. The control clip generated less attention, emotional reaction, and recall than the experimental video clips. The video clips about maternal and neonatal health were shown to be effective in the transference and comprehension of information. Therefore, cognitive neuroscience techniques are useful in evaluating knowledge translation strategies through audiovisual formats. [ABSTRACT FROM AUTHOR]

Background: Are we more risk-averse or risk-seeking when we make decisions on behalf of other people as opposed to ourselves? So far, findings have not been able to provide a clear and consistent answer. Method: We propose a meta-analysis to assess whether self-other differences vary according to particular features of the decision. We reviewed 78 effect sizes from 49 studies (7,576 participants). Results: There was no overall self-other difference, but there were moderating effects of domain and frame. Decisions in the interpersonal domain were more risk-averse for self than for other. Decisions in the medical domain were more risk-seeking for self than for other. There were no overall self-other differences in the financial domain, however there was a moderating effect of frame: decisions in a gain frame were more risk-averse for self than other whereas decisions in a loss frame were more risk-seeking for self than other. This effect of frame was slightly different overall and in the medical domain, where self-other differences occurred in a loss frame but not in a gain frame. Conclusion: Future work should continue to investigate how the specific content and context of the decision impacts self-other differences in order to understand the effects of domain and frame we report. [ABSTRACT FROM AUTHOR]

When designing mobile games, how to understand preferences and cognition of players is a topic worth exploring. The main objectives of this paper are to obtain design features of music games on mobile devices, and explore players’ perceptions toward music games. The results can serve as an orientation during decision-making in game design. Based on Miryoku Engineering and the Evaluation Grid Method, this study interviewed 22 frequent users to get concrete features of game design; Moreover, 210 subjects were divided into high, medium, and low involvement groups according to CIP measures, and then this study used Multiple Regression analysis to determine whether players with different levels of involvement had different perceptions of the design features of music games. The results found 44 concrete features and six original evaluations items of game design, and also discovered that there were perception differences in different involvement groups, and only two concrete design features significantly influenced all three groups: ‘Extra games to earn more points after completing levels’ and ‘Playable without internet’. [ABSTRACT FROM AUTHOR]

Most studies of social cognition have focused on dyadic relationships, and rather few have looked at how we engage with individuals in the wider social world into which we are embedded. Here we use principle component analysis (PCA) and path analysis to explore how different aspects of human sociality interact. We demonstrate two distinct clusters in both sexes relating to (i) romantic relationships and (ii) wider social engagement, such as that with the local community. These two domains of relationship were associated with different dispositional traits: individual variation in impulsivity in the former, and in empathy and avoidant attachment in the latter. Although these clusters were broadly similar across both sexes, clearer differentiation is evident in males. In females only, support network size was positively related to the anxious dimension of attachment and, unlike in males, was not related to feelings of inclusion in the local community. This suggests that support networks may play different roles in the two sexes, indicating a productive line of future research. These findings have important practical applications: loneliness interventions that target the specific type of relationship that is felt to be lacking and the associated dispositional traits are likely to be more effective than more generic approaches. [ABSTRACT FROM AUTHOR]

Introduction: Factors associated with persistently high Human Immunodeficiency Virus (HIV) prevalence levels in several districts of India are not well understood. This study was undertaken to determine the association of socio-demographic characteristics, economic factors, awareness about HIV and Sexually Transmitted Infections (STIs), and condom use with consistently high HIV prevalence in the Indian districts and to ascertain whether these associations differed across various regions of India. Methods: This study was carried out including all 640 districts of India. Secondary analysis of data obtained from the Census of India-2011, HIV Sentinel Surveillance in India and District Level Household Survey-III was done. Population profile, socio-economic characteristics, levels of HIV/STI/condom awareness and condom use, were compared between the districts with and without consistently high HIV prevalence. Due to the presence of collinearity among predictor variables, we used principal component analysis and the principal component scores were included as covariates for further analysis. Considering the districts at level 1 and the regions at level 2, multi-level analysis was done by generalised linear mixed models. Variance partition coefficient and median odds ratio were also calculated. Results: Sixty-three districts with consistently high HIV prevalence were found clustered in the South and the North-east regions of India. Population size, density and urbanisation were found to be positively associated with consistently high HIV prevalence in these districts. Higher levels of literacy, better socio-economic status, higher proportion of population in reproductive age group and late marriages were positively associated with consistently high HIV prevalence in all regions of India except in the Southern region. Higher levels of knowledge about the role of condoms in HIV prevention and condom use were associated with low HIV prevalence at the district level. Conclusions: Considerable heterogeneity among factors associated with consistently high HIV prevalence at the district level in different regions of India necessitates special region-specific strategies for HIV control. Increasing awareness about HIV alone is not sufficient for controlling the HIV epidemic and there is a need to raise knowledge levels about preventive measures against HIV and promote the use of condoms amongst population. [ABSTRACT FROM AUTHOR]

Feature subspace learning plays a significant role in pattern recognition, and many efforts have been made to generate increasingly discriminative learning models. Recently, several discriminative feature learning methods based on a representation model have been proposed, which have not only attracted considerable attention but also achieved success in practical applications. Nevertheless, these methods for constructing the learning model simply depend on the class labels of the training instances and fail to consider the essential subspace structural information hidden in them. In this paper, we propose a robust feature subspace learning approach based on a low-rank representation. In our approach, the low-rank representation coefficients are considered as weights to construct the constraint item for feature learning, which can introduce a subspace structural similarity constraint in the proposed learning model for facilitating data adaptation and robustness. Moreover, by placing the subspace learning and low-rank representation into a unified framework, they can benefit each other during the iteration process to realize an overall optimum. To achieve extra discrimination, linear regression is also incorporated into our model to enforce the projection features around and close to their label-based centers. Furthermore, an iterative numerical scheme is designed to solve our proposed objective function and ensure convergence. Extensive experimental results obtained using several public image datasets demonstrate the advantages and effectiveness of our novel approach compared with those of the existing methods. [ABSTRACT FROM AUTHOR]

Introduction: Orthorexia nervosa, a term used to describe an obsession with healthy eating, has been shown to have major health implications for those affected. The aim of this study was to validate a Spanish version of the Düsseldorfer Ortorexie Skala (DOS), a questionnaire for the detection of orthorexic behavior. Methods: A cross-sectional study comprising a total sample of 492 Spanish participants recruited from the University of Castilla-La Mancha, Spain, and randomly divided into two groups. The following tools were applied: the DOS and the Eating Disorder Inventory (EDI-2). The factorial structures were analyzed using exploratory and confirmatory factorial analysis. Results: The internal consistency of the DOS-ES was α = .841. The exploratory factor analysis has revealed the existence of a single factor with factor loadings ranging from .508 to .802. A confirmatory factor analysis was applied to the second half of the random sample in order to confirm the factor solution. Conclusion: The Spanish adaptation of the DOS-ES is proven to be a reliable and valid questionnaire for evaluating the obsessive tendency towards healthy eating among university students. [ABSTRACT FROM AUTHOR]

Purpose: To examine the association between adverse childhood experiences (ACEs) and early sexual initiation. Methods: We analyzed retrospective data of (n = 241) Black women recruited from public STD clinics in Baltimore, MD. Multinomial logistic and linear regression models estimated associations between ACEs and early sexual initiation; contextual variables at initiation were examined as mediators. Results: Twelve percent of our sample reported very early sexual initiation (11–12 years) and 29% reported early sexual initiation (13–14 years). Each additional ACE reported was associated with greater risk of very early sexual initiation (RRR = 1.49; 95%CI:1.23,1.80). Specifically, emotional abuse (RRR = 3.71; 95%CI:1.55,8.89), physical abuse (RRR = 9.45; 95%CI:3.56,25.12), sexual abuse (RRR = 8.60; 95%CI:3.29,22.51), witnessing maternal abuse (RRR = 5.56; 95%CI:2.13,14.52), and household substance misuse (RRR = 3.21; 95%CI:1.38,7.47) at or before the age of 18 were associated with very early sexual initiation. As for context of initiation, age at sexual initiation was younger if the man at initiation was a non-partner (ß = -0.88; 95%CI:-1.36,-0.40), was ≥3 years older (ß = -1.30; 95%CI:-1.82,-0.77), had pressured or forced sexual intitiation (ß = -1.09; 95%CI:-1.58,-0.59), and was under the influence of drugs/alcohol (ß = -0.97; 95%CI:-1.62,-0.32). Contextual variables at first sex, including being pressured or forced, and the man being ≥3 years older fully mediated the association between ACEs and early sexual initiation. Conclusions: This study highlights the critical need to develop interventions that reduce the impact of ACEs on women’s health and delay age at sexual initiation. Health education efforts are needed for clinicians and parents to identify and prevent childhood abuse and to identify and report sexual coercion and abuse for girls and adolescents. [ABSTRACT FROM AUTHOR]

Human decision making involving many alternatives is encumbered with inconsistent prioritization. Although inconsistency is assumed to grow with the number of comparisons, it is shown to be reduced by conscious awareness under certain conditions. This study experimentally investigated the effect of repeating a criteria ranking task on inconsistency scores as measured by four different inconsistency coefficients. A total of 107 participants were engaged in a selection task that comprised of ranking from 3 to 10 criteria and was repeated in three trials. Upon completing the first trial, the participants were informed about the inconsistency issues and could improve their ranking in another two trials. The inconsistency score was computed for each set of comparisons and the effect of repeating the selection task on inconsistency concerning the number of criteria was analyzed using the repeated measures ANOVA. The results reveal a significant change in the inconsistency as the task was repeated but the difference depended on the number of criteria. There exists a borderline in the problem size under which the rankings are associated with significantly lower inconsistency, while the rankings with the larger number of criteria were found to have significantly higher inconsistency. [ABSTRACT FROM AUTHOR]

It is easier to indicate the ink color of a color-neutral noun when it is presented in the color in which it has frequently been shown before, relative to print colors in which it has been shown less often. This phenomenon is known as color-word contingency learning. It remains unclear whether participants actually learn semantic (word-color) associations and/or response (word-button) associations. We present a novel variant of the paradigm that can disentangle semantic and response learning, because word-color and word-button associations are manipulated independently. In four experiments, each involving four daily sessions, pseudowords—such as enas, fatu or imot—were probabilistically associated with either a particular color, a particular response-button position, or both. Neutral trials without color-pseudoword association were also included, and participants’ awareness of the contingencies was manipulated. The data showed no influence of explicit contingency awareness, but clear evidence both for response learning and for semantic learning, with effects emerging swiftly. Deeper processing of color information, with color words presented in black instead of color patches to indicate response-button positions, resulted in stronger effects, both for semantic and response learning. Our data add a crucial piece of evidence lacking so far in color-word contingency learning studies: Semantic learning effectively takes place even when associations are learned in an incidental way. [ABSTRACT FROM AUTHOR]

Anorexia nervosa (AN) and body dysmorphic disorder (BDD) are potentially life-threatening conditions whose partially overlapping phenomenology—distorted perception of appearance, obsessions/compulsions, and limited insight—can make diagnostic distinction difficult in some cases. Accurate diagnosis is crucial, as the effective treatments for AN and BDD differ. To improve diagnostic accuracy and clarify the contributions of each of the multiple underlying factors, we developed a two-stage machine learning model that uses multimodal, neurobiology-based, and symptom-based quantitative data as features: task-based functional magnetic resonance imaging data using body visual stimuli, graph theory metrics of white matter connectivity from diffusor tensor imaging, and anxiety, depression, and insight psychometric scores. In a sample of unmedicated adults with BDD (n = 29), unmedicated adults with weight-restored AN (n = 24), and healthy controls (n = 31), the resulting model labeled individuals with an accuracy of 76%, significantly better than the chance accuracy of 35% (). In the multivariate model, reduced white matter global efficiency and better insight were associated more with AN than with BDD. These results improve our understanding of the relative contributions of the neurobiological characteristics and symptoms of these disorders. Moreover, this approach has the potential to aid clinicians in diagnosis, thereby leading to more tailored therapy. [ABSTRACT FROM AUTHOR]

Background: With the advance of medical care, chronic non-communicable diseases, like chronic kidney disease (CKD), have become the predominant diseases around the world. With heavy society and economy burden, we shall make full use of chronic disease management, including precision therapies. And the prerequisite for implementing precision medicine is to fully understand the characteristics of patients. Being the basis of the Knowledge-Attitude-Practice Model, patient’s awareness is essential to conduct individualized treatments. However, there have been no validated questionnaires specific to the awareness of patients with CKD. Therefore, this study aims to develop and validate an awareness questionnaire for patients with CKD. Methods: From March 2013 to September 2014, a cross-sectional study was conducted at Guangdong Provincial Hospital of Chinese Medicine. Age 18 or above were enrolled in the study. After signing the informed consent, they received a self-developed questionnaire to evaluate their CKD-related awareness. Then we collected their demographic data for further analyses. We also conducted item analyses/ validity and reliability analysis to filter out improper items and to retain the eligible ones. Results: We totally distributed 110 copies of the questionnaires and 100 of them were returned. After item analyses, 2 items were excluded because of Cronbach’s Alpha analysis. In total, 18 items were retained, comprising the final set of the questionnaire. For validity analysis, 4 components could explain the cumulative 73.966% extraction sums of the squared loadings; for reliability analysis, the Guttman Split-Half coefficient was 0.918. Conclusions: This awareness questionnaire has favorable validity and reliability. It is a sound method for evaluating and measuring levels of disease-related awareness in CKD patients. [ABSTRACT FROM AUTHOR]

After years of hypothetical surveys and simulator studies, automated vehicles (AVs) are now being tested in realistic traffic environments adding validity to knowledge about their acceptance. We present data from a pilot test with participants (n = 125) after experiencing a ride in an electric AV on a large clinic area in Berlin, Germany. As a first contribution, we bridge the gap between missing definitions of key constructs, confusion about their operationalisations, and a rigorous test of their statistical properties and data structure by examining scales on acceptance, trust, perceived safety, intention to use, and—for the first time applied to AVs—the emotions amusement, fear, surprise, and boredom. Tests of reliability and normality were satisfying for almost all constructs (Cronbach’s alphas ≥ .69; six of eight scales normally distributed). The vehicles were accepted (M = 1.22; SD = 0.70; range -2 to 2), trusted (M = 3.29; SD = 0.81; range 1 to 5), and perceived as safe (M = 3.29; SD = 1.03; range 1 to 5). However, factor analyses did not reflect the hypothesised data structure, and validity concerns question the suitability of some constructs for attitude assessment of electric AVs. Our open item for comments added valuable insights in qualitative aspects of user attitudes towards electric AVs regarding driving style, technical features, and (unsettling) audio-visual feedback. We thus argue for broader conceptualisations of key constructs based on interdisciplinary exchange and multi-methodical study designs. [ABSTRACT FROM AUTHOR]

Background: Guangxi is one of the provinces having the highest notification rate of tuberculosis in China. However, spatial and temporal patterns and the association between environmental diversity and tuberculosis notification are still unclear. Objective: To detect the spatiotemporal pattern of tuberculosis notification rates from 2010 to 2016 and its potential association with ecological environmental factors in Guangxi Zhuang autonomous region, China. Methods: We performed a spatiotemporal analysis with prediction using time series analysis, Moran’s I global and local spatial autocorrelation statistics, and space-time scan statistics to detect temporal and spatial clusters of tuberculosis notifications in Guangxi between 2010 and 2016. Spatial panel models were employed to identify potential associating factors. Results: The number of reported cases peaked in spring and summer and decreased in autumn and winter. The predicted number of reported cases was 49,946 in 2017. Moran's I global statistics were greater than 0 (0.363–0.536) during the study period. The most significant hot spots were mainly located in the central area. The eastern area exhibited a low-low relation. By the space-time scanning, the clusters identified were similar to those of the local autocorrelation statistics, and were clustered toward the early part of 2016. Duration of sunshine, per capita gross domestic product, the treatment success rate of tuberculosis and participation rate of the new cooperative medical care insurance scheme in rural areas had a significant negative association with tuberculosis notification rates. Conclusion: The notification rate of tuberculosis in Guangxi remains high, with the highest notification cluster located in the central region. The notification rate is associated with economic level, treatment success rate and participation in the new cooperative medical care insurance scheme. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorders (ASD) are lifelong neurodevelopmental disorders. It is not clear whether working memory (WM) deficits are commonly experienced by individuals with ASD. Aim: To determine whether individuals with ASD experience significant impairments in WM and whether there are specific domains of working memory that are impaired. Methods: We conducted a meta-analysis using four electronic databases EMBASE (OVID), MEDLINE (OVID), PsychINFO (EBSCOHOST), and Web of Science, to examine the literature to investigate whether people with ASD experience impairments related to WM. Meta-analyses were conducted separately for phonological and visuospatial domains of WM. Subgroup analyses investigated age and intelligence quotient as potential moderators. Results: A total of 29 papers containing 34 studies measuring phonological and visuospatial domains of WM met the inclusion criteria. WM scores were significantly lower for individuals with ASD compared to typically developed (TD) controls, in both the visuospatial domain when investigating accuracy (d: -0.73, 95% CI -1.04 to -0.42, p < 0.05) and error rates (d: 0.56, 95% CI 0.25 to 0.88, p<0.05), and the phonological domain when investigating accuracy (d:-0.67, 95% CI -1.10 to -0.24, p>0.05) and error rate (d: 1.45, 95% CI -0.07 to 2.96, p = 0.06). Age and IQ did not explain the differences in WM in ASD. Conclusions: The findings of this meta-analysis indicate that across the lifespan, individuals with ASD demonstrate large impairments in WM across both phonological and visuospatial WM domains when compared to healthy individuals. [ABSTRACT FROM AUTHOR]

Empathy is a key notion in the study of sociality. A phenomenological perspective on empathy as intersubjective understanding offers a common ground for multiple dimensions. Corresponding to the dichotomy between perceptual and cognitive levels, two constructs can be distinguished: vicariously experiencing and intuitively understanding others’ emotions. We developed and validated a new questionnaire for the assessment of individual differences in empathy. In a first study (N = 921), we created a questionnaire measuring empathy consisting of a pool of 75 items. Exploratory factor analysis suggested to retain two factors (“Intuitive Understanding” and “Vicarious Experience”), whereas a 30-item version of the questionnaire had satisfactory psychometric properties. In a second study (N = 504), we administered the 30-items questionnaire and several concurrent/divergent measures. Confirmatory factor analysis indicated that a two-factor structure best represented its latent factor structure. The results show that our questionnaire could be considered a reliable and valid measure of empathy with internal consistencies of 0.93 and 0.95 for Vicarious Experience and Intuitive Intuitive Understanding, respectively. Whereas our questionnaire mostly showed the expected convergence with existing scales of empathy, the correlations also suggest that it adds valuable new information to the assessment of empathy. The two-factor structure suggests that the perceptual (vicarious) experience and the basic (non-effortful) cognitive awareness of others’ emotions can be assessed as distinct constructs. This bidimensional structure that distinguishes between the perceptual experience and the basic cognitive awareness of others’ emotional states connects theoretical, empirical, and clinical data from psychology and neuroscience. [ABSTRACT FROM AUTHOR]

Persistent neural activity that encodes online mental representations plays a central role in working memory (WM). However, there has been debate regarding the number of items that can be concurrently represented in this active neural state, which is often called the “focus of attention.” Some models propose a strict single-item limit, such that just 1 item can be neurally active at once while other items are relegated to an activity-silent state. Although past studies have decoded multiple items stored in WM, these studies cannot rule out a switching account in which only a single item is actively represented at a time. Here, we directly tested whether multiple representations can be held concurrently in an active state. We tracked spatial representations in WM using alpha-band (8–12 Hz) activity, which encodes spatial positions held in WM. Human observers remembered 1 or 2 positions over a short delay while we recorded electroencephalography (EEG) data. Using a spatial encoding model, we reconstructed active stimulus-specific representations (channel-tuning functions [CTFs]) from the scalp distribution of alpha-band power. Consistent with past work, we found that the selectivity of spatial CTFs was lower when 2 items were stored than when 1 item was stored. Critically, data-driven simulations revealed that the selectivity of spatial representations in the two-item condition could not be explained by models that propose that only a single item can exist in an active state at once. Thus, our findings demonstrate that multiple items can be concurrently represented in an active neural state. [ABSTRACT FROM AUTHOR]

Quigley derived his hybrid price model to improve the precision of predicted prices of sold homes by statistically merging data of resold homes in a repeat sales model with that of once-sold homes in a single sales hedonic price model. The literature has few applications of the hybrid model aside from those by Quigley and his collaborators. Two reasons for this underuse may be its computational intensiveness and its marginal empirical improvement in comparison with two other models. This paper first demystifies this computational intensiveness by calibrating models in Microsoft Excel with transferable procedures into other software. It second evaluates the hybrid price model’s empirical improvement as a reason for its underuse by predicting prices of 2,559 sold and resold homes observed in two inner-city neighbourhoods in Windsor, Ontario, during a 30-year period. The results as hypothesized are its lower standard errors of regression coefficients and higher simple R-squared than those of a single sales hedonic price model. Moreover, the hybrid model’s predictions have higher correlations than those of the single sales model with not only in-sample observed prices or changes in prices but also out-of-sample ones. The conclusion speculates in plans for future research about reasons for two models’ similar or dissimilar regression coefficients and standard errors predicting correspondingly similar or dissimilar sale prices of homes through time. [ABSTRACT FROM AUTHOR]

An important goal in researching the biology of olfaction is to link the perception of smells to the chemistry of odorants. In other words, why do some odorants smell like fruits and others like flowers? While the so-called stimulus-percept issue was resolved in the field of color vision some time ago, the relationship between the chemistry and psycho-biology of odors remains unclear up to the present day. Although a series of investigations have demonstrated that this relationship exists, the descriptive and explicative aspects of the proposed models that are currently in use require greater sophistication. One reason for this is that the algorithms of current models do not consistently consider the possibility that multiple chemical rules can describe a single quality despite the fact that this is the case in reality, whereby two very different molecules can evoke a similar odor. Moreover, the available datasets are often large and heterogeneous, thus rendering the generation of multiple rules without any use of a computational approach overly complex. We considered these two issues in the present paper. First, we built a new database containing 1689 odorants characterized by physicochemical properties and olfactory qualities. Second, we developed a computational method based on a subgroup discovery algorithm that discriminated perceptual qualities of smells on the basis of physicochemical properties. Third, we ran a series of experiments on 74 distinct olfactory qualities and showed that the generation and validation of rules linking chemistry to odor perception was possible. Taken together, our findings provide significant new insights into the relationship between stimulus and percept in olfaction. In addition, by automatically extracting new knowledge linking chemistry of odorants and psychology of smells, our results provide a new computational framework of analysis enabling scientists in the field to test original hypotheses using descriptive or predictive modeling. [ABSTRACT FROM AUTHOR]

Background: Brief interventions have been increasingly investigated to promote early intervention in gambling problems; an accurate estimate of the impact of these interventions is required to justify their widespread implementation. The goal of the current investigation was to evaluate the efficacy of in-person brief interventions for reducing gambling behaviour and/or problems, by quantifying the aggregate effect size associated with these interventions in the published literature to date. Methods: Randomized controlled trials including the following design features were identified via systematic review: an adult sample experiencing problems associated with gambling; an in-person individual psychosocial intervention of brief duration (≤3 sessions); a control/comparison group; and an outcome related to gambling behaviour and/or problems. Results: Five records compared brief interventions to assessment only control; using a random effect model, brief interventions were associated with a small but statistically significant reduction in gambling behaviour across short-term follow-up periods versus assessment only control (g = -.19, 95% CI [-.37, -.01]). Aggregate effect sizes for gambling problems and long-term follow-up periods were not statistically significant. Five records compared brief interventions to longer active interventions; there was no significant difference between brief interventions and longer active interventions. Conclusions: Results supported the efficacy of brief interventions for problem gambling compared to inactive control in the reduction of gambling behaviour; no differences were found across brief versus longer interventions for both gambling behaviour and problems. While these findings must be interpreted in the context of the limited number of studies and small magnitude of the combined effect sizes, the current meta-analysis supports the further investigation of the public health impact of these cost-effective interventions. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate whether changes in psychosocial factors and pain severity were associated with reduction in disability due to pain among patients with chronic pain. We hypothesized that increased self-efficacy would reduce disability. Patients and methods: This longitudinal observational study included 72 patients. Patients’ psychological and physical variables were assessed before and after 3 months of treatment. Demographic and clinical information were collected, including the Pain Disability Assessment Scale (PDAS), the Pain Self-Efficacy Questionnaire (PSEQ), the Hospital Depression and Anxiety Scale, and the Numeric Rating Scale (NRS) to assess pain intensity. First, univariate regression analyses were conducted to clarify associations between change in PDAS and sex, age, pain duration, changes in psychosocial factors (self-efficacy, anxiety, and depression) and change in pain intensity. Second, multivariate regression was conducted using the variables identified in the univariate analyses (PSEQ and NRS) to detect the most relevant factor for reducing disability. Results: Univariate regression analyses clarified that changes in PSEQ (β = −0.31; 95% CI: −0.54–−0.08, p = 0.008) and NRS (β = 0.24; 95% confidence interval [CI]: 0.01–0.47, p = 0.04) were associated with reduction in PDAS. Multivariate regression analysis demonstrated that change in PSEQ (β = 0.26; 95% CI: −0.50–−0.02; p = 0.01) was associated with a reduction in disability, independent of change in NRS. Conclusion: These findings suggest improved self-efficacy is associated with reduced disability in patients with chronic pain, independent of reduction in pain intensity. Focusing on improvement in self-efficacy may be an effective strategy in chronic pain treatment in addition to pain relief. [ABSTRACT FROM AUTHOR]

Background: This study aimed to investigate the distribution of European Union (EU) healthcare research grants across EU countries, and to study the effect of the potential influencing factors on grant allocation. Methods: We analysed publicly available data on healthcare research grants from the 7th Framework Programme and the Horizon 2020 Programme allocated to beneficiaries between 2007 and 2016. Grant allocation was analysed at the beneficiary-, country-, and country group-level (EU-15 versus newer Member States, defined as EU-13). The investigated country-level explanatory variables included GDP per capita, population size, overall disease burden, and healthcare research excellence. Grant amounts per 100,000 inhabitants were used as an outcome variable in the regression analyses. Results: Research funds were disproportionally allocated to EU-15 versus the EU-13, as 96.9% of total healthcare grants were assigned to EU-15 countries. At the beneficiary level, EU funding was positively influenced by participating in previous grants. The average grant amount per beneficiary was higher for EU-15 organizations. In the multiple regression analysis GDP per capita (p = 0.002) and research excellence (p<0.001) had a significant positive association with EU funding. Population size had an inverted U-shaped relationship with EU funding for healthcare research, having the largest per capita funding in second and the third quartiles (p = 0.03 and p = 0.02). Conclusion: The uneven allocation of healthcare research funds across EU countries was influenced by GDP per capita, medical research excellence and population size. Wealthier countries with an average population size and strong research excellence in healthcare had more EU funding for healthcare research. Higher disease burden apparently was not associated with more EU research funding. While our findings are in line with analyses on previous periods, they suggest that the EU did not implement any effective policy measures to improve the unfair allocation of research grants. [ABSTRACT FROM AUTHOR]

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

The differential contribution of maternal and paternal acceptance-rejection to children’s psychological adjustment has been explained by differences in interpersonal power and prestige within families; however, there is not yet enough empirical support for this explanation. This study examines the moderating effects of interpersonal power and prestige on the relationship between perceived parental acceptance-rejection and psychological adjustment across children’s sex and age. The sample was composed of 913 children ranging in age from 9 to 16 years. Multiple hierarchical regression analyses in the total sample showed a significant and independent contribution of parental acceptance-rejection and parental power and prestige. No moderating effects of interpersonal power and prestige were found for the total sample. However, when the regression analyses were conducted across different age groups, maternal acceptance had a higher contribution to psychological adjustment in children from nine to ten years old. Interestingly, the moderating effects of interpersonal prestige (not interpersonal power) were also significant in younger participants. Furthermore, the moderating effects of prestige on maternal acceptance-rejection were different in late childhood than in early adolescence. These results suggest how parental prestige may explain the higher contribution of maternal acceptance to younger children’s psychological adjustment. [ABSTRACT FROM AUTHOR]

Background: Gene expression may be an important biological mediator in associations between social factors and health. However, previous studies were limited by small sample sizes and use of differing cell types with heterogeneous expression patterns. We use a large population-based cohort with gene expression measured solely in monocytes to investigate associations between seven social factors and expression of genes previously found to be sensitive to social factors. Methods: We employ three methodological approaches: 1) omnibus test for the entire gene set (Global ANCOVA), 2) assessment of each association individually (linear regression), and 3) machine learning method that performs variable selection with correlated predictors (elastic net). Results: In global analyses, significant associations with the a priori defined socially sensitive gene set were detected for major or lifetime discrimination and chronic burden (p = 0.019 and p = 0.047, respectively). Marginally significant associations were detected for loneliness and adult socioeconomic status (p = 0.066, p = 0.093, respectively). No associations were significant in linear regression analyses after accounting for multiple testing. However, a small percentage of gene expressions (up to 11%) were associated with at least one social factor using elastic net. Conclusion: The Global ANCOVA and elastic net findings suggest that a small percentage of genes may be “socially sensitive,” (i.e. demonstrate differential expression by social factor), yet single gene approaches such as linear regression may be ill powered to capture this relationship. Future research should further investigate the biological mechanisms through which social factors act to influence gene expression and how systemic changes in gene expression affect overall health. [ABSTRACT FROM AUTHOR]

Background: The 2010 World Health Organization Global Strategy to Reduce the Harmful Use of Alcohol recommends countries adopt evidence-based interventions. Aim: To update, summarize, and appraise the methodological rigour of systematic reviews of selected alcohol control interventions in the Strategy. Methods: We searched for systematic reviews across PUBMED, EMBase and The Cochrane Library in 2016 and updated in 2017 with no language limits. Two investigators independently in duplicate conducted screening, eligibility, data extraction, and quality assessment using the ROBIS tool. We categorised interventions according to the WHO recommendations, and rated reviews as at high, low or unclear risk of bias. We applied a hierarchical approach to summarising review results. Where overlap existed we report results of high quality reviews and if none existed, by most recent date of publication. We integrated the ROBIS rating with the results to produce a benefit indication. Results: We identified 42 systematic reviews from 5,282 records. Almost all eligible reviews were published in English, one in German and one in Portuguese. Most reviews identified only observational studies (74%; 31/42) with no studies from low or lower-middle income (LMIC) countries. Ten reviews were rated as low risk of bias. Methodological deficiencies included publication and language limits, no duplicate assessment, no assessment of study quality, and no integration of quality into result interpretation. We evaluated the following control measures as possibly beneficial: 1) community mobilization; 2) multi-component interventions in the drinking environment; 3) restricting alcohol advertising; 4) restricting on- and off-premise outlet density; 5) police patrols and ignition locks to reduce drink driving; and 6) increased price and taxation including minimum unit pricing. Conclusions: Robust and well-reported research synthesis is deficient in the alcohol control field despite the availability of clear methodological guidance. The lack of primary and synthesis research arising from LMIC should be prioritised globally. [ABSTRACT FROM AUTHOR]

Measuring whole-brain functional connectivity patterns based on task-free (‘resting-state’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisition is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns (commonly termed ‘resting state networks’). We employed a ‘steady-states’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing us to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis) using standard resting-state functional connectivity (FC) analysis, we show that the whole-brain network architecture characteristic of the resting-state is comparable across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Changes in functional connectivity were detected locally, within the active networks. But to identify these local changes, the contributions of different FC networks to the global intrinsic connectivity pattern had to be isolated. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state. [ABSTRACT FROM AUTHOR]

Multivariate analysis methods have been widely applied to decode brain states from functional magnetic resonance imaging (fMRI) data. Among various multivariate analysis methods, partial least squares regression (PLSR) is often used to select relevant features for decoding brain states. However, PLSR is seldom directly used as a classifier to decode brain states from fMRI data. It is unclear how PLSR classifiers perform in brain-state decoding using fMRI. In this study, we propose two types of two-step PLSR classifiers that use PLSR/sparse PLSR (SPLSR) to select features and PLSR for classification to improve the performance of the PLSR classifier. The results of simulated and real fMRI data demonstrated that the PLSR classifier using PLSR/SPLSR to select features outperformed both the PLSR classifier using a general linear model (GLM) and the support vector machine (SVM) using PLSR/SPLSR/GLM in most cases. Moreover, PLSR using SPLSR to select features showed the best performance among all of the methods. Compared to GLM, PLSR is more sensitive in selecting the voxels that are specific to each task. The results suggest that the performance of the PLSR classifier can be largely improved when the PLSR classifier is combined with the feature selection methods of SPLSR and PLSR. [ABSTRACT FROM AUTHOR]

Introduction: Safety climate, which provides a snapshot of safety culture, is rarely measured in Indonesian healthcare organisations because there are no validated surveys that can be administered in its native language, Bahasa Indonesia. The objectives of this study were to translate and linguistically adapt the Safety Attitudes Questionnaire into Bahasa Indonesia, and investigate the internal construct validity and reliability of the translated survey. Methods: The Safety Attitudes Questionnaire was translated into Indonesian language through forward and backward translation. The internal construct validity and reliability of the translated survey was assessed using Rasch analysis which examines overall model fit, unidimensionality, response format, targeting, internal consistency reliability and item bias. Results: A total of 279 nurses (response rate 82%) completed the Indonesian version of the Safety Attitudes Questionnaire. Most respondents were Division 2 registered nurses (n = 209; 75%), female (n = 174; 62%), and aged less than 30 years (n = 187; 67%). All six domains of the Indonesian version of the Safety Attitudes Questionnaire demonstrated unidimensionality (t-test less than 0.05 threshold value). However, suboptimal targeting (ceiling effect) was observed in all domains, and had at least one misfitting item (item fit residual beyond ±2.5) Item bias was also evident in most domains. Conclusion: This study has translated and validated an Indonesian version of the Safety Attitudes Questionnaire for the first time. Whilst there was general support to sum items to obtain domain scores, further work is required to refine the response options as well as the wording and number of items in this survey to improve its overall measurement properties. [ABSTRACT FROM AUTHOR]

Background: The process of growing leads to inter-individual differences in the timing of growth, maturational, and developmental processes during childhood and adolescence, also affecting balance performance in youth. However, differences in balance performance by age and sex in youth have not been systematically investigated yet. Objective: The objective of the present study was to characterize and quantify age- and sex-related differences in balance performance in healthy youth. Methods: A computerized systematic literature search was performed in the electronic databases PubMed, Web of Science, and SPORTDiscus. To be applicable for analysis, studies had to report at least one measure of static steady-state, dynamic steady-state, proactive or reactive balance in healthy children (6–12 years) and/or adolescents (13–18 years). Coding of the studies was done according to the following criteria: age, sex, and balance outcome. Study quality was assessed using the Appraisal tool for Cross-Sectional Studies. Weighted standardized mean differences were calculated and classified according to their magnitude. Results: Twenty-one studies examined age-related differences in balance performance. A large effect for measures of static steady-state balance (SMDba = 1.20) and small effects for proxies of dynamic steady-state (SMDba = 0.26) and proactive balance (SMDba = 0.28) were found; all in favor of adolescents. Twenty-five studies investigated sex-related differences in balance performance. A small-sized effect was observed for static steady-state balance (SMDbs = 0.33) in favor of girls and for dynamic steady-state (SMDbs -0.02) and proactive balance (SMDbs = -0.15) in favor of boys. Due to a lack of studies, no analysis for measures of reactive balance was performed. Conclusions: Our systematic review and meta-analysis revealed better balance performances in adolescents compared to children, irrespective of the measure considered. Sex-related differences were inconsistent. These findings may have implications for example in terms of trainability of balance in youth that should be investigated in future studies. [ABSTRACT FROM AUTHOR]

Rationale: As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI). Objectives: To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California. Methods: We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained. Measurements and main results: In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4–16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY. Conclusions: Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks. [ABSTRACT FROM AUTHOR]

England’s national Improving Access to Psychological Therapies (IAPT) programme advocates stepped care as its organizational delivery of psychological therapies to common mental health problems. There is limited evidence regarding the efficacy of stepped care as a service delivery model, heterogeneity of definition and differences in model implementation in both research and routine practice, hence outcome comparison in terms of effectiveness of model is difficult. Despite sound evidence of the efficacy of low intensity interventions there appears to be a perpetuation of the notion that severity and complexity should only be treated by a high intensity intervention through the continuation of a stratified care model. Yet no psychotherapy treatment is found to be more superior to another, and not enough is known about what works for whom to aid the matching of treatment decision. In the absence of understanding precise treatment factors optimal for recovery, it may be useful to better understand the impact of a service delivery model, and whether different models achieve different outcomes. This study aims to contribute to the discussion regarding the stepped care definition and delivery, and explores the impact on clinical outcomes where different types of stepped care have been implemented within the same service. An observational cohort study analysed retrospective data (n = 16,723) over a 4 year period, in a single IAPT service, where delivery changed from one type of stepped care model to another. We compared the outcomes of treatment completers with a stratified care model and a progression care model. We also explored the assumption that patients who score severe on psychological measures, and therefore are potentially complex, would achieve better outcomes in a stratified model. Outcomes in each model type were compared, alongside baseline factor variables. A significant association was observed between a recovery outcome and model type, with patients 1.5 times more likely to recover in the progression delivery model. The potential implications are that with a progression stepped care model of service delivery, more patients can be treated with a lower intensity intervention, even with initial severe presentations, ensuring that only those that need high intensity CBT or equivalent are stepped up. This could provide services with an effective clinical model that is efficient and potentially more cost effective. [ABSTRACT FROM AUTHOR]

Background: Posttraumatic stress disorder is a debilitating psychiatric disorder characterized by symptoms of intrusive re-experiencing of trauma, avoidance and hyper-arousal. Diagnosis and treatment of PTSD is further complicated by concurrently occurring disorders, the most frequent being major depressive disorder and anxiety disorders. Previous research highlights that attentional processing in posttraumatic stress disorder is associated with substantial interference by emotional stimuli, a phenomenon also observed in these concurrently occurring psychiatric disorders. However, the diagnosis-relevance of this interference remains elusive. Here, we investigated the emotional Stroop interference for diagnosis-related stimuli, generally negative stimuli, and generally positive stimuli in posttraumatic stress disorder, major depressive disorder and anxiety disorders. Methods: We performed a systematic database search in PubMed (Medline), Cochrane Library and PsycINFO on emotional Stroop performance in individuals with a diagnosis of posttraumatic stress disorder, major depressive disorder or anxiety disorders separately. Mean effect sizes, standard errors and confidence intervals were estimated for each clinical group and healthy control group comparison using random effect models. Results: As compared to healthy control group, the posttraumatic stress disorder group displayed greater interference by diagnosis-related stimuli and positive stimuli but not for generally negative stimuli. The major depressive disorder and anxiety disorders groups showed greater interference by diagnosis-related and negative stimuli, but not by positive stimuli. The age and sex had no significant impact on interference. Conclusions: These findings highlight the importance of diagnosis-relevant information on attentional processing in all three clinical populations, posttraumatic stress disorder, major depressive disorder and anxiety disorders. Further, the impact of generally negative stimuli but not generally positive stimuli in major depressive disorder and anxiety disorders indicate impaired attentional bias for mood-congruent stimuli but not for general stimuli. Finally, it remains to be studied whether the influence of generally positive stimuli in posttraumatic stress disorder indicate that positive stimuli are perceived as PTSD related. [ABSTRACT FROM AUTHOR]