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Objectives: There is limited evidence on the effect of exposure to second hand smoke (SHS) in non-smoking pregnant mothers and infant health. We assessed the effects of maternal antenatal exposure to SHS on infant growth rate, and secondarily, on birth weight, birth length and head circumference at birth. Methods: In this prospective cohort, 305 mother-infant pairs were studied. Mothers filled out questionnaires about exposure to SHS in pregnancy at the 3rd trimester of pregnancy. Infant anthropometry was performed at birth, day 7, and months 1, 2, 4, and 6, postnatally. Linear mixed modeling and linear regression were used to calculate growth rates over the first 6 months. The association between SHS-exposure with growth rate and birth sizes was assessed using multivariate linear regression adjusted for confounders, with SHS as both number of cigarettes and as groups (no exposure, SHS < 23 cigarettes, SHS ≥ 23 cigarettes). Results: Seventy-three mothers were not exposed and 232 were exposed. SHS exposure (per cigarette) was not related to gain in weight, length, head circumference, and weight for length. However, infants born to mothers exposed to ≥ 23 cigarettes/d had lower head circumference gain (-0.32 mm/m, 95% CI -0.60, -0.03) than those born to non-exposed mothers. SHS exposure (per cigarette) was not related to birth weight, length, and head circumference, but exposure to ≥ 23 cigarettes was related to lower head circumference at birth (-11.09 mm, -20.03, -2.16). Conclusions: Heavy antenatal exposure to SHS in non-smoking mothers results in reduced neonatal head circumference at birth and head circumference gain over the first 6 months of life. Our findings show no clear relations between exposure to SHS during pregnancy and other markers of neonatal growth and birth size. [ABSTRACT FROM AUTHOR]

A large proportion of Depression Disorder patients do not receive an effective diagnosis, which makes it necessary to find a more objective assessment to facilitate a more rapid and accurate diagnosis of depression. Speech data is easy to acquire clinically, its association with depression has been studied, although the actual predictive effect of voice features has not been examined. Thus, we do not have a general understanding of the extent to which voice features contribute to the identification of depression. In this study, we investigated the significance of the association between voice features and depression using binary logistic regression, and the actual classification effect of voice features on depression was re-examined through classification modeling. Nearly 1000 Chinese females participated in this study. Several different datasets was included as test set. We found that 4 voice features (PC1, PC6, PC17, PC24, P<0.05, corrected) made significant contribution to depression, and that the contribution effect of the voice features alone reached 35.65% (Nagelkerke's R2). In classification modeling, voice data based model has consistently higher predicting accuracy(F-measure) than the baseline model of demographic data when tested on different datasets, even across different emotion context. F-measure of voice features alone reached 81%, consistent with existing data. These results demonstrate that voice features are effective in predicting depression and indicate that more sophisticated models based on voice features can be built to help in clinical diagnosis. [ABSTRACT FROM AUTHOR]

Introduction: Response rates in health research are declining, and low response rates could result in biased outcomes when population characteristics of participants systematically differ from the non-respondents. Few studies have examined key factors of non-response beyond demographic characteristics, such as behavioral and psychological factors. The aim of the current study was to identify predictors of non-response and loss to follow-up in a longitudinal sexual health study. Materials and methods: A longitudinal cohort study (iMPaCT) was conducted from November 2016 to July 2018 among heterosexual STI clinic visitors aged 18–24 years. At four different time points in one year, data was collected on sexual behavior, psychological determinants and chlamydia infections. The national STI surveillance database provided data on demographic, behavioral and sexual health-related characteristics for non-respondents. Predictors of non-response at baseline and of loss to follow-up were identified using multivariable logistic regression analyses. Results: In total, 13,658 STI clinic visitors were eligible to participate, of which 1,063 (8%) participated. Male gender, low/medium education level, young age (≤ 20 years) and having a non-Dutch migration background were significant predictors of non-response at baseline. Furthermore, non-respondents at baseline were more likely to report STI-related symptoms, to have been notified by a partner, to have had condomless sex, and to have had ≤ 2 partners in the past six months, compared to participants. Psychological predictors of loss to follow-up differed between STI clinic regions, but low perceived importance of health at baseline was associated with loss to follow-up in all regions. The baseline chlamydia positivity rate was significantly higher in the non-respondents (17%) compared to the participants (14%), but was not a predictor of loss to follow-up. Discussion: Targeted recruitment aimed at underrepresented groups in the population based on demographic, behavioral and psychological characteristics, might be necessary to decrease loss to follow-up, and to prevent non-response bias in health research. [ABSTRACT FROM AUTHOR]

Introduction: Research has demonstrated benefits of social capital on depression, but variations in this relationship by geographic characteristics such as urbanicity have rarely been investigated. Methods: Using survey data on 4,209 Ghanaian and 3,148 South African adults aged 50 and above from the World Health Organization (WHO) Study on Global AGEing and Adult Health (SAGE), exploratory and confirmatory factor analyses were conducted to extract dimensions of social capital from survey items. Structural equation models with the extracted factors were then used to estimate the associations between social capital and depression in each sample and assess differences between urban and rural settings with measurement and structural invariance tests. Results: Factor analyses suggested three dimensions of social capital representing community engagement, sociability, and trust. Urbanicity did not substantially modify the effects of social capital on depression in either setting, but urban-rural differences in the measurement and level of social capital were observed. Urban Ghanaian older adults were less socially integrated and trusting than older rural residents (standardized mean difference: -0.28, -0.24, and -0.38 for community engagement, sociability, and trust, respectively) while urban South African older adults appeared less engaged in community activities but significantly more trusting and socially active informally than older rural residents (standardized mean difference: -0.33, 0.30, and 0.17 for community engagement, sociability, and trust, respectively). Moreover, while trust was associated with a lower risk of depression in South Africa overall, sociability and trust were associated with an increased risk of depression in Ghana. Conclusions: Results indicate that the composition and average levels of social capital differ between urban and rural older adult residents in Ghana and South Africa although urban-rural differences in the strength of the association between social capital and depression were not substantial. Furthermore, the associations between social capital and depression are context-specific and are not uniformly beneficial. [ABSTRACT FROM AUTHOR]

We studied whether medical conditions across 21 broad categories were predictable from social media content across approximately 20 million words written by 999 consenting patients. Facebook language significantly improved upon the prediction accuracy of demographic variables for 18 of the 21 disease categories; it was particularly effective at predicting diabetes and mental health conditions including anxiety, depression and psychoses. Social media data are a quantifiable link into the otherwise elusive daily lives of patients, providing an avenue for study and assessment of behavioral and environmental disease risk factors. Analogous to the genome, social media data linked to medical diagnoses can be banked with patients’ consent, and an encoding of social media language can be used as markers of disease risk, serve as a screening tool, and elucidate disease epidemiology. In what we believe to be the first report linking electronic medical record data with social media data from consenting patients, we identified that patients’ Facebook status updates can predict many health conditions, suggesting opportunities to use social media data to determine disease onset or exacerbation and to conduct social media-based health interventions. [ABSTRACT FROM AUTHOR]

Differentiation between phenotypically neutral and disease-causing genetic variation remains an open and relevant problem. Among different types of variation, non-frameshifting insertions and deletions (indels) represent an understudied group with widespread phenotypic consequences. To address this challenge, we present a machine learning method, MutPred-Indel, that predicts pathogenicity and identifies types of functional residues impacted by non-frameshifting insertion/deletion variation. The model shows good predictive performance as well as the ability to identify impacted structural and functional residues including secondary structure, intrinsic disorder, metal and macromolecular binding, post-translational modifications, allosteric sites, and catalytic residues. We identify structural and functional mechanisms impacted preferentially by germline variation from the Human Gene Mutation Database, recurrent somatic variation from COSMIC in the context of different cancers, as well as de novo variants from families with autism spectrum disorder. Further, the distributions of pathogenicity prediction scores generated by MutPred-Indel are shown to differentiate highly recurrent from non-recurrent somatic variation. Collectively, we present a framework to facilitate the interrogation of both pathogenicity and the functional effects of non-frameshifting insertion/deletion variants. The MutPred-Indel webserver is available at . [ABSTRACT FROM AUTHOR]

Objective: To assess the sociodemographic factors associated with the double burden of malnutrition (DBM) among Brazilian adolescents. Methods: This was a descriptive study based on data from 59,637 and 10,770 students who participated in the National Adolescent School-Based Health Survey (PeNSE), 2009 and 2015 editions, respectively. Weight and height measurements were obtained to evaluate nutritional status. DBM was classified as follows: adolescents with high BMI-for-age and low height-for-age (BMI/A: Z-score > +1 and H/A: Z-score < -2). Sociodemographic data on the participants were also collected. A multinomial logistic regression analysis was used to detect associations of interest. Results: The prevalence of DBM in the 2009 and 2015 editions of the PeNSE was 0.4% and 0.3%, respectively. In the 2009 edition, the chance of DBM was lower among boys (OR = 0.60; 95% CI = 0.45–0.81) and higher among those over 14 years old (OR = 2.40; 95% CI = 1.80–3.20), living in the country’s north and northeast regions (OR = 2.01; 95% CI = 1.49–2.84), and from families with a low maternal education level (OR = 1.48; 95% CI = 1.07–2.04). In the 2015 edition, no significant associations were found regarding the DBM outcome. Conclusion: The results indicate the presence of socioeconomic inequalities in the occurrence of DBM in the 2009 edition of the PeNSE. Simultaneous interventions in the area of equity are necessary to prevent the advancement of nutrition-related problems. [ABSTRACT FROM AUTHOR]

The construction of large renewable energy projects is characterized by the great uncertainties associated with their administrative complexity and their constructive characteristics. For proper management, it is necessary to undertake a thorough project risk assessment prior to construction. The work presented in this paper is based on a hierarchical risk structure identified by a group of experts, from which a Probabilistic Fuzzy Sets with Analysis Hierarchy Process (PFSAHP) was applied. This probabilistic analysis approach used expert opinion based on the Monte Carlo Method that allows for extracting more information from the original data. In addition, the coherence of the experts’ opinions is assessed using a novel parameter known as Confidence Level, which allows for adjusting the opinions of experts and weighting their judgments regarding impact and probability according to their coherence. This model has the advantage of offering a risk analysis in the early stages of the management of renewable energy projects in which there is no detailed information. This model is also more accurate than the classic fuzzy methodology when working with complete distribution functions, whilst it avoids the loss of information that results from the traditional mathematical operations with Fuzzy numbers. To test the model, it was applied to a 250 MW photovoltaic solar plant construction project located in southeast of Spain (Region of Murcia). As a result of the application of the proposed method, risk rankings are obtained with respect to the cost, the time, the scope and from a general point of view of the project. [ABSTRACT FROM AUTHOR]

Brain-Computer Interfaces (BCIs) based on visual evoked potentials (VEPs) allow high communication speeds and accuracies. The fastest speeds can be achieved if targets are identified in a synchronous way (i.e., after a pre-set time period the system will produce a command output). The duration a target needs to be fixated on until the system classifies an output command affects the overall system performance. Hence, extracting a data window dedicated for the classification is of critical importance for VEP-based BCIs. Secondly, unintentional fixation on a target could easily lead to its selection. For the practical usability of BCI applications it is desirable to distinguish between intentional and unintentional fixations. This can be achieved by using threshold-based target identification methods. The study explores personalized dynamic classification time windows for threshold-based time synchronous VEP BCIs. The proposed techniques were tested employing the SSVEP and the c-VEP paradigm. Spelling performance was evaluated using an 8-target dictionary-supported BCI utilizing an n-gram word prediction model. The performance of twelve healthy participants was assessed with the information transfer rate (ITR) and accuracy. All participants completed sentence spelling tasks, reaching average accuracies of 94% and 96.3% for the c-VEP and the SSVEP paradigm, respectively. Average ITRs around 57 bpm were achieved for both paradigms. [ABSTRACT FROM AUTHOR]

Background: Knowledge of urogenital schistosomiasis can empower individuals to limit surface water contact and participate in mass drug administration campaigns, but nothing is currently known about the schistosomiasis knowledge that schoolchildren have in Ghana. We developed and implemented a survey tool aiming to assess the knowledge of urogenital schistosomiasis (treatment, transmission, prevention, symptoms) among science teaches and primary and junior high school students in the Eastern Region of Ghana. Methods: We developed a 22-question knowledge survey tool and administered it to 875 primary and 938 junior high school students from 74 schools in 37 communities in the Eastern Region of Ghana. Teachers (n = 57) answered 20 questions matched to student questions. We compared knowledge scores (as percent of correct answers) across topics, gender, and class year and assessed associations with teacher’s knowledge scores using t-tests, chi-squared tests, univariate, and multivariate linear regression, respectively. Results: Students performed best when asked about symptoms (mean±SD: 76±21% correct) and prevention (mean±SD: 69±25% correct) compared with transmission (mean±SD: 50±15% correct) and treatment (mean±SD: 44±23% correct) (p<0.0005). Teachers performed best on prevention (mean±SD: 93±12% correct, p<0.0005) and poorest on treatment (mean±SD: 69±16% correct, p<0.001). When listing five facts about urogenital schistosomiasis, teachers averaged 2.9±1.2 correct. Multiple regression models suggest that gender, class year, teacher score, and town of residency explain ~27% of variability in student scores. On average, junior high school students outperformed primary school students by 10.2 percentage points (CI95%: 8.6–11.8); boys outperformed girls by 3.5 percentage points (CI95%: 2.3–4.7). Conclusions: Our survey parsed four components of student and teacher knowledge. We found strong knowledge in several realms, as well as knowledge gaps, especially on transmission and treatment. Addressing relevant gaps among students and science teachers in UGS-endemic areas may help high-risk groups recognize risky water contact activities, improve participation in mass drug administration, and spark interest in science by making it practical. [ABSTRACT FROM AUTHOR]

Current predictive models of collective action have devoted little attention to personal values, such as morals or ideology. The present research addresses this issue by incorporating a new axiological path in a novel predictive model of collective action, named AICAM. The axiological path is formed by two constructs: ideology and moral obligation. The model has been tested for real normative participation (Study 1) and intentional non-normative participation (Study 2). The sample for Study 1 included 531 randomly selected demonstrators and non-demonstrators at the time of a protest that took place in Madrid, May 2017. Study 2 comprised 607 randomly selected participants who filled out an online questionnaire. Structural equation modelling analysis was performed in order to examine the fit and predictive power of the model. Results show that the model is a good fit in both studies. It has also been observed that the new model entails a significant addition of overall effect size when compared with alternative models, including SIMCA. The present research contributes to the literature of collective action by unearthing a new, independent path towards collective action that is nonetheless compatible with previous motives. Implications for future research are discussed, mainly stressing the need to include moral and ideological motives in the study of collective action engagement. [ABSTRACT FROM AUTHOR]

This paper aims to demonstrate the impact of coal enterprises’ vertical integration on the performance of innovation corporate social responsibility (ICSR) and to elaborate its specific transmission path through financing structure and market power. This paper takes the data of A-share listed coal company from 2008 to 2017 as samples, uses input-output table method to measure the degree of vertical integration, and explores the relationship between the four factors through multiple linear regression and Bootstrap method. We found that: (1) the vertical integration of coal enterprises has positive incentives for the promotion of ICSR. (2) Financing structure and market power play a chain intermediary role in this process of incentive. (3) In areas with high marketization process, vertical integration has more significant incentive effect on ICSR. The paper extends the research on the relationship between vertical integration and innovation, which provides a reference for the improvement of China’s supply-side reform and corporate social responsibility (CSR) fulfillment policy. It is helpful to promote the sustainable development of the coal industry, stimulate the innovation vitality of enterprises, and improve the fulfillment of CSR. [ABSTRACT FROM AUTHOR]

The study shows the feasibility of predicting firms’ expenditures in innovation, as reported in the Community Innovation Survey, applying a supervised machine-learning approach on a sample of Italian firms. Using an integrated dataset of administrative records and balance sheet data, designed to include all informative variables related to innovation but also easily accessible for most of the cohort, random forest algorithm is implemented to obtain a classification model aimed to identify firms that are potential innovation performers. The performance of the classifier, estimated in terms of AUC, is 0.794. Although innovation investments do not always result in patenting, the model is able to identify 71.92% of firms with patents. More encouraging results emerge from the analysis of the inner working of the model: predictors identified as most important—such as firm size, sector belonging and investment in intangible assets—confirm previous findings of literature, but in a completely different framework. The outcomes of this study are considered relevant for both economic analysts, because it demonstrates the potential of data-driven models for understanding the nature of innovation behaviour, and practitioners, such as policymakers or venture capitalists, who can benefit by evidence-based tools in the decision-making process. [ABSTRACT FROM AUTHOR]

Background: The Lower Extremity Functional Scale evaluates the functional status of patients that have lower extremity conditions of musculoskeletal origin. Regional Arabic dialects often create barriers to clear communication and comparative research. We aimed to cross-culturally adapt the Lower Extremity Functional Scale in modern standard Arabic that is widely used and understood in the Middle East and North Africa region, and assess its psychometric properties. Methods: Cross-cultural adaptation followed a combination of recommended guidelines. For psychometric evaluation 150 patients with anterior cruciate ligament injury and 65 asymptomatic individuals were recruited. All measurement properties as indicated by the Consensus-based Standards for the selection of health status Measurement Instruments recommendations were evaluated, including content-relevance analysis, structural validity, longitudinal reproducibility, anchor- and distribution-based methods of responsiveness, as well as the longitudinal pattern of change of Lower Extremity Functional Scale in anterior cruciate ligament injured patients’ functional status. Results: The questionnaire presented excellent internal consistency (α = 0.96), reliability (0.80–0.98), and good convergent validity (ρ = 0.85). For reproducibility testing: minimal detectable change was 9.26 points; for responsiveness assessment: minimal clinically important difference was 9 points and presented moderate effect sizes (Glass’Δ = 0.71, Cohen’s d = 0.81). Its unidimensionality was not confirmed and an exploratory factor analysis indicated a 2-factor solution explaining 78.1% of the variance. Conclusion: The Arabic Lower Extremity Functional Scale presented acceptable psychometric properties comparable to the original version. The Arabic version of Lower Extremity Functional Scale can be used in research and clinical practice to assess the functional status of Arabic-patients suffering an anterior cruciate ligament injury. [ABSTRACT FROM AUTHOR]

The assessment of daily living activities could provide information about daily functions and participation restrictions to develop intervention strategies. The purposes of this study were to assess the scores of the Barthel Index (BI) and Lawton Instrumental Activities of Daily Living (IADL) scale in older adults with cognitive impairment and to explore the different effects that levels of cognitive functions have on changes in IADL functions. We recruited 31 participants with dementia, 36 with mild cognitive impairment (MCI), and 35 normal controls (NCs) from the neurology outpatient department of a regional hospital. The results of the demographic and clinical characteristics through the Lawton IADL scale, BI, Quick Mild Cognitive Impairment (Qmci) screen, Montreal Cognitive Assessment (MoCA), and Mini-Mental State Examination (MMSE), were collected on the same day and compared with the Kruskal–Wallis test, Wilcoxon rank-sum test, Fisher’s exact test, and a multiple linear regression analysis, as appropriate. In the BI, bathing was the most discriminating activity to differentiate patients with MCI and dementia; in the Lawton IADL scale, medication responsibility and shopping were the most discriminating activities to differentiate NCs and patients with MCI, and patients with MCI and dementia, respectively. In addition, the predictors of changes in Lawton IADL scale scores were the problem-solving score of the Clinical Dementia Rating scale, a Qmci score of > 20.4 and an age of ≤ 81.2 years, a MoCA score of < 9.4 and an age of > 81.2 years, and the MMSE score and an age of > 81.2 years. This study adds to the evidence that the description of basic and instrumental daily activities is integrated in older adults with cognitive impairment. Notably, the Qmci is the most significant predictor of changes in IADL function for “young” older adults, as are the MoCA and MMSE for “old” older adults. [ABSTRACT FROM AUTHOR]

Purpose: First, to evaluate inter-rater reliability when human raters estimate the reading performance of visually impaired individuals using the MNREAD acuity chart. Second, to evaluate the agreement between computer-based scoring algorithms and compare them with human rating. Methods: Reading performance was measured for 101 individuals with low vision, using the Portuguese version of the MNREAD test. Seven raters estimated the maximum reading speed (MRS) and critical print size (CPS) of each individual MNREAD curve. MRS and CPS were also calculated automatically for each curve using two different algorithms: the original standard deviation method (SDev) and a non-linear mixed effects (NLME) modeling. Intra-class correlation coefficients (ICC) were used to estimate absolute agreement between raters and/or algorithms. Results: Absolute agreement between raters was ‘excellent’ for MRS (ICC = 0.97; 95%CI [0.96, 0.98]) and ‘moderate’ to ‘good’ for CPS (ICC = 0.77; 95%CI [0.69, 0.83]). For CPS, inter-rater reliability was poorer among less experienced raters (ICC = 0.70; 95%CI [0.57, 0.80]) when compared to experienced ones (ICC = 0.82; 95%CI [0.76, 0.88]). Absolute agreement between the two algorithms was ‘excellent’ for MRS (ICC = 0.96; 95%CI [0.91, 0.98]). For CPS, the best possible agreement was found for CPS defined as the print size sustaining 80% of MRS (ICC = 0.77; 95%CI [0.68, 0.84]). Absolute agreement between raters and automated methods was ‘excellent’ for MRS (ICC = 0.96; 95% CI [0.88, 0.98] for SDev; ICC = 0.97; 95% CI [0.95, 0.98] for NLME). For CPS, absolute agreement between raters and SDev ranged from ‘poor’ to ‘good’ (ICC = 0.66; 95% CI [0.3, 0.80]), while agreement between raters and NLME was ‘good’ (ICC = 0.83; 95% CI [0.76, 0.88]). Conclusion: For MRS, inter-rater reliability is excellent, even considering the possibility of noisy and/or incomplete data collected in low-vision individuals. For CPS, inter-rater reliability is lower. This may be problematic, for instance in the context of multisite investigations or follow-up examinations. The NLME method showed better agreement with the raters than the SDev method for both reading parameters. Setting up consensual guidelines to deal with ambiguous curves may help improve reliability. While the exact definition of CPS should be chosen on a case-by-case basis depending on the clinician or researcher’s motivations, evidence suggests that estimating CPS as the smallest print size sustaining about 80% of MRS would increase inter-rater reliability. [ABSTRACT FROM AUTHOR]

Railways are classic instances of complex socio-technical systems, whose defining characteristic is that they exist and function by integrating (continuous-time) interactions among technical components and human elements. Typically, unlike physical systems, there are no governing laws for describing their dynamics. Based purely on micro-unit data, here we present a data-driven framework to analyze macro-dynamics in such systems, leading us to the identification of specific states and prediction of transitions across them. It consists of three steps, which we elucidate using data from the Dutch railways. First, we form a dimensionally reduced phase-space by extracting a few relevant components, wherein relevance is proxied by dominance in terms of explained variance, as well as by persistence in time. Secondly, we apply a clustering algorithm to the reduced phase-space, resulting in the revelation of states of the system. Specifically, we identify 'rest' and 'disrupted' states, for which the system operations deviates respectively little and strongly from the planned timetable. Third, we define an early-warning metric based on the probability of transitions across states, predict whether the system is likely to transit from one state to another within a given time-frame and evaluate the performance of this metric using the Peirce skill score. Interestingly, using case studies, we demonstrate that the framework is able to predict large-scale disruptions up to 90 minutes beforehand with significant skill, demonstrating, for the railway companies, its potential to better track the evolution of large-scale disruptions in their networks. We discuss that the applicability of the three-step framework stretches to other systems as well—i.e., not only socio-technical ones—wherein real-time monitoring can help to prevent macro-scale state transitions, albeit the methods chosen to execute each step may depend on specific system-details. [ABSTRACT FROM AUTHOR]

The ability to efficiently perform actions immediately following instructions and without prior practice has previously been termed Rapid Instructed Task Learning (RITL). In addition, it was found that instructions are so powerful that they can produce automatic effects, reflected in activation of the instructions in an inappropriate task context. RITL is hypothesized to rely on limited working memory (WM) resources for holding not-yet implemented task rules. Similarly, automatic effects of instructions presumably reflect the operation of task rules kept in WM. Therefore, both were predicted to be influenced by WM load. However, while the involvement of WM in RITL is implicated from prior studies, evidence regarding WM involvement in instructions-based automaticity is mixed. In the current study, we manipulated WM load by increasing the number of novel task rules to be held in WM towards performance in the NEXT paradigm. In this task, participants performed a series of novel tasks presented in mini-blocks, each comprising a) instructions of novel task rules; b) a NEXT phase measuring the automatic activation of these instructed rules, in which participants advance the screen using a key-press; and c) a GO phase in which the new rules are first implemented and RITL is measured. In three experiments, we show a dissociation: While RITL (rule implementation) was impaired by increased WM load, the automatic effects of instructions were not robustly influenced by WM load. Theoretical implications are discussed. [ABSTRACT FROM AUTHOR]

The current study evaluated the efficacy of self-chosen music listening for the function of affect regulation comparing effects in younger and older adults. Forty younger (18–30 years, M = 19.75, SD = 2.57, 14 males) and forty older (60–81 years, M = 68.48, SD = 6.07, 21 males) adults visited the laboratory and were randomised to either the intervention (10 minutes of listening to self-chosen music) or the active control condition (10 minutes of listening to an experimenter-chosen radio documentary). Negative affect (NA) was induced in all participants using a speech preparation and mental arithmetic task, followed by the intervention/control condition. Measures of self-reported affect were taken at baseline, post-induction and post-intervention. Controlling for baseline affect and reactivity to the NA induction, in comparison with the active control group the music listening group demonstrated greater reduction in NA. Supporting developmental theories of positive ageing, analyses also found significant main effects for age, with older adults experiencing greater reduction of NA than younger adults, regardless of condition. Results of the current study provide preliminary insights into the effects of self-chosen music on induced NA, however, additional experimental control conditions comparing self-chosen and experimenter-chosen music with self-chosen and experimenter-chosen active controls are needed to fully understand music listening effects for affect regulation. [ABSTRACT FROM AUTHOR]

In 2008, the NIH launched an undiagnosed diseases program to investigate difficult to diagnose, and typically, multi-system diseases. The objective of this study was to evaluate the presence of psychiatric symptoms or psychiatric diagnoses in a cohort of patients seeking care at the Emory Special Diagnostic Service clinic. We hypothesized that psychiatric symptoms would be prevalent and associated with trauma exposure, and a decreased quality of life and functioning. This is a cross-sectional, retrospective analysis of 247 patients seen between February 7, 2014 and May 31, 2017. The sources for data included the Emory Health History Questionnaire (HHQ) that had the work and social adjustment and quality of life enjoyment and satisfaction questionnaire–short form (QLSQ) embedded in it; medical records, and the comprehensive standardized special diagnostic clinic forms. Primary outcomes were presence of any psychiatric symptom, based on report of the symptom on the HHQ or medical record, or presence of a confirmed preexisting psychiatric disorder. Seventy-two percent of patients had at least one psychiatric symptom while 24.3% of patients had a pre-existing psychiatric diagnosis. Patients with any psychiatric symptom had significantly diminished Q-LES-Q scores (45.27 ± 18.63) versus patients with no psychiatric symptoms (62.01 ± 21.57, t = 5.60, df = 225, p<0.0001) and they had significantly greater functional disability. Patients with a psychiatric disorder also had significantly diminished Q-LES-Q scores (45.16 ± 17.28) versus those without a psychiatric diagnosis (51.85 ± 21.54, t = 2.11, df = 225, p = 0.036) but did not have significantly increased functional impairment. Both patients with psychiatric symptoms and ones with psychiatric disorders had an increased prevalence of trauma. Psychiatric symptoms are prevalent in patients evaluated for undiagnosed disorders. The presence of any psychiatric symptom, with or without a formal psychiatric diagnosis, significantly decreases quality of life and functioning. This suggests that assessment for psychiatric symptoms should be part of the evaluation of individuals with undiagnosed disorders and may have important diagnostic and treatment implications. [ABSTRACT FROM AUTHOR]

Objective: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Korean adolescents of high risk suicide (= who have history of suicide ideation/attempt in previous year) using machine learning techniques. Methods: A nationally representative dataset of Korea Youth Risk Behavior Web-based Survey (KYRBWS) was used (n = 59,984 of middle and high school students in 2017). The classification process was performed using machine learning techniques such as logistic regression (LR), random forest (RF), support vector machine (SVM), artificial neural network (ANN), and extreme gradient boosting (XGB). Results: A total of 7,443 adolescents (12.4%) had a previous history of suicidal ideation/attempt. In the multivariable analysis, sadness (odds ratio [OR], 6.41; 95% confidence interval [95% CI], 6.08–6.87), violence (OR, 2.32; 95% CI, 2.01–2.67), substance use (OR, 1.93; 95% CI, 1.52–2.45), and stress (OR, 1.63; 95% CI, 1.40–1.86) were associated factors. Taking into account 26 variables as predictors, the accuracy of models of machine learning techniques to predict the high-risk suicidal was comparable with that of LR; the accuracy was best in XGB (79.0%), followed by SVM (78.7%), LR (77.9%), RF (77.8%), and ANN (77.5%). Conclusions: The machine leaning techniques showed comparable performance with LR to classify adolescents who have previous history of suicidal ideation/attempt. This model will hopefully serve as a foundation for decreasing future suicides as it enables early identification of adolescents at risk of suicide and modification of risk factors. [ABSTRACT FROM AUTHOR]

Previous studies have shown that self-esteem modulates attentional responses to emotional stimuli. However, it is well known that emotional stimuli can vary in intensity. The main objective of the present study was to further investigate self-esteem related emotional intensity processing in happy and anger faces. Event-related potentials (ERPs) were recorded while 27 high-esteem versus 27 low self-esteem participants carried out a visual oddball task, with neutral faces as the standard stimuli and deviant stimuli varying on valence (happy and anger) and intensity (40%, 70%, and 100% emotive) dimensions. The results showed only high self-esteem people, instead of those with low self-esteem, displayed significant emotion intensity effects for 100% than for 70% happy faces in P3 component. On the other hand, only people with low self-esteem exhibited pronounced intensity effects for anger faces in P3 amplitudes. Moreover, only people with low self-esteem displayed significant intensity effects for 100% compared to both 70% and 40% anger stimuli in N2 amplitudes at central sites. These findings indicate that high self-esteem individuals were typically more susceptible to highly as well as mildly positive stimuli yet less reactive to negative stimuli compared with people with low self-esteem. [ABSTRACT FROM AUTHOR]

Objective: Assessing the epidemiological association between herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections in the United States, and characterizing the trends in the standardized HSV-1 and HSV-2 antibody prevalences (seroprevalences), 1999–2016. Methods: Source of data was the cross-sectional and nationally-representative biennial surveys of the National Health and Nutrition Examination Survey (NHANES). All nine NHANES rounds for 1999–2016 were included in analysis. Datasets of these rounds were combined and analyzed accounting for survey design and applying weighting procedures. Logistic regressions were used to identify associations with seropositivity. Sensitivity analyses were conducted. Results: Odds of HSV-1 infection declined by 2.84% (95% CI: 1.70%-4.00%) annually among men, and by 2.22% (95% CI: 1.23%-3.21%) among women. Declines were highest at younger ages. Odds of HSV-2 infection declined by 2.23% (95% CI: 0.71%-3.82%) annually among men, and by 2.89% (95% CI: 1.57%-4.28%) among women. Odds ratio of the association between HSV-2 and HSV-1 seropositivity was 0.71 (95% CI: 0.60–0.84) for men and 0.81 (95% CI: 0.72–0.91) for women, after adjustment for age, ethnicity, and year. Conclusion: HSV-1 and HSV-2 seroprevalences showed a strong declining trend for at least two decades, for both sexes and for the different ethnicities, possibly reflecting improvements in hygiene and living conditions (for HSV-1), and safer sexual behavior (for HSV-2). HSV-1 seroprevalence declines are most pronounced among young individuals. There is evidence for cross protection between the two infections, suggestive of HSV-1 seropositivity being partially protective against HSV-2 infection. [ABSTRACT FROM AUTHOR]

Owing to the emergence of the Internet and its rapid growth, people can use mobile devices on many social media platforms (blogs, Facebook forums, etc.), and the platforms provide well-known websites for people to express and share their daily activities and ideas on global issues. Many consumers utilize product review websites before making a purchase. Many well-known websites are searched for relevant product reviews and experiences of product use. We can easily collect large amounts of structured and unstructured product data and further analyze the data to determine the desired product information. For this reason, many researchers are gradually focusing on sentiment analysis or opinion exploration (opinion mining) and use this technique to extract and analyze customer opinions and emotions. This paper proposes a sentimental text mining method based on an additional features method to enhance accuracy and reduce implementation time and uses singular value decomposition and principal component analysis for data dimension reduction. This study has four contributions: (1) the proposed algorithm for preprocessing the data for sentiment classification, (2) the additional features to enhance the accuracy of the sentiment classification, (3) the application of singular value decomposition and principal component analysis for data dimension reduction, and (4) the design of five modules based on different features, with or without stemming, to compare the performance results. The experimental results show that the proposed method has better accuracy than other methods and that the proposed method can decrease the implementation time. [ABSTRACT FROM AUTHOR]

Film clips, music, and self-referential statements (termed Velten, after their originator) have been successfully used to temporarily induce sadness and happiness. However, there is little research on the effectiveness of these procedures combined, particularly in internet-based settings, and whether Velten statements contribute to alter mood beyond the effect of simple instructions to close one's eyes and enter the targeted mood. In Study 1 (N = 106) we examined the effectiveness 80 Velten statements (positive, negative, neutral-self, neutral-facts) to create brief and effective sets that might be used in future research. In Study 2 (N = 445) we examined the effect size of 8-min combined mood induction procedures, which presented video clips in the first half and music excerpts with Velten statements or closed eyes instructions in the second half. Participants answered questionnaires on social desirability, joviality, and sadness before being randomly assigned to 1 of 7 groups varying in Valence (positive, negative, neutral) and Velten (closed eyes control, self-referential Velten, and, in the case of neutral condition, factual statements). Subsequently, participants completed the joviality and sadness scales a second time. Compared to the neutral conditions, the positive mood inductions increased joviality (Hedges G = 1.35, 95% CI [1.07, 1.63]), whereas the negative mood inductions increased sadness (Hedges G = 1.28, 95% CI [1.01, 1.55]). We did not observe any significant difference between Velten and closed eyes instructions in inducing joviality or sadness, nor did we observe any significant difference between neutral Velten statements referring to self and facts. Although social desirability bias was associated with reports of greater joviality and lower sadness, it could not account for the effects of the positive and negative mood induction procedures. We conclude that these combined mood induction procedures can be used in online research to study happy and sad mood. [ABSTRACT FROM AUTHOR]

Violations of personal space are associated with discomfort. However, the exact function linking the magnitude of discomfort to interpersonal distance has not yet been specified. In this study, we explore whether interpersonal distance and discomfort are isotropic with respect to uncomfortably far or close distances. We also extend previous findings with regard to intrusions into personal space as well as maintenance of distances outside of personal space. We presented subjects with 15 interpersonal distances ranging from 40 to 250 cm and obtained verbal and joystick-based ratings of discomfort. Whereas discomfort rose immediately when personal space was entered, the gradient was less steep for distances that exceeded the comfort region of personal space. Thus, personal space is anisotropic with regard to experienced discomfort. [ABSTRACT FROM AUTHOR]

We propose a machine learning (ML)-based model for predicting cochlear dead regions (DRs) in patients with hearing loss of various etiologies. Five hundred and fifty-five ears from 380 patients (3,770 test samples) diagnosed with sensorineural hearing loss (SNHL) were analyzed. A threshold-equalizing noise (TEN) test was applied to detect the presence of DRs. Data were collected on sex, age, side of the affected ear, hearing loss etiology, word recognition scores (WRS), and pure-tone thresholds at each frequency. According to the cause of hearing loss as diagnosed by the physician, we categorized the patients into six groups: 1) SNHL with unknown etiology; 2) sudden sensorineural hearing loss (SSNHL); 3) vestibular schwannoma (VS); 4) Meniere's disease (MD); 5) noise-induced hearing loss (NIHL); or 6) presbycusis or age-related hearing loss (ARHL). To develop a predictive model, we performed recursive partitioning and regression for classification, logistic regression, and random forest. The overall prevalence of one or more DRs in test ears was 20.36% (113 ears). Among the 3,770 test samples, the overall frequency-specific prevalence of DR was 6.7%. WRS, pure-tone thresholds at each frequency, disease type (VS or MD), and frequency information were useful for predicting DRs. Sex and age were not associated with detecting DRs. Based on these results, we suggest possible predictive factors for determining the presence of DRs. To improve the predictive power of the model, a more flexible model or more clinical features, such as the duration of hearing loss or risk factors for developing DRs, may be needed. [ABSTRACT FROM AUTHOR]

Cortical responses to sensory inputs vary across repeated presentations of identical stimuli, but how this trial-to-trial variability impacts detection of sensory inputs is not fully understood. Using multi-channel local field potential (LFP) recordings in primary somatosensory cortex (S1) of the awake mouse, we optimized a data-driven cortical state classifier to predict single-trial sensory-evoked responses, based on features of the spontaneous, ongoing LFP recorded across cortical layers. Our findings show that, by utilizing an ongoing prediction of the sensory response generated by this state classifier, an ideal observer improves overall detection accuracy and generates robust detection of sensory inputs across various states of ongoing cortical activity in the awake brain, which could have implications for variability in the performance of detection tasks across brain states. [ABSTRACT FROM AUTHOR]

Background: Whilst there has been extensive study of the mechanisms underlying the regulation for pictures, the ability and the mechanisms beyond the regulation of words remains to be clarified. Similarly, the effect of strategy when applying a regulatory process is still poorly explored. The present study seeks to elucidate these issues comparing the effect of regulation and of strategy to both neutral and emotional words and pictures. Methodology/Principal findings: Thirty young adults applied the strategy of distancing to the emotions elicited by unpleasant and neutral pictures and words while their subjective ratings and ERPs were recorded. At a behavioral level, participants successfully regulated the arousal and the valence of both pictures and words. At a neural level, unpleasant pictures produced an increase in the late positive potential modulated during the regulate condition. Unpleasant linguistic stimuli elicited a posterior negativity as compared to neutral stimuli, but no effect of regulation on ERP was detectable. More importantly, the effect of strategy independently of stimulus type, produced a significant larger Stimulus Preceding Negativity. Dipole reconstruction localized this effect in the middle frontal areas of the brain. Conclusions: As such, these new psychophysiological findings might help to understand how pictures and words can be regulated by distancing in daily life and clinical contexts, and the neural bases of the effect of strategy for which we suggest an integrative model. [ABSTRACT FROM AUTHOR]

Background and objective: Education of disease plays an important role in management of Parkinson's disease (PD). However, little is known about the link between the understanding of disease and the burden of care. This study was carried out to find the correlation between the burden of care and the understanding of disease in caregivers for PD patients. Methods: Non-demented patients with PD and their caregivers participated in structured interviews. Understanding of patients and caregivers was evaluated through newly-devised questions. The caregiver burden inventory was used to assess the burden of care. Results: A total of 142 pairs of patients and their caregivers were recruited. A correlation analysis showed that the burden of care was positively associated with low understanding of the disease by the caregiver. Daily care time and female patients were revealed to be independently associated with the burden of care through a multivariate analysis. Further analyses were performed in the caregiver group according to relationship with patients. The spouse group showed an increased burden of care and poor understanding compared to the offspring group. A multivariate analysis revealed that daily care time and understanding were independent predictors for the burden of care in the spouse group. There was no significant association in the offspring group. Conclusion: The burden of care was associated with higher daily caregiving time and female gender of the patient, and was significantly increased in the spouse of the patient. In the spouse group, better understanding of the caregiver correlated with less burden of care. [ABSTRACT FROM AUTHOR]

People maintain a positive self-concept through positive self-appraisals (Self-Serving Bias Effect, SSBE) and a diminished memory for self-threatening information (Mnemic-Neglect Effect, MNE). Other people also influence a person’s self-concept. This study investigated SSBE and MNE in 60 females by using a trait-judgment paradigm applying two perspectives (self- and third-person appraisals) and a recall task. Additionally, self-esteem was assessed as an associated factor. SSBE and MNE were found in both kinds of appraisal perspectives. Interestingly, participants saw themselves as even more positive in reflected appraisals. SSBE and self-esteem were associated only in self-appraisals, indicating a larger SSBE on self-appraisals with raising self-esteem. In conclusion, both what females think about themselves and how they assume that others think about them preserve their overall positive self-concept. [ABSTRACT FROM AUTHOR]

The aim of this investigation was to establish the validity of a GPS-based tracking system (Polar Team Pro System, PTPS) for estimating sprint performance and to evaluate additional diagnostic indices derived from the temporal course of the movement velocity. Thirty-four male soccer players (20 ± 4 years) performed a 20 m sprint test measured by timing gates (TG), and while wearing the PTPS. To evaluate the relevance of additional velocity-based parameters to discriminate between faster and slower athletes, the median-split method was applied to the 20-m times. Practical relevance was estimated using standardized mean differences (d) between the subgroups. Differences between the criterion reference (TG) and PTPS for the 10 and 20 m splits did not vary from zero (dt10: -0.01 ± 0.07 s, P = 0.7, d < -0.1; dt20: -0.01 ± 0.08 s, P = 0.4, d < -0.2). Although subgroups revealed large differences in their sprint times (d = -2.5), the average accelerations between 5 and 20 km/h as well as 20 and 25 km/h showed merely small effects (d < 0.5). Consequently, analyses of velocity curves derived from PTPS may help to clarify the occurrence of performance in outdoor sports. Thus, training consequences can be drawn which contribute to the differentiation and individualization of sprint training. [ABSTRACT FROM AUTHOR]

The occurrence of a stressful event is considered to increase the risk of developing depression. In the present study we explore whether the breakup of a romantic relationship can be used as an experimental model to study a depression-like state during a period of stress in individuals without a psychiatric disorder. The primary aim of our study was to investigate: 1) whether individuals with a recent romantic relationship breakup (‘‘heartbreak”) demonstrate symptoms of depression, 2) how to describe heartbreak characteristics based on data from a comprehensive questionnaire battery, and 3) whether this description can capture severity of depression symptoms. Secondary, we were interested in gender differences with regard to the above study objectives. Subjects who have experienced a relationship breakup in the preceding six months (N = 71) or are in a romantic relationship (N = 46) participated in our study. A questionnaire battery was administered to acquire information related to depression, mood, the breakup and (former) relationship. Principal Component Analysis with Procrustes bootstrapping was performed to extract components from the questionnaire data. Even though our sample of individuals who recently have experienced a relationship breakup can be on average considered non-depressed, group-level depression scores were elevated compared to individuals in a relationship (p = .001) and 26.8% reported symptoms corresponding to mild, moderate or severe depression. We described heartbreak by two principal components interpreted as ‘‘sudden loss” and ‘‘lack of positive affect”, respectively. Highly significant correlations between the component scores and depression scores were found (p < .001 and p < .001, respectively), although these correlations differed between the genders. Based on these findings, we propose that the experience of a romantic relationship breakup is a viable experimental model to examine symptoms of depression in individuals without a psychiatric disorder. This way, stress-related coping and depression vulnerability can be studied in further research. [ABSTRACT FROM AUTHOR]

Angry rumination and hostile attribution bias are important cognitive factors of aggression. Although prior theoretical models of aggression suggest that aggressive cognitive factors may influence each other, there are no studies examining the longitudinal relationship between angry rumination and hostile attribution bias. The present study used cross-lagged structural equation modeling to explore the longitudinal mutual relationship between hostile attribution bias and angry rumination; 941 undergraduate students (38.5% male) completed questionnaires assessing the variables at two time points. The results indicate that hostile attribution bias showed a small but statistically significant effect on angry rumination 6 months later, and angry rumination showed a quite small but marginally significant effect on hostile attribution bias across time. The present study supports the idea that hostile attribution bias influences angry rumination, and argue that the relationship between angry rumination and hostile attribution bias may be mutual. Additionally, the results suggest that there may be a causal relation of different aggression-related cognitive factors. [ABSTRACT FROM AUTHOR]

Objective: The special status accorded to elite athletes stems from their uncommon genetic potential to excel in world-class power sports (PS). Genetic polymorphisms have been reported to influence elite PS status. Reports of associations between the α-actinin-3 gene (ACTN3) R577X polymorphism and PS have been inconsistent. In light of new published studies, we perform a meta-analysis to further explore the roles of this polymorphism in PS performance among elite athletes. Methods: Multi-database literature search yielded 44 studies from 38 articles. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were used in estimating associations (significance threshold was set at Pa ≤ 0.05) using the allele-genotype model (R and X alleles, RX genotype). Outlier analysis was used to examine its impact on association and heterogeneity outcomes. Subgroup analysis was race (Western and Asian) and gender (male/female)-based. Interaction tests were applied to differential outcomes between the subgroups, P-values of which were Bonferroni corrected (Pinteraction BC). Tests for sensitivity and publication bias were performed. Results: Significant overall R allele effects (OR 1.21, 95% CI 1.07–1.37, Pa = 0.002) were confirmed in the Western subgroup (OR 1.11, 95% CI 1.01–1.22, Pa = 0.02) and with outlier treatment (ORs 1.12–1.20, 95% CIs 1.02–1.30, Pa < 10−5–0.01). This treatment resulted in acquired significance of the RX effect in Asian athletes (OR 1.91, 95% CI 1.25–2.92, Pa = 0.003). Gender analysis dichotomized the RX genotype and R allele effects as significantly higher in male (OR 1.14, 95% CI 1.02–1.28, Pa = 0.02) and female (OR 1.58, 95% CI 1.21–2.06, Pa = 0.0009) athletes, respectively, when compared with controls. Significant R female association was improved with a test of interaction (Pinteraction BC = 0.03). The overall, Asian and female outcomes were robust. The R allele results were more robust than the RX genotype outcomes. No evidence of publication bias was found. Conclusions: In this meta-analysis, we present clear associations between the R allele/RX genotype in the ACTN3 polymorphism and elite power athlete status. Significant effects of the R allele (overall analysis, Western and female subgroups) and RX genotype (Asians and males) were for the most part, results of outlier treatment. Interaction analysis improved the female outcome. These robust findings were free of publication bias. [ABSTRACT FROM AUTHOR]

Objectives: Reviews of violence against children in disaster settings focus on armed conflict. Little is understood about natural disasters which has implications in planning humanitarian response. We examined the magnitude and direction of the association between exposure to natural disasters and physical, emotional, and sexual violence against children, and assessed the quality of the evidence. Methods: We searched 15 health and social science databases from first record until May 16, 2018. Publications describing all types of quantitative study design were eligible for inclusion. We presented study characteristics and quality in a narrative form and generated pooled estimates using a three-level random effects model. We evaluated Cochrane’s Q with p-values below 0.10 and radial plots to assess heterogeneity. Planned subgroup analyses explored differential results by violence form, study design, and analysis method. Results: 11 publications met inclusion criteria. The majority were cross-sectional studies examining physical or sexual violence in the United States. We found no evidence of a consistent association or directional influence between natural disasters and violence against children. Combined categorical violence outcomes had substantial heterogeneity [Q (df = 66) = 252.83, p < 0.001]. Subgroups without evidence of heterogeneity had confidence intervals that included a possible null effect. Our findings were mainly limited by inconsistencies in operational definitions of violence, a lack of representative sampling, and unclear establishment of temporal order between natural disaster exposure and violence outcomes. Conclusions: Based on the available evidence, we cannot confidently conclude that natural disasters increase the level or severity of violence against children above non-disaster settings, however heterogeneity and study quality hamper our ability to draw firm conclusions. More nuanced and rigorous research is needed to inform practice and policy as natural disasters increasingly affect human populations. [ABSTRACT FROM AUTHOR]

Background: Family carers are an important source of care for older people. Although several studies have reported that subjective caregiver burden is related to depressive symptoms there are no systematic reviews quantifying this association. Objective: To establish the extent to which subjective caregiver burden is associated with depressive symptoms and whether this association would vary by study or care characteristics. Methods: We searched major databases such as PubMed, CINAHL, PsycINFO, Scopus and ISI Proceedings up to March 2018, and conducted a meta-analysis of included studies. Summary estimates of the association were obtained using a random-effects model to improve generalisation of findings. Results: After screening of 4,688 articles, 55 studies were included providing a total of 56 independent comparisons with a total of 9,847 carers from data across 20 countries. There was a large, positive association between subjective caregiver burden and depressive symptoms ( = 0.514; 95% CI = 0.486, 0.541), with very low heterogeneity amongst individual studies (I2 = 8.6%). Sensitivity analyses showed no differences between cross-sectional or repeated measures ( = 0.521; 95% CI = 0.491, 0.550; 51 samples) and longitudinal studies ( = 0.454; 95% CI = 0.398, 0.508; 6 samples). We found a higher effect size for those caring for people living with dementia compared to those caring for frail older people, and stroke survivors. Carer sex, age and kinship did not change the estimate of the effect. Conclusions: Subjective caregiver burden is a significant risk factor for depressive symptoms in carers of older people and may precipitate clinical depression. Those caring for people with dementia experience greater burden. There is a need for longitudinal evaluations examining the effects of potential mediators of the association of subjective burden and depressive symptoms. Future interventions should test whether minimizing subjective burden may modify the risk of developing depression in carers of older relatives. [ABSTRACT FROM AUTHOR]

Reliability and economic assessment of the Multiplex® optical sensor employed for non-destructive grape parameters estimates was evaluated in 2017 against a wet chemistry approach in mature vineyards including five cultivars (two whites, two red and one pink colored) assuring a broad range of variation in both technological and phenolic maturity parameters. Among the five Multiplex (Mx) indices evaluated (SFR_R, FLAV, FLAV-UV, ANTH_RG and FERARI) in all cultivars with the exception of Barbera SFR_R showed a significant and linear correlation with total soluble solids (TSS) for TSS ≥ 10 °Brix. Conversely, no significant correlation was found between FLAV and total flavonols concentration, whereas a significant linear correlation was found in Barbera (R2 = 0.66) and Ervi (R2 = 0.63) when the FLAV index was replaced with the FLAV_UV index. Within each cultivar, both ANTH_RG and FERARI showed close correlations with total anthocyanins concentration determined by wet chemistry although under different model shapes. Expressing berry color accumulation on a per skin mass basis rather than for whole berry mass basis, allowed for better separation of behavior of single cultivars and improved accuracy of model fitting for the combination of Barbera and ANTH_RG. A strict linear correlation was always found, within each index, for Mx readings taken on the two opposite sides of the same cluster, implying no significant within-cluster differences in sugar, color and flavonol concentrations. Economic assessment of Mx by means of the Net Present Value (NPV) approach showed that Mx is economically viable for a two hectare vineyard cultivating three red grape varieties (90 samples per year) if its lifetime is at least 7 years. Conversely, if only two red varieties are grown Mx should be used at least 11 years to make it economic suitable. Bigger properties growing a higher number of red varieties are the more interested in Mx as the expected NPV assumes positive values with a Mx usage of minimum 3 years. [ABSTRACT FROM AUTHOR]

For at least four decades, researchers have studied the effectiveness of interventions designed to increase well-being. These interventions have become known as positive psychology interventions (PPIs). Two highly cited meta-analyses examined the effectiveness of PPIs on well-being and depression: Sin and Lyubomirsky (2009) and Bolier et al. (2013). Sin and Lyubomirsky reported larger effects of PPIs on well-being (r = .29) and depression (r = .31) than Bolier et al. reported for subjective well-being (r = .17), psychological well-being (r = .10), and depression (r = .11). A detailed examination of the two meta-analyses reveals that the authors employed different approaches, used different inclusion and exclusion criteria, analyzed different sets of studies, described their methods with insufficient detail to compare them clearly, and did not report or properly account for significant small sample size bias. The first objective of the current study was to reanalyze the studies selected in each of the published meta-analyses, while taking into account small sample size bias. The second objective was to replicate each meta-analysis by extracting relevant effect sizes directly from the primary studies included in the meta-analyses. The present study revealed three key findings: (1) many of the primary studies used a small sample size; (2) small sample size bias was pronounced in many of the analyses; and (3) when small sample size bias was taken into account, the effect of PPIs on well-being were small but significant (approximately r = .10), whereas the effect of PPIs on depression were variable, dependent on outliers, and generally not statistically significant. Future PPI research needs to focus on increasing sample sizes. A future meta-analyses of this research needs to assess cumulative effects from a comprehensive collection of primary studies while being mindful of issues such as small sample size bias. [ABSTRACT FROM AUTHOR]

Although interpersonal coordinative activities have been shown to produce prosocial effects in both adults and children, the underlying mechanisms remain unclear. While most approaches focus on the effect of mimicry and synchronous behavioral matching, we hypothesize that temporal predictability might play a central role in producing prosocial effects, as it directs coordination and might therefore strengthen shared intentionality. In a percussion task with pairs of 5-year old children, we manipulated temporal predictability and movement similarity/predictability between the pair’s movements. Temporal predictability was manipulated by instructing the pair to play the instruments either to beats that were evenly-spaced, and therefore predictable, or to beats that were random, and therefore unpredictable. Movement similarity/predictability was manipulated by having the pair play rhythmic patterns that were similar, predictable, or independent from each other. Children who played to predictable beats were more willing to solve problems cooperatively with their partners and to help when their partners had an accident. In contrast, there was no positive effect of rhythmic predictability or similarity. These results are the first to show that temporal predictability affects prosociality independent of movement similarity or predictability. We conclude that the predictable time frame commonly seen in coordinative activities may be key to strengthening shared intentionality and producing prosocial effects. [ABSTRACT FROM AUTHOR]

The performance of data clustering algorithms is mainly dependent on their ability to balance between the exploration and exploitation of the search process. Although some data clustering algorithms have achieved reasonable quality solutions for some datasets, their performance across real-life datasets could be improved. This paper proposes an adaptive memetic differential evolution optimisation algorithm (AMADE) for addressing data clustering problems. The memetic algorithm (MA) employs an adaptive differential evolution (DE) mutation strategy, which can offer superior mutation performance across many combinatorial and continuous problem domains. By hybridising an adaptive DE mutation operator with the MA, we propose that it can lead to faster convergence and better balance the exploration and exploitation of the search. We would also expect that the performance of AMADE to be better than MA and DE if executed separately. Our experimental results, based on several real-life benchmark datasets, shows that AMADE outperformed other compared clustering algorithms when compared using statistical analysis. We conclude that the hybridisation of MA and the adaptive DE is a suitable approach for addressing data clustering problems and can improve the balance between global exploration and local exploitation of the optimisation algorithm. [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]

We study the relative importance of the three dimensions of need-supportive teaching (NST) and students’ self-efficacy to gain new knowledge about students’ achievement in higher education. NST assumes that teachers are key to the motivation of students, providing autonomy support, structure (support of competence), and involvement (support of relatedness). In turn, self-efficacy raises students’ confidence in their ability to succeed in academic tasks. Drawing on 86,000 records of teaching evaluations by students at the University of Girona (Spain), we present evidence that teachers’ involvement and students’ self-efficacy are the two elements most strongly and positively related to achievement. Students obtain higher marks when they believe that their teachers are dependable and available to offer resources, and when they feel capable of organizing and implementing the courses of action necessary to acquire knowledge. We also find that students’ experience of autonomy support and structure are negatively (or not) correlated with achievement. Subgroup analyses also indicate that students have different needs in different knowledge areas. [ABSTRACT FROM AUTHOR]

Interoception is impaired in different psychiatric disorders and is also associated with emotions. Only one study could show a higher interoceptive accuracy (IAcc) in patients with obsessive-compulsive disorder (OCD). Based on the predictive coding system we assume contrary results, indicating a decreased IAcc in patients with OCD. So far, there is no study investigating the effect of cognitive-behavioral therapy on IAcc in patients with OCD. Therefore, we hypothesize that patients with OCD improve their IAcc during the time course of therapy compared to healthy controls. Twenty-six patients with OCD from the Psychosomatic Clinic in Windach were examined in the time course of cognitive-behavioral therapy. They were compared to 26 matched healthy controls. IAcc via the heartbeat perception task as well as questionnaire data (OCD-, depression- and anxiety symptoms) were assessed. Results showed that IAcc, OCD-, depression- and anxiety symptoms were attenuated in patients with OCD. Patients recovered in the time course of therapy regarding OCD-, depression- and anxiety symptoms. Interoceptive deficits did not change in the time course of cognitive-behavioral therapy. We demonstrated that IAcc is affected in patients with OCD and this deficit does not change during the time course of a standardized therapy. Future studies should investigate, whether an inaccuracy in perceiving one’s bodily signals constitutes a risk factor for relapse. Further, it could be examined if IAcc can be increased via self- and body focus interventions in patients with OCD. [ABSTRACT FROM AUTHOR]

Managed honey bee (Apis mellifera) colonies are kept at much greater densities than naturally occurring feral or wild colonies, which may have detrimental effects on colony health and survival, disease spread, and drifting behavior (bee movement between natal and non-natal colonies). We assessed the effects of a straightforward apiary management intervention (altering the density and visual appearance of colonies) on colony health. Specifically, we established three “high density / high drift” (“HD”) and three “low density / low drift” (“LD”) apiary configurations, each consisting of eight bee colonies. Hives in the HD apiary configuration were of the same color and placed 1m apart in a single linear array, while hives in the LD apiary configuration were placed 10m apart at different heights, facing outwards in a circle, and made visually distinctive with colors and symbols to reduce accidental drift between colonies. We investigated disease transmission and dynamics between the apiary configurations by clearing all colonies of the parasitic mite Varroa destructor, and subsequently inoculating two randomly-chosen colonies per apiary with controlled mite doses. We monitored the colonies for two years and found that the LD apiary configuration had significantly greater honey production and reduced overwinter mortality. Inoculation and apiary management intervention interacted to affect brood mite levels, with the highest levels in the inoculated colonies in the HD configuration. Finally, foragers were more than three times more likely to drift in the HD apiary configurations. Our results suggest that a relatively straightforward management change–placing colonies in low-density visually complex circles rather than high-density visually similar linear arrays–can provide meaningful benefits to the health and productivity of managed honey bee colonies. [ABSTRACT FROM AUTHOR]

Research on awe has grown exponentially in recent decades; however, few studies have considered whether awe-inspiring experiences also inspire other emotions. In two studies, we explored whether interventions targeting awe also evoke other discrete emotions. Additionally, we considered two constructs that may be associated with increases in each emotion—self-relevant thoughts and connectedness. In Study 1, we manipulated awe in virtual reality and examined the potential effects of a prototypical awe experience—a spacewalk accompanied by an audio clip of Carl Sagan’s Pale Blue Dot. In Study 2, we manipulated awe with a video depicting scenes of Earth from outer space paired with the same audio clip. Across both studies, a prototypical awe experience was associated not only with awe, but with compassion, gratitude, love, and optimism, along with connectedness and self-relevant thoughts. Furthermore, we found that increases in self-relevant thoughts and connectedness in response to the awe induction predicted increases in each emotion evoked and vice-versa. These findings suggest that experiences that are commonly considered awe-inspiring—such as viewing a picturesque landscape—may be more appropriately conceptualized more broadly as self-transcendent. More work is needed to determine whether the documented benefits of awe may be more appropriately interpreted as the benefits of self-transcendent emotions. [ABSTRACT FROM AUTHOR]

In this study, we designed a delayed payment mechanism in laboratory second price auctions (SPAs), under which subjects received a cash endowment two weeks after the experiment day and had to use their own money to pay the experimental losses (if any) on the experiment day. We compared the effect of delayed payment on overbidding in the induced value SPAs with the conventional “on-the-spot” payment mechanism where the subjects received an endowment on the experiment day, and the prepaid mechanism where the subjects received the endowment two weeks before the experiment day. Each auction was repeated for 20 rounds to provide sufficient learning opportunities to the bidders. Our results showed that bids converged to the corresponding values over auction rounds and overbidding was reduced by previous losses, consistently with the adaptive learning theory. Moreover, overbidding seems to depend significantly on bidders’ cash holding, and the magnitude of the payment treatment effects depends crucially on liquidity constraints. In the presence of liquidity constraints, both delayed and prepaid payment mechanisms reduced overbidding, while in the absence of liquidity constraints, only the delayed endowment mechanism reduced overbidding. Furthermore, when controlling the degree of liquidity constraints, subjects with higher GPAs were less likely to overbid and the delayed endowment mechanism significantly reduced overbidding compared to other payment mechanisms. These results suggest that overbidding in SPAs might be caused by bounded rationality and could be reduced by adaptive learning especially when overbidding becomes “truly” costly to subjects. [ABSTRACT FROM AUTHOR]

This paper analyzes seasonal effects and their potential drivers in charitable giving. We conduct two studies to analyze whether donations to the German Red Cross differ between the Christmas season and summer. In study 1 we find that in the pre-Christmas shopping season prosocial subjects almost donate 50% less compared to prosocials in summer. In study 2 we replicate the low donations in the Christmas season. In an extensive questionnaire we control for several causes of this effect. The data suggest that the higher prosocials’ self-reported stress level, the lower the donations. The higher their relative savings, the lower the giving. Our questionnaire rules out that “donation fatigue” matters. That is, donations do not depend on the number of charitable campaigns subjects are confronted with and their engagement in these activities during Christmas season outside the lab. [ABSTRACT FROM AUTHOR]

Caring is the essence of nursing practice. Caring Efficacy scale was developed with the purpose of measuring nurses’ perceived self-efficacy in orienting and maintaining caring relationships with patients. Since any instruments measuring caring self-efficacy have not been developed in Italy, the study aimed at culturally adapting and validating Caring Efficacy scale in a sample of Italian nurses. A total of 300 registered nurses were asked to fill a self-reported questionnaire; translation-back-translation procedure was carried out to maintain semantic, idiomatic and conceptual equivalence of the original scale. Then, factor analysis was performed in order to test appropriateness of the factor structure. Convergent and discriminant validity was also tested. A two-factor structure with 17 items was found. Results show that Cronbach’s Alpha value was 0.84 for Confidence to Care, and 0.75 for Doubts and Concerns. Correlation analysis for convergent and discriminant validity showed that Confidence to Care was positively correlated with sense of coherence and no significant correlation with Doubts and Concerns was found. Caring efficacy scale can be used by nurse managers as a way of assessing nurses’ self-efficacy and their caring orientation, thus improving quality of patient care. [ABSTRACT FROM AUTHOR]

The development of industrial agriculture has enabled a sharp increase in food trade at the global scale. Worldwide trade underpins food security by distributing food surpluses to food deficient countries. The study of agricultural product flows can provide insights on the complex interactions between exporting and importing countries and the resulting network structures. Commercial partnerships between countries can be modelled using a complex network approach. Based on the detailed trade matrices from FAO covering the period from 1986 to 2013, we present an analysis of the world cereal trade in terms of weighted and directed networks. The network nodes are the countries and the links are the trades of agricultural products in mass. We reveal the changing topology and degree distribution of the world network during the studied period. We distinguish three entangled subnetwork structures when considering the temporal stability of the trades. The three subnetworks display distinct properties and a differential contribution in total trade. Trades of uninterrupted activity over the 28-year study period compose the backbone network which accounts for two thirds of all traded mass and is scale-free. Inversely, two thirds of the trades only have one or two consecutive years of activity and define the transient subnetwork which displays random growth and accounts for very little traded mass. The trades of intermediate duration display an exponential growth both in numbers and in traded mass and define the intermediate subnetwork. The topology of each subnetwork is a time invariant. The identification of invariant structures is a useful basis for developing prospective agri-food network modelling to assess their resilience to perturbations and shocks. [ABSTRACT FROM AUTHOR]