Background and objectivesThe study of brain functional connectivity alterations in children with Attention-Deficit/Hyperactivity Disorder has been the subject of considerable investigation, but the biological mechanisms underlying these changes remain poorly understood. Here, we aim to investigate the brain alterations in patients with ADHD and Typical Development children and accurately classify ADHD children from TD controls using the graph-theoretical measures obtained from resting-state fMRI.Materials and methodsWe investigated the performances of rs-fMRI data for classifying drug-naive children with ADHD from TD controls. Fifty (...) six drug-naive ADHD children and 56 age matched TD controls were included in this study. The graph measures extracted from rs-fMRI functional connectivity were used as features. Extracted network-based features were fed to the RFE feature selection algorithm to select the most discriminating subset of features. We trained and tested Support Vector Machine, Random Forest, and Gradient Boosting using Peking center data from ADHD-200 database to classify ADHD and TD children using discriminative features. In addition to the machine learning approach, the statistical analysis was conducted on graph measures to discover the differences in the brain network of patients with ADHD.ResultsAn accuracy of 78.2% was achieved for classifying drug-naive children with ADHD from TD controls employing the optimal features and the GB classifier. We also performed a hub node analysis and found that the number of hubs in TD controls and ADHD children were 8 and 5, respectively, indicating that children with ADHD have disturbance of critical communication regions in their brain network. The findings of this study provide insight into the neurophysiological mechanisms underlying ADHD.ConclusionPattern recognition and graph measures of the brain networks, based on the rs-fMRI data, can efficiently assist in the classification of ADHD children from TD controls. (shrink)

Introduction Ethical climate in medical contexts is referred to the organizational environment consisting of medical staff interpersonal relationships regarding patient care. This element affects staff behavior in an organization. The investigation and comparison of the effects of the interventions promoting ethical climate are among important nursing challenges that should be considered by researchers. The present study was conducted to compare the effect of nurses’ ethical decision-making skills and interpersonal communication training on their ethical climate. Materials and methods This experimental study (...) was performed on 90 nurses working in the general teaching hospitals of Mashhad, Iran. The sampling process was conducted in two stages. Nurses were divided into three groups: intervention 1, intervention 2 and control group. The intervention was separate 12-h workshops for each of the intervention groups. The ethical climate questionnaire by Victor and Cullen was used to assess the score of ethical climate in the three groups both at the beginning and 4 weeks after the workshop. The data were analyzed in Statistical Package for Social Sciences software using descriptive statistics, analysis of variance, Kruskal–Wallis, paired sample t-test, Wilcoxon test, and post hoc Tukey’s test. Ethical considerations were as follows: The study design was approved by the Research Ethics Committee of Mashhad University of Medical Sciences. Informed consent was obtained from all subjects, and they were ensured about the confidentiality terms. Results The mean scores of the ethical climate test at the first stage were obtained as 66.0 ± 5.5, 67.8 ± 6.9, and 67.7 ± 7.2 in the ethical decision-making, interpersonal communication, and control groups, respectively. Accordingly, the three groups were not significantly different in terms of this variable. However, after the intervention, a significant difference was observed among the three groups regarding the mean scores of the ethical climate test In this regard, the calculated mean scores in the ethical decision-making, interpersonal communication, and control groups were 99.3 ± 6.3, 90.4 ± 7.7, and 67.4 ± 7.9, respectively. Conclusion Training workshops about ethical decision-making skills and interpersonal communication on the ethical professional climate of nurses was effective. Nonetheless, the effect of ethical decision-making skill training was found to be higher than interpersonal communication skill training. Therefore, it is recommended that nursing managers hold training workshops to improve the ethical climate for nurses. (shrink)

Consumers’ inclinations towards materialism and compulsive buying are influenced by a variety of factors. Materialistic consumers face maladies that cause stress and lower subjective well-being and are unable to control their buying behaviour that in turn leads to social and financial issues. This paper aims to investigate the effect of emotional intelligence training on consumers’ materialism and compulsive buying. The experimental design involves 36 respondents across both groups. Findings confirm the hypothesis that ability-based training programmes can help consumers improve their (...) emotional intelligence whilst also lowering their levels of materialism and compulsive buying. In sum, the results extend the existing literature on consumer materialism by providing an explanation on how specific emotional ability-based training can diminish materialistic and excessive buying inclinations. The development of emotional intelligence skills-based training programmes contributes to more sustainable consumer behaviour, mitigating the vulnerability to materialism and related addictive behavioural consequences. (shrink)

Artificial Intelligence (AI) must be directed at humane ends. The development of AI has produced great uncertainties of ensuring AI alignment with human values (AI value alignment) through AI operations from design to use. For the purposes of addressing this problem, we adopt the phenomenological theories of material values and technological mediation to be that beginning step. In this paper, we first discuss the AI value alignment from the relevant AI studies. Second, we briefly present what are material values and (...) technological mediation and reflect on the AI value alignment through the lenses of these theories. We conclude that a set of finite human values can be defined and adapted to the stable life tasks that AI systems will be called upon to accomplish. The AI value alignment can also be fostered between designers and users through technological mediation. Upon that foundation, we propose a set of common principles to understand the AI value alignment through phenomenological theories. This paper contributes the unique knowledge of phenomenological theories to the discourse on AI alignment with human values. (shrink)