Dalydamgaard4881

Most patients (75%) lived within 25 miles of our clinics and experienced an average commute time of 79.4 min, though 10% required 3 h or more. Additional family/caregiver assistance was required for 76% of patients, which resulted in an inclusive average commute time of 138.2 min per patient. Conclusion Chronically neurologically-disabled patients and their caregivers may be burdened by the commute to outpatient appointments. To minimize this burden, increased emphasis on telemedicine coverage for those with chronic neurologic disability should be considered by all payors.

Co-morbid insomnia and sleep apnea (COMISA) is a common and debilitating condition that is more difficult to treat compared to insomnia or sleep apnea-alone. Emerging evidence suggests that cognitive behavioral therapy for insomnia (CBTi) is effective in patients with COMISA, however, those with more severe sleep apnea and evidence of greater objective sleep disturbance may be less responsive to CBTi. Polysomnographic sleep study data has been used to predict treatment response to CBTi in patients with insomnia-alone, but not in patients with COMISA. We used randomized controlled trial data to investigate polysomnographic predictors of insomnia improvement following CBTi, versus control in participants with COMISA.

One hundred and forty five participants with insomnia (ICSD-3) and sleep apnea [apnea-hypopnea index (AHI) ≥ 15] were randomized to CBTi (

= 72) or no-treatment control (

= 73). Mixed models were used to investigate the effect of pre-treatment AHI, sleep duration, and other traditional (AASven in the presence of severe OSA and objective sleep disturbance.New types of artificial intelligence products are gradually transferring to voice interaction modes with the demand for intelligent products expanding from communication to recognizing users' emotions and instantaneous feedback. At present, affective acoustic models are constructed through deep learning and abstracted into a mathematical model, making computers learn from data and equipping them with prediction abilities. Although this method can result in accurate predictions, it has a limitation in that it lacks explanatory capability; there is an urgent need for an empirical study of the connection between acoustic features and psychology as the theoretical basis for the adjustment of model parameters. Accordingly, this study focuses on exploring the differences between seven major "acoustic features" and their physical characteristics during voice interaction with the recognition and expression of "gender" and "emotional states of the pleasure-arousal-dominance (PAD) model." In this study, 31 females and 31 males aged between 21 and 60 were invited using the stratified random sampling method for the audio recording of different emotions. Subsequently, parameter values of acoustic features were extracted using Praat voice software. Finally, parameter values were analyzed using a Two-way ANOVA, mixed-design analysis in SPSS software. Results show that gender and emotional states of the PAD model vary among seven major acoustic features. Moreover, their difference values and rankings also vary. The research conclusions lay a theoretical foundation for AI emotional voice interaction and solve deep learning's current dilemma in emotional recognition and parameter optimization of the emotional synthesis model due to the lack of explanatory power.University students (n = 758) from Bulgaria, Estonia, Finland, and Portugal were given a list of morally relevant behaviors (MRB), the Schwartz Value Survey (PVQ40) and Tangney's TOSCA, measuring empathic guilt, guilt over norm-breaking, and shame. A factor analysis of MRB yielded 4 dimensions prosocial behaviors, interpersonal transgressions, antisocial behaviors and secret transgressions. Prosocial behaviors were predicted by self-transcendence-self-enhancement (SET) value contrast only while the three transgression categories were associated with both SET and openness to change-conservation (hedonism-conformity) contrast. Norm-breaking guilt was more strongly associated with behaviors than were empathic guilt and shame. However, shame was (positively) associated with secret transgressions in three countries, after controlling for values. The associations were strongest in Bulgaria and Estonia while fewer associations were found in Finland and Portugal. The implications of the findings for the cross-cultural psychology of morality are discussed.According to the broaden-and-build theory of positive emotions, the frequency of positive emotions is associated with the development of positive attitudes, cognitions, and behaviors in organizational contexts. However, positive and negative attitudes at work might also be influenced by different personal and job resources. While emotional intelligence has been significantly associated with positive job attitudes and personal well-being, no studies have yet examined the joint role of teacher happiness and emotional intelligence in key teacher job attitudes. The present study assesses whether emotional intelligence interacts with levels of teacher happiness to jointly explain important teacher job attitudes (i.e., job satisfaction and turnover intention). A total sample of 685 teaching professionals (431 female) filled out a battery of scales including subjective happiness, emotional intelligence, job satisfaction, and turnover intention. Our results revealed that subjective happiness was significantly associated with both higher job satisfaction and lower turnover intention. Likewise, emotional intelligence was positively related to happiness and job satisfaction, and negatively related to turnover intention. click here Finally, interaction analysis showed the main effects of happiness and emotional intelligence in explaining teacher job attitudes. Beyond the main effects, the interaction effects of happiness and emotional intelligence were significant in predicting all teachers' job attitude indicators, even controlling for the effects of their sociodemographic variables. This work expands our knowledge about the role of teachers' positive emotions in the development of positive work attitudes, and also supports the inclusion of emotional skills in future teacher preparation programs as resources to facilitate work-related well-being.The feeling thinking talking (FTT) intervention was designed because early childhood seems to be a prime time for fostering young children's language skills. This intervention involved teaching teachers from N = 28 kindergarten groups in N = 13 German kindergartens language support strategies (LSS) to be used in everyday conversations with the children in their care. The FTT intervention was evaluated in a business-as-usual control group design with N = 281 children (mean age = 49.82 months, range = 33-66 months at T1, mixed SES) who were individually tested using objective tests on grammar, vocabulary and working memory before (T1) and after the FTT intervention (T2), and in a follow-up about one year after T1 (T3). After propensity matching was applied, multilevel models demonstrated that the children taught by the intervention group teachers made faster progress in their understanding of sentences, their application of morphological rules, and their memory for sentences when numerous covariates (child age, gender, behavioral self-regulation, multilingual upbringing, and family SES) were controlled. Results suggest that complex language processing abilities in young children can be promoted by a teacher-led intervention in early childhood education. Improved language skills will further all children's academic and social success in school.Our work aimed to study the relationships between different dimensions of school climate, moral disengagement, empathy, and bullying behaviors (perpetration and victimization). The study sample consisted of 629 students (304 boys and 325 girls) aged 12-14 years (M = 12.55, SD = 0.67). Results showed how different dimensions of school climate predicted moral disengagement, empathy, and victimization, and these, in turn, predicted bullying perpetration. The results show the need to generate favorable educational environments to reduce the levels of moral disengagement and victimization and to increase empathy in students as a strategy to prevent negative consequences related to bullying.Experiences of contact with nature in school education might be beneficial for promoting ecological lifestyles and the wellbeing of children, families, and teachers. Many theories and empirical evidence on restorative environments, as well as on the foundations of classical pedagogical approaches, recognize the value of the direct experience with natural elements, and the related psychological and educational outcomes (e.g., positive emotions, autonomy, self-efficacy, empathy). In this work we present two studies focusing on the contact with nature in outdoor education interventions with primary and secondary school students in Italy. A questionnaire measuring connectedness to nature, psycho-physical wellbeing, pro-environmental attitudes, students' life satisfaction, pro-social behavior, empathy and anxiety was completed before and after the education program by the participants to the intervention group and by students of a control group. The students in the intervention groups (154 in study 1 and 170 in study 2) participated in environmental education programs consisting in guided activities in contact with the nature during four visits in one of two natural protected areas. The students in the control groups (253 in study 1 and 168 in study 2) attended the same schools as the intervention group but they were not involved in the environmental education program. The students in both the groups completed the questionnaire in the same weeks of the year. Findings show that taking part to the outdoor education program has positive outcomes on psycho-physical wellbeing, on connectedness to nature and on pro-social behavior of students in the intervention group, compared to the control group. The implications related to the effectiveness of outdoor education interventions and future directions of research and practice in environmental psychology and education are discussed.The COVID-19 global health emergency has greatly impacted the educational field. Faced with unprecedented stress situations, professors, students, and families have employed various coping and resilience strategies throughout the confinement period. High and persistent stress levels are associated with other pathologies; hence, their detection and prevention are needed. Consequently, this study aimed to design a predictive model of stress in the educational field based on artificial intelligence that included certain sociodemographic variables, coping strategies, and resilience capacity, and to study the relationship between them. The non-probabilistic snowball sampling method was used, involving 337 people (73% women) from the university education community in south-eastern Spain. The Perceived Stress Scale, Stress Management Questionnaire, and Brief Resilience Scale were administered. The Statistical Package for the Social Sciences (version 24) was used to design the architecture of artificial neural networks.