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Background Past research has highlighted the role of trauma in social adjustment problems, but little is known about the underlying process. This is a barrier to developing effective interventions for social adjustment of traumatized individuals. The present study addressed this research gap through a cognitive model. Methods A total of 604 young adults (aged 18-24; living in Australia) from different backgrounds (refugee, non-refugee immigrant, and Australian) were assessed through self-report questionnaires. The data were analyzed through path analysis and multivariate analysis of variance. Two path analyses were conducted separately for migrant (including non-refugee and refugee immigrants) and Australian groups. Results Analyses indicated that cognitive avoidance and social problem solving can significantly mediate the relation between trauma and social adjustment (p 0.95). According to the model, reacting to trauma by cognitive avoidance (i.e., chronic thought suppression and over-general autobiographical memory) can disturb the cognitive capacities that are required for social problem solving. Consequently, a lack of effective social problem solving significantly hinders social adjustment. There were no significant differences among the Australian, non-refugee immigrant and refugee participants on the dependent variables. Moreover, the hypothesized links between the variables was confirmed similarly for both migrant (including refugee and non-refugee immigrants) and Australian groups. Conclusion The findings have important implications for interventions targeting the social adjustment of young individuals. We assert that overlooking the processes identified in this study, can hinder the improvement of social adjustment in young adults with a history of trauma. Recommendations for future research and practice are discussed.Generalized linear mixed models (GLMMs) estimate fixed and random effects and are especially useful when the dependent variable is binary, ordinal, count or quantitative but not normally distributed. They are also useful when the dependent variable involves repeated measures, since GLMMs can model autocorrelation. This study aimed to determine how and how often GLMMs are used in psychology and to summarize how the information about them is presented in published articles. Our focus in this respect was mainly on frequentist models. In order to review studies applying GLMMs in psychology we searched the Web of Science for articles published over the period 2014-2018. A total of 316 empirical articles were selected for trend study from 2014 to 2018. We then conducted a systematic review of 118 GLMM analyses from 80 empirical articles indexed in Journal Citation Reports during 2018 in order to evaluate report quality. Results showed that the use of GLMMs increased over time and that 86.4% of articles were published in first- or second-quartile journals. Although GLMMs have, in recent years, been increasingly used in psychology, most of the important information about them was not stated in the majority of articles. Report quality needs to be improved in line with current recommendations for the use of GLMMs.This study aims to examine key attributes affecting Airbnb users' satisfaction and dissatisfaction through the analysis of online reviews. A corpus that comprises 59,766 Airbnb reviews form 27,980 listings located in 12 different cities is analyzed by using both Latent Dirichlet Allocation (LDA) and supervised LDA (sLDA) approach. Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb accommodation. In particular, the emergence of the topic "guest conflicts" in this study leads to a new direction in future sharing economy accommodation research, which is to study the interactions of different guests in a highly shared environment. The results of topic distribution analysis show that in different types of Airbnb properties, Airbnb users attach different importance to the same service attributes. The topic correlation analysis reveals that home like experience and help from the host are associated with Airbnb users' revisit intention. We determine attributes that have the strongest predictive power to Airbnb users' satisfaction and dissatisfaction through the sLDA analysis, which provides valuable managerial insights into priority setting when developing strategies to increase Airbnb users' satisfaction. Methodologically, this study contributes by illustrating how to employ novel approaches to transform social media data into useful knowledge about customer satisfaction, and the findings can provide valuable managerial implications for Airbnb practitioners.Although narcissism is an important factor influencing entrepreneurial activity and outcomes, not much research has been conducted on the relationship between narcissism and entrepreneurship. To summarize the current literature on this relationship and provide an agenda for further in-depth research, a systematic review was conducted based on the PRISMA guidelines using Web of Science, Elsevier ScienceDirect, and EBSCO host databases. check details Accordingly, 33 articles have been identified as being eligible for the final synthesis. The findings of the present study showed, in general, that (1) life history theory, person-environment fit theory (P-E theory), and career choice theory were mostly used to explore the topic of narcissism and entrepreneurial intention, social exchange theory was used to analyze narcissistic entrepreneurs' entrepreneurial motives and attitudes, and upper echelons theory (UET) was applied to research on the relationship between narcissism and entrepreneurial outcomes, (2) Narcissistic Personalities.Forgiveness seeking after a relational transgression is an important aspect of relational repair from an interpersonal perspective, although it has received much less attention than the process of granting forgiveness. This research focuses on the victim's perspective of the transgressor's behaviors and how they are related to forgiveness and offense characteristics. This paper proposes a multidimensional concept of seeking forgiveness that includes four dimensions apologies, restorative action, relational caring behaviors, and diverting behaviors. A questionnaire for assessing these dimensions was developed and tested with a general population sample of 450 subjects. Participants recalled a specific offense and then answered a questionnaire about the perceived usefulness of different forgiveness-seeking behaviors, a forgiveness inventory, and several questions regarding the characteristics of the offense (severity, intentionality, and frequency). Our results support the four-factor structure of the questionnaire.
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