15Internet addiction has become an increasingly researched area in many Westernized countries. Results showed that Internet addiction is a predictor of stress, depression, anxiety, and Introduction 34Easy access to the Internet has led to an increase in the number of studies investigating the 35 incidence and prevalence of Internet addiction (IA) (Pontes, Kuss & Griffiths, 2015). Prevalence 36 of IA among adolescents and adults in Western and Eastern countries has gained the attention of 37 researchers from different disciplines such as communication, education and psychology (Caplan 38 & High, 2007; Greenfield, 2007; Li, O'Brien, Snyder, & Howard, 2015; Yen et al., 2008 (Christakis, 2010; Smahel, Brown, & Blinka, 2012). This is because adolescents spend a lot of 45Several psychological studies associated IA with personality traits of adolescents (i.e., 46aggression and lack of self-control) (Öztürk, Bektas, Ayar, Özgüven Öztornacı, & Yağcı, 2015) 47The social and emotional risks of IA and its treatments have also been studied extensively (Hahn 48 & Kim, 2014; Ko, Yen, Yen, Chen, & Chen, 2012 Internet use, and Internet use disorder among others (Huang, Chen, Wang, & Wang, 2014). IA 60 has often been referred to as the failure or lack of ability of a person to manage their use of the 61 Internet, and that consequently triggers emotional and social difficulties in a person's personal 62 and professional life (Pontes et al, 2015; Young & Rogers, 1998 Internet addict was operationally defined as anyone who scored more than 61 on the IA Test 126 whereas a non-addict was anyone who scored less than 60 (Young, 1998 Measures 131Three psychometric instruments were utilized to assess the variables in this study (i.e., 132Depression Anxiety and Stress Scale-21, the Internet Addiction Test, and the Loneliness Scale). Depression Anxiety and Stress Scale-21 (DASS-21) 134The DASS-21 (Lovibond & Lovibond, 1995), comprises 21 questions, and assesses three 135 separate dimensions of negative emotional states including anxiety, depression, and stress (see 136 Table 1). Each of the three emotional subscales has seven questions. Each item is rated on a five-137 point Likert scale ranging from always (0) to never (4). Questions 1 to 7 assess depression, Results 195Before employing MANOVA, bivariate Pearson's correlation coefficients were run to 196 determine the association between the variables (see Table 2). The results revealed that significant 197 correlations (p<0.01) exist among the variables. In Table 2 Table 4). SEM with maximum likelihood (ML) estimation was Table 5). 240As expected, the mean scores on stress, depression, anxiety, and loneliness among Internet 241 addicts were higher than those of non-addicts. These findings suggest that the more addicted a 242 person is to the Internet, the more stressed, depressed, anxious, and lonely the person is. The The association between IA and psychological symptoms appears to be reciprocal, indicating 256 that excessive Internet use might incr...

No abstract

No abstract

The current study examined the associations between critical thinking (CT) with emotional intelligence (EI) and also with self-efficacy at high schools. To this aim, 64 high school EFL teachers participated in the study. The participants were required to complete the "Teachers' Sense of Efficacy Scale", the "Emotional Intelligence Questionnaire" and the "Watson-Glaser Critical Thinking Appraisal". ِ Descriptive statistics, Pearson product-Moment correlations and regression analyses were employed to analyze the data. The findings of the study revealed that CT was related to EI, but not to self-efficacy. Furthermore, no moderating roles were found for age, gender or teaching experience in the relationship between CT and EI. Taken together, these findings advance the understanding of the interplay between CT and EI.

The study examined the realization of refusal of request speech act in Persian, English, and Balouchi languages. 219 individuals participated in the study. Discourse completion task was employed to elicit the participants’ refusals. Descriptive statistics and Chi-square were used to analyze the data. The findings revealed the existence of statistically significant differences among the three groups of speakers concerning both the total frequencies and the frequencies of direct, indirect, and adjuncts to refusals strategies. Furthermore, concerning social status, no statistically significant differences were detected either for total number of strategies or for the number of strategies in main categories in each language, except for the indirect strategies among Persian speakers. In Persian language, with the increase in the interlocutors’ social status level, the increase in the number of indirect strategies was discerned. Likewise, the frequency differences of some semantic formulas were statistically significant regarding the social status in each language.