مطالب

The digital era has introduced mental health challenges, especially for youth. Despite increasing awareness, comprehensive analyses of these challenges remain limited. This study collects and examines the prevalence of 15 key mental health challenges related to digital engagement, based on a sample of 555 participants. The prevalence of these challenges varied, with pressures related to parenting, hoarding, and inappropriate content being the most common, affecting 60.13%, 52.76%, and 45.39% of the participants, respectively. The research also highlights gender and age differences, noting that males report higher levels of issues like FOMO and Nomophobia compared to females. Adults (18+) face more severe challenges, such as memory decline, while younger individuals report fewer problems. Correlation analysis revealed significant relationships between several mental health challenges, such as Nomophobia and TAD (r = 0.68) and FOMO and TAD (r = 0.50), indicating that individuals experiencing one challenge are likely to face others. A decision tree analysis was used to predict mental health challenges by examining the relationships between different mental health conditions, uncovering specific patterns and rules associated with the occurrence of these challenges. Additionally, cluster analysis in this study identified distinct population segments, with 21% of individuals falling into a cluster that experiences severe mental health challenges. The findings suggest that a significant portion of the population is at risk for severe mental health issues, highlighting the need for targeted interventions.

IoT is a dynamic network of interconnected things that communicate and exchange data, where security is a significant issue. Previous studies have mainly focused on attack classifications and open issues rather than presenting a comprehensive overview on the existing threats and vulnerabilities. This knowledge helps analyzing the network in the early stages even before any attack takes place. In this paper, the researchers have proposed different security aspects and a novel Bayesian Security Aspects Dependency Graph for IoT (BSAGIoT) to illustrate their relations. The proposed BSAGIoT is a generic model applicable to any IoT network and contains aspects from five categories named data, access control, standard, network, and loss. This proposed Bayesian Security Aspect Graph (BSAG) presents an overview of the security aspects in any given IoT network. The purpose of BSAGIoT is to assist security experts in analyzing how a successful compromise and/or a failed breach could impact the overall security and privacy of the respective IoT network. In addition, root cause identification of security challenges, how they affect one another, their impact on IoT networks via topological sorting, and risk assessment could be achieved. Hence, to demonstrate the feasibility of the proposed method, experimental results with various scenarios has been presented, in which the security aspects have been quantified based on the network configurations. The results indicate the impact of the aspects on each other and how they could be utilized to mitigate and/or eliminate the security and privacy deficiencies in IoT networks.

Philologie in German (English philoloy; French philologie; Latin philologia ‘love of word’) is defined as the study of language in its historical context. It is considered a part of historical linguistics which traces the development and etymology of words in a language and across languages. John Peile defines philology as follows: It is the science which teaches us what language is. The philologist deals with the words which make up a language, not merely to learn their meaning, but to find out their history. He pulls them to pieces, just as a botanist dissects flowers, in order that he may discover the parts of which each word is composed and the relation of those parts to each other: then he takes another and yet another language and deals with each in the same way: then by comparing the results he ascertains what is common to these different languages and what is peculiar to one or more: lastly, he tries to find out what the causes are which operate on all these languages, in order that he may understand that unceasing change and development which we may call, figuratively, the life of language. (Peile1988, 5) In his book, Cours de linguistique générale, Ferdinand de Saussure offers a comprehensive definition of philology. Language is not the unique object of philology. The task of philology is above all to establish, interpret, and comment upon texts. This just concern leads philology to concern itself with literary history, customs, institutions, etc. . . . Everywhere it makes use of its own method, which is textual criticism. (qut. in Watkins 1990, 21)

Background: The emergence of amateur critics and vernacular reviewers as non-institutional cultural voices is one of the consequences of social media's development and widespread use.Aims: This study aims to better understand reviewers and their types by examining how they establish critical authority in comparison to institutional critics and their potential influence on cultural valuation.Methodology: This subject is explored through the rhetorical analysis of their linguistic strategies. The research draws theoretically on existing literature regarding cultural criticism and review in social media. Methodologically, it combines qualitative content analysis and rhetorical analysis, emphasizing identifying Aristotelian persuasive elements within the data, including ethos, pathos, and logos. The study sample consists of 350 Instagram posts gathered from 30 film review pages.Findings: The findings indicate that most reviewers adopt a consumer-oriented perspective, distancing themselves from institutional critics. They have also emphasized using Instagram's affordances, particularly its interactive and participatory features, to construct their cultural authority. Furthermore, they have employed rational and emotional appeals in alignment with presenting "summaries and supplementary movie information" and expressing "emotional appeal and affective experience of consumption". These strategies, along with the reviewers' focus on "addressing the audience's emotional needs", "personal growth and self-improvement", and "less dependence on institutional critics", reflect their disinterest in delving into deeper levels of critical evaluation and rhetorical directness in constructing their authority. In the final section of the article, the impact of reviewers on cultural valuation is further discussed, distinguishing three types: "film-style bloggers", "cinema influencers", and "critical reviewers".Conclusions: Based on the results, the first two types of reviewers demonstrate how Instagram’s platform-specific features primarily shape critical authority. While diverse reviewers enhance access to information, they often marginalize critical evaluation and cultural value in favor of consumerism and commercial competition. Only "Critical Reviewers" have successfully integrated critical evaluation with Instagram’s affordances through distinct rhetorical strategies, emphasizing the need to increase their numbers in the era of digital media.

Background: The 2024 Iranian presidential election intensified political polarization on Persian Twitter (X), where ideological factions engaged in networked contestation. This study employs social network analysis to examine polarization mechanics, mapping key actors, echo chambers, and discursive strategies. Findings illuminate digital factionalism, algorithmic amplification, and the role of influencers in political mobilization.Aims: This study explores the mechanisms driving political polarization on Persian Twitter (X) during the 2024 Iranian presidential election.Methodology: Utilizing computational social science methodologies, the research combines social network analysis (SNA) and thematic analysis to examine over 133,000 active users and numerous election-related hashtags. Data collection spanned June 1–16, 2024, leveraging Twitter's API to identify clusters, user interactions, and thematic trends. Key tools included the Louvain algorithm for community detection and centrality measures for network analysis, visualized through Gephi software.Findings: Findings reveal a fragmented political landscape characterized by ideological divides, echo chambers, and limited interaction between opposing factions. Analysis identified six major clusters, each aligned with distinct political affiliations, including reformists, conservatives, and opposition groups. Thematic analysis further highlighted the rhetoric surrounding leading candidates Masoud Pezeshkian and Saeed Jalili, revealing polarized sentiments and distinct narratives among their supporters and detractors. The study also underscores the role of platform algorithms, influencer strategies, and group identities in deepening polarization.Conclusions: This research contributes to the understanding of digital polarization within Iran's socio-political context. It emphasizes the dual role of social media as both a space for public discourse and a driver of ideological segregation. Recommendations include strategies for promoting digital literacy, fostering inclusive discussions, and enhancing algorithmic transparency to mitigate polarization in Iran.

Objective: This study aimed to evaluate the effectiveness of a forgiveness-based intervention in enhancing marital commitment and restoring trust among married individuals experiencing relational distress. Methods: A randomized controlled trial was conducted with 30 married participants from Indonesia, randomly assigned to either an intervention group (n = 15) or a control group (n = 15). The intervention group received six structured forgiveness-based therapy sessions over six weeks, while the control group received no intervention. Standardized measures of marital commitment and trust were administered at three time points: pre-test, post-test, and five-month follow-up. Data were analyzed using repeated measures analysis of variance (ANOVA) and Bonferroni post-hoc tests, with SPSS version 27. Findings: Results from repeated measures ANOVA revealed significant time × group interaction effects for marital commitment (F(2, 54) = 17.12, p < .001, η² = .39) and trust (F(2, 54) = 19.68, p < .001, η² = .42). Bonferroni post-hoc analyses indicated that both marital commitment and trust significantly increased from pre-test to post-test (p < .001) and were maintained at the five-month follow-up (p < .001), with no significant decline between post-test and follow-up (p > .05). Conclusion: The therapeutic gains were not only immediate but also sustained over time, supporting the use of structured forgiveness interventions in marital counseling settings. These findings highlight the potential of forgiveness as a valuable tool in relationship repair and emotional healing.

Objective: This study aimed to evaluate the effectiveness of Acceptance and Commitment Therapy (ACT) in reducing negative affect, improving emotional processing, and enhancing psychological hardiness in women experiencing domestic violence. Methods and Materials: A randomized controlled trial was conducted with 30 participants, divided equally into intervention and control groups. The intervention group underwent eight 90-minute ACT sessions over eight weeks, while the control group received no treatment. Outcomes were assessed at pre-intervention, post-intervention, and five-month follow-up stages using validated tools for Negative Affect, Emotional Processing, and Psychological Hardiness. Data were analyzed using repeated-measures ANOVA and Bonferroni post-hoc tests, with SPSS-27. Findings: Significant improvements were observed in the intervention group across all variables. For Negative Affect, mean scores decreased from 3.52 (SD = 0.45) at pre-intervention to 2.89 (SD = 0.39) post-intervention and 2.45 (SD = 0.33) at follow-up (F(1,28) = 30.19, p = 0.001, η² = 0.52). Emotional Processing scores increased from 3.20 (SD = 0.40) to 3.80 (SD = 0.37) post-intervention and 4.25 (SD = 0.31) at follow-up (F(1,28) = 34.38, p = 0.001, η² = 0.55). Psychological Hardiness improved from 3.15 (SD = 0.38) to 3.95 (SD = 0.35) post-intervention and 4.10 (SD = 0.32) at follow-up (F(1,28) = 36.57, p = 0.001, η² = 0.58). The control group showed minimal changes across all measures. Conclusion: ACT was highly effective in reducing negative affect, improving emotional processing, and enhancing psychological hardiness in women experiencing domestic violence. The results suggest that ACT is a valuable therapeutic approach for this population, with sustained benefits over time.