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The present research paper aims to examine the inter-relationship between organizational justice (Henceforth termed as OJ), psychological well-being at work (henceforth termed as PWBW) and organizational citizenship behavior (henceforth termed as OCB). More specifically, this paper attempts to critically analyze the mediating role of PWBW in the relationship between OJ and OCB. The study solely focuses on nurses working at private hospitals in Kerala, who are the largest group of healthcare personnel.

Data collected from 308 nursing employees were analyzed by using statistical package for the social sciences (SPSS) software.

The outcomes of the analysis demonstrate that significant correlations exist between all the three key variables and their dimensions. Moreover, it has been found that the relationship between OJ and OCB is partially mediated by PWBW.

In the present healthcare scenario, just after the Covid-19 pandemic, there is a paramount need for the well-being of healthcare staff in order to improve the functioning of the healthcare system.

The study enabled us to develop and provide an explanation as to how social exchange relationship works between OJ and OCB.

Bullying negatively affects victims’ mental health and has been shown to be associated with anxiety and depression. Moreover, many studies have reported the prevalence of mistreatment among medical students (MS), interns and junior physicians. However, there are limited studies on bullying in the Middle East, and no studies on higher education in Bahrain. The authors’ aim was to investigate and compare the prevalence of bullying between MS at a major public university and non-medical students (NMS) at a private university in Bahrain. The authors also sought to explore the associations between bullying, depression and anxiety.

The authors conducted a survey-based cross-sectional study from October 1 to December 31, 2018, using convenient sampling method. A total of 300 students (150 MS and 150 NMS) participated in the study by answering a questionnaire that explored exposure to different types of bullying. In addition, standard anxiety and depression instruments were distributed to students.

The results showed that MS were more exposed to bullying than NMS, with a significant number (41%) reporting mistreatment from multiple sources, including teachers, consultants and peers. Furthermore, the authors found that bullying was significantly correlated with psychological health, anxiety and depression.

There are limited studies on bullying in the Middle East and no studies on the topic of higher education in Bahrain. Furthermore, the learning environment of tertiary education institutions can be improved by addressing the concerns associated with bullying identified in this study.

Although microfinancing is considered a key tool for fostering women's entrepreneurship development, there is growing concern regarding the impact of loan repayment strategies on the mental health of women entrepreneurs. This study seeks to unravel the implications of microfinance loans on the mental well-being of women entrepreneurs.

A carefully structured questionnaire was distributed to a purposive sample of one hundred women entrepreneurs in Lagos State using a mixed-method research approach. Also, interviews were conducted using an interview guide, which directly mirrored the questionnaire administered to five focus groups within Lagos State.

The study found that loan repayment and recovery strategies positively and significantly impact women entrepreneurs' mental well-being, with psychological distress serving as a measure for measuring mental well-being. Additionally, other factors such as the number of dependants and household headship trigger psychological distress, while age in business was associated with a reduction in psychological distress.

This study contributes to the existing literature by delving into the psychological implications of loan repayment strategies on the mental health of female entrepreneurs in Lagos State, Nigeria. Furthermore, it employs a triangulation research approach to validate questionnaire responses through focus group discussions.

This paper aims to explore how environmental employment can promote desistance among criminalised children. Research demonstrates that being immersed in and interacting with the natural environment has a positive impact upon well-being and behaviour, including reduced aggressive and violent behaviours. However, how exposure to the natural environment might promote desistance amongst children with persistent criminal involvement is unclear.

This paper examines, through semi-structured interviews and participant observations, the experiences of n = 23 criminalised children aged 16–18 employed in outdoor work at a UK social enterprise.

The findings demonstrate how working in the natural environment can provide a safe space for children, where they can build positive relationships, learn valuable skills and reconnect with the world outside of the high-pressure, conflict-driven spaces in which they typically occupy.

This research highlights the relevance of the setting in which child rehabilitation takes place and the potential role of natural environments in providing places and opportunities which support pro-social identity development and desistance for children.

Social networks (SNs) have recently evolved from a means of connecting people to becoming a tool for social engineering, radicalization, dissemination of propaganda and recruitment of terrorists. It is no secret that the majority of the Islamic State in Iraq and Syria (ISIS) members are Arabic speakers, and even the non-Arabs adopt Arabic nicknames. However, the majority of the literature researching the subject deals with non-Arabic languages. Moreover, the features involved in identifying radical Islamic content are shallow and the search or classification terms are common in daily chatter among people of the region. The authors aim at distinguishing normal conversation, influenced by the role religion plays in daily life, from terror-related content.

This article presents the authors' experience and the results of collecting, analyzing and classifying Twitter data from affiliated members of ISIS, as well as sympathizers. The authors used artificial intelligence (AI) and machine learning classification algorithms to categorize the tweets, as terror-related, generic religious, and unrelated.

The authors report the classification accuracy of the K-nearest neighbor (KNN), Bernoulli Naive Bayes (BNN) and support vector machine (SVM) [one-against-all (OAA) and all-against-all (AAA)] algorithms. The authors achieved a high classification F1 score of 83\%. The work in this paper will hopefully aid more accurate classification of radical content.

In this paper, the authors have collected and analyzed thousands of tweets advocating and promoting ISIS. The authors have identified many common markers and keywords characteristic of ISIS rhetoric. Moreover, the authors have applied text processing and AI machine learning techniques to classify the tweets into one of three categories: terror-related, non-terror political chatter and news and unrelated data-polluting tweets.