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The purpose of this paper is to explore what characterizes cyberbullying when it is performed in digital space and in an increasingly boundary blurred working life context.

Cyberbullying is explored through the lens of Erving Goffman’s theories on everyday life interaction and social media scholars understanding of social life on the internet today. The empirical material for the study is grounded in eight in-depth interviews with individuals who have been subjected to cyberbullying behavior in their professional life. The interview data were analyzed by means of thematic analysis.

Three key themes were identified: spatial interconnectedness, colliding identities and the role of the audience. The empirical data indicate that in order to understand cyberbullying in working life, it is necessary to consider the specific context that emerges with social network sites and blogs. Moreover, this study shows how social network sites tend to blur boundaries between the private and the professional for the targeted individual.

Cyberbullying in working life is a relatively under-researched area. Most existing research on cyberbullying follows the tradition of face-to-face bullying by addressing the phenomenon with quantitative methods. Given the limited potential of this approach to uncover new and unique features, this study makes an important contribution by exploring cyberbullying with a qualitative approach that provides in-depth understanding of the new situations that emerge when bullying is performed online.

The purpose of this paper is to examine the experiences of employees who are exposed to dysfunctional behaviors by their leaders in a healthcare organization.

This study employed a qualitative methodology drawing on 25 semi-structured interviews with administrative and clinical employees working in a healthcare setting operating in Riyadh, Saudi Arabia.

This study’s findings provide insights into dysfunctional leadership phenomena based on employees’ personal experiences with dysfunctional leaders. Dysfunctional leaders have several harmful behaviors, such as behaving in abusive ways, marginalizing others, engaging in favoritism, and degrading employees. This study also demonstrated that the leaders’ negative behavior directly influences employees to leave their jobs, contributes to feelings of alienation at work, reduces their commitment, and frequently creates serious psychological and physical problems. This study also discovered that over time the negative effects of a dysfunctional leader do not stop at employees; it also filters through to other areas such as the organizational environment and family life.

Dysfunctional leadership is under-studied within the context of the Middle Eastern region. Therefore, this study’s findings provide theoretical and practical implications. It provides information about employee experiences and how dysfunctional behavior influences individuals and, ultimately, organizational life. Furthermore, this study has value to practitioners by offering suggestions for organizational interventions for creating more effective policies and programs to support employees’ careers and well-being.

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.

This study aims to explore the viability of using C-17 reduced-engine taxi procedures from a cost savings and capability perspective.

This study model expected engine fuel flow based on the number of operational engines, aircraft gross weight (GW) and average aircraft groundspeed. Using this model, the research executes a cost savings simulation estimating the expected annual savings produced by the proposed taxi methodology. Operational and safety risks are also considered.

The results indicate that significant fuel and costs savings are available via the employment of reduced-engine taxi procedures. On an annual basis, the mobility air force has the capacity to save approximately 1.18 million gallons of jet fuel per year ($2.66m in annual fuel costs at current rates) without significant risk to operations. The two-engine taxi methodology has the ability to generate capable taxi thrust for a maximum GW C-17 with nearly zero risks.

This research was limited to C-17 procedures and efficiency improvements specifically, although it suggests that other military aircraft could benefit from these findings as is evident in the commercial airline industry.

This research recommends coordination with the original equipment manufacturer to rework checklists and flight manuals, development of a fleet-wide training program and evaluation of future aircraft recapitalization requirements intended to exploit and maximize aircraft surface operation savings.

If implemented, the proposed changes would benefit the society as government resources could be spent elsewhere and the impact on the environment would be reduced. This research conducted a rigorous analysis of the suitability of implementing a civilian airline’s best practice into US Air Force operations.

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

The purpose of this paper is to describe experiences of caregivers in managing psychotic symptoms of persons with schizophrenia in various circumstances.

The data were obtained via a focus group and in-depth interviews among caregivers who cared for relatives with schizophrenia for more than five years. Thematic analysis was used for data analysis.

“Making it better” emerged as the main theme describing caregivers’ experiences in trying to manage psychotic symptoms. It comprises four sub-themes including cutting off the wind, protecting from harm, preventing relapses and pulling back to normality. The caregivers gradually learned and adjusted their strategies through trial and error. They tried to stop aggressive and violent behaviors soon after they had begun by giving cool water to their relatives to drink or shower, while expressing their own affect with gently talking. They also dealt with a hardship in protecting the patients, other people, their properties and their own selves from harm resulting from violent behavior. When the psychotic symptoms improved, the caregivers tried to prevent relapses by using various strategies to maintain medication adherence and by soothing their relatives’ mental state. They also tried to pull their relatives back to normal as much as they could by promoting their relatives’ memories and abilities to perform daily functions.

The findings increase knowledge in nursing regarding psychotic symptoms management. The findings can be applied to the development of a program to help caregivers to manage psychotic symptoms effectively in order to promote good clinical outcomes of patients and alleviate the caregivers’ burden.