Northumbria Journals
Not a member yet
1008 research outputs found
Sort by
Gratitude writing for positive and negative affect: moderation by life satisfaction
Full text linkGratitude writing interventions have been found to enhance wellbeing; however, these effects may not be equally effective for everyone. A moderator of interest is life satisfaction. The aim of this study was to explore the effects of a gratitude writing intervention on positive affect (PA) and negative affect (NA). The other aim of the present study was to explore the moderating role of life satisfaction on the effect of a gratitude writing intervention on PA and NA. A cross-sectional, quantitative design was employed. A convenience sample of 90 participants, aged over 18 from the general population, were recruited. Participants completed two self-report questionnaires: the Satisfaction with Life Scale to measure life satisfaction and the Positive and Negative Affect Schedule (PANAS) to measure PA and NA. Participants were randomised to a gratitude writing condition (n = 44), where they expressed gratitude to a person that had changed their life and wrote how that made them feel, or a control writing condition (n = 46), before repeating the PANAS. There was no significant effect found for the gratitude writing intervention on PA and NA, relative to the control condition. There was no significant effect found for the moderator of life satisfaction, possibly due to the length of the gratitude writing. This study demonstrates that further research is required into how life satisfaction moderates gratitude writing, and to assess under what conditions gratitude interventions are most effective. Studies should use a larger sample and a larger dosage
Comparative Analysis of Traditional Machine Learning, Deep Learning, and Hybrid Ensemble Models for Anomaly Detection and Web Application Firewall Optimisation
No full textAnomaly detection is an important component of cybersecurity, particularly in safeguarding web application firewalls (WAFs) from malicious traffic. In this study, we perform a comparative analysis of three Machine Learning (ML) approaches: Random Forest (RF), Convolutional Neural Network (CNN), and a stacking ensemble combining RF and CNN with Logistic Regression (LR) as the meta-learner to explore the most effective approach for anomaly detection. To ensure a fair comparison, we trained all models under consistent preprocessing pipelines, including data class balancing using the SMOTE technique to address the common imbalance in attack data. The results of this study showed that the stacking ensemble outperformed the other models, achieving the highest accuracy (99.97%). The CNN model followed closely with comparable accuracy (99.94%), while also offering significant advantages in terms of computational efficiency and interpretability, particularly when supplemented with SHAP analysis. In contrast, the RF model achieved moderate accuracy (80.41%) but demonstrated strengths in interpretability and efficiency. These findings highlight that, with effective preprocessing, a standalone CNN can provide a practical and resource-efficient alternative to more complex ensemble models. The findings of this study highlight the importance of preprocessing in optimising model performance and propose CNN as a suitable solution for real-time cybersecurity applications. Future research should explore these models across diverse datasets, further investigate hybrid deep learning (DL) frameworks, and integrate advanced interpretability methods to enhance model transparency and trust in ML-based security systems
Risk in Outsourced IT Operations: A Systematic Literature Review of Technological Uncertainty, Knowledge Management and Opportunistic Behaviour
No full textTechnological adoption and digital transformation are increasingly enabling organisations to gain a competitive advantage, underpin business processes and create efficiencies. Utilisation of technologies brings several risks such as the risk of cyber-attacks and infrastructure dependency. To mitigate these, and to reap other benefits, organisations are increasingly turning to third-party IT suppliers to innovate and manage their IT estates. The field of IT operations and supply chain management has gained extensive research over the decades; however, none seem to bring these aspects together with technology risk mitigation in a systematic way. This paper systematically reviews 63 articles to ascertain historical research trends to indicate future research interest and consolidate research themes to discuss the gaps in the extant research. Alongside the fact that academic interest is projected to continue, closely coupled with world events, important findings show that technological uncertainty, information asymmetry and opportunistic behaviour are closely coupled in outsourced IT operations, and that knowledge management acts as a key mitigation mechanism which is illustrated by a new conceptual model. The review also reveals that existing research focuses heavily on ex-ante IT operations outsourcing decisions, with limited attention given to the ex-post operational phase, where most risks in IT operations materialise. Several gaps are identified for the field including how knowledge management can be utilised to mitigate technology risk within the IT operations function linking out to technology adoption. More generally, research into the public sector is found to be underreported giving researchers another lens to investigate current research themes with or adopt those previously listed. Overall, the review provides an integrated understanding of technological uncertainty in outsourced IT operations and highlights key opportunities for further research into ex-post phase, specifically long-term knowledge management in sector-specific outsourcing
Influence Of Personal Branding on Entrepreneurial Success of Fitness Coaches in the UK
No full textPersonal branding allows entrepreneurs to develop strong relationships with their customers and drive emotional affinity, trust, and loyalty. Nonetheless, the specific strategies that lead to entrepreneurial success in the fitness industry remain less clear. The present study evaluates the influence of three personal branding strategies (authenticity, attractiveness, and credibility) on the tribalist entrepreneurial success of fitness coaches in the UK. Drawing on data from 169 surveys, the study reveals that when examining each dimension separately, authenticity has a significant influence (β = 0.612, p < .001) on entrepreneurial success, while credibility has a suggestive influence although below the significance threshold (β = 0.186, p = .068), and attractiveness has no significant influence on entrepreneurial success (β = 0.006, p = .944). Moreover, the composite variable of personal branding strategies indicated a significant influence on entrepreneurial success (β = 0.796, p < .001). These findings allow practical recommendations to be provided to fitness coaches to develop an integrated personal branding strategy that encompasses the three dimensions evaluated in this research to maximise their entrepreneurial outcomes. Additional research utilising qualitative or mixed methodology and focusing on both customers' and fitness coaches' perspectives would be valuable to obtain a comprehensive understanding of the influence of personal branding strategies on the tribalist entrepreneurial success of fitness coaches in the UK
From Maverick to Mainstream: Autoethnography’s Place in Legal Research
No full textAutoethnography, a research method that uses lived experience as data, has grown steadily in prominence over the past two decades. Once a marginal approach, autoethnographic research is now recognised across disciplines, with dedicated conferences, textbooks and journals. Legal scholarship has begun to engage with autoethnography more recently, with applications emerging across legal education, legal practice, and doctoral research.
This growing body of work represents a welcome methodological expansion within the legal academy. At the same time, it marks a critical moment for autoethnography’s development in law. As interest in the approach increases, three interrelated challenges have become apparent. First, autoethnography is sometimes conflated with reflective or autobiographical writing, overlooking the thick description and analytical rigour the method demands. Second, to date, the breadth of autoethnographic practice remains underutilised within law; the field has yet to engage fully with the diversity of forms and frameworks available. The third and most complex challenge relates to ethical risk. Questions of researcher vulnerability and self-care remain insufficiently addressed within legal autoethnography.
This paper traces the emergence of autoethnography in legal research and offers a critical examination of its possibilities, its perils, and the ethical complexities that accompany its practice. In doing so, it argues for a more methodologically informed and ethically attentive engagement with autoethnography in law
Relationships between Airline Sustainability and Consumer Behaviour: An assessment of the influence of environmental awareness on the decision-making process of European airline customers
No full textThe aviation industry increasingly contributes to the global share of carbon emissions and therefore also to increasing global average temperatures. Although forecasts for growing emissions and solutions to decrease CO2 by aircraft usage are well described in the extant literature, the debate has failed to address how aviation passengers feel influenced in their choice as consumers. The study investigates possible relationships between civil aviation environmental sustainability, passenger environmental awareness and consumer behaviour. We use the European airline industry as a geographical focus of the study. Five hypotheses are developed related to (i) environmental awareness by airline passengers, (ii) the influence of sustainability on ticket booking behaviour, (iii) the influence of Sustainable Aviation Fuel and carbon offsetting on consumer behaviour and (iv) the influence of environmental awareness on airline image and customer satisfaction. To test the hypotheses, a survey method is used to gather data from airline passengers. The results show that environmental awareness is indeed increasing among airline passengers and as such has an influence on consumer behaviour. Our data indicates that the image of the sector is declining due to a perceived lack of urgency by the airlines. At the same time consumers are willing to pay higher ticket prices is airlines invest into sustainability. However, it is found that, although environmental awareness and concern are growing amongst aviation consumers, price is yet the most important factor that influences ticket booking behaviour and passenger satisfaction
AI-Driven Personalized Learning: Predicting Academic Performance Through Leadership Personality Traits
No full textThe study explores the potential of AI technologies in personalized learning, suggesting the prediction of academic success through leadership personality traits and machine learning modelling. The primary data were obtained from 129 master's students in the Environmental Engineering Department, who underwent five leadership personality tests with 23 characteristics. Students used self-assessment tools that included Personality Insight, Workplace Culture, Motivation at Work, Management Skills, and Emotion Control tests. The test results were combined with the average grade obtained from academic reports. The study employed exploratory data analysis and correlation analysis. Feature selection utilized Pearson correlation coefficients of personality traits. The average grades were separated into three categories: “Fail”, “Pass”, and “Excellent”. The modelling process was performed by tuning seven ML algorithms, such as Support Vector Machine, Logistic Regression, K-Nearest Neighbors, Decision Tree, Gradient Boosting, Random Forest, XGBoost and LightGBM. The highest predictive performance was achieved with the Random Forest classifier, which yielded an accuracy of 87.50% for the model incorporating 17 personality trait features and the leadership mark feature, and an accuracy of 85.71% for the model excluding this feature. In this way, the study offers an additional opportunity to identify students' strengths and weaknesses at an early stage of their education process and select the most suitable strategies for personalized learning
Exploring the Experience and Efficacy of Online Interventions for Mental Health: A Qualitative Study
Full text linkRemote care for a range of mental health needs is now increasingly offered using online support. Understanding the benefits and challenges of receiving remote mental healthcare, from the perspectives of individuals accessing support, is important for considering the development of future interventions. In this study, semi-structured interviews were conducted with 10 participants who were receiving two or more online mental health support interventions. Thematic analysis was used to identify patterns and gain meaningful interpretations of these experiences. These data revealed advantages and challenges regarding receiving online support for disorders such as anxiety and depression. Three key themes (‘accessibility of treatment’; ‘therapeutic process’; ‘options and choices’) were identified, which related to the accessibility of online support, the therapeutic process with regards to the role of the therapist and expectations of the intervention recipient, and the individual options and choices. These results suggest that the increased availability of psychological interventions (through telephone and videoconferencing platforms), and establishing remote therapeutic relationships, contributes to the effective delivery of these services. In this study, participants considered online support to be largely advantageous, however, many participants had the view that online support should remain supplementary or act as a gateway to face-to-face support. Future mental health services could be improved by increasing options and the length of support where possible, as a ‘hybrid’ approach might allow for more flexibility and better meet individual needs
Vol 2 Issue 1 - Welcome to the Issue (Guest Editorial): Guest Editorial by Professor Andrew Scholey (School of Psychology)
No full textWelcome to this second edition of Northumbria Psychology Bulletin which showcases the outstanding research conducted by our Psychology students at all levels, both on campus and remote. Having returned to Northumbria following a seventeen year absence, I am struck by the transformation of the research infrastructure and culture during the intervening period. This bulletin is a perfect example of that upward trajectory in Psychology research excellence. The quality of papers in this volume is a testament to the staff and students in the School of Psychology, as is the range of subject matter and methodologies. The papers in this issue include: a cross-sectional, quantitative investigation into the impact of gratitude writing; an examination of the influence of atypical sensory processing on autistic and ADHD traits; a qualitative exploration of the efficacy of online mental health interventions; and assessment of the effectiveness of a brief checklist for mitigating attentional blindness in radiology. Taken together, these papers reflect both the methodological breadth and the applied aspects of our Psychology degrees. Each study also has clear benefits with respect to impact on, and engagement with, relevant communities. To echo the editorial from Volume 1 of this series, it is particularly impressive that this bulletin exists because of continued student engagement beyond the degree. While there are institutional benefits from distinguishing our students with respect to research track record, clearly this bulletin stems from the intrinsic personal motivation to take self-initiated research ideas through to publication. I am sure that this volume will stimulate and engage readers and form part of a highly successful series
Preserving Cognitive Ownership in Higher Education: A Sustainable Hybrid Pedagogical Framework for Reasoning-Centred AI Integration
No full textThis study explores how distinctive types of generative artificial intelligence (AI) practice, augmentation, co-construction, and replacement shape students’ reasoning skills and sense of cognitive ownership in higher education (HE) academic writing. This research also responds to growing humanitarian concerns about the erosion of student commitment, the undermining of autonomy, and ethical learning in HE. To address this core gap, an explanatory sequential mixed-methods design was employed. Data were collected from 412 UK HE students, complemented with in-depth interviews from 24 participants. Quantitative modelling showed that augmentation strengthens reasoning through reflective engagement, co-construction yields mixed cognitive outcomes, and replacement significantly weakens ownership and efficacy. Qualitative findings revealed subsistent experiences behind these practices: some students articulated no ethical harm by AI-supported reflection, while others exhibited a quiet disarticulation of their self-learning skills. Incorporating these insights, this study proposed the Hybrid Human–AI Reasoning Integrity Model (HHARIM), a sustainable pedagogical framework in HE that centres human reasoning in ethical AI use. The recommended model also highlights cognitive ownership as an essential element and outlines a robust framework for responsible AI use to safeguard learning, ethics, and autonomy in HE. This study contributes theoretically by offering HHARIM as a framework for effectively embedding AI, thereby upholding ethical, sustainable, and human-centred learning. Ultimately, the implications of this proposed model will influence HE systems to encourage sustainable AI pedagogical practices that reinforce academic writing rather than compromise students’ learning efficacy