3830 research outputs found
Sort by
Psychotherapy with eco-anxiety: Implications from a study of the climate emergency in Ireland using discourse analysis
No full textEco-anxiety is an increasingly common presentation for psychotherapists. This paper aimed to explore the discursive construction of the climate emergency in Ireland in 2024 and its implications for psychotherapy with eco-anxiety. The starting premise was that eco-anxiety emerges from a rupture in Western Modernity’s order of discourse; in particular, a rupture in the alliance between science and capitalism. Critical Discourse Analysis (Fairclough, 2013) was employed to examine representations of the climate emergency produced during the Irish general election of 2024. The analysis suggests broad acceptance of the reality of climate breakdown in Irish discourse; and competing views on whether this is manageable or catastrophic. The research explores how power is employed, subjectivities are created and cultural complexes are activated in discourse about the climate emergency; and how and why this is relevant for psychotherapists working with eco-anxiety
The role of coping self-efficacy, social support, and loneliness on acculturative stress and life Satisfaction among Brazilians in Ireland
No full textThe mental health of migrants is a complex issue influenced by various factors, including acculturative stress, social support systems, coping mechanisms, and individual resilience. This study investigated the mental health experiences of Brazilian migrants in Ireland (N = 96; 75% female), focusing on the interplay of acculturative stress, social support, coping mechanisms, loneliness, and life satisfaction. This is a quantitative study with correlational design employed, with data collected through an online questionnaire comprising demographic questions and five psychometric scales: Satisfaction with Life Scale (SWLS), Acculturative Stress Scale for International Students (ASSIS), Coping Self-Efficacy Scale (CSES), UCLA Loneliness Scale (ULS-10), and Multidimensional Scale of Perceived Social Support (MSPSS). The results revealed that longer time spent in Ireland was associated with decreased acculturative stress and increased life satisfaction. Additionally, coping self-efficacy, perceived social support, and time spent in Ireland positively correlated with life satisfaction, while loneliness negatively correlated with coping self-efficacy. The study also found that social support, coping self-efficacy, and time in Ireland were positive predictors of life satisfaction, whereas acculturative stress and loneliness were negative predictors. These findings underscore the crucial role of social support, coping skills, and addressing loneliness and acculturative stress in promoting the well-being of Brazilian migrants in Ireland. Future research could delve into the specific coping strategies employed by this population and the influence of cultural factors on their acculturation process
From Theory to Practice: Irish Psychotherapists’ Perspectives on Delivering Psychedelic-Assisted Therapy
No full textIn light of growing international interest in psychedelic-assisted therapy (PAT), this study explored what prepares Irish psychotherapists to engage with this emerging therapeutic modality. Five accredited psychotherapists working in diverse modalities were recruited to participate in semi-structured interviews. Transcripts were analysed using reflexive thematic analysis to explore their views on readiness, training, ethics, and future models of delivery. Five themes were identified: embodied readiness and the ethical necessity of lived experience; the need for specialised, experiential training and supervision; ethical complexities in client vulnerability and practitioner responsibility; structural gaps in regulation and professional governance; and a strong preference for community-based, nature-connected models of care. Overall, the study found that while participants were open to the potential of PAT, their readiness was shaped by both internal and external factors including ethical concerns, legal ambiguity, and the absence of formal training pathways. Participants emphasised the need for culturally responsive, relationally grounded frameworks that move beyond clinical models. It is hoped that these findings contribute to an evolving conversation around safe, ethical, and inclusive psychedelic practice in Ireland, and help inform the development of future guidelines, training, and policy
Addiction as a Response to Complex Trauma: The Role of Psychotherapy in Long-Term Recovery
No full textThis thesis explores addiction in individuals with co-occurring complex trauma, framing it as a complex, relational, and developmentally rooted response to psychological distress. Moving beyond dominant biomedical and behaviourist models, it argues for an integrative biopsychosocial perspective in which addiction is understood not merely as compulsive behaviour, but as a survival strategy shaped by early adversity, disrupted attachment, and impaired emotional regulation. Drawing on developmental psychology, attachment theory, and neurobiology, the work highlights how Adverse Childhood Experiences (ACEs), Complex PTSD (CPTSD), and Disturbances in Self-Organisation (DSOs) often underpin addictive patterns in this population. These insights suggest that, for individuals with significant trauma histories, addiction is deeply embedded in disrupted relational contexts and cannot be fully addressed without attending to the underlying psychological and interpersonal wounds. The thesis makes the case for long-term, trauma-informed psychotherapy as central, rather than supplementary, to recovery. It critiques short-term, acute care responses that dominate many addiction treatment systems and advocates for recovery models that prioritise consistency, relational safety, and developmental repair. The evolving framework of Recovery-Oriented Systems of Care (ROSCs) is examined as a promising foundation for integrating psychotherapy into long-term addiction support. Across three chapters, the thesis explores: (1) the developmental and relational links between trauma and addiction; (2) the role of psychotherapy within contemporary treatment systems; and (3) how diverse therapeutic modalities, such as psychodynamic, humanistic, somatic, and mentalisation-based approaches, can be integrated across the stages of recovery. 3 This thesis argues that sustained psychotherapeutic engagement offers the best opportunity to rebuild emotional and psychological resilience and personal agency in individuals affected by complex trauma and addiction. Addiction is not solely a clinical or public health issue; it is a profoundly human struggle rooted in the need for connection and meaning. Effective treatment must honour the relational nature and duration of recovery
The Influence of Artificial Intelligence in Risk Management Practices Among Irish Construction Industry
No full textThis dissertation investigates the adoption of Artificial Intelligence (AI) in risk management within the Irish construction industry. Grounded in the Theory of Planned Behaviour (TPB), the study examines professionals’ perceptions of AI’s usefulness, identifies barriers to adoption, and evaluates the role of organisational support. A quantitative survey of 108 industry participants was conducted, with data analysed using descriptive statistics, cross-tabulations, ANOVA, correlation, and regression. Findings reveal positive perceptions of AI’s potential to improve accuracy, efficiency, and decision-making, yet adoption is constrained by high costs, limited training, and cultural resistance. Regression results indicate that attitudes and perceived behavioural control are significant predictors of adoption intentions, while subjective norms are less influential. The study contributes to theory by validating TPB in the Irish construction context and offers practical recommendations for industry, policymakers, and technology providers to enhance AI adoption in risk management
AI-Based Animal Detection System for Road Safety
No full textAnimal-related road accidents are still a big issue, especially on highways and backroads where animals often show up without much warning. Solutions like thermal cameras, wildlife crossings, and sensor-triggered signs do help—but they’re usually expensive, tied to a specific spot, and not easy to roll out across large areas.This project takes a different route—using computer vision and deep learning to detect animals in real-time, with the long-term goal of integrating these detections into GPS systems like Google Maps or Apple Maps to alert drivers on the move. To explore this, I trained two powerful object detection models—YOLOv8m and Faster R-CNN—on a carefully selected 30,000-image subset from the Open Images dataset. The process involved weeks of preprocessing, cleaning, model tuning, and testing. YOLOv8m was optimized for real-time use: lightweight, fast, and surprisingly accurate, Faster R-CNN leaned more toward precision. It took its time, but often gave sharper, more accurate detections—especially when it came to identifying specific animal classes. In terms of performance, YOLOv8m delivered a mAP@50 of 75.3% and held a solid F1 score. Meanwhile, Faster R-CNN performed better on class-level accuracy and produced tighter bounding boxes overall. I ran side-by-side visual comparisons, created heatmaps, analyzed confidence levels, and documented failure cases. The result? Each model brought something unique to the table, and combining their strengths could lead to even better performance in future versions. More than just a technical study, this work shows how AI can actually serve people and wildlife at the same time. It opens the door for smarter, more proactive safety tools on the road—where detecting a deer before it crosses could save a life
When Consent Is Unclear: The Presentation of Unacknowledged Sexual Trauma in Psychotherapy and Its Impact on Clients’ Lives
No full textThis thesis explores the phenomenon of unacknowledged sexual trauma in psychotherapy, particularly in cases involving ambiguous consent. Many survivors enter therapy without recognising their experiences as sexual abuse, particularly when confusion around consent, nonverbal freeze responses, or the absence of overt resistance are involved. Drawing on theoretical understandings of trauma, feminist critique, neuroscience, and legal analysis, the research considers how trauma is often expressed through physiological and emotional symptoms rather than explicit memory. This research evaluates the sociocultural and legal discourses that obscure recognition, including rape myths, epistemic injustice, and restrictive consent frameworks in Irish law. Highlighting how neurobiological responses, such as dissociation, autonomic dysregulation, and implicit memory, manifest in symptoms. Therapists are encouraged to interpret these cues as meaningful expressions of trauma, rather than signs of pathology. Using an interdisciplinary methodology the thesis proposes a model of attuned, trauma-informed care that validates non-verbal and non-linear presentations. It argues that healing requires not just individual insight but cultural shifts in how we understand consent, violation, and credibility. Ultimately, the work advocates for a therapeutic approach that honours the complexity of unspoken trauma and facilitates integration through relational and embodied attunement
A literature review: Exploring the influence of trust on knowledge sharing in project teams within project-based organisation
No full textThe characterisation of knowledge as the primary productive resource of organisations rather than capital, natural resources, or labour, has prompted an increase in the interest of knowledge, however, it is acknowledged that it is in the sharing of knowledge where the value is held. From this perspective it is conceded that knowledge sharing amongst team members as an intangible asset, has the power to maintain and sustain organisational growth, and survival. Therefore, the factors which enable or inhibit knowledge sharing among team members needs to be identified. Trust has been recognised as a prominent influencing factor on knowledge sharing and it is here where the focus of this literature review lies. This paper offers a review of the literature on knowledge sharing in teams, presenting enabling and inhibiting factors, giving prominence to trust. Trust is investigated to include the role of trust in teams and in knowledge sharing and factors which enables and inhibits the development of trust
'Desafío Playablanca’: An innovative educational experience in the training Of secondary education teachers
No full textThis study, part of the 'Desafío Playablanca' initiative, explores methodological innovation in secondary education teacher training, focusing on gamification and active learning strategies. It addresses the impact of these methodologies on student motivation and academic performance in e-learning environments, a relatively underexplored area. Using a quantitative research design, participants were divided into four groups based on motivation levels—two control and two experimental—to assess the innovative strategies' effects. The study analysed academic performance in oral expression, written expression, visual-spatial, and logical-mathematical skills, using grades collected at the beginning and end of the study and statistical tools such as the Shapiro-Wilk test, Student's T-test, and Wilcoxon test. Findings revealed that the motivated experimental group (Group B) showed significant improvements in all skills, validating the effectiveness of gamified learning. The unmotivated experimental group (Group D) also improved, indicating benefits irrespective of initial motivation levels. Control groups showed no significant changes, underscoring the intervention's positive impact. The 'Desafío Playablanca' project enhances e-learning knowledge by demonstrating that active learning methodologies, like gamification and flipped classrooms, significantly enrich educational experiences, increase engagement and motivation, and improve knowledge assimilation and application. This research offers a scalable, replicable model adaptable across disciplines, promoting dynamic, interactive, and student-centred learning environments, and supports a shift towards more engaging, participatory, and technologically integrated educational practices
Deep Learning Study for Image Classification of Alzheimer's MRI
No full textAlzheimer's disease is a leading cause of dementia, impacting millions worldwide. Early diagnosis is crucial for improving patient outcomes, yet traditional methods often lack the sensitivity to detect early-stage neurodegeneration. This study investigates the application of deep learning models for the classification of Alzheimer’s disease using MRI scans. The research follows the CRISP-DM framework and utilises the "Alzheimer MRI Disease Classification Dataset" from Kaggle, comprising 5,120 MRI images categorised into four classes. To enhance classification performance, the dataset was transformed into a binary classification problem—distinguishing between "No Alzheimer" and "Early Alzheimer" cases—while addressing class imbalance through oversampling techniques. Five deep learning architectures were implemented and compared: Convolutional Neural Networks (CNN), Artificial Neural Networks (ANN), Residual Networks (ResNet50), Visual Geometry Group Network (VGGNet16), and Vision Transformers (ViT). The models were trained and evaluated based on accuracy, precision, recall, and F1-score. Results indicate that CNN achieved the highest accuracy (93.46%), followed by ANN (90.10%) and ViT (86.23%), demonstrating their effectiveness in automated MRI-based Alzheimer’s detection. Future work includes refining model interpretability through explainable AI techniques and integrating larger datasets for improved generalisation. This research highlights the potential of deep learning in advancing early Alzheimer’s diagnosis and supporting clinical decision- making