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Research citations building trust in Wikipedia: Results from a survey of published authors
No full text© 2025 The Authors. Published by Public Library of Science. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0320334
The data underlying the results presented in the study are available from Figshare, https://doi.org/10.6084/m9.figshare.26037646.v2The use of Wikipedia citations in scholarly research has been the topic of much inquiry over the past decade, however little is known regarding perceived Researchers trustworthiness of Wikipedia citations and representation of their work. This cross-publisher study (Taylor & Francis and University of Michigan Press) aimed to investigate author sentiment towards Wikipedia as a source of trusted information.
Methods
A short survey was distributed to 40,402 authors of papers cited in Wikipedia (n=21,854 surveys sent, n=750 complete responses received). The survey gathered responses from published authors in relation to their views on Wikipedia’s trustworthiness in relation to the citations to their published works. The unique findings of the survey were analysed using a mix of quantitative and qualitative methods using Python, Google BigQuery and Looker Studio.
Results
Overall, authors expressed positive sentiment towards research citation in Wikipedia and researcher engagement practices (mean scores >7/10). Sub-analyses revealed significant differences in sentiment based on publication type (articles vs. books) and discipline (Humanities and Social Sciences vs. Science, Technology, and Medicine), but not access status (open vs. closed access).
Conclusions
This study provides unique insights into author perceptions of Wikipedia’s trustworthiness. Further research is needed to deepen the understanding of the benefits for researchers and publishers including academic citations in Wikipedia.Funding: The author(s) received no specific funding for this work
Brands and Psychological Influences on Consumer Behaviour
No full textThis is an accepted manuscript of a book chapter published by Palgrave MacMillan in Brands, Branding, and Consumerism on 11/03/2025, available online: https://doi.org/10.1007/978-3-031-80859-3_2
The accepted version of the publication may differ from the final published version.
Terms and conditions for the use of this book chapter can be found on the SpringerNature website at https://www.springernature.com/gp/open-science/policies/accepted-manuscript-terms.Consumers are influenced by a myriad of factors in their choices of brands which can be categorised differently. The impact of psychological and personal influences which comprise of factors like perception, motivation, learning and memory, and attitudes on brand consumption is considerable. This chapter features a meticulous discussion of these issues and their implications on brand consumption and branding strategies. These are underpinned by themes such as brand positioning/repositioning, the extended realities, webrooming, and showrooming and how they explain consumer day-to-day brand decisions. The understanding of consumer learning and memory are usually linked to brand awareness, brand association, brand recognition, brand recall, brand relearning and brand associative networks. These are carefully examined in this chapter. Moreover, the issues around the underpinning factors that motivate consumer brand choices, their attitude formation and change for brands are also examined with a robust discussion of their implication for strategic brand management.Published versio
A qualitative mixed-method narrative study on psychotherapeutic support needs based on a series of 11 cases of survivors of the 2023 Odisha train accident
No full text©2025 The Authors. Published by Springer Nature. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link: https://www.cureus.com/articles/349096-a-qualitative-mixed-method-narrative-study-on-psychotherapeutic-support-needs-based-on-a-series-of-11-cases-of-survivors-of-the-2023-odisha-train-accident#!/Background: Rail and road accidents are common in India and are extremely stressful life events. Many accident survivors develop stress-related mental health problems but do not get psychotherapeutic support. We intended to analyse the needs and types of techniques for the psychotherapeutic support of the survivors of the 2023 train accident in Odisha and to reflect on how the services can be facilitated.
Methods: It was a qualitative, mixed-method, narrative study based on the interview of a sample of 11 survivors of the train accident.
Results: It was observed that the survivors and their families had many unresolved psychological issues related to the trauma of the train accident and its consequences. The survivors articulated their mental health concerns holistically in a comprehensive way. It appeared that their psychotherapeutic needs were unmet. Examples of psychological interventions needed were psychoeducation, relaxation, supportive and cognitive therapies, and specific trauma-focused cognitive behavioural therapy. Many challenges in providing psychotherapies were identified, such as limited awareness about the need for psychotherapeutic intervention, affected persons in geographically highly dispersed areas, unavailability of psychotherapeutic services or personnel in most places, and lack of resources.
Conclusion: The train accident survivors have immense psychotherapeutic needs, but these are mostly unmet. Modifying the provision methods to tele-psychotherapy and training other healthcare personnel such as nurses, and counsellors might help the resource-scarce situation
Beyond Futures - Festival of Research & Innovation 2025
Get PDF© 2025 The Authors. Published by the University of Wolverhampton. This is an open access book available under a Creative Commons licence.Book of abstracts and full paper proceedings for Beyond Futures - Festival of Research and Innovation, Research Student Conference, 9th-11th September 2025, University of Wolverhampton
Biologically plausible energy-efficient context-sensitive neural networks
No full textA thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.The rapid advancements in artificial intelligence (AI), particularly in deep neural networks (DNNs), have significantly driven the demand for specialised hardware, such as GPUs and TPUs, to meet the growing computational requirements. However, this surge in computational power has led to substantial increases in energy consumption, raising critical concerns about the economic, technical, and environmental sustainability of AI technologies. For instance, training a single large-scale neural network can generate as much carbon dioxide as five automobiles over their lifespans.
While notable efforts have been made to enhance the energy efficiency of deep learning (DL) models, the challenge of sustainable computation persists, especially in resource-constrained environments like hearing aid devices. Despite being inspired by the human brain’s functionality, DNNs fall short of matching the brain’s remarkable energy efficiency, where the human brain operates at merely 20 watts while performing complex cognitive tasks.
This thesis addresses the imperative need for human-level computational efficiency in DL models through a multidisciplinary approach synthesising AI, neuroscience, and hardware engineering insights. Central to this work is integrating concepts derived from recent neurological discoveries of context-sensitive neurons into DNNs, aiming to enhance energy efficiency in neural network processing.
The research introduces a novel context-sensitive (CS) mechanism within a deep convolution network (DNN), demonstrating significant reductions in neural activity and energy consumption compared to state-of-the-art methods. The CS DNN with 18 convolution layers is employed for multimodal (MM) non-linear regression tasks, such as audio-visual speech enhancement (AVSE). It is then compared against a conventional point neuron-inspired DCN in terms of perceptual evaluation of speech (PESQ) and short-time objective intelligibility (STOI). This research shows that the two-point neuron-driven DCN performs comparable to point-neuron DCN. However, the twopoint neuron uses up to 7 times fewer neurons. Furthermore, to demonstrate the scalability of this energy efficiency, the DCN is mapped to a 50-layer convolution network and implemented on Xilinx UltraScale+ MPSoC based Open-MHA (Multimodal hearing aid) platform. The two-point neuron architecture showed 103 times lesser energy (J) consumption for an inference.
This research introduces a novel context-sensitive (CS) mechanism within a deep convolutional network (DNN), demonstrating significant reductions in neural activity and energy consumption compared to state-of-the-art methods. The proposed CSDNN, comprising 18 convolutional layers, is employed for multimodal non-linear regression tasks such as audio-visual speech enhancement (AVSE). Its performance is evaluated against a conventional point-neuron-inspired deep convolutional network (DCN) using the Perceptual Evaluation of Speech Quality (PESQ) and Short-Time Objective Intelligibility (STOI) metrics. The results indicate that the two-point neuron-driven DCN performs comparably to the point-neuron DCN while utilizing up to seven times fewer neurons. To demonstrate the scalability of this energy-efficient architecture, the DCN is expanded to a 50-layer convolutional network and implemented on the Xilinx UltraScale+ MPSoC-based Open-MHA (Open Multimodal Hearing Aid) platform. The two-point neuron architecture exhibited a 103-fold reduction in energy consumption (J) per inference.
Furthermore, this research adopts a two-point neuron-based, biologically plausible training mechanism, which is transformed into a novel multimodal setting and applied to the audio-visual speech enhancement task. Experimental results, compared to a backpropagation-based baseline model, demonstrate outstanding energy efficiency, reducing neuron firing rates by up to 70%. This reduction implies more sustainable implementations, making the approach highly suitable and desirable for embedded systems.
Finally, this thesis explores the biological plausibility of the proposed mechanism by implementing context-sensitive (CS) spiking neurons within a spiking neural network (SNN). This implementation provides a comprehensive understanding of the role of two-point neurons both mathematically and empirically. The CS-SNN is applied to a classical non-linear XOR learning task, demonstrating rapid learning—twice as fast as the baseline model—along with improved performance.
Building on these contributions, this research contributes to the ongoing pursuit of sustainable and biologically inspired AI by proposing and validating a context-sensitive approach that advances the energy efficiency of deep neural networks (DNNs)
Assessing the societal influence of academic research with ChatGPT: Impact case study evaluations
No full textThis is an author's accepted manuscript of an article published by Wiley in Journal of the Association for Information Science and Technology (JASIST) on 15 May 2025, available online https://doi.org/10.1002/asi.25021. The accepted manuscript may differ from the final published version.Academics and departments are sometimes judged by how their research has benefitted society. For example, the UK’s Research Excellence Framework (REF) assesses Impact Case Studies (ICSs), which are five-page evidence-based claims of societal impacts. This article investigates whether ChatGPT can evaluate societal impact claims and therefore potentially support expert human assessors. For this, various parts of 6,220 public ICSs from REF2021 were fed to ChatGPT 4o-mini along with the REF2021 evaluation guidelines, comparing ChatGPT’s predictions with published departmental average ICS scores. The results suggest that the optimal strategy for high correlations with expert scores is to input the title and summary of an ICS but not the remaining text, and to modify the original REF guidelines to encourage a stricter evaluation. The scores generated by this approach correlated positively with departmental average scores in all 34 Units of Assessment (UoAs), with values between 0.18 (Economics and Econometrics) and 0.56 (Psychology, Psychiatry and Neuroscience). At the departmental level, the corresponding correlations were higher, reaching 0.71 for Sport and Exercise Sciences, Leisure and Tourism. Thus, ChatGPT-based ICS evaluations are simple and viable to support or cross-check expert judgments, although their value varies substantially between fields
Empowering women entrepreneurs through digital upskilling: driving economic recovery in Türkiye, post-earthquake
No full text© 2025 UK Parliament. In development proposal topic submitted to the International Development Committee of UK Parliament.The February 2023 earthquakes in Türkiye caused widespread devastation, erasing 48,422 businesses and leaving communities grappling with the challenges of recovery. Among those most severely impacted were women-led Micro, Small, and Medium-Sized Enterprises (MSMEs), with 88% of women entrepreneurs, including refugees, facing significant disruptions to their operations. Alarmingly, 50% of these businesses remain unable to resume, revealing entrenched systemic inequalities and structural barriers, such as limited access to resources, markets, and digital tools. Without targeted intervention, these women entrepreneurs risk permanent exclusion from economic systems, exacerbating regional disparities and delaying recovery
Towards a sustainable future: decarbonising the health sector. learnings from NHS, UK case study
No full textThis is an abstract of a conference paper presented at Indian society of hospital waste management, Silver Jubilee National Conference, 28th &
29th November, 2025, Bangalore Medical College and Research Institute Bangalore, India.
The accepted manuscript may differ from the version as published
“It’s literally like I’m sat right there in the room with you!” A generic qualitative study of formative audio feedback within pre-registration nurse education
No full textA thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Professional Doctorate in Health and Wellbeing.Introduction: For pre-registration student nurses’ provision of academic feedback contributes to academic performance, professional practice and their professional identity, and technological advancements have created opportunities for Higher Education Institutions to diversify approaches to feedback.
Aim: To explore how the embodied voice of the nurse academic, delivered through formative audio feedback, mediates pre-registration student nurses learning, facilitating knowledge construction and mean-making, and contributing to development of professional identity.
Methodology: This Generic Qualitative study initially explored sixteen pre-registration student nurses’ expectations of formative audio feedback through meta-planned focus groups. Following receipt of digital audio files, without any additional written commentary, twelve pre-registration student nurses within individual semi-structured interviews articulated their experiences of formative audio feedback. Data analysis was facilitated through using reflexive thematic data analysis (Braun and Clarke, 2013).
Findings: Conceptualised through the four themes of (1) “Literally like I’m sat there”; (2) “Knowing what you meant”; (3) “Creating professional identity” and (4) “Knowledge created through technological mediation but...” this study highlights that as an embodied vocal practice, the nurse academic’s voice through formative audio feedback is less formal and nuanced, and is linked to the way in which pre-registration student nurses learn and subsequently develop their professional identity. Formative audio feedback elicits feelings of connection conceptualised through the notion of “virtual academic-student interaction” whereby voice as a semiotic resource enables the exchange of meanings. Emerging from the findings, was the development of the Initiation, Preamble, Focused, Explanations and Disengagement (IPFED) Framework for formative audio feedback, intended to provide a structured approach for provision of formative audio feedback.
Conclusions: Formative audio feedback alone, without any written feedback is sufficient as a feedback modality as the embodied voice of nurse academic mediates pre-registration student nurses learning, supports knowledge construction and mean-making which contributes to the development of professional identity
The Children – Sit Less, Move More (C-SLAMM) pilot intervention: Feasibility and acceptability of a multi-component school and home-based intervention to promote physical activity
Get PDF© 2025 The authors. Published by PLOS. This is an open access article available under a Creative Commons licence.
The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1371/journal.pone.0335933Background A high proportion of primary school children in Northern Ireland (NI) are insufficiently active. In response, an intervention adapted from the TransformUs programme was established to promote physical activity (PA) and reduce sedentary behaviour (SB). This study aimed to assess the feasibility of recruitment and retention, data collection procedures, intervention acceptability and explore preliminary effectiveness on children’s PA and SB levels. Methods The Children – Sit Less, Move More (C-SLAMM) intervention integrated behavioural, pedagogical, and environmental strategies across classroom, school, and home settings. Eight primary schools were recruited and randomly assigned (1:1) to either the intervention or control. Feasibility measures included school and participant recruitment, retention and completion rates. Acceptability was assessed using weekly diary logbooks, fidelity checklists and qualitative methods (write and draw activity, focus groups, interviews). Children (aged 7–9 years) wore activPAL accelerometers continuously for 7 days at baseline and post-intervention (Week 8) to measure time spent sitting, standing, and stepping. Results A total of 194 consent forms were distributed. Of the 162 children who consented (84% response rate), 76 (46.9%) met the valid wear-time criteria at both baseline and follow-up. Intervention delivery varied across schools, impacting fidelity. Qualitative analysis revealed four themes: (1) engagement, (2) positive aspects of C-SLAMM intervention, (3) barriers to intervention delivery, and (4) recommendations for improvement. Children and teachers generally found the intervention acceptable, though barriers included limited parental support, inadequate classroom space and time constraints. There were no significant differences in sitting time (β = −6.5 minutes/day; 95%CI: −36.4, 23.4), standing or stepping time between groups. Nevertheless, the intervention was seen as enhancing classroom experiences for both children and teachers. Conclusions The C-SLAMM intervention was well-received and shows promise as an acceptable approach to reduce sitting time and promote PA. Further refinement of data collection methods is needed before progressing to a pilot trial.Northern Ireland Chest, Heart and Stroke.Published versio