11237 research outputs found
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Investigating the impairment-performance relationship during competition in elite blind and partially sighted football
No full textIntroduction: Classification systems aim to minimise the impact of impairment on competition outcome. To measure the effectiveness of a classification system, the relationship between impairment and performance must be investigated. There are two forms of football for athletes with vision impairment (VI): blind football and partially sighted football. Athletes are allocated to either one based on VI severity. Research is yet to assess the impact of impairment on performance in competition; therefore, this study aimed to measure the impairment-performance relationship in male blind, partially sighted and women's blind football. Methods: Notational data consisting of several technical performance measures were assessed (including, but not limited to, possession, passing, shots, and goals) and combined with visual function data from elite blind and partially sighted footballers. Correlations of notational match data and visual acuity (VA) were measured for male blind and partially sighted footballers (study one) and women's blind footballers (study two). Results: In study 1: the team-level analysis revealed a weak but statistically significant correlation between win ratio and VA for male blind football ( r = 0.227). The player-level analysis revealed that VA was correlated with defensive zone clearances ( r = 0.198), shots on target ( r = 0.237), and shots saved ( r = 0.229). In partially sighted football, team-level analysis revealed that VA was significantly correlated with win ratio ( r = −0.534) and ball possession ( r = 0.419). The player-level analysis revealed that VA was correlated with the number of fouls committed ( r = 0.273) and fouls won ( r = −0.273). These findings suggest that impairment may impact the outcome of competition in male blind and partially sighted football. In study two, win ratio was not correlated with VA ( r = −0.095) in women's blind football, implying that impairment does not impact competition outcome and that fairness may be achieved.Discussion: These results evidence a different impairment-performance relationship for each version of the sport, and that the current classification system may not optimise fairness across each form of football.</p
A collaborative approach to co‐creating contact confident, an evidence‐informed tackle safety and technique intervention for coaches and players in rugby union
No full textTraining strategies to promote safe and effective tackle technique are an important target for injury prevention and enhancing performance across the rugby codes. However, there is a research‐to‐implementation gap in ‘real‐world’ settings and a need for more studies with women and girls. This article outlines the development of an evidence‐informed tackle coaching intervention co‐created with content and context experts in women's rugby union. Based on previous work which developed a context‐specific injury‐prevention programme for women playing Australian Football, a 7‐step process was adopted. After gaining organisational support, the process included using research evidence and applied experience and engaging intervention implementers to co‐create the content for ‘Contact Confident’. Iterative integration of feedback from early implementers enhanced practical relevance for coaches. This study underlines the importance of stakeholder collaboration in cocreating and implementing injury prevention interventions, offering a scalable resource for tackle and ball carrier skill development in rugby union for women and girls, with wider relevance for other genders and sports. Future research should look to evaluate the impact of this and similar context‐specific interventions on coach behaviour and athlete outcomes across varied global rugby settings.</p
The non-synthetic sweeteners, miraculin and mogroside V, but not stevia, disrupt the intestinal epithelial barrier function through a sweet taste receptor-dependent mechanism
No full textImpaired intestinal barrier function is a precursor to various metabolic diseases which can occur when the intestinal epithelium is directly exposed to certain dietary components. Previous studies have demonstrated the barrier disruptive effect of artificial sweeteners such as sucralose and saccharin, in the intestinal epithelium. In the present study, we aimed to evaluate the impact of 3 non-synthetic sweeteners, stevia, miraculin, and mogroside V, on Caco-2 monolayer barrier integrity, reactive oxygen species (ROS) production, and tight junction protein expression as compared to the artificial sweetener saccharin. Miraculin and mogroside V exerted a significant impact on cell numbers with decreased cell viability at both 24 and 48 h. ROS production was also significantly increased by miraculin and mogroside V and epithelial barrier function, assessed by transepithelial electrical resistance and FITC-dextran leak, was significantly disrupted with both miraculin and mogroside V. Stevia exhibited no effect on epithelial cell viability, ROS accumulation or barrier function, despite a range of concentrations investigated. Knockdown of the sweet taste receptor, T1R3, significantly attenuated miraculin- and mogroside V-induced loss of cell viability, ROS accumulation and barrier disruption suggesting a T1R3-dependent mechanism. Gene expression analysis revealed differential regulation of cell junction-related genes by mogroside V and miraculin with upregulated expression of genes such as CAV1 , CLDN2 and CLDN10 , and downregulated expression of genes such as CAV3 and CDH2 . These findings demonstrate that miraculin and mogroside V, but not stevia, negatively regulate ROS formation and intestinal epithelial barrier function in a T1R3-dependent manner and potentially through modulation of tight junction proteins. This highlights the need for further investigation into the long-term dietary implications of natural sweeteners, particularly miraculin and mogroside V, on gut health.</p
National trends in the prevalence of suicide attempts among adolescents by self-perceived weight, 2005–2023: a nationwide representative study in South Korea
No full textObjective: Suicide is a leading cause of death among adolescents, and despite the need to distinguish between suicidal consideration and suicide attempts, research focused on suicide attempts remains insufficient. Therefore, this study aims to investigate the influence of self-perceived weight on suicide attempts.Methods: This study utilized data from the Korea Youth Risk Behavior Web-based Survey for its analysis from 2005 to 2023, including a total of 1,156,728 participants. This study utilized various analytical methods to examine the influence of self-perceived weight on suicide attempts. We estimated weighted prevalence and used linear regression to assess temporal trend β coefficients and their differences (βdiff) with 95% confidence intervals (CIs), and survey-weighted logistic regression to estimate weighted odds ratios (wORs) and 95% CIs for the association between self-perceived weight and suicide attempts.Results: A comparison of suicide attempts based on self-perceived weight suggested that individuals who perceived themselves as overweight (weighted prevalence, 3.97% [95% CI, 3.89 to 4.04]) had the highest rate of suicide attempts, followed by those who perceived themselves as underweight (3.36% [95% CI, 3.28 to 3.44]), while those who perceived themselves as having a normal weight (3.20% [95% CI, 3.14 to 3.27]) had the lowest rate. Additionally, females (underweight: 4.47% [95% CI, 4.32 to 4.62]; normal weight: 3.91% [95% CI, 3.81 to 4.01]; overweight: 5.23% [5.11 to 5.35]) experienced more suicide attempts than males (underweight: 2.73% [95% CI, 2.65 to 2.82]; normal weight: 2.43% [95% CI, 2.35 to 2.51]; overweight: 2.60% [95% CI, 2.52 to 2.69]).Conclusion: Findings from the present study suggest that self-perceived weight was associated with suicide attempts and interaction analyses indicated a potential sex-based difference in the impact of body image distortion. Therefore, this study suggests the introduction of programs and campaigns aimed at correcting distorted self-perceived weight.</p
A Guide for UK-Based Research Ethics Committees Assessing Health Research with Gypsy, Roma, Traveller, Showmen and Boater (GTRSB) Communities
No full textThis is one of five new guides designed to support Research Ethics Committees (RECs) in reviewing health research involving diverse inclusion health communities.
The collection includes one overarching guide and four specialist guides focused on research with Gypsy, Roma, Traveller, Showmen and Boater communities, people seeking asylum or with refugee status, people who are unhoused and individuals with impaired capacity.
Written and reviewed by experts, including people with lived experience, the guides offer practical tips, checklists, and best practice advice for panel members.</p
A Guide for UK-Based Research Ethics Committees Assessing Health and Care Research with People with Impaired Capacity
No full textThis is one of five new guides designed to support Research Ethics Committees (RECs) in reviewing health research involving diverse inclusion health communities.
The collection includes one overarching guide and four specialist guides focused on research with Gypsy, Roma, Traveller, Showmen and Boater communities, people seeking asylum or with refugee status, people who are unhoused and individuals with impaired capacity.
Written and reviewed by experts, including people with lived experience, the guides offer practical tips, checklists, and best practice advice for panel members.</p
The use of digital technologies in construction safety: a systematic review
No full textThe global construction industry faces serious safety challenges, characterised by high rates of accidents and fatalities. A systematic review that analysed 95 academic articles from the Scopus and Web of Science databases investigated the current use of digital technologies (DTs) in construction safety management across developed and developing countries. The research discovered that digital technology applications in construction safety primarily focus on developing models and simulations. These technologies are making significant contributions by enhancing worker training, improving risk prediction capabilities, enabling real-time monitoring, facilitating better communication, and supporting more proactive safety interventions. The most frequently utilised digital technologies in this domain include virtual reality (VR), building information modelling (BIM), machine learning, and artificial intelligence (AI). Despite the promising potential of these technologies, their actual implementation remains somewhat limited, especially in developing countries. This study identified critical knowledge gaps, specifically the limited understanding of digital technology trends in construction safety management across different economic contexts, the insufficient research on strategies to increase digital technology adoption in the construction sector, and the need for more comprehensive investigations into how the technology adoption divide can be bridged. This research aimed to facilitate future empirical studies that can advance the understanding of digital technologies and the development of strategies to integrate them more comprehensively into construction safety practices. By providing a detailed overview of current digital technology applications, highlighting research limitations, and suggesting future research directions, this review seeks to contribute to both academic understanding and practical improvements in global construction industry safety.</p
Exploring the Impact of Lived Experience Contributions to Social Work and Healthcare Programmes: A Scoping Review
No full textThe integration of lived experience educators (LEEs) in social work and healthcare educational programmes has evolved to recognise its potential to enhance learning, empathy and professional development among students. This scoping review explores the level of LEEs’ engagement in academic models and the different perspectives of LEEs, academic staff and students on lived experience education, analysing both the merits and challenges of this pedagogical approach. A systematic search was conducted across multiple academic databases and identified 37 articles on lived experience education. Arnstein’s Ladder of Citizen Participation was used as an evaluation tool to assess the levels of engagement described in the studies. The common themes across studies were analysed and synthesised for each perspective of the stakeholders. The findings of this review evidence that while lived-experience-led education enhances students’ performance, the depth of participation of LEEs varies widely. The ladder-level analysis found that many educational programmes are designed at the higher rungs of “co-production”, where LEEs collaborate equally with academics. However, some practices are at the lower rungs of “tokenism”, where LEEs are consulted but have limited decision-making power. This may be due to challenges such as a lack of structured support systems, emotional labour for LEEs and inconsistencies in practice. Therefore, greater efforts are needed to move beyond tokenistic involvement towards meaningful co-production in education for people-centred services. By embedding lived experience contributions, education becomes a synergistic practice, continuously shaping and enriching the professional development of both students and the communities they serve.</p
Detection and classification of captive coppery titi monkey calls
No full textEcoacoustic monitoring has many applications in conservation and welfare but generates large amounts of data that are extremely time-intensive to manually process. This has led to an increased interest in the use of machine learning methods to increase efficiency and reduce workload. Common issues within this area include noisy, unbalanced and limited datasets, making it challenging to make effective machine learning models. This study aimed to determine the vocal repertoire of the coppery titi monkey, Plecturocebus cupreus, and develop a machine learning model that can detect, segment and classify calls within streaming audio using a small and unbalanced dataset with overlapping calls from other species. Acoustic data were collected across three zoo populations of P. cupreus using passive acoustic monitors. From this, 3302 calls were manually labelled to use as training data. Ten call types were established manually, corresponding to three groups: short calls, long calls and harsh calls. A Long Short-Term Memory neural network was created that successfully detected calls (accuracy = 0.95) and classified call types (accuracy = 0.97). Potential applications for the model include welfare monitoring in captivity and population monitoring of P. cupreus and related endangered species in the wild.</p
Automated lightweight model for asthma detection using respiratory and cough sound signals
No full textBackground and objective: Chronic respiratory diseases, such as asthma and COPD, pose significant challenges to human health and global healthcare systems. This pioneering study utilises AI analysis and modelling of cough and respiratory sound signals to classify and differentiate between asthma, COPD, and healthy subjects. The aim is to develop an AI-based diagnostic system capable of accurately distinguishing these conditions, thereby enhancing early detection and clinical management. Our study, therefore, presents the first AI system that leverages dual acoustic signals to enhance the diagnostic ACC of asthma using automated, lightweight deep learning models. Methods: To build an automated, lightweight model for asthma detection, tested separately with respiratory and cough sounds to assess their suitability for detecting asthma and COPD, the proposed AI models integrate the following ML algorithms: RF, SVM, DT, NN, and KNN, with an overall aim to demonstrate the efficacy of the proposed method for future clinical use. Model training and validation were performed using 5-fold cross-validation, wherein the dataset was randomly divided into five folds and the models were trained and tested iteratively to ensure robust performance. We evaluated the model outcomes with several performance metrics: ACC, precision, recall, F1 score, and area under the AUC. Additionally, a majority voting ensemble technique was employed to aggregate the predictions of the various classifiers for improved diagnostic reliability. We applied Gabor time–frequency transformation for feature extraction and NCA) for feature selection to optimise predictive accuracy. Independent comparative experiments were conducted, where cough-sound subsets were used to evaluate asthma detection capabilities, and respiratory-sound subsets were used to evaluate COPD detection capabilities, allowing for targeted model assessment. Results: The proposed ensemble approach, facilitated by a majority voting approach for model efficacy evaluation, achieved acceptable ACC values of 94.05% and 83.31% for differentiating between asthma and normal cases utilising separate respiratory sounds and cough sounds, respectively. The results highlight a substantial benefit in integrating multiple classifier models and sound modalities while demonstrating an unprecedented level of ACC and robustness for future diagnostic predictions of the disease. Conclusions: The present study sets a new benchmark in AI-based detection of respiratory diseases by integrating cough and respiratory sound signals for future diagnostics. The successful implementation of a dual-sound analysis approach promises advancements in the early detection and management of asthma and COPD.We conclude that the proposed model holds strong potential to transform asthma diagnostic practices and support clinicians in their respiratory healthcare practices.</p
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