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Paddle-to-podium: A constraints-led approach to sprint-paddle training in competitive Australian female surfers
No full textFemale surfing is evolving rapidly with increasing expectations for athletes aspiring to qualify for the Olympics and World Championship Tour. Sprint paddling is a critical component of surfing performance, and paddling velocity in a pool setting has been shown to be a strong predictor of competition level in the ocean environment. Therefore, this study aimed to enhance sprint paddling performance among female surfers through a technique training intervention utilising a constraints-led approach. Experimental design included baseline testing prior to a 6-week control period, assessments pre and post the approximately 6-week training intervention, and a 6-week non-trained retention period with a final follow-up testing session. Pool-based testing consisted of a 15-m sprint-paddle test with video analysis for spatiotemporal data, a 12-s paddling force test, and a perception of paddling proficiency questionnaire. Additionally, internal and external shoulder strength and range of motion, and a 1RM maximum pull-up test were assessed in the gym. The training intervention applied Newell's Model of Constraints by manipulating task constraints to enhance paddling technique. Results showed significant improvements in sprint time to 15 m (PRE: M = 10.79 ± 0.40 s, POST: M = 10.50 ± 0.32 s) and average velocities (PRE: M = 1.57 ± 0.07 m/s, POST: M = 1.63 ± 0.04 m/s), stroke efficiency (decreased stroke count and increased stroke length), maximal and average force in the pool, and perceived paddling proficiency. These findings suggest that coaches should integrate this novel training into the daily training environment to continue to advance female surfing performance
The Contributions of Student-Level and Classroom-Level Factors for Australian Grade 2 Students’ Writing Performance
Full text linkUsing multilevel modeling, the current study examined student-level predictors of compositional quality and productivity in Grade 2 Australian children (N = 544), including handwriting automaticity, literacy skills, executive functioning, writing attitudes, and gender; and classroom-level (n = 47) variables predicting students’ writing outcomes, including the amount of time for writing practices and the explicit teaching of foundational (handwriting, spelling, grammar) and process writing skills (planning and revision strategies). Multilevel analyses revealed that student-level factors, including gender, general attitudes, and transcription skills (handwriting automaticity and spelling), were key predictors of writing outcomes. Interaction analyses showed that spelling and word reading influenced writing outcomes, with effects varying by gender. At the classroom-level, time spent on planning had a positive effect on students’ compositional quality, and time spent on spelling instruction had a negative effect on students’ compositional productivity. Implications for research and education are discussed
Clinicians’ perceptions of a mobile app decision-aid for improving patient compression stocking adherence: a qualitative descriptive approach guided by the technology acceptance model
Full text linkBackground:A novel mobile app decision-aid was developed to improve patient adherence to compression stockings and was tested in a tertiary hospital outpatient clinic, demonstrating improved adherence in the intervention group compared to usual care. The successful integration of new technology into clinical practice depends on clinician acceptance of the technology. The objective of this research was to investigate clinicians’ acceptance of the mobile app decision-aid, exploring their experiences and perceptions regarding its use in clinical practice.Methods:A qualitative descriptive approach was used in this two-phased study: (a) capturing clinician perceptions throughout the conduct of the main study and (b) semi-structured interviews guided by the Technology Acceptance Model (TAM). Themes were analyzed using NVIVO-12 software.Results:Nine clinicians participated in the first phase, with four completing follow-up interviews in the second phase. Key themes, organized using TAM constructs (ease of use, perceived usefulness, attitudes, and behavioural intentions), highlighted the integration of the technology into practice, emphasizing efficiency, benefits, and challenges. The mobile app decision-aid may have gently guided clinicians and patients towards certain evidence-based choices, while allowing for clinicians to override recommendations based on their professional judgement and experience. Clinicians reported that the decision-aid supported a non-judgmental approach, strengthening the therapeutic relationship with the patient, challenged assumptions, provided structure, facilitated skill-development, and encouraged persistence in identifying and addressing patient barriers.Conclusion:Clinicians positively perceived the mobile app delivering the decision-aid, emphasizing its ease of use and benefits for patients as key factors supporting its adoption in clinical practice to improve compression stocking adherence. These findings suggest that the mobile app decision-aid could be a feasible and effective resource for improving adherence, with opportunities for tailoring and broader applicability to other patient populations in the future. Further research is warranted to explore its long-term impact and scalability.Trial registrationThe research is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) 12,620,000,544,976. Ethical Approval was granted through the Gold Coast Hospital and Health Service Human Research Ethics Committee and Bond University Human Research Ethics Committee HREC/2020/QGC/62,843 and SSA/2020/QGC/62,843
Lower limb exoskeleton training as part of home rehabilitation: a systematic review
Full text linkIntroduction: Individuals with neurological conditions often have difficulty accessing and mobilising in the community, requiring home rehabilitation. Portable lower-limb exoskeletons, often used for indoor gait training, may have broader applications and assist in community mobility. This review explores the feasibility and effectiveness of using an exoskeleton in home rehabilitation. Methods: A search of PubMed, Embase, Web of Science, CINAHL, and Scopus. Studies reporting on exoskeleton-based home rehabilitation for individuals with mobility-impairing health conditions, compared to physiotherapy, with outcomes focused on balance, mobility, or functional improvement were eligible for inclusion. Reported outcomes were categorised based on the purpose of exoskeleton use, i.e. rehabilitation, performance, or training effects. Results: The initial search yielded 7444 records, of which seven studies and one follow-up report were included. Participants had a range of neurological conditions all used a different exoskeleton. The supervision provided by clinicians varied from none to continuous. The activities undertaken with the exoskeletons differed. Five studies reported on the rehabilitation effects, showing improvements in distance, balance, complex walking, and physiological cost. Five studies also reported on performance, with some improvement in peak propulsion of the ankle and an increase in the number of steps. Two studies reported on the training effect: participants with wheelchair-dependent spinal cord injuries took 5000 steps, and their most common activity was individual exercises. Discussion: Findings from this review indicate that the use of exoskeletons as part of home rehabilitation for different neurological conditions, including wheelchair-dependent participants, is feasible and effective, particularly when targeting the rehabilitation effect
Dynamic and Explainable Mortality Risk Prediction for TBI Patients in the ICU
No full textDynamic mortality risk prediction in the intensive care unit (ICU) is crucial for supporting clinicians’ decision-making, specifically in traumatic brain injury (TBI) patients. We aim to develop and evaluate a dynamic deep learning (DL) framework that can provide hourly updates of 30-day mortality risk prediction for TBI patients following ICU admission. Using demographics and time-series physiological data, a recurrent neural network-based model was trained on data from 135 TBI patients admitted to the Gold Coast University Hospital (GCUH) in Australia. Model’s performance was evaluated utilizing the area under the receiver operating characteristics (AUC), Matthews correlation coefficient (MCC), accuracy, and other metrics, performed calibration and decision curve analysis to interpret the model’s output and determine its clinical usefulness. The Shapley additive explanation algorithm was utilized to clarify the contribution of features to the predictions. The proposed method showed predictive performance on the cross-validation dataset that improved over time: MCC 0.24 and AUC 0.713 for the prediction at 24 h after admission, 0.451 and 0.756 at 72 h, 0.519 and 0.803 at 120 h, and 0.748 and 0.946 before twelve hours to the outcome (either death or discharge), respectively. The model was further tested with a holdout test dataset with 34 TBI patients, achieving an average prediction accuracy of 0.851, AUC of 0.632, and MCC of 0.403, respectively, in the first 24-h interval. The proposed model demonstrates proof of principle with explainable results in predicting mortality risk, encouraging further development and validation in a clinical setting
Working status prediction for a high-formwork support system using finite element model-informed deep learning model and GPT-aided method
Full text linkA High-formwork support system (HFSS) is essential during the construction process for complex structures. A lack of an effective monitoring method occasionally causes the system’s tragic collapse. In order to establish a reliable method for structural condition identification, experimental measurements on structures are always required. However, in practice, the experiments on sites are either expensive or difficult to conduct. A data-driven algorithm convolutional neural networks (CNNs) for working status monitoring of the HFSS structure is proposed in this study. First, a finite element (FE) model for the HFSS was developed and optimized by using the genetic algorithm (GA). Then, the optimal FE model was employed to produce structural response data for three statuses of the HFSS, such as normal working status, local instability, and fully unstable statuses. The generated dataset was adopted to train a CNNs classifier, which can correctly predict the working states of the structure. Finally, the potential of CNNs was validated on the experimental measurements derived from the HFSS, and the performance of CNNs and support vector machine (SVM) was compared. CNNs performed much better than SVM on the experimental dataset. Moreover, this study developed a Retrieval-Augmented Generation (RAG) model by leveraging a Generative Pre-Trained Transformer (GPT) to synthetically generate an SHM report to describe the structural condition of the given HFSS structures. A knowledge graph (KG) was also developed to enable comprehensive, reliable, informative SHM contexts. Multiple evaluation metrics were employed to assess the performance of the RAG model. The findings indicate that the RAG model could generate accurate and reasonable SHM reports for HFSS.</p
Perceptions of Sustainable Leadership in Australian Healthcare
No full textPurpose: Sustainable leadership is essential for addressing workforce shortages, technological advancements, and increasing regulatory demands in Australian healthcare. Many healthcare leaders assume their roles based on clinical expertise rather than formal leadership training, highlighting the need for structured support. This study explores sustainable leadership in Australian healthcare, identifying key challenges, support mechanisms, and strategies for improvement.Methods: A cross-sectional survey was conducted among 276 managers, leaders, and supervisors working in Australian healthcare organisations. Participants were recruited through professional networks, social media, and direct invitations. The survey, administeredvia Qualtrics, examined leadership training, characteristics of sustainable leadership, challenges, and available support systems. Quantitative data were analysed using IBM SPSS Statistics, while qualitative responses underwent thematic analysis.Results: Leadership training was primarily informal, with limited access to structured programs due to time and financial constraints. Sustainable leadership was defined as balancing operational demands with long-term planning, ethical decision-making, and fostering a resilient workplace culture. Key challenges included staff retention, change management, and hierarchical structures limiting innovation. Support for leaders was inconsistent, with male leaders reporting higher perceived support. Systemic barriers, such as outdated leadershipmodels and a focus on financial performance over workplace culture, restricted sustainable leadership implementation.Conclusion: To enhance sustainable leadership, organisations must prioritize structured training, mentorship, and inclusive leadership pathways. Addressing systemic barriers and redefining leadership success beyond financial metrics will strengthen leadership resilience, reduce burnout, and improve healthcare outcomes
Depression and Subjective Well-Being in University Students: The Mediating Roles of Meaning in Life and Perceived Negative Interactions
Full text linkMeaning in life is recognised as an important determinant of subjective well-being and is linked to a decreased risk of depression and despair. Additionally, the quality of social interactions significantly influences students’ well-being. This study investigates the relationship between depression and subjective well-being among university students and explores the potential mediating roles of meaning in life and perceived negative interactions. A sample of 198 university students aged 18 to 29 completed an online survey comprising of the Satisfaction with Life Scale, Positive and Negative Affect Schedule, The Centre for Epidemiological Studies Depression Scale, The Meaning in Life Questionnaire, and The Test of Negative Social Exchange. The results indicated a negative relationship between depression and subjective well-being (p < .001), including meaning in life as a mediator (p < .001), whereas perceived negative interactions was not a mediator. These findings offer valuable insights in relation to mental health as they emphasise the importance of understanding correlates of students’ well-being, which are relevant for researchers and educators
Digital Accessibility and Poverty Reduction: Global Perspectives
Full text linkThis study investigates the poverty reduction gains that are associated with access to digital technologies by using panel data based on 113 countries from 2000 to 2022. We address crosssectional and temporal dependency with the Driscoll-Kraay technique, and endogeneity with the Lewbel two-stage least squares technique. The results indicate that the digital technology access index—comprising broadband, telephone, mobile, and internet access—contributes to poverty reduction, with the effect being persistent. Except for mobile phone usage, the rest of the digital technology proxies do not follow the critical mass hypothesis. Mediation analysis indicates that access to digital technologies contributes to poverty reduction by working through increasing gross domestic product per capita; accessing finance, education, and employment; and reducing income inequality. The poverty reduction gains of digital technologies are evident in developing Asia, landlocked/island nations, coastal/non-island countries, and advanced economies, with broadband and internet access contributing to poverty reduction during the coronavirus disease (COVID-19) pandemic. Given the role of digital technologies in strengthening resilience, we call on policymakers to invest in and expand digital connectivity, particularly to vulnerable communities
New Zealand Plays 2025
No full textThe 2025 New Zealand Plays report is the 9th in a series of studies that we have published since 2010. The purpose of this research has been to provide evidence and encourage conversation about who among us plays video games, why we play, how we play and what we think of this dynamic and often breathtaking medium. For one-and-a-half decades, we have seen the rapid maturation of the video games audience. While the early reports in this series surprised many in our community that video games were so popular – and the typical player was an adult – today the reality that video games are not only popular, but that they are popular for everyone at every age has been well documented through this research. We have long argued that video games give rise to digital fluency. The digital economy is flourishing, if not because of video games creating capacity, then at least in part because they contribute. We have also argued that the technologies underpinning video games has been an important part of innovation, giving rise to new capabilities