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An exploratory study on virtual reality technology for fall prevention in older adults with mild cognitive impairment
Get PDFINTRODUCTION: Virtual Reality (VR) training has potential evidence for reducing the risks of falls of older adults with mild cognitive impairment (MCI). There are indications of a positive training effect of a cognitive-motor intervention method to improve the postural balance and cognition for safer walking. This study aimed to evaluate the training effects of VR training for reducing the risks of falls among older adults with mild cognitive impairment (MCI).METHODS: An experimental design was employed to evaluate how the participants attended a full-immersive VR Cave Automatic Virtual Environment (CAVE) training program. Fifty-five participants were randomly assigned to the VR group or the control group. The VR group received 16 training sessions over 8-10 weeks, while the control group received a non-VR falls prevention program. The primary outcome assessed any falls after the study, and the secondary outcomes assessed changes in cognition and executive function, walk speed and balance performances, and the psychological factor such as fear of falling relating to the risk factors of fall.RESULTS: The VR group showed significantly greater improvement than the control group in terms of measures of cognitive-motor performance across group and time interaction. However, there were inconsistent results in functional mobility and fall efficacy between the two groups.CONCLUSION: This study provides promising evidence on the VR CAVE training for reducing the risks of falls among older adults with MCI from Hong Kong. VR technology-based applications are an emerging area in current aged care and rehabilitation services.</p
Six tips when undertaking a curriculum framework review
No full textFor a curriculum framework to deliver for both students and educators, it must be regularly updated. Here are six things to remember when embarking on a framework review
The role of artificial intelligence in hotel operations: revolutionising efficiency
No full textThe hotel industry over the past recent years has been revived by AI innovations. These innovations have assisted the industry to survive tough times and overcome challenges. Hoteliers have managed to increase profitability by enhancing efficiency, and hence reducing costs and maximising revenue through integrating AI innovations into hotel operations. Reviewing the literature on the role of AI on hotel operations reveals that two key areas have been researched: robotics innovations and hotel revenue management systems. While AI innovations are very significant to the hotel industry, they are not perfect and have their own limitations. However, they are advancing fast and digital transformations are unavoidable for the future of the hotel industry. Investing in AI innovations reshapes hotels’ strategies and brand image and helps hoteliers develop a sustainable competitive advantage that allows hotels to expand and grow globally
Isolated and invisible:the barriers to implementing constructive resettlement approaches in two English young offenders institutions
Get PDFThe custodial estate for children aged 10–17 years across England and Wales faces a number of challenges. This article focuses on the perceptions of Resettlement Officers in two Young Offender’s Institutions (YOIs) in England on the challenges of their role: successfully reintegrating children from custody into the community using ‘Constructive Resettlement’ approaches. The findings will present a range of internal barriers encountered by Resettlement Officers that leave them feeling isolated, invisible and misunderstood. Finally, implications for future policy and practice will be considered.</p
The potential of virtual reality-based multisensory interventions in enhancing cognitive function in mild cognitive impairment: a systematic review
Get PDFBackground: This systematic review investigates the role of virtual reality (VR)-based multisensory cognitive training in cognitive function, executive function and wayfinding ability among people diagnosed with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Methods: The review was carried out using PRISMA guidelines. PubMed, Scopus, Embase, and Google Scholar were searched up from inception to February 2025 using terms related to MCI, AD, VR, and cognitive functions. Studies were included if they involved participants with MCI or early AD, used VR-based training, collected baseline data, and reported cognitive outcomes. Results: Nine studies with MCI were included, but no eligible studies focused on AD. Seven out of nine eligible studies in MCI reported significant improvements in global cognitive function (MoCA, CERAD-K, MMSE). Some studies showed improvements in executive function (EXIT-25, TMT-A/B, and SCWT), while others found no significant differences. One study reported improved depression/mental status (GDS, MOSES, QoL-AD). Just one study reported improvement in functional ability (IADL). One study reported enhanced cognition and reduced discomfort (SSQ). VR programs were generally well-tolerated, with no significant adverse events reported. Conclusions: VR shows promise for improving cognitive function in MCI. VR also showed potential benefits in executive function and psychological outcomes like depression and quality of life, though consistency varied.</p
Five actions to drive your career forward in the third space
No full textThird spaces professionals can often find themselves excluded from traditional academic promotion or career development opportunities. Here’s how to carve your own path
Towards a holistic understanding of digital innovation:a multidimensional approach
Get PDFThis study develops and empirically validates an integrative model explaining how firms achieve digital innovation through the interplay among digital strategy, absorptive capacity, digital technology deployment, and environmental dynamism. Drawing on the content-context-process-outcome framework, digital strategy provides the guiding content; absorptive capacity and environmental dynamism act as contextual enablers; and digital technology deployment functions as the central process driving innovation outcomes. Survey data from 250 Chinese firms were analyzed using partial least squares structural equation modeling (PLS-SEM) and contextualized and externally validated through cross-case and cross-industry validation. The findings reveal an inverted U-shaped relationship between digital technology deployment and innovation, challenging the linear assumption of prior research. While deployment is essential, overinvestment without strategic alignment leads to diminishing returns, underscoring the need for strategic coherence and absorptive alignment. Digital strategy and absorptive capacity directly and indirectly enhance innovation through digital technology deployment, while environmental dynamism amplifies the strategic-innovation linkage. Theoretically, the study contributes to the engineering management literature by advancing a holistic, dynamic, and nonlinear understanding of digital innovation as an optimization and orchestration process rather than a purely technological one. It offers a generalizable framework that strengthens integrative and system-oriented perspectives in engineering management research
Explainable DEA–ensemble approach with golden jackal optimization:efficiency evaluation and prediction for United States information technology firms
Get PDFThis study presents an integrated Data Envelopment Analysis (DEA) and ensemble learning framework optimized with the Golden Jackal Optimization (GJO) algorithm to evaluate and predict the efficiency of United States information technology firms. Both Constant Returns to Scale and Variable Returns to Scale models were applied to measure firm efficiency and compute scale efficiency, providing a clearer distinction between managerial and scale-related effects. Using data from 3940 firms over the period 2013 to 2023, a robustness test introducing ±20% random noise to a 10% random sample confirmed that the CCR model achieved stronger stability, with a correlation coefficient of 0.795 compared to 0.773 for the BCC model. Consequently, the CCR results were adopted as the basis for predictive modeling. DEA efficiency scores were predicted using six ensemble learners, including XGBoost, Gradient Boosting Regressor, AdaBoost, Extra Trees Regressor, Random Forest, and LightGBM, with GJO employed for hyperparameter tuning. The Gradient Boosting Regressor optimized with GJO achieved the best predictive performance, accurately reproducing the observed efficiency scores. SHAP and feature importance analyses revealed that Total Equity, Operating Income, and Total Assets were the most influential determinants of efficiency. This research contributes a scalable and interpretable approach to efficiency prediction, offering actionable insights for managers, investors, and policymakers in volatile financial markets.</p
Design and delivery of a holistic three-day post-COVID-19 psychological intervention for care staff in the UK as part of stage 2 health psychology training
Get PDFAs part of achieving Chartered status in Health Psychology in the UK one has to create an online intervention. This study showcases such an intervention to support care workers by addressing stress management, mindfulness, resilience, and sleep hygiene. The delivery of the intervention was via Microsoft Teams and it focused on a) psychoeducation, b) mindfulness, c) resilience-building, d) and peer support. The intervention assessments included the Perceived Stress Scale (PSS-10), Pittsburgh Sleep Quality Index (PSQI), Quality of life scale (EQ-5D), and the Visual Analog Mood Scale (VAS). The results demonstrated a reduction in stress and an improvement in sleep quality and mood; however no statistical significance in quality of life was observed. Qualitative feedback highlighted the benefits of psychoeducation, mindfulness training, and the buddy system. Staff reported a greater awareness over their stress, improved sleep hygiene and a sense of connection with colleagues. Despite the short duration the intervention was positively received, suggesting that structured targeted interventions can be beneficial for front-line care workers and can be created by small organisations. Future research should explore extending the intervention’s duration and incorporating follow-up support to enhance long-term effectiveness as well as training guidance for in-house teams.<br/
Explainable DEA–ensemble approach with golden jackal optimization:efficiency evaluation and prediction for United States information technology firms
Get PDFThis study presents an integrated Data Envelopment Analysis (DEA) and ensemble learning framework optimized with the Golden Jackal Optimization (GJO) algorithm to evaluate and predict the efficiency of United States information technology firms. Both Constant Returns to Scale and Variable Returns to Scale models were applied to measure firm efficiency and compute scale efficiency, providing a clearer distinction between managerial and scale-related effects. Using data from 3940 firms over the period 2013 to 2023, a robustness test introducing ±20% random noise to a 10% random sample confirmed that the CCR model achieved stronger stability, with a correlation coefficient of 0.795 compared to 0.773 for the BCC model. Consequently, the CCR results were adopted as the basis for predictive modeling. DEA efficiency scores were predicted using six ensemble learners, including XGBoost, Gradient Boosting Regressor, AdaBoost, Extra Trees Regressor, Random Forest, and LightGBM, with GJO employed for hyperparameter tuning. The Gradient Boosting Regressor optimized with GJO achieved the best predictive performance, accurately reproducing the observed efficiency scores. SHAP and feature importance analyses revealed that Total Equity, Operating Income, and Total Assets were the most influential determinants of efficiency. This research contributes a scalable and interpretable approach to efficiency prediction, offering actionable insights for managers, investors, and policymakers in volatile financial markets.</p
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