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Medication Adherence and its Associated Factors and Glycemic Control in Older Outpatients with Type 2 Diabetes Mellitus in Vietnam
No full textObjective: This study aims to address the prevalence and determine associated factors of medication adherence and glycemic control among older patients with type 2 diabetes mellitus (T2DM) in Vietnam. Methods: This study was a cross-sectional study conducted from July to December 2023 in Hanoi. Participants living with T2DM aged 60 years and over were included in this study. Data were collected from medical records, functional mobility measurement, and face-to-face interviews. Medication nonadherence was defined by Morisky Medication Adherence-8, and poor glycemic control was evaluated by HbA1c indicator. Results: In total, 587 participants were enrolled in the study, with a mean age of 72.9 (SD = 7.5) years. The prevalence of medication nonadherence was 23.9% and poor glycemic control was 71.4%. In the multivariate logistic regression analysis, instrument activity daily living dependency (OR: 2.44; 95% CI 1.3–4.6), low physical activity (OR: 1.69; 95% CI 1.06– 2.67), having depression symptoms (OR: 1.76, 95% CI 1.07–2.9), and poor diabetes knowledge (OR: 2.44; 95% CI 1.53–3.9) were significantly associated with medication nonadherence. Moreover, age (OR: 0.97; 95% CI 0.94–0.99), having diabetes ≥ 5 years (OR: 2.3; 95% CI 1.43–3.7), and having more diabetes complications (OR: 1.28; 95% CI 1.01–1.61) were significantly associated with poor glycemic control. Conclusion: This study highlights the significant burden of medication nonadherence and poor glycemic control among older adults with T2DM in Vietnam, identifying key factors such as depressive symptoms, low physical activity, and inadequate diabetes knowledge.</p
Lifting the veil:probing altered visual perception in derealization
No full textDuring an acute episode of depersonalization/derealization (DP/DR), people report a complex and idiosyncratic change in their perceptual experience. Specifically, derealisation describes the experience of detachment from the external world and altered visual perception in which the surroundings look faded, foggy, or dream-like. Whilst some have argued that there may not be genuine perceptual changes in derealization, this proposal is yet to be tested empirically. Thus, we set out to investigate the potential perceptual changes in derealization. In this Registered Report, we conducted two online experiments to reveal the impact of DP/DR symptoms measured via the state version of the Cambridge Depersonalisation Scale (CDS) on how people evaluate (Experiment 1, N= 200, CDSstate mean: 32.43 ± 29.94 SD) and adjust (Experiment 2, N= 125, CDS-state mean: 29.38 ± 30.47 SD) naturalistic scene images with different levels of saturation and contrast. Participants were asked to rate how real the presented images look compared to their everyday experience (in Experiment 1) and to adjust the contrast or saturation level of images to match their everyday visual experience (in Experiment 2). We tested the effect of CDS-state scores on these subjective ratings via model comparison with Bayes Factors. In both experiments, we found strong evidence supporting the null models, suggesting that DP/DR symptoms did not affect realness ratings or vividness adjustments. These results provide empirical support for theories suggesting that self-reported altered vividness experience in derealization does not reflect genuine perceptual changes, instead they signify the (meta-)cognitive interpretation of these experiences. We discuss pros and cons of the current research practices when assessing derealization and highlight key avenues for the future investigation.</p
Communication strategies used by Australian residential aged care staff with residents with limited English proficiency
No full textGlobal migration and an ageing world population have increased demand in Residential Aged Care (RAC) services for older adults that do not speak the national language. A range of strategies may help overcome this linguistic barrier, but the frequency of use of different strategies is currently unknown. This study therefore aimed to profile the communication strategies currently used by staff in Australian RAC homes when interacting with residents with Limited English Proficiency (LEP).A cross-sectional survey was conducted with 52 service and care staff in Australian RAC homes who had interacted with residents with LEP from March – September 2023. Participant demographics, frequency and type of interactions, and use and perception of communication strategies were collected and analyzed using descriptive statistics.Simplified spoken English, non-verbal communication, and using words in residents’ languages were used at least weekly by most respondents for 8 of 10 care interaction types. Most participants had never used professional interpreters despite a willingness to use them in the future and 14 participants reported using Google Translate, perceiving it as an accurate and useful translation tool.The significant reliance on simplified English, non-verbal communication and words or phrases in residents’ preferred languages and underutilization of professional interpreters, contrary to industry guidelines, creates a significant risk of miscommunication when addressing complex care needs with residents. Further work is needed to raise awareness of underutilized and effective communication tools including free translation and interpretation services within Australian RAC homes to improve the quality of care for residents with LEP
Washington, Paris, Dublin, New Delhi? An analytical tour through potential republican constitutional models for headships of state for Australia and other Commonwealth realms
No full textWith the accession of a new Monarch in the United Kingdom, Commonwealth realms now find that they have a new head of state. In some realms, the end of the long and iconic reign of Elizabeth II may revive discussion of whether those states may wish to consider having their own heads of state, albeit remaining within the Commonwealth. If so, debate will focus on the historically developed republican models – presidential, semi-presidential and prime ministerial. The third model is notable for the separation of the roles of head of state and head of government. Yet the models may intersect, particularly where popular election is instituted for a ceremonial head of state leading to a heightened status. The ceremonial head of state will also retain key reserve powers and their role in proroguing the Parliament was recently considered in the UK Supreme Court decision of Miller v The Prime Minister [2019] UKSC 41. How monarchical reserve powers translate into powers of a republican head of state, and how such head of state is appointed, are key issues in the republican debate in Australia as exemplified in the republican models that have been postulated there and are here also considered
Governing University Living Labs for sustainability transformations:insights from 18 international case studies
No full textIn recent years, scholarly debate has grown around a perceived gap between societal impact rhetoric and the support structures for interdisciplinary and applied research, education, and innovation in universities. University Living Labs (UniLLs) provide a window into this relationship as they transcend disciplinary boundaries and linear modes of engagement to enable real-world experimentation and learning in response to societal challenges such as sustainable development. However, few studies examine the institutional contexts in which UniLLs operate, thus limiting our understanding of universities’ capacity for sustainability experimentation. This study examines how the institutional structures, cultures, and practices of universities enable or constrain the governance of sustainability-oriented UniLLs. Our study is grounded in the practical work of organising and conducting UniLLs, drawing on interviews with 39 academics and practitioners involved in UniLLs at 18 universities in Australia, Brazil, Canada, Germany, France, The Netherlands, Singapore, the UK, and the USA. Our research findings demonstrate that (1) UniLLs are enabled by the institutionalisation of sustainable development agendas, and the relational and discursive work of key university staff. (2) UniLLs are often limited in scope and longevity by a project logic and work against entrenched academic and operational organising structures and corporate logics. (3) Some UniLLs overcome these barriers by leveraging institutional power and mobilising resources to embed UniLL governance in university-wide structures. We present practical enabling processes for institutionalising UniLLs in universities demonstrated by the cases and reflect on the university governance paradigm for advancing a transformative impact agenda.</p
Breaking human dominance:Investigating learners' preferences for learning feedback from generative AI and human tutors
No full textUnderstanding learners' preferences in educational settings is crucial for optimizing learning outcomes and experience. As artificial intelligence (AI) becomes increasingly integrated into educational contexts, it is crucial to understand learners' preferences between AI and human tutors to support their learning. While AI demonstrates growing potential in education, the phenomenon of algorithm aversion, which is a tendency to favour human decision making over algorithmic solutions, requires further investigation. To explore this issue, an experiment involving 114 university students was conducted to measure learners' preferences for different feedback sources before and after exposure to one of four conditions: no feedback, human tutor feedback, ChatGPT feedback through a free-dialogue user interface, and AI-powered writing analytics tool feedback through a structured interface. Our results revealed a strong initial preference for human tutors. However, the post-task analysis showed an important nuance. While the general preference for human tutors persisted, learners' preference towards the free-dialogue interface (ChatGPT 4.0) of ChatGPT increased, whereas the structured AI interface (AI-powered writing analytics tool) reinforced the preference for human tutors. These findings offer theoretical and practical contributions by extending algorithm aversion theory to educational contexts and demonstrating that appropriate interaction design can mitigate this aversion. The success of free-dialogue interfaces suggests that overcoming algorithm aversion may depend more on creating natural, flexible interaction experiences than purely technical optimization. However, we must also consider that increased preference for AI tools, particularly those with more engaging interfaces, may potentially lead to over-reliance and metacognitive laziness among learners, highlighting the importance of balancing technological support with the development of independent learning skills. Practitioner notes What is already known about this topic? Algorithm aversion exists across various contexts where individuals tend to prefer human over algorithmic decision-making. The introduction of generative AI brings new possibilities for AI-supported learning. What this paper adds? In academic writing tasks, learners show strong initial preference for human tutors over Generative AI feedback. Strong initial preference for human tutors persists even after exposure to generative AI feedback. Different interaction designs lead to divergent preference patterns: Free-dialogue interface increases preference for AI feedback, structured interface reinforces preference for human tutors. Implications for practice and/or policy Algorithm aversion in educational contexts can be mitigated through appropriate interaction design, particularly through natural dialogue interfaces. Design AI educational tools with back-and-forth, conversational interfaces to reduce algorithm aversion.</p
Unravelling public preferences for the use of Artificial Intelligence mobile health applications in Australia
No full textObjectives: To explore public opinion on the factors that drive the use of artificial intelligence (AI) mobile health (mHealth) applications for heart disease and mental health, with a particular emphasis on diagnostics and virtual health assistance (VHA). Methods: This study adopted a discrete choice experiment to investigate the preferences of the Australian general public for heart disease and depression. A total of 5 attributes were considered, including anonymized data sharing, human-AI interaction, accuracy of AI results, explanation of results provided by AI, and funding source. Mixed logit and latent class logit models were used to investigate potential preference heterogeneity among respondents. Results: Respondents (n = 1176) showed that AI accuracy was the most crucial factor in AI mHealth applications, followed by human doctor-AI interaction. Preferences for not sharing anonymized data were reported in depression, whereas there were no statistically significant results for heart disease. Results explained by AI and funding source were generally less important. Those who expressed fear of AI were less likely to opt for AI diagnostics and VHA in heart disease. Older adults (60+) were less likely to use AI in both health conditions, whereas younger adults (18-29) were more inclined to use VHA for heart disease. Conclusions: It is evident that beyond the technical feasibility of AI applications, there are nuanced differences in public preferences for AI mHealth applications in Australia. Understanding factors leading to these discrepancies would be valuable for ensuring safe and equitable acceptance and harnessing the full potential of AI in healthcare delivery and outcomes.</p
SAFE:A Novel Approach For Software Vulnerability Detection from Enhancing The Capability of Large Language Models
No full textSoftware vulnerabilities (SVs) have emerged as a prevalent and crucial concern for safety-critical systems. This has spurred significant advancements in utilizing AI-based methods, including machine learning and deep learning, for software vulnerability detection (SVD). While AI-based methods have shown promising performance in SVD, their effectiveness on real-world, complex, and diverse source code datasets remains limited in practice. To tackle this challenge, in this paper, we propose a novel framework that enhances the capability of large language models to learn and utilize semantic and syntactic relationships from source code data for SVD. As a result, our proposed SAFE approach can enable the acquisition of fundamental knowledge from source code data while adeptly utilizing crucial relationships, i.e., semantic and syntactic associations, to improve the effectiveness of solving the SVD problem. The rigorous and extensive experimental results on three real-world challenging datasets (i.e., Devign, ReVeal, and D2A) demonstrate the superiority of our approach over eight effective and state-of-the-art baselines. In summary, on average, our SAFE approach achieves higher performances from 4.79% to 11.57% for F1-measure and from 16.93% to 26.24% for Recall compared to the baseline methods across all the datasets used.</p
Performances of emergent masculinities amongst rickshaw drivers in Nepal
No full textThis paper provides insights into emergent masculinities amongst a group of cycle and auto rickshaw drivers in Dhangadhi, far-west Nepal. The main focus of this paper is to explore various Janajati (Indigenous) masculinities as they are changing as a consequence of both moving to a city to work as rickshaw drivers along with automation within the rickshaw occupation. Cycle rickshaw driving had profound implications both for the bodies and masculinities, with tensions emerging between the performances of masculinity expected and encouraged within rickshaw driving and the bodies of the men who are rickshaw drivers. These associations are being reconfigured through the introduction of automated rickshaws, something that is a unique focus of this paper. The process of automation also disrupted the occupation of rickshaw driving being a largely male occupation. Ultimately, this paper explores the implications of automation for gendered associations within certain occupations.</p
