69238 research outputs found
Sort by
Exploring How Rheumatic Fever Is Portrayed on TikTok: A Descriptive Content Analysis
No full textTikTok is a popular social media platform offering educational opportunities for health issues such as rheumatic fever, which primarily affects 4-19-year-olds globally. This content analysis aimed to explore the type of rheumatic fever content available and popular on TikTok and the role that rheumatic fever representation may play in shaping public understanding and attitudes. The top 100 TikTok video posts under the hashtag #rheumaticfever were examined. Descriptive statistics were used to summarize video metrics and deductive thematic analysis enabled the coding of video content. The majority of TikTok users creating rheumatic fever content were patients or family members of people suffering from rheumatic fever (42%), followed by health professionals (30%). Forty-three percent of videos had negative connotations and personal stories were the most commonly coded type of video (42%). In terms of rheumatic fever content, symptoms (n = 59), medications/treatment (n = 37) and disease pathogenesis (n = 36) were the most common themes. Misinformation was identified in 3% of videos. This study provides a unique insight into who is making rheumatic fever-related content on TikTok and the primarily negative framing of narratives people are exposed to. There are opportunities for future health promotion strategies to focus on the gaps identified in this study, including information on where to seek health services, primordial prevention and stories of recovery
Reconceptualising student feedback agency from a social cognitive perspective
No full textStudent agency is a key feature in feedback practices. Student feedback agency is generally defined as students’ active engagement in the feedback process. Its conceptualisation has evolved from individualistic views, through unidirectional structure-agency perspectives, to more socially oriented approaches. However, this commentary argues that current conceptualisations remain limited, as they often regard student feedback agency as a static, one-way, and context-enabled construct. To address these limitations, we propose a reconceptualisation informed by social cognitive theory. This expanded model is grounded in Bandura’s core features of human agency and the principle of triadic reciprocal causation. We reconceptualise student feedback agency as students’ proactive engagement with feedback, shaped by the dynamic interplay of three dimensions: personal, behavioural, and environmental. Drawing on this framework, we offer suggestions for future research
Neonatal Nutrition and Brain Structure at 7 Years in Children Born Very Preterm
No full textImportanceNeonatal protein intake following very preterm birth has long lasting effects on brain development. However, it is uncertain whether these effects are associated with improved or impaired brain maturation.ObjectiveTo assess the association of neonatal protein intake following very preterm birth with brain structure at 7 years of age.Design, setting, and participantsThis cohort study involved children born very preterm before or after a change in neonatal intensive care unit nutritional protocol that increased protein intake at the National Women's Hospital in Auckland, New Zealand. The children completed magnetic resonance imaging (MRI) scanning at 7 years. There were 128 children who were initially eligible. MRI data were ineligible for analysis if excessive head motion or clinical brain abnormalities were present. Data were collected from July 2012 to January 2016, and data analysis took place from January 2017 to March 2024.ExposureNeonatal intensive care unit nutritional protocol. Those who were born before the protocol change took place (July 2005 to December 2006) were in the old protocol group, while those who were born after the protocol change (January 2007 to October 2008) were in the new protocol group. Observers were blind to participant grouping.Main outcomes and measuresAll actual enteral and parenteral intakes of protein, fat, energy, and breast milk for days 1 to 7 and days 1 to 14, and growth velocity to postnatal day 28 were calculated for each infant. Preplanned outcomes were group comparisons between regional brain volumes and diffusion parameters of major white matter tracts along with analyses with both groups combined exploring associations of nutrition with brain metrics.ResultsData from 99 children were analyzed, including 42 in the old protocol group (26 female [55%]; mean [SD] gestational age at birth, 27 [2] weeks) and 57 in the new protocol group (27 female [47%]; mean [SD] gestational age at birth, 26 [2] weeks). Protein intake differed between the groups at both 7 days (old protocol: mean [SD] intake, 17 [2] g/kg-1; new protocol: mean [SD] intake, 21 [2] g/kg-1) and 14 days after birth (old protocol: mean [SD] intake, 41 [6] g/kg-1; new protocol: mean [SD] intake, 45 [7] g/kg-1). The new protocol group had smaller brain volume as a percentage of intercranial volume than the old protocol group (mean [SD], 80% [4%] vs 86% [7%]) but absolute brain volumes were similar. The new protocol group had significantly thinner lateral occipital and lateral parietal cortices than the old protocol group. With both groups combined, those with greater protein, fat, energy, and breast milk intake had more mature diffusion tensor metrics (higher fractional anisotropy and less diffusion) across multiple tracts, although this finding did not reach statistical significance for every tract.Conclusions and relevanceIn this cohort of children born very preterm, children with greater neonatal protein intake had a more mature profile of brain metrics assessed with MRI at 7 years of age. These results contribute to the ongoing evaluation of optimal nutrition for infants born very preterm and suggest that the protein intake experienced by the new protocol group may promote brain maturation in a way that is still observable at 7 years of age
The roles of immuno-modulator treatment and echocardiographic screening in rheumatic fever and rheumatic heart disease control: research from Aotearoa, New Zealand
No full textThis review summarises advances in research from Aotearoa, New Zealand (NZ) that have potential to reduce the inequitable distribution of acute rheumatic fever (ARF) and rheumatic heart disease (RHD). ARF incidence and RHD prevalence are unacceptably inequitable for Māori and Pacifica. Recent qualitative research has demonstrated mismatches between the lived experience of those with ARF/RHD and health service experience they encounter. NZ-led research has contributed knowledge to all stages of disease prevention (primordial, primary and secondary) and for tertiary management. Modifiable risk factors for ARF are racism across health sectors, household crowding, barriers to accessing primary health care, a high intake of sugar-sweetened beverages and preceding sore throat and skin infections. NZ research has evaluated the impact of a large-scale sore throat management programme and Streptococcal A vaccine development. This review highlights two programme domains of research by the authors that have the potential to reduce the burden of chronic RHD: firstly, effective immunomodulation of ARF to reduce the severity of carditis, with current clinical trials of hydroxychloroquine in NZ; secondly, the development of echocardiographic screening of previously undetected RHD. This now meets criteria for an effective screening test and has potential translation for disease control of RHD
Investigating the link between oral health conditions and systemic diseases: A cross-sectional analysis
No full textThis study investigates the association between oral health issues, specifically periodontitis and dental caries, and systemic health conditions such as diabetes and hypertension. The goal is to determine the strength of these associations using statistical analysis. We conducted a cross-sectional study utilizing the National Health and Nutrition Examination Survey (NHANES) data from 2017-2020, focusing on 13,772 adults with complete data on oral and systemic health variables. Oral health indicators were periodontitis and dental caries, while systemic health variables included diabetes and hypertension. The statistical analysis involved Cramer's V to assess the strength of associations between these health conditions. The study found statistically significant associations between oral and systemic health conditions. There was a moderate association between periodontitis and diabetes (Cramer's V = 0.14) and a moderate association between dental caries and hypertension (Cramer's V = 0.12). The results underscore the interconnected nature of oral and systemic health, suggesting that poor oral health can be an indicator of broader health issues. These associations could guide integrated health care strategies, emphasizing the need for dental health evaluations in patients with diabetes and hypertension
Teacher conceptions of assessment and feedback predicting formative feedback practices: Helping students to not ignore improvement-oriented feedback
No full textTeachers’ formative feedback provides motivational and cognitive support for student engagement in learning and raises their achievement. Because feedback arises from assessment, teacher conceptions of both assessment and feedback matter to how feedback is practised. This study determines how teacher conceptions of assessment and feedback are linked to each other and to self-reported practices in a repeated measures survey 18 months apart. All factors in the Swedish Teachers Conceptions of Assessment inventory predicted all six Conceptions of Feedback, which fully mediated influence of assessment conceptions on teachers’ self-reported formative feedback practices. Two conceptions of feedback (i.e., feedback improves learning, and students ignore feedback) were important predictors of teachers' practice, and these feedback conceptions were predicted by the corresponding conceptions of assessment (i.e., it improves learning and it is ignored by students). The results imply that teacher formative feedback practices depend on an improvement-oriented conception of assessment as a prior belief
National, Regional, and Local Scale Sea Level Rise Risk to Coastal Archaeological Sites in Aotearoa/New Zealand Te Mōrearea o Te Rewanga o Te Moana ki Ngā Wāhi Whaipara i Ngā Takutai o Aotearoa
No full textClimate change-induced sea-level rise (SLR) poses a substantial threat to coastal cultural heritage sites worldwide. This thesis investigates the impact of SLR on coastal archaeology in Aotearoa, utilising a multi-scalar analytical framework that integrates geomorphology, archaeology, and mātauranga (Indigenous knowledge). It explores the vulnerabilities of archaeological sites to erosion and inundation, contributing to the comprehensive insight and governance of heritage sites under climate stress.
At the national scale, a GIS-based assessment is conducted to quantify archaeological sensitivity to SLR, determining the possible scale of impact across diverse landscapes. The examination furnishes a foundational understanding of what is at risk, laying the groundwork for targeted regional studies.
The regional analysis applies a coastal erosion hazard zone (CEHZ) methodology, to determine future risks to archaeological sites from coastal erosion driven by SLR. It integrates these insights with management strategies, advocating for dynamic adaptive policy pathways (DAPP) as a solution for at-risk heritage sites. This methodology permits for responsive and flexible management practices that can adjust to evolving coastal dynamics.
At the local scale, this research combines mātauranga with scientific methods in a case study of a prograded barrier system. This spatiotemporal study shows how local communities, heritage sites, and scientific research intersect, enabling the salvage of archaeological information before it is irretrievably lost. This examination not only underscores the immediate threats to specific sites but also serves as a microcosm of the national and regional challenges.
Overall, this thesis contributes to the literature around combining geomorphological insights, archaeological data, and Indigenous knowledge to effectively identify and manage at-risk coastal heritage in Aotearoa. It contributes to the broader discourse on adaptive, culturally-integrated heritage management practices, advocating for strategies that solve the challenges of climate change. This research coincides with global calls for a multidisciplinary approach to heritage management that accommodates both cultural values and scientific realities in the context of climate change
Scaling Up Urban Nature Through Equitable Land Use Planning: Lessons from Australia on Community-Driven and Socially Responsible Climate Action
No full textThis paper explains how community-driven and socially responsible nature-based solutions (NbS) can shape transformative urban land use planning for climate action in Australia. Through a detailed analysis of four case studies in Sydney, Canberra, Brisbane, and Logan (Brisbane Metropolitan Area), the research shows how local communities and social enterprises embed principles of social equity, ecological stewardship, and the Indigenous Australian’s notion of Caring for Country (or the reciprocal relationships between people and land) in climate action, and reinterpret land not as a commodity, but as a site of ecological, cultural, and social significance. These practices demonstrate how NbS can support inclusive and locally grounded climate responses in cities and reveals that current land use planning systems often lack the flexibility, adaptability, and recognition necessary to respond to and support such practices. The paper highlights the need to reframe the assumptions regarding scaling up climate action and planning reforms that enable secure land access, clear guidelines for NbS in cities, and co-governance with community actors. Importantly, the paper underscores the risk of green gentrification, wherein greening efforts may contribute to displacement and exclusion if they’re not carefully managed. Ultimately, the findings advocate for a reimagined planning paradigm that places equity, Indigenous knowledge systems, ecological restoration, and community agency at its core, to achieve truly transformative climate action in Australian cities
Developing Low-Thrust Gravity Assist Trajectory Planning Tools and Methods for Saturn Orbiters
No full textCubeSats have great potential as interplanetary explorers. To enable their success on this front, small satellites will need to rely on low-thrust propulsion and gravity assists. The Tool for Initial Low-Thrust Design (TILTD) was created by Darcey Graham to model low-thrust gravity assist trajectories. Previous work using this code adapted it to plan moon tour trajectories in the Saturnian system.
To make TILTD a more realistic tool, a list of trajectory planning constraints ranked by impact on navigation was developed by reviewing the literature and consulting with Jet Propulsion Laboratory (JPL) navigation engineer Duane Roth. The list identifies spacecraft attitude requirements, inclination and altitude requirements for scientific objectives, and non-gravitational forces such as solar radiation pressure as the three most important outstanding factors to implement into the code. The Cassini spacecraft's navigation methodology was studied with the intent of applying it to future work using TILTD to plan Saturnian moon-tour trajectories.
TITLD was tested on the ARDC Nectar Research Cloud and NeSI's Mahuika cluster. The Nectar Virtual Machine proved to be slower than running the code on the author's laptop. Mahuika was able to reduce TILTD runtimes by 55% with the use of additional CPUs, and by up to 88% after the code was overhauled to support parallel computing. Major improvements were made to the code's ease of use with the addition of input configuration files for each trajectory and the combination of multiple functions with similar content into a single, user-customizable function. The Titan → Enceladus → Enceladus (TiEE) and Titan → Dione → Enceladus (TiDE) trajectories from Senturia (2024) were successfully reproduced, indicating that the updates made to the code did not cause any undesirable changes in its outputs, though an error persistent from the original version of TILTD was discovered that allows flybys to pass through a flyby body. Twenty-five low-fidelity solutions for a Titan → Dione → Enceladus → Tethys (TiDETe) trajectory were found over 20 runs of TILTD's updated 'lofi_search' code
Utilizing Specialized Graph Partitioning and Adaptive GNNs: A Comparative Study for Large-Scale Traffic Forecasting
No full textAs urban areas grow and transportation networks become increasingly complex, accurate
large-scale traffic forecasting is essential for effective Intelligent Transportation
Systems (ITS). Traditional statistical and machine learning approaches often fail to
capture the spatial-temporal patterns in large-scale transportation data, while conventional
deep learning methods struggle with non-Euclidean network structures. Graph
Neural Networks (GNNs) address these challenges by modeling road networks as a
graph, resulting in improved forecasting.
This thesis builds on the state of the art in large-scale traffic prediction. This is
done by integrating an Adaptive Graph Convolutional Recurrent Network (AGCRN)
with a high-quality, domain-specific graph partitioning tool - the Buffoon-optimized
Karlsruhe High Quality Partitioning (KaHIP). Building on the limitations observed
in established models like the Diffusion Convolutional Recurrent Neural Network
(DCRNN), AGCRN introduces node-adaptive parameters to more effectively learn
localized, evolving traffic patterns. To overcome computational challenges associated
with large networks, we employ specialized partitioning frameworks. While graph partitioners
like METIS has been the standard choice, we demonstrate that the Buffoonoptimized
KaHIP - framework produces higher quality partitions, resulting in higher
forecasting accuracy.
Tests conducted on a California highway network dataset show that the AGCRNKaHIP
integration outperforms DCRNN-METIS and baseline statistical methods.
The integration delivers lower prediction errors and more stable forecasts. These results
highlight the value of using domain-specific partitioning strategies and adaptive
GNN architectures for large-scale traffic forecasting