50716 research outputs found
Sort by
Profiles of fraction knowledge in first grade and their relation to cognitive and mathematical skills
No full textLatent profile analysis was used to examine variation in early fraction knowledge among first graders (N = 204; Mage = 6.68 years) across nonsymbolic and symbolic representations. Three distinct profiles of fraction understanding emerged. Profile 1 exhibited strong nonsymbolic knowledge, Profile 2 demonstrated similarly strong knowledge, except for weaker performance in nonsymbolic equivalence, and Profile 3 showed generally limited understanding across most areas. However, by the end of first grade, children initially identified as Profile 2 performed comparably to those in Profile 1 on measures of equivalence. Additionally, children in both Profiles 1 and 2 showed stronger cognitive skills and higher year-end mathematics achievement than those in Profile 3. These findings suggest that understanding of nonsymbolic equivalence may develop over the course of first grade in children who otherwise demonstrate strong foundational fraction knowledge, so that an initial relative weakness in that area is not concerning
Modelling factors associated with the probability of seeking traditional care after dog bites in Sierra Leone
Get PDFEvidence suggests a rising incidence of dog bites in Sierra Leone despite ongoing efforts to prevent rabies. However, little is known about the factors influencing the decision to seek medical care following a dog bite. To address this gap, we developed a probabilistic model to examine factors associated with the likelihood of seeking traditional care in Sierra Leone. Among the 2558 respondents who completed the survey, 31 % (782/2558) indicated that they would seek traditional care after a dog bite. The posterior distributions of our model estimates indicated that the probability of seeking traditional care was higher among respondents with lower levels of education, those residing in rural areas, individuals lacking knowledge about rabies virus transmission and its hosts, and those who owned vaccinated dogs. Conversely, respondents living in locations with a livestock officer or veterinary establishment had lower odds of seeking traditional remedies compared with those uncertain about access. We observed a negative relationship between the percentage of health facilities and the probability of seeking traditional care, with higher percentages associated with a decreased likelihood of seeking traditional remedies. We also found regional variation in the probability of seeking traditional care. Respondents in the Eastern and Western Area were less likely to seek traditional remedies than those in the Northern and Southern Provinces. These findings highlight the need for targeted educational campaigns to raise awareness about rabies and the importance of timely medical care after exposure. Improving healthcare access in rural areas and fostering collaboration with traditional healers are also essential for reducing reliance on traditional care and strengthening rabies prevention and control efforts
MIP-GAF: A MLLM-annotated Benchmark for Important Person Localization and Group Context Understanding
No full textEstimating the Most Important Person (MIP) in any social event setup is a challenging problem mainly due to contextual complexity and scarcity of labeled data. Moreover, the causality aspects of MIP estimation are quite subjective and diverse. To this end, we aim to address the problem by annotating a large-scale `in-the-wild' dataset for identifying human perceptions about the `Most Important Person (MIP)' in an image. The paper provides a thorough description of our proposed Multimodal Large Language Model (MLLM) based data annotation strategy, and a thorough data quality analysis. Further, we perform a comprehensive benchmarking of the proposed dataset utilizing state-of-the-art MIP localization methods, indicating a significant drop in performance compared to existing datasets. The performance drop shows that the existing MIP localization algorithms must be more robust with respect to `in-the-wild' situations. We believe the proposed dataset will play a vital role in building the next-generation social situation understanding methods. The code and data is available at https://github.com/surbhimadan92/MIP-GA
The effect of anti-pronation and anti-supination taping on neuromuscular control in recreational athletes with Achilles Tendinopathy:A randomized controlled cross-over trial
No full textObjectives: To investigate the effects of different directions of athletic taping on neuromuscular control of the lower limb in recreational athletes with Achilles tendinopathy (AT). Design: Crossover Study. Setting: Functional assessment laboratory. Participants: Thirty recreational athletes with AT. Main outcome measures: Participants were randomly treated with anti-pronation taping, anti-supination taping, or no-taping. Under different taping conditions, neuromuscular tests were performed in random order: ankle proprioception Active Movement Extent Discrimination Assessment (AMEDA), Weight-Bearing Lunge Test (WBLT), single leg hop test, figure-of-eight hop test and Lower Extremity Functional Test (LEFT). Results: Compared with no-taping, both anti-pronation taping and anti-supination taping significantly improved AMEDA proprioception test scores (p < 0.001,ηp2 = 0.466), figure-of-eight hop performance (p < 0.001,ηp2 = 0.307), unilateral LEFT scores (p < 0.001,ηp2 = 0.448), and may reduce risk of lower limb injury in recreational athletes with AT (p < 0.001,ηp2 = 0.432). Taping significantly reduced WBLT values (p < 0.001,ηp2 = 0.259) but had no significant effect on single leg hop test scores (p = 0.139). Importantly, no difference between the two taping conditions was observed. Conclusions: Both directions of athletic taping were equally effective in improving ankle proprioception, lower extremity functional performance, and reducing the risk of injury in athletes with AT, but had no significant effect on lower limb explosive strength and were associated with significantly reduced ankle dorsiflexion.</p
Do fluctuations in oestradiol and progesterone across the menstrual cycle affect mechanical stiffness in female athletes?
No full textObjectives: This exploratory study investigated the effect of fluctuations in sex hormones, oestradiol and progesterone, during the menstrual cycle, on mechanical stiffness, in naturally menstruating females and hormonal contraceptive users. Design: Observational, within subjects. Methods: Participants were 24 female (18–29 years) National Rugby League Indigenous Women's Academy players. At three phases of the menstrual cycle (early-follicular, late-follicular and mid-luteal), venous blood samples (oestradiol and progesterone) were collected. To quantify mechanical stiffness (vertical, leg and hip, knee, and ankle joint) analogue and co-ordinate data were collected, whilst participants completed three drop jumps, landing on two force plates. Trajectory and analogue data were reconstructed, labelled, and filtered in Vicon Nexus software. A linear mixed model was used to determine if there were significant interactions between hormone concentrations and measures of mechanical stiffness. Results: Ankle joint stiffness was significantly positively associated with oestradiol and progesterone concentration (p = 0.006, p = 0.020, respectively). Knee joint stiffness and leg stiffness were positively associated with oestradiol concentration (p = 0.009, p = 0.006, respectively), but not progesterone concentration. Hip joint and vertical stiffness were not significantly associated with either hormone. Conclusions: Female rugby league players have significantly higher ankle joint, knee joint and leg mechanical stiffness when oestradiol was highest, typically during Phase-2 of the menstrual cycle. It is possible that dynamic stiffness of the lower limb joints acts as a protective mechanism. Future research should confirm this relationship and examine interventions to address changes in athletes' mechanical stiffness across the menstrual cycle in order to enhance performance and injury prevention.</p
Assessing the feasibility of adapting a nursing questionnaire for evaluating patient safety education in pharmacy
No full textAbstractBackground: Understanding pharmacy students’ views on patient safety learning during clinical placements is vital for addressing educational gaps and promoting safe practices. The Patient Safety in Nursing Education Questionnaire (PaSNEQ) assesses students’ perceptions of patient safety education. Objective: To assess PaSNEQ for evaluating pharmacy students’ perceptions of patient safety education during placements. Methods: In a mixed-methods approach, post-clinical placement students adapted PaSNEQ, measuring perceptions of patient safety learning. Focus groups of four participants explored their experiences. Data were analysed for reliability and consistency through thematic analysis. Results: The adapted PaSNEQ showed strong internal consistency and was feasible. Participants reported frequent discussions about patient safety with supervisors and a supportive safety environment. However, 55% lacked experience in reporting safety incidents. Focus group revealed perceived gaps in structured patient safety practices and inconsistencies in their inclusion across placements. Students emphasised the importance of hands-on experience and systematic patient safety learning. Conclusion: The adapted PaSNEQ is reliable for assessing pharmacy students' perceptions. Students recognised the importance of patient safety education and desire more structured, experiential learning, particularly in incident reporting. Integrating tools like the PaSNEQ into pharmacy education can help educators identify gaps, support curriculum development, and better prepare students for pharmacy practice
Integration of fNIRS and Machine Learning for Identifying Parkinson's Disease
No full textParkinson's disease (PD) is a neurodegenerative disorder where early diagnosis is crucial for effective management. However, current diagnostic methods are often invasive or delayed, hindering early intervention. This study evaluates the effectiveness of combining functional near-infrared spectroscopy (fNIRS) with machine learning to distinguish individuals with PD from age-matched controls.Data were collected using fNIRS from 28 people with PD and 32 age-matched controls while performing the Timed Up and Go (TUG) test under three conditions: simple TUG, cognitive dual-task TUG, and motor dual-task TUG. Changes in cerebral blood oxygenation in the prefrontal cortex (PFC) were analysed using four machine learning models: Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), and Extreme Gradient Boosting (XGB), along with statistical analyses. Two feature selection models identified key features and channels for differentiating PD from controls.The SVM model achieved the highest accuracy (0.85 0.35) in distinguishing PD from CG. Feature selection and statistical analysis showed that dual-task activities were more effective than simple tasks for distinguishing PD from CG. Specific PFC subregions exhibited distinct activation patterns, which could serve as potential biomarkers for PD detection. Combining fNIRS with machine learning shows promise for PD diagnosis, with dual-task activities enhancing accuracy. Further investigation into PFC subregion behaviour could reveal stronger biomarkers
Validating adverse events in administrative healthcare data in ireland:a retrospective chart review study
Get PDFBACKGROUND: Pneumonia, urinary tract infections, pressure ulcers and delirium are adverse events that affect older inpatients. Accurate administrative data are key to improving patient safety and healthcare quality. The aim of the study was to validate Hospital In-Patient Enquiry (HIPE) data on the occurrence of pneumonia, urinary tract infections, pressure ulcers and delirium in older patients discharged from an acute hospital in Ireland through retrospective chart review.METHODS: A cohort of one thousand randomly selected admissions of inpatients aged over 65 from a university, tertiary hospital in 2022 were reviewed using a two-stage retrospective chart review. The researchers, healthcare professionals and patient representatives co-produced a study-specific chart review protocol and data collection instrument. HIPE data were validated by comparing the chart review data to the HIPE data. Since HIPE only codes the presence of the respective adverse event once, the comparisons between the HIPE data and the chart review data were carried out at admission level.RESULTS: Of the 1,000 admissions reviewed, 231 (23.1%) contained at least one adverse event. At event level, 373 adverse events were identified including 133 pressure ulcers in 71 admissions, 101 delirium episodes in 100 admissions, 84 pneumonia episodes in 79 admissions and 55 urinary tract infections in 52 admissions. Of the 302 adverse events found in chart review on admission level, 96 (31.8%) of these were coded in the HIPE data and flagged by the Hospital Acquired Diagnosis indicator. Compared with chart review data, the overall sensitivity of the administrative data was low, and the specificity was high. The positive predictive values varied, and the negative predictive values were generally high. In HIPE data, 42 adverse events were found that were not identified in the chart review.CONCLUSIONS: The results demonstrate that HIPE data may not accurately represent these specific adverse events as experienced by older patients. Improving the accuracy of these data may facilitate benchmarking of adverse events across hospitals and countries and provide opportunities for improvements in patient safety.</p
Physico-Chemical Characterisation of Particulate Matter and Ash from Biomass Combustion in Rural Indian Kitchens
Get PDFIn developing countries, indoor air pollution in rural areas is often attributed to the use of solid biomass fuels for cooking. Such fuels generate particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO2), polyaromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). PM created from biomass combustion is a pollutant particularly damaging to health. This rigorous study employed a personal sampling device and multi-stage cascade impactor to collect airborne PM (including PM2.5) and deposited ash from 20 real-world kitchen microenvironments. A robust analysis of the PM was undertaken using a range of morphological, physical, and chemical techniques, the results of which were then compared to a controlled burn experiment. Results revealed that airborne PM was predominantly carbon (~85%), with the OC/EC ratio varying between 1.17 and 11.5. Particles were primarily spherical nanoparticles (50–100 nm) capable of deep penetration into the human respiratory tract (HRT). This is the first systematic characterisation of biomass cooking emissions in authentic rural kitchen settings, linking particle morphology, chemistry and toxicology at health-relevant scales. Toxic heavy metals like Cr, Pb, Cd, Zn, and Hg were detected in PM, while ash was dominated by crustal elements such as Ca, Mg and P. VOCs comprised benzene derivatives, esters, ethers, ketones, tetramethysilanes (TMS), and nitrogen-, phosphorus- and sulphur-containing compounds. This research showcases a unique collection technique that gathered particles indicative of their potential for penetration and deposition in the HRT. Impact stems from the close link between the physico-chemical properties of particle emissions and their environmental and epidemiological effects. By providing a critical evidence base for exposure modelling, risk assessment and clean cooking interventions, this study delivers internationally significant insights. Our methodological innovation, capturing respirable nanoparticles under real-world conditions, offers a transferable framework for indoor air quality research across low- and middle-income countries. The findings therefore advance both fundamental understanding of combustion-derived nanoparticle behaviour and practical knowledge to inform public health, environmental policy, and the UN Sustainable Development Goals