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The Distributed Practice Effect on Classroom Learning: A Meta-Analytic Review of Applied Research
No full textThere is extensive evidence that distributed practice produces superior learning to massed practice, predominantly from laboratory studies often featuring decontextualized learning. A systematic review of applied research was undertaken to assess the impact of distributed practice on classroom learning. Inclusion criteria were classroom studies with learning materials and timescales relevant to curriculum-based learning. The screening of over 3000 articles resulted in 22 reports containing 31 effect sizes (N > 3000). A meta-analysis found a moderate effect in favor of distributed over massed practice (d = 0.54, 95% CI [0.31, 0.77]). Although a comprehensive quantitative moderator analysis was not possible due to the number of studies, generally larger effect sizes were associated with studies that featured longer retention intervals, had learners at higher education levels, and had fewer re-exposures to the materials
Sustaining meaningful journeys in transdisciplinary practice
No full textThis presentation was delivered at the Theatre and Performance Studies Association (TaPRA) annual conference. Exploring arts and science projects and residencies, emerging themes included language, space/place, hierarchy and access
Preoperative focused echocardiography on patients with fractured neck of femur. ECHONOF-III trial: study protocol for a multicenter randomized controlled trial
No full textBACKGROUND: Hip fractures are common in older people and are associated with high perioperative mortality. Prompt surgical intervention within the first 48 h of fraction reduces complications; however, surgical urgency often precludes a comprehensive preoperative cardiac evaluation. Preliminary data suggests that performing a focused cardiac ultrasound (FCU) before surgery may reduce postoperative complications. We therefore propose to test the primary hypothesis that FCU reduces a 30-day composite of mortality and serious complications. METHODS: We plan a definitive multicenter pragmatic randomized trial that will enroll 2000 adults with hip fractures. Participants will be randomized before surgery to either receive FCU as part of their preoperative assessment or to routine care without FCU. FCU is a brief, 10-min, goal-directed echocardiography performed at the patient's bedside. FCU will be conducted by physicians trained in FCU and the information gathered will be shared immediately with all clinicians involved in the patient's care (anesthesiologists, orthopedic surgeons, geriatricians). The primary outcome will be a 30-day composite of all-cause mortality, hospital readmission, acute kidney injury, cardiac failure, and myocardial injury after noncardiac surgery. Secondary and exploratory outcomes include hospital length of stay, days to return to original residence, postoperative recovery, and quality of life. Additionally, a health cost analysis will be conducted to weigh costs against benefits. DISCUSSION: Our large RCT aims to determine whether preoperative focused ultrasound examinations of hip fracture patients reduce serious postoperative complications, improves the quality of recovery, improves life quality, and is cost-effective. TRIAL REGISTRATION: Registration number: ACTRN12622001546741. Date registered 14/12/2022
Potential to perpetuate social biases in health care by Chinese large language models: a model evaluation study
No full textBackground: Large language models (LLMs) may perpetuate or amplify social biases toward patients. We systematically assessed potential biases of three popular Chinese LLMs in clinical application scenarios. Methods: We tested whether Qwen, Erine, and Baichuan encode social biases for patients of different sex, ethnicity, educational attainment, income level, and health insurance status. First, we prompted LLMs to generate clinical cases for medical education (n = 8,289) and compared the distribution of patient characteristics in LLM-generated cases with national distributions in China. Second, New England Journal of Medicine Healer clinical vignettes were used to prompt LLMs to generate differential diagnoses and treatment plans (n = 45,600), with variations analyzed based on sociodemographic characteristics. Third, we prompted LLMs to assess patient needs (n = 51,039) based on clinical cases, revealing any implicit biases toward patients with different characteristics. Results: The three LLMs showed social biases toward patients with different characteristics to varying degrees in medical education, diagnostic and treatment recommendation, and patient needs assessment. These biases were more frequent in relation to sex, ethnicity, income level, and health insurance status, compared to educational attainment. Overall, the three LLMs failed to appropriately model the sociodemographic diversity of medical conditions, consistently over-representing male, high-education and high-income populations. They also showed a higher referral rate, indicating potential refusal to treat patients, for minority ethnic groups and those without insurance or living with low incomes. The three LLMs were more likely to recommend pain medications for males, and considered patients with higher educational attainment, Han ethnicity, higher income, and those with health insurance as having healthier relationships with others. Interpretation: Our findings broaden the scopes of potential biases inherited in LLMs and highlight the urgent need for systematic and continuous assessments of social biases in LLMs in real-world clinical applications
Cardiac structural and molecular alterations in rodent models of temporal lobe epilepsy
No full textOBJECTIVE: Cardiac structural and molecular changes are prevalent in people with chronic epilepsy, possibly contributing to an increased risk of premature mortality. However, understanding of the underlying pathophysiological mechanisms is limited. Here, we investigated the subacute and chronic changes in cardiac structure and ion channel/exchanger expression in different rodent models of temporal lobe epilepsy (TLE). METHODS: Two models of TLE were used: the kainic acid-induced post-status epilepticus (KASE) model in Wistar rats and the electrical self-sustained status epilepticus (SSSE) model in C57BL/6J mice. Heart tissue was collected at subacute (7 days post-SE) and chronic (12-16 weeks post-SE) timepoints from both models. Histological analysis for cardiac fibrosis and qPCR of ion channel/exchanger mRNA expression was performed. RESULTS: Increased cardiac fibrosis was found in the KASE rats at the subacute (p = 0.016) and chronic (p = 0.003) timepoints compared with sham rats. In chronically epileptic KASE rats, mRNA expression analyses showed that NaV1.5 and NCX1 were reduced in the septum (p = 0.026 and p = 0.020, respectively) compared with shams. In SSSE mice, NaV1.5 was decreased in the right atrium (p = 0.039), and CaV3.2 and NCX1 were increased in the left ventricle subacutely (p = 0.033 and p = 0.003, respectively), and NaV1.5 was increased in the septum at the chronic timepoint (p = 0.008), compared with the non-epileptic sham group. SIGNIFICANCE: Cardiac alterations at structural and molecular levels were found in both experimental rodent epilepsy models, subacutely post-SE and during the chronically epileptic timepoint. The presence of similar cardiac changes across the models, despite being different species and having different modes of epilepsy indication, suggests that these changes are a direct or indirect result of the seizures. PLAIN LANGUAGE SUMMARY: Epilepsy may lead to heart problems, which could raise the risk of early death, but the exact causes are unclear. This study examined heart changes in two rodent models of epilepsy. In rats, heart scarring and stiffness (fibrosis) increased both shortly after seizures and during chronic epilepsy, and the ability to produce key heart proteins was altered. In mice, similar changes in heart proteins appeared in different heart areas. These findings suggest seizures can directly or indirectly cause harmful heart changes. Understanding these effects might help improve care for people with epilepsy and reduce related heart risks
Perceptions of AI adoption and their impact on supply chain learning
No full textOperationalisation of supply chain learning (SCL) is a major challenge. Technologies such as artificial intelligence (AI) are expected to favour supply chain information sharing, collaboration, and coordination, hence, supporting SCL. This paper examines how organisations’ perceptions about AI adoption influence SCL, exploring the relationship between AI’s perceived usefulness and ease of use with the SCL dimensions. We performed an online survey-based investigation with 206 Brazilian practitioners from different organisations of several industry sectors, whose responses were examined using multivariate data techniques. Similar trends in results were observed regardless of whether the relationship was between the focal company and its suppliers or between the focal company and its customers. When the perception about AI’s usefulness and ease of use are both low, captive SCL tends to occur; when both are high, SCL might occur in a distributed way. A consortium SCL prevails if only AI’s perceived ease of use is high; a selective SCL occurs if only the perceived usefulness is high. Identifying how SCL is impacted by organisations’ perceptions about AI adoption may help managers to prioritise their digitalisation efforts, adjusting them according to the expected type of knowledge to be created and shared across the supply chain
Machine-learnt closure models based on computational space training frameworks for large-eddy simulations in natural convection
No full textNatural convection heat transfer at very high Rayleigh numbers (Ra) is a commonly occurring phenomenon in many industry applications. Practically, Large Eddy Simulations (LES) are often chosen as an economical method for the numerical prediction of these flows. However, developing accurate LES models that generalize well to complex geometries poses a challenge, particularly for data-driven methods. Thus, in the current study, machine-learnt closure models with the general choice of length scales for different geometries are proposed, where the subgrid-scale (SGS) stress and heat-flux models developed by using Gene Expression Programming (GEP) are built in the computational space. Two geometrically distinct natural convection cases (Rayleigh–Bénard convection and the concentric horizontal annulus) are chosen to develop and generalize the models. Subsequently, the formulation between the SGS closures, the total and the resolved large-scale turbulent stress and heat-flux is derived in the compressible LES context. The a-priori results show that the GEP models developed in computational space significantly improve both the SGS stress and SGS heat-flux prediction while being robust to complex flows. Similarly, the a-posteriori results demonstrate that the GEP models perform better than the wall-adapting local eddy-viscosity (WALE) model in the prediction of the mean SGS stress and the SGS heat-flux. The data-driven approach for turbulence model development presented clearly offers a promising models’ generalization for LES in the prediction of SGS stress and heat-flux
Clinical course of patients with bloodstream infections enrolled in the BALANCE clinical trial
No full textOBJECTIVES: There is a lack of data describing the longitudinal clinical trajectories of vital signs and laboratory tests in patients with bloodstream infection (BSI). The BALANCE trial, which randomly assigned patients with BSI to receive 7 or 14 days of antibiotic treatment, provided rich daily data to describe these trajectories. METHODS: As part of the BALANCE trial, we collected several daily parameters (temperature, heart rate, mean arterial pressure, systolic blood pressure, respiratory rate, WBC count, C-reactive protein, platelet count and SOFA score) until Day 14 of illness, discharge or death. In this post hoc descriptive sub-study, we described trajectories of these parameters, stratified by treatment group allocation and by the primary outcome of 90-day all-cause mortality. RESULTS: Among 3608 patients included, median age was 70 years and 46.7% were female. At enrolment, 55.0% were admitted in the ICU and 21.2% required mechanical ventilation. Longitudinal trajectories of vital signs, laboratory tests and SOFA scores were almost identical comparing the two treatment groups, including from Day 7 after treatment divergence. These trajectories were markedly different when comparing survivors (3034 patients; 84.7%) and non-survivors (547 patients; 15.3%), with non-survivors demonstrating a slower recovery course throughout the 14-day period. CONCLUSIONS: Among hospitalized patients with BSI, recovery trajectories were similar in patients assigned to 7- versus 14-day antibiotic treatment durations but were different comparing survivors versus non-survivors. These data could be used to inform daily clinical management, formulate predictive risk scores or clinical decision rules, and guide future research into individualized therapeutic strategies
