The learning objectives, curriculum content, and assessment standards for distributed medical education programs must be aligned across the health care systems and community contexts in which their students train. In this article, the authors describe their experiences at Monash University implementing a distributed medical education program at metropolitan, regional, and rural Australian sites and an offshore Malaysian site, using four different implementation models. Standardizing learning objectives, curriculum content, and assessment standards across all sites while allowing for site-specific implementation models created challenges for educational alignment. At the same time, this diversity created opportunities to customize the curriculum to fit a variety of settings and for innovations that have enriched the educational system as a whole.Developing these distributed medical education programs required a detailed review of Monash's learning objectives and curriculum content and their relevance to the four different sites. It also required a review of assessment methods to ensure an identical and equitable system of assessment for students at all sites. It additionally demanded changes to the systems of governance and the management of the educational program away from a centrally constructed and mandated curriculum to more collaborative approaches to curriculum design and implementation involving discipline leaders at multiple sites.Distributed medical education programs, like that at Monash, in which cohorts of students undertake the same curriculum in different contexts, provide potentially powerful research platforms to compare different pedagogical approaches to medical education and the impact of context on learning outcomes.
In polygenic score (PGS) analysis, the coefficient of determination (R2) is a key statistic to evaluate efficacy. R2 is the proportion of phenotypic variance explained by the PGS, calculated in a cohort that is independent of the genome-wide association study (GWAS) that provided estimates of allelic effect sizes. The SNP-based heritability (hSNP2, the proportion of total phenotypic variances attributable to all common SNPs) is the theoretical upper limit of the out-of-sample prediction R2. However, in real data analyses R2 has been reported to exceed hSNP2, which occurs in parallel with the observation that hSNP2 estimates tend to decline as the number of cohorts being meta-analyzed increases. Here, we quantify why and when these observations are expected. Using theory and simulation, we show that if heterogeneities in cohort-specific hSNP2 exist, or if genetic correlations between cohorts are less than one, hSNP2 estimates can decrease as the number of cohorts being meta-analyzed increases. We derive conditions when the out-of-sample prediction R2 will be greater than hSNP2 and show the validity of our derivations with real data from a binary trait (major depression) and a continuous trait (educational attainment). Our research calls for a better approach to integrating information from multiple cohorts to address issues of between-cohort heterogeneity.
The burden of AIDS-defining cancers has remained relatively steady for the past two decades, whilst the burden of non-AIDS-defining cancer has increased. Here, we conduct a study to describe mortality trends attributed to HIV-associated cancers in 31 countries. We extracted HIV-related cancer mortality data from 2001 to 2018 from the World Health Organization Mortality Database. We computed age-standardized death rates (ASDRs) per 100,000 population using the World Standard Population. Data were visualized using Locally Weighted Scatterplot Smoothing (LOWESS). Data for females were available for 25 countries. Overall, there has been a decrease in mortality attributed to HIV-associated cancers among most of the countries. In total, 18 out of 31 countries (58.0%) and 14 out of 25 countries (56.0%) showed decreases in male and female mortality, respectively. An increasing mortality trend was observed in many developing countries, such as Malaysia and Thailand, and some developed countries, such as the United Kingdom. Malaysia had the greatest increase in male mortality (+495.0%), and Canada had the greatest decrease (-88.5%). Thailand had the greatest increase in female mortality (+540.0%), and Germany had the greatest decrease (-86.0%). At the endpoint year, South Africa had the highest ASDRs for both males (16.8/100,000) and females (19.2/100,000). The lowest was in Japan for males (0.07/100,000) and Egypt for females (0.028/100,000).
Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.