Academic Self-Concept and Master Adaptive Learning in First Year Medical Students: A Validation and Scale Construction Study

Students’ academic self-concepts (ASC) and their orientation towards self-regulated learning are important elements of success. Despite this fact, little work has been conducted exploring these areas medical students. Given the shifting priorities of medical education toward competency-based education and self-directed learning, the goals of this study were to validate an existing measure of ASC and to improve our measurement capabilities for understanding the Master Adaptive Learner (MAL). Evidence for validity and scale reliability was collected for the ASCS with this novel population and a range of motivational and self-regulative variables (Goal orientation, academic emotion regulation, and lifelong learning) were analyzed and reduced to produce a single scale for MAL. Surveys were administered to 203 medical students at an urban, Mid-Atlantic medical school and students’ grades were linked to survey responses. Results of a confirmatory factor analysis indicated that the original factor structure was not a good fit to the data for the current data. An exploratory factor analysis (EFA) was conducted to identify which structure fit better, and while a three-factor structure was produced, only one factor met reliability standards. This factor, confidence, was merged with items from the other surveys, and reliability scores for a composite MAL scale were identified. Based on these findings and the result of an EFA, the total item pool was reduced from 83 to 25. These 25 items discriminated between two clusters of students: MALs and others. Students’ membership in the MAL cluster predicted greater performance on the first exam in medical school, but not on any other grade outcomes. These results provide early evidence for the continued study of MAL and motivation in medical school, which will help researchers and curriculum designers support the development of future physicians

Middle Level Learning: Compendium of Research and Best Practice

Young adolescence is a time of important transition. It is a time when youth strive to define themselves as individuals while at the same time establishing their relationship within social groups. It is a developmental period characterized by curiosity and exploration. From a certain perspective, these qualities of young adolescents seem to be a good match for school settings. Schools might offer the social spaces for establishing individual and group identity and the academic space that harnesses curiosity and allows youth to find direction as they move toward high school, college and career. And yet, middle grades education – that is education for students between the ages of 10 and 15 – has consistently emerged within the K-12 educational reform debates as a problem that needs to be solved. Since the early 20th century, the idea has persisted that the structure and the philosophy of schools for young adolescents are grossly mismatched with the needs of youth. Those making the case for the failure of middle grades schools point to declining outcomes in academic achievement and loss of student engagement. This perceived problem has spurred an on-going effort to reform both the philosophy and the design of middle grades education. Junior high schools were originally proposed in the early 20th century to solve problems related to retention of upper grade students in the traditional K-8 schools. The middle school movement of the 1960s and 1970s was a response to the problem of junior high schools that many considered inattentive to the developmental needs of young adolescents. In the late 1990s, a push to return to the K-8 grade configuration emerged as a solution to the problem of the middle school model, which came under attack for their over-emphasis on the socialemotional dimensions of education and lack of attention to academic rigor. In certain ways, this series of solutions offered by the reform community have come full circle, yet the problems and possibilities of middle grades education persists. This paper is designed to serve as a resource for practitioners, administrators, policy makers, and community members from the Richmond-area who are interested in developing a better understanding of the history and core themes of the middle level learning space and grounding their work and decision-making in the national research and literature on best practice for middle level learning

Lower amounts of daily and prolonged sitting do not lower free-living continuously monitored glucose concentrations in overweight and obese adults: a randomised crossover study

Data Availability Statement: The data presented in this study are available on request from the corresponding author.Copyright: © 2021 by the authors. This study compared the short-term continuously monitored glucose responses between higher and lower amounts of prolonged sitting in overweight and obese adults under free-living conditions. In a randomised crossover design, 12 participants (age 48 ± 10 years, body mass index 33.3 ± 5.5 kg/m2) completed two four-day experimental regimens while wearing a continuous glucose monitor, as follows: (1) uninterrupted sitting (participants were instructed to sit for ≥10 h/day and accrue ≥7, 1 h sitting bouts each day), and (2) interrupted sitting (participants were instructed to interrupt sitting every 30 min during ten of their waking hours with 6–10 min of activity accrued in each hour). Linear mixed models compared outcomes between regimens. None of the continuously monitored glucose variables differed between regimens, e.g., 24 h net incremental area under the glucose curve was 5.9 [95% CI: −1.4, 13.1] and 5.6 [95% CI: −1.7, 12.8] mmol/L∙24 h, respectively (p = 0.47). Daily sitting (−58 min/day, p = 0.001) and sitting bouts lasting ≥30 min (−99 min/day, p < 0.001) were significantly lower and stepping time significantly higher (+40 min/day, p < 0.001) in the interrupted sitting than the uninterrupted sitting regimen. In conclusion, lower amounts of daily and prolonged sitting did not improve free-living continuously measured glucose among overweight and obese adults

Metabonomics and Intensive Care

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency medicine 2016. Other selected articles can be found online at http://www.biomedcentral.com/collections/annualupdate2016. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901

Short and long term retention in antiretroviral care in health facilities in rural Malawi and Zimbabwe.

Despite the successful scale-up of ART services over the past years, long term retention in ART care remains a major challenge, especially in high HIV prevalence and resource-limited settings. This study analysed the short (<12 months) and long (>12 months) term retention on ART in two ART programmes in Malawi (Thyolo district) and Zimbabwe (Buhera district)

Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network

The need for smallholder farmers to adapt their practices to a changing climate is well recognised, particularly in Africa. The cost of adapting to climate change in Africa is estimated to be $20 to$30 billion per year, but the total amount pledged to finance adaptation falls significantly short of this requirement. The difficulty of assessing and monitoring when adaptation is achieved is one of the key barriers to the disbursement of performance-based adaptation finance. To demonstrate the potential of Bayesian Belief Networks for describing the impacts of specific activities on climate change resilience, we developed a simple model that incorporates climate projections, local environmental data, information from peer-reviewed literature and expert opinion to account for the adaptation benefits derived from Climate-Smart Agriculture activities in Malawi. This novel approach allows assessment of vulnerability to climate change under different land use activities and can be used to identify appropriate adaptation strategies and to quantify biophysical adaptation benefits from activities that are implemented. We suggest that multiple-indicator Bayesian Belief Network approaches can provide insights into adaptation planning for a wide range of applications and, if further explored, could be part of a set of important catalysts for the expansion of adaptation finance

A comparison of satellite remote sensing data fusion methods to map peat swamp forest loss in Sumatra, Indonesia

The loss of huge areas of peat swamp forest in Southeast Asia and the resulting negative environmental effects, both local and global, have led to an increasing interest in peat restoration in the region. Satellite remote sensing offers the potential to provide up‐to‐date information on peat swamp forest loss across large areas, and support spatial explicit conservation and restoration planning. Fusion of optical and radar remote sensing data may be particularly valuable in this context, as most peat swamp forests are in areas with high cloud cover, which limits the use of optical data. Radar data can ‘see through’ cloud, but experience so far has shown that it doesn't discriminate well between certain types of land cover. Various approaches to fusion exist, but there is little information on how they compare. To assess this untapped potential, we compare three different classification methods with Sentinel‐1 and Sentinel‐2 images to map the remnant distribution of peat swamp forest in the area surrounding Sungai Buluh Protection Forest, Sumatra, Indonesia. Results show that data fusion increases overall accuracy in one of the three methods, compared to the use of optical data only. When data fusion was used with the pixel‐based classification using the original pixel values, overall accuracy increased by a small, but statistically significant amount. Data fusion was not beneficial in the case of object‐based classification or pixel‐based classification using principal components. This indicates optical data are still the main source of information for land cover mapping in the region. Based on our findings, we provide methodological recommendations to help those involved in peatland restoration capitalize on the potential of big data