Improving Pediatric Basic Life Support Performance Through Blended Learning With Web-Based Virtual Patients: Randomized Controlled Trial

BACKGROUND E-learning and blended learning approaches gain more and more popularity in emergency medicine curricula. So far, little data is available on the impact of such approaches on procedural learning and skill acquisition and their comparison with traditional approaches. OBJECTIVE This study investigated the impact of a blended learning approach, including Web-based virtual patients (VPs) and standard pediatric basic life support (PBLS) training, on procedural knowledge, objective performance, and self-assessment. METHODS A total of 57 medical students were randomly assigned to an intervention group (n=30) and a control group (n=27). Both groups received paper handouts in preparation of simulation-based PBLS training. The intervention group additionally completed two Web-based VPs with embedded video clips. Measurements were taken at randomization (t0), after the preparation period (t1), and after hands-on training (t2). Clinical decision-making skills and procedural knowledge were assessed at t0 and t1. PBLS performance was scored regarding adherence to the correct algorithm, conformance to temporal demands, and the quality of procedural steps at t1 and t2. Participants' self-assessments were recorded in all three measurements. RESULTS Procedural knowledge of the intervention group was significantly superior to that of the control group at t1. At t2, the intervention group showed significantly better adherence to the algorithm and temporal demands, and better procedural quality of PBLS in objective measures than did the control group. These aspects differed between the groups even at t1 (after VPs, prior to practical training). Self-assessments differed significantly only at t1 in favor of the intervention group. CONCLUSIONS Training with VPs combined with hands-on training improves PBLS performance as judged by objective measures.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

Knowledge Management and Decision Support for Sustainable Land Management

Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

Individual Video Training iVT - Development of a National Infrastructure for Video-Supported Learning

Introduction: Video‐Supported Learning is particularly effective when it comes to skills and behaviors. Video registration of patient‐physician interviews, class room instruction or practical skills allow it to learners themselves, their peers, and their tutors to assess the quality of the learner's performance, to give specific feedback, and to make suggestions for improvement. Methods: In Switzerland, four pedagogical universities and two medical faculties joined to initiate the development of a national infrastructure for Video Supported Learning. The goal was to have a system that is simple to use, has most steps automated, provides the videos over the Internet, and has a sophisticated access control. Together with SWITCH, the national IT‐Support‐Organisation for Swiss Universities, the program iVT (Individual Video Training) was developed by integrating two preexisting technologies. The first technology is SWITCHcast, a podcast system. With SWITCHcast, videos are automatically uploaded to a server as soon as the registration is over. There the videos are processed and converted to different formats. The second technology is the national Single Logon System AAI (Authentification and Authorization Infrastructure) that enables iVT to link each video with the corresponding learner. The learner starts the registration with his Single Logon. Thus, the video can unambiguously be assigned. Via his institution's Learning Management System (LMS), the learner can access his video and give access to his video to peers and tutors. Results: iVT is now used at all involved institutions. The system works flawlessly. In Bern, we use iVT for the communications skills training in the forth and sixth year. Since students meet with patient actors alone, iVT is also used to certify attendance. Students are encouraged to watch the videos of the interview and the feedback of the patient actor. The offer to discuss a video with a tutor was not used by the students. Discussion: We plan to expand the use of iVT by making peer assessment compulsory. To support this, annotation capabilities are currently added to iVT. We also want to use iVT in training of practical skills, again for self as well as for peer assessment.  At present, we use iVT for quality control of patient actor's performance.

Linking Applied Ethnobotany to Social Learning: A Participatory Tool for the Promotion of Indigenous Plants Use in Matutuíne, Southern Mozambique

In its search for pathways towards a more sustainable management of natural resources, development oriented research increasingly faces the challenge to develop new concepts and tools based on transdisciplinarity. Transdisciplinarity can, in terms of an idealized goal, be defined as a research approach that identifies and solves problems not only independently of disciplinary boundaries, but also including the knowledge and perceptions of non-scientific actors in a participatory process. In Mozambique, the Centre for Development and Environment (Berne, Switzerland), in partnership with Impacto and Helvetas (Maputo, Mozambique), has elaborated a new transdisciplinary tool to identify indigenous plants with a potential for commercialization. The tool combines methods from applied ethnobotany with participatory research in a social learning process. This approach was devised to support a development project aimed at creating alternative sources of income for rural communities of Matutuíne district, Southern Mozambique, while reducing the pressure on the natural environment. The methodology, which has been applied and tested, is innovative in that it combines important data collection through participatory research with a social learning process involving both local and external actors. This mutual learning process provides a space for complementary forms of knowledge to meet, eventually leading to the adoption of an integrated approach to natural resource management with an understanding of its ecological, socio-economic and cultural aspects; local stakeholders are included in the identification of potentials for sustainable development. Sustainable development itself, as a normative concept, can only be defined through social learning and consensus building between the local and external stakeholders.

Decision-Support tools for assessing land degradation and realising sustainable land management, Study Case of El Mkhachbiya Catchment, Northwest of Tunisia

Land degradation is intrinsically complex and involves decisions by many agencies and individuals, land degradation map- ping should be used as a learning tool through which managers, experts and stakeholders can re-examine their views within a wider semantic context. In this paper, we introduce an analytical framework for mapping land degradation, developed by World Overview for Conservation Approaches and technologies (WOCAT) programs, which aims to develop some thematic maps that serve as an useful tool and including effective information on land degradation and conservation status. Consequently, this methodology would provide an important background for decision-making in order to launch rehabilitation/remediation actions in high-priority intervention areas. As land degradation mapping is a problem-solving task that aims to provide clear information, this study entails the implementation of WOCAT mapping tool, which integrate a set of indicators to appraise the severity of land degradation across a representative watershed. So this work focuses on the use of the most relevant indicators for measuring impacts of different degradation processes in El Mkhachbiya catchment, situated in Northwest of Tunisia and those actions taken to deal with them based on the analysis of operating modes and issues of degradation in different land use systems. This study aims to provide a database for surveillance and monitoring of land degradation, in order to support stakeholders in making appropriate choices and judge guidelines and possible suitable recommendations to remedy the situation in order to promote sustainable development. The approach is illustrated through a case study of an urban watershed in Northwest of Tunisia. Results showed that the main land degradation drivers in the study area were related to natural processes, which were exacerbated by human activities. So the output of this analytical framework enabled a better communication of land degradation issues and concerns in a way relevant for policymakers.

Brain-borne IL-1 adjusts glucoregulation and provides fuel support to astrocytes and neurons in an autocrine/paracrine manner.

It is still controversial which mediators regulate energy provision to activated neural cells, as insulin does in peripheral tissues. Interleukin-1β (IL-1β) may mediate this effect as it can affect glucoregulation, it is overexpressed in the 'healthy' brain during increased neuronal activity, and it supports high-energy demanding processes such as long-term potentiation, memory and learning. Furthermore, the absence of sustained neuroendocrine and behavioral counterregulation suggests that brain glucose-sensing neurons do not perceive IL-1β-induced hypoglycemia. Here, we show that IL-1β adjusts glucoregulation by inducing its own production in the brain, and that IL-1β-induced hypoglycemia is myeloid differentiation primary response 88 protein (MyD88)-dependent and only partially counteracted by Kir6.2-mediated sensing signaling. Furthermore, we found that, opposite to insulin, IL-1β stimulates brain metabolism. This effect is absent in MyD88-deficient mice, which have neurobehavioral alterations associated to disorders in glucose homeostasis, as during several psychiatric diseases. IL-1β effects on brain metabolism are most likely maintained by IL-1β auto-induction and may reflect a compensatory increase in fuel supply to neural cells. We explore this possibility by directly blocking IL-1 receptors in neural cells. The results showed that, in an activity-dependent and paracrine/autocrine manner, endogenous IL-1 produced by neurons and astrocytes facilitates glucose uptake by these cells. This effect is exacerbated following glutamatergic stimulation and can be passively transferred between cell types. We conclude that the capacity of IL-1β to provide fuel to neural cells underlies its physiological effects on glucoregulation, synaptic plasticity, learning and memory. However, deregulation of IL-1β production could contribute to the alterations in brain glucose metabolism that are detected in several neurologic and psychiatric diseases.Molecular Psychiatry advance online publication, 8 December 2015; doi:10.1038/mp.2015.174.