Qu’en penseraient mes pairs? Comparaison entre la méthode fondée sur l'opinion et celle fondée sur la prédiction dans l'évaluation de cours de formation médicale continue

Background: Although medical courses are frequently evaluated via surveys with Likert scales ranging from “strongly agree” to “strongly disagree,” low response rates limit their utility. In undergraduate medical education, a new method with students predicting what their peers would say, required fewer respondents to obtain similar results. However, this prediction-based method lacks validation for continuing medical education (CME), which typically targets a more heterogeneous group than medical students. Methods: In this study, 597 participants of a large CME course were randomly assigned to either express personal opinions on a five-point Likert scale (opinion-based method; n = 300) or to predict the percentage of their peers choosing each Likert scale option (prediction-based method; n = 297). For each question, we calculated the minimum numbers of respondents needed for stable average results using an iterative algorithm. We compared mean scores and the distribution of scores between both methods. Results: The overall response rate was 47%. The prediction-based method required fewer respondents than the opinion-based method for similar average responses. Mean response scores were similar in both groups for most questions, but prediction-based outcomes resulted in fewer extreme responses (strongly agree/disagree). Conclusions: We validated the prediction-based method in evaluating CME. We also provide practical considerations for applying this method.Contexte : Bien que les cours de médecine soient fréquemment évalués au moyen d'enquêtes avec des échelles de Likert allant de « totalement d'accord » à « totalement en désaccord », les faibles taux de réponse en limitent l'utilité. Dans l'enseignement médical prédoctoral, une nouvelle méthode dans laquelle les étudiants prédisent ce que leurs pairs diraient, nécessite moins de répondants pour obtenir des résultats similaires. Cependant, cette méthode fondée sur la prédiction n'est pas validée pour la formation médicale continue (FMC), qui cible généralement un groupe plus hétérogène que les étudiants en médecine. Méthodes : Dans cette étude, 597 participants à un grand cours de FMC ont été choisis au hasard pour exprimer leur opinion personnelle sur une échelle de Likert en cinq points (méthode fondée sur l'opinion; n = 300) ou à prédire le pourcentage de leurs pairs choisissant chaque option de l'échelle de Likert (méthode fondée sur la prédiction; n = 297). Pour chaque question, nous avons calculé le nombre minimum de répondants nécessaire pour obtenir des résultats moyens stables à l'aide d'un algorithme itératif. Nous avons comparé les scores moyens et la distribution des scores entre les deux méthodes. Résultats : Le taux de réponse global était de 47 %. La méthode fondée sur la prédiction a nécessité moins de répondants que celle fondée sur l'opinion pour des réponses moyennes similaires. Les scores moyens des réponses étaient similaires dans les deux groupes pour la plupart des questions, mais les résultats fondés sur la prédiction ont donné lieu à moins de réponses extrêmes (totalement d'accord/totalement en désaccord). Conclusions : Nous avons validé la méthode fondée sur la prédiction dans l'évaluation de la FMC. Nous présentons également des considérations pratiques pour la mise en œuvre de cette méthode

Development of a gut-on-a-chip model for high throughput disease modeling and drug discovery

A common bottleneck in any drug development process is finding sufficiently accurate models that capture key aspects of disease development and progression. Conventional drug screening models often rely on simple 2D culture systems that fail to recapitulate the complexity of the organ situation. In this study, we show the application of a robust high throughput 3D gut-on-a-chip model for investigating hallmarks of inflammatory bowel disease (IBD). Using the OrganoPlate platform, we subjected enterocyte-like cells to an immune-relevant inflammatory trigger in order to recapitulate key events of IBD and to further investigate the suitability of this model for compound discovery and target validation activities. The induction of inflammatory conditions caused a loss of barrier function of the intestinal epithelium and its activation by increased cytokine production, two events observed in IBD physiopathology. More importantly, anti-inflammatory compound exposure prevented the loss of barrier function and the increased cytokine release. Furthermore, knockdown of key inflammatory regulators RELA and MYD88 through on-chip adenoviral shRNA transduction alleviated IBD phenotype by decreasing cytokine production. In summary, we demonstrate the routine use of a gut-on-a-chip platform for disease-specific aspects modeling. The approach can be used for larger scale disease modeling, target validation and drug discovery purpose

A cluster randomized controlled trial aimed at implementation of local quality improvement collaboratives to improve prescribing and test ordering performance of general practitioners: Study Protocol

<p>Abstract</p> <p>Background</p> <p>The use of guidelines in general practice is not optimal. Although evidence-based methods to improve guideline adherence are available, variation in physician adherence to general practice guidelines remains relatively high. The objective for this study is to transfer a quality improvement strategy based on audit, feedback, educational materials, and peer group discussion moderated by local opinion leaders to the field. The research questions are: is the multifaceted strategy implemented on a large scale as planned?; what is the effect on general practitioners' (GPs) test ordering and prescribing behaviour?; and what are the costs of implementing the strategy?</p> <p>Methods</p> <p>In order to evaluate the effects, costs and feasibility of this new strategy we plan a multi-centre cluster randomized controlled trial (RCT) with a balanced incomplete block design. Local GP groups in the south of the Netherlands already taking part in pharmacotherapeutic audit meeting groups, will be recruited by regional health officers. Approximately 50 groups of GPs will be randomly allocated to two arms. These GPs will be offered two different balanced sets of clinical topics. Each GP within a group will receive comparative feedback on test ordering and prescribing performance. The feedback will be discussed in the group and working agreements will be created after discussion of the guidelines and barriers to change. The data for the feedback will be collected from existing and newly formed databases, both at baseline and after one year.</p> <p>Discussion</p> <p>We are not aware of published studies on successes and failures of attempts to transfer to the stakeholders in the field a multifaceted strategy aimed at GPs' test ordering and prescribing behaviour. This pragmatic study will focus on compatibility with existing infrastructure, while permitting a certain degree of adaptation to local needs and routines.</p> <p>Trial registration</p> <p>Nederlands Trial Register ISRCTN40008171</p

Biomarkers in anal cancer: from biological understanding to stratified treatment

Squamous cell carcinomas of the anus and anal canal represent a model of a cancer and perhaps the first where level 1 evidence supported primary chemoradiotherapy (CRT) in treating locoregional disease with curative intent. The majority of tumours are associated with infection with oncogenic subtypes of human papilloma virus and this plays a significant role in their sensitivity to treatment. However, not all tumours are cured with CRT and there remain opportunities to improve outcomes in terms of oncological control and also reducing late toxicities. Understanding the biology of ASCC promises to allow a more personalised approach to treatment, with the development and validation of a range of biomarkers and associated techniques that are the focus of this review

The application of genetic algorithms to lot streaming in a job-shop scheduling problem

A new approach using genetic algorithms (GAs) is proposed to determine lot streaming (LS) conditions in a job-shop scheduling problem (JSP). LS refers to a situation that a job (lot) can be split into a number of smaller jobs (sub-lots) so that successive operations of the same job can be overlapped. Consequently, the completion time of the whole job can be shortened. By applying the proposed approach called LSGAVS, two sub-problems are solved simultaneously using GAs. The first problem is called the LS problem in which the LS conditions are determined and the second problem is called JSP after the LS conditions have been determined. Based on timeliness approach, a number of test problems will be studied to investigate the optimum the LS conditions such that all jobs can be finished close to their due dates in a job-shop environment. Computational results suggest that the proposed model, LSGAVS, works well with different objective measures and good solutions can be obtained with reasonable computational effort

‘What would my peers say?’ Comparing the opinion-based method with the prediction-based method in Continuing Medical Education course evaluation

Background: Although medical courses are frequently evaluated via surveys with Likert scales ranging from “strongly agree” to “strongly disagree,” low response rates limit their utility. In undergraduate medical education, a new method with students predicting what their peers would say, required fewer respondents to obtain similar results. However, this prediction-based method lacks validation for continuing medical education (CME), which typically targets a more heterogeneous group than medical students.Methods: In this study, 597 participants of a large CME course were randomly assigned to either express personal opinions on a five-point Likert scale (opinion-based method; n = 300) or to predict the percentage of their peers choosing each Likert scale option (prediction-based method; n = 297). For each question, we calculated the minimum numbers of respondents needed for stable average results using an iterative algorithm. We compared mean scores and the distribution of scores between both methods.Results: The overall response rate was 47%. The prediction-based method required fewer respondents than the opinion-based method for similar average responses. Mean response scores were similar in both groups for most questions, but prediction-based outcomes resulted in fewer extreme responses (strongly agree/disagree).Conclusions: We validated the prediction-based method in evaluating CME. We also provide practical considerations for applying this method.Contexte : Bien que les cours de médecine soient fréquemment évalués au moyen d'enquêtes avec des échelles de Likert allant de « totalement d'accord » à « totalement en désaccord », les faibles taux de réponse en limitent l'utilité. Dans l'enseignement médical prédoctoral, une nouvelle méthode dans laquelle les étudiants prédisent ce que leurs pairs diraient, nécessite moins de répondants pour obtenir des résultats similaires. Cependant, cette méthode fondée sur la prédiction n'est pas validée pour la formation médicale continue (FMC), qui cible généralement un groupe plus hétérogène que les étudiants en médecine.Méthodes : Dans cette étude, 597 participants à un grand cours de FMC ont été choisis au hasard pour exprimer leur opinion personnelle sur une échelle de Likert en cinq points (méthode fondée sur l'opinion; n = 300) ou à prédire le pourcentage de leurs pairs choisissant chaque option de l'échelle de Likert (méthode fondée sur la prédiction; n = 297). Pour chaque question, nous avons calculé le nombre minimum de répondants nécessaire pour obtenir des résultats moyens stables à l'aide d'un algorithme itératif. Nous avons comparé les scores moyens et la distribution des scores entre les deux méthodes.Résultats : Le taux de réponse global était de 47 %. La méthode fondée sur la prédiction a nécessité moins de répondants que celle fondée sur l'opinion pour des réponses moyennes similaires. Les scores moyens des réponses étaient similaires dans les deux groupes pour la plupart des questions, mais les résultats fondés sur la prédiction ont donné lieu à moins de réponses extrêmes (totalement d'accord/totalement en désaccord).Conclusions : Nous avons validé la méthode fondée sur la prédiction dans l'évaluation de la FMC. Nous présentons également des considérations pratiques pour la mise en oeuvre de cette méthode

The challenge of transferring an implementation strategy from academia to the field. A process evaluation of local quality improvement collaboratives in Dutch primary care using the normalization process theory

Rationale, aims and objectives Aquality improvement strategy consisting of comparative feedback and peer review embedded in available local quality improvement collaboratives proved to be effective in changing the test-ordering behaviour of general practitioners. However, implementing this strategy was problematic. We aimed for large-scale implementation of an adapted strategy covering both test ordering and prescribing performance. Because we failed to achieve large-scale implementation, the aim of this study was to describe and analyse the challenges of the transferring process. Methods In a qualitative study 19 regional health officers, pharmacists, laboratory specialists and general practitioners were interviewed within 6 months after the transfer period. The interviews were audiotaped, transcribed and independently coded by two of the authors. The codes were matched to the dimensions of the normalization process theory. Results The general idea of the strategy was widely supported, but generating the feedback was more complex than expected and the need for external support after transfer of the strategy remained high because participants did not assume responsibility for the work and the distribution of resources that came with it. Conclusion Evidence on effectiveness, a national infrastructure for these collaboratives and a general positive attitude were not sufficient for normalization. Thinking about managing large databases, responsibility for tasks and distribution of resources should start as early as possible when planning complex quality improvement strategies. Merely exploring the barriers and facilitators experienced in a preceding trial is not sufficient. Although multifaceted implementation strategies to change professional behaviour are attractive, their inherent complexity is also a pitfall for large-scale implementation