The design of probiotic studies to substantiate health claims

The EC Regulation No. 1924/2006 on Nutrition and Health claims made on foods has generated considerable debate and concern among scientists and industry. At the time of writing, the European Food Safety Authority (EFSA) has not approved any probiotic claims despite numerous human trials and meta-analyses showing evidence of beneficial effects. On 29th and 30th September 2010, ten independent, academic scientists with a documented record in probiotic research, met to discuss designs for future probiotic studies to demonstrate health benefits for gut and immune function. The expert panel recommended the following: (i) always formulate a precise and concrete hypothesis, and appropriate goals and parameters before starting a trial; (ii) ensure trials have sufficient sample size, such that they are adequately powered to reach statistically significant conclusions, either supporting or rejecting the a priori hypothesis, taking into account adjustment for multiple testing (this might necessitate more than one recruitment site); (iii) ensure trials are of appropriate duration; (iv) focus on a single, primary objective and only evaluate multiple parameters when they are hypothesis-driven. The panel agreed that there was an urgent need to better define which biomarkers are considered valuable for substantiation of a health claim. As a first step, the panel welcomed the publication on the day of the meeting of EFSA's draft guidance document on immune and gut health, although it came too late for study designs and dossiers to be adjusted accordingly. New validated biomarkers need to be identified in order to properly determine the range of physiological functions influenced by probiotics. In addition, validated biomarkers reflecting risk factors for disease, are required for article 14 claims (EC Regulation No. 1924/2006). Finally, the panel concluded that consensus among scientists is needed to decide appropriate clinical endpoints for trials.

The Institute of Psychoplasmics

ABSTRACT: The Institute of Psychoplasmics is a group exhibition dealing with cults, rituals and the metaphor of the body politic. A key interest of the project is the way in which cultic groupings challenge the integrity of the social body by producing another within it. The exhibition, book and events explore parallels between the operations of new religious movements in the context of neo-liberalism and the forms of collectivity posited by contemporary art. These issues were addressed through a gallery display, academic essays, discussion, adult and children focused workshops and live performance event. The exhibition design, which considered the gallery as a research institute, itself investigated strategies of collaboration and psycho-social manipulation. The show was curated by Pil and Galia Kollectiv and commissioned by the Pump House Gallery in London and supported by Outset, Arts Council England and the Henry Moore Foundation. The exhibition included work by a.a.s., Insectoid, Diann Bauer, Amanda Beech, Mikko Canini, Seth Coston, Rod Dickinson, Pil and Galia Kollectiv, Tai Shani, Francis Upritchard and Roman Vasseur. A publication edited by the curators, features writing by Suhail Malik, Amanda Beech, Pil and Galia Kollectiv, Gilad Elbom, Tom McCarthy, Emily McMehen and Travis Jeppesen.

Evoked prior learning experience and approach to learning as predictors of academic achievement

Background. In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students’ perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. Aim. To investigate how students’ evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Sample. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. Method. A 77-item questionnaire was used to gather students’ self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. Results. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Conclusions. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching–learning contexts are analysed using multi-variable methods.