Using a Discrete Choice Experiment to Elicit Consumers’ WTP for Health Risk Reductions Achieved By Nanotechnology in the UK

We present research findings on consumers’ willingness to pay (WTP) for reductions in the level of foodborne health risks. The research addresses how such valuations are affected by the means of which the risk reduction is delivered and the methods of risk presentations used in choice tasks. In this case, the research has two treatments. In the first treatment, the comparison is between risk reductions achieved by an improvement in the food system in general (e.g., more stringent regulations and inspection regimes) within the slaughter and meat processing stages of the food chain, as opposed to a risk reduction achieved via innovations in food packaging using nanotechnology, which is the use of nanosensors in packaging. If there is a contamination in packaging, nanosensors reveal a colour change on the packaging material. In the second treatment, the comparison is between valuations of risk reductions in which reductions in risks are presented via absolute values and grids and absolute values together. Both comparisons are achieved via split sample Discrete Choice Experiment surveys. The difference between consumers’ valuations of foodborne risk reductions provides an implicit value for nanotechnology (i.e., WTP to avoid) and the effect of risk grids on choices people make. General results show the existence of heterogeneity in British consumers’ preferences. The effects of nanosensors and risk grids on consumers’ choices are not strong across the models. The valuations of health risk reductions show some variations across the models in both treatment groups.Discrete Choice Experiments, Nanotechnology, Nanosensors, Health Risks, Grids, UK, Health Economics and Policy,

Consumers’ preferences for nanotechnology in food packaging: a discrete choice experiment

We examine consumers' preferences for chickens under different levels of foodborne health risk, animal welfare and pric attributes. We analyse how their preferences vary according to the risk reduction method. Our comparison is between risk reductions achieved by conventional improvements in the meat supply chain system (e.g. more stringent regulations and inspection regimes), and risk reductions achieved by food packaging nanosensors. Our comparison uses a two-treatment discrete choice experiment in which each treatment sample is only presented with one of the risk reductions: either nanotechnology or conventional methods. We also investigate heterogeneity in preferences for two consumer groups: (i) consumers who usually buy conventional raw, whole chickens, and (ii) consumers who usually buy niche, welfare-improved chickens, such as free-range and organic. Our results show evidence of heterogeneity in preferences and willingness- to-pay values of the both consumer groups. We find that consumers, on average, prefer raw, whole chicken with a lower risk of food poisoning, better animal welfare, and lower costs, regardless of the presence of nanosensors. Although consumers in general showed no strong preferences towards or resistance to nanotechnology, those who buy chickens with better animal welfare, on average, showed higher WTP for food risk reduction and animal welfare relative to conventional chicken consumers

Nanotechnology could make our food tastier and healthier – but can we stomach it?

First paragraph: Every mouthful of food we eat isteeming with chemical reactions. Adding ingredients and cooking helps us control these reactions and makes the food taste better and last longer. So what if we could target food at the molecular level, sending in specially designed particles to control reactions even more tightly? Well, this is exactly what scientists are trying to do and it has already produced some impressive results – from food that tastes salty without the health risks of adding salt, to bread that contains healthy fish oil but without any fishy aftertaste.  Access this article on The Conversation website: https://theconversation.com/nanotechnology-could-make-our-food-tastier-and-healthier-but-can-we-stomach-it-6034

Who do UK consumers trust for information about nanotechnology?

This paper investigates UK consumers’ trust in sixteen information sources, from government institutions to food handlers and media, to provide accurate information about the use of nanotechnology in food production and packaging. We elicit the perceived trust using a well-known choice-based stated preference technique, namely best-worst scaling. The results from the analysis of a scale-adjusted latent class model show considerable heterogeneity in consumers’ perceptions of trust and choice variability. The findings from this study provide insights into the development of best practices and policies in risk communication and management for novel foods produced by nanotechnologies. More specifically, they highlight how targeted approaches can be used by policymakers responsible for disseminating information relating to novel technologies

WHO IS MOST RESPONSIBLE FOR ENSURING THE MEAT WE EAT IS SAFE?

We report results of an analysis of the attribution of relative responsibility across the stages of the food chain for ensuring food safety. Specifically, we identify perceptions of the share of the overall responsibility that each stage in the food chain has to ensure that the meat people cook and eat at home does not cause them to become ill. Results are reported for two groups of stakeholders: consumers and farmers, and for two types of meat: chicken and beef. The stakeholders’ opinions regarding the relative degrees of responsibility of the sequential food chain stages (feed supplier, farmer, livestock transportation, abattoir,… consumer) are elicited via surveys using the Maximum Difference technique (best-worst scaling). The data are analyzed using mixed logit models estimated via Bayesian techniques. We find that consumers and farmers both tend to allocate a relatively low share of responsibility to their own food safety role. So, consumers tend to think farmers are more responsible for ensuring meat safety than farmers do. Similarly, farmers tend to think consumers have a greater degree of responsibility than consumers themselves believe. Thus, there is a consistent pattern of downplaying the extent of one’s own responsibility. Further, consumers tend to allocate the highest shares of responsibility to the middle stages of the meat food chain. This contrasts with farmers who tend to allocate the highest shares of responsibility to the latter stages of the chain towards consumers, believing that the earlier stages of the chain (until the livestock arrive at the abattoir) have a relatively low share of responsibility. The analysis is currently being extended to a third group of food chain actors: abattoir workers.Maximum Difference, Best Worst Scaling, Responsibility, Food Safety, Perception, Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety, Institutional and Behavioral Economics, Research Methods/ Statistical Methods, Q18, Q51, D03, D12,

Preferences for public involvement in health service decisions: a comparison between best-worst scaling and trio-wise stated preference elicitation techniques

Stated preference elicitation techniques, such as discrete choice experiments and best-worst scaling, are now widely used in health research to explore the public’s choices and preferences. In this paper, we propose an alternative stated preference elicitation technique, which we refer to as ‘trio-wise’. We explain this new technique, its relative advantages, modeling framework, and how it compares to the best-worst scaling method. To better illustrate the differences and similarities, we utilize best-worst scaling Case2, where individuals make best and worst (most and least) choices for the attribute levels that describe a single profile. We demonstrate this new preference elicitation technique using an empirical case study that explores preferences among the general public for ways to involve them in decisions concerning the health care system. Our findings show that the best-worst scaling and trio-wise preference elicitation techniques both retrieve similar preferences. However, the capability of our trio-wise method to provide additional information on the strength of rank preferences and its ability to accommodate indifferent preferences lead us to prefer it over the standard best-worst scaling technique

Prioritising Health Service Innovation Investments Using Public Preferences: A Discrete Choice Experiment

Background: Prioritising scarce resources for investment in innovation by publically funded health systems is unavoidable. Many healthcare systems wish to foster transparency and accountability in the decisions they make by incorporating the public in decision-making processes. This paper presents a unique conceptual approach exploring the public's preferences for health service innovations by viewing healthcare innovations as 'bundles' of characteristics. This decompositional approach allows policy-makers to compare numerous competing health service innovations without repeatedly administering surveys for specific innovation choices. Methods: A Discrete Choice Experiment (DCE) was used to elicit preferences. Individuals chose from presented innovation options that they believe the UK National Health Service (NHS) should invest the most in. Innovations differed according to: (i) target population; (ii) target age; (iii) implementation time; (iv) uncertainty associated with their likely effects; (v) potential health benefits; and, (vi) cost to a taxpayer. This approach fosters multidimensional decision-making, rather than imposing a single decision criterion (e.g., cost, target age) in prioritisation. Choice data was then analysed using scale-adjusted Latent Class models to investigate variability in preferences and scale and valuations amongst respondents. Results: Three latent classes with considerable heterogeneity in the preferences were present. Each latent class is composed of two consumer subgroups varying in the level of certainty in their choices. All groups preferred scientifically proven innovations, those with potential health benefits that cost less. There were, however, some important differences in their preferences for innovation investment choices: Class-1 (54%) prefers innovations benefitting adults and young people and does not prefer innovations targeting people with 'drug addiction' and 'obesity'. Class- 2 (34%) prefers innovations targeting 'cancer' patients only and has negative preferences for innovations targeting elderly, and Class-3 (12%) prefers spending on elderly and cancer patients the most. Conclusions: DCE can help policy-makers incorporate public preferences for health service innovation investment choices into decision making. The findings provide useful information on the public's valuation and acceptability of potential health service innovations. Such information can be used to guide innovation prioritisation decisions by comparing competing innovation options. The approach in this paper makes, these often implicit and opaque decisions, more transparent and explicit

Including opt-out options in discrete choice experiments: issues to consider

Background: Providing an opt-out alternative in discrete choice experiments can often be considered to be important for presenting real-life choice situations in different contexts, including health. However, insufficient attention has been given to how best to address choice behaviours relating to this opt-out alternative when modelling discrete choice experiments, particularly in health studies. Objective: The objective of this paper is to demonstrate how to account for different opt-out effects in choice models.We aim to contribute to a better understanding of how to model opt-out choices and show the consequences of addressing the effects in an incorrect fashion.We present our code written in the R statistics program so that others can explore these issues in their own data. Methods: In this practical guideline, we generate synthetic data on medication choice and use Monte Carlo simulation. We consider three different definitions for the opt-out alternative and four candidate models for each definition. We apply a frequentist-based multimodel inference approach and use performance indicators to assess the relative suitability of each candidate model in a range of settings. Results: We show that misspecifying the opt-out effect has repercussions for marginal willingness to pay estimation and the forecasting of market shares. Our findings also suggest a number of key recommendations for DCE practitioners interested in exploring these issues. Conclusions: There is no unique best way to analyse data collected from discrete choice experiments. Researchers should consider several models so that the relative support for different hypotheses of opt-out effects can be explored

Classroom teachers’ professional development activities within the scope of life long learning in Turkey

Among all the factors affecting education, teachers have more important role in ensuring the effectiveness of the teaching process. Teachers’ professional development is a subject that directly affect the teaching process. Researches on the development of teaching profession indicate that professional training is a necessity for better education and better schools. Because if the teacher learns during performing the teaching profession, the quality of the education offered by the teacher will be higher. Teachers who develop themselves in terms of profession provide both a better education and a positive learning environment for the students. In this context, the aim of this research is to investigate the activities of the classroom teachers participate in Turkey in order to ensure their professional development. The study is prepared depending on the views of the classroom teachers. The data were obtained from the classroom teachers who teach 1, 2, 3, and 4. classes in public and private elementary schools in Ankara, in the 2014-2015 academic year. Questionnaire developed by the researchers was used for collecting the data

A comparative analysis of handling level of lifelong learning competences in social education curricula, Turkey and Ireland sample

Developing and ever-changing information technology brings together many innovations by renewing the human profile societies need in a significant way. “Lifelong Learning Understanding” which is one of the most important of these innovations, makes it necessary to change the basic competences and skills stand in the curricula. Accordingly, the education curricula are expected to provide lifelong learning understanding.  In this study it was aimed to analyze the handling level of the lifelong learning competences in the social education curricula of Turkey and Ireland comparatively. Eight key competences, recommended EU member countries to conduct their educational policies within the context of lifelong learning by the European Union (EU), was used as references in the analysis of the curricula.  It has been tried to determine whether lifelong learning competences are included in the curricula or not and which competences have been mentioned the most and which has been mentioned the least. Data required was collected in accordance with “document analysis” method, which is one of the qualitative research methods, and utilized from “content analysis” technique for the analysis of the collected data. According to the findings of the study it was found that the most frequent competences were mathematical competence and basic competences in science and technology in TSCC.  It was also seen that the competences of communication in the mother tongue, social and civic competences, the learning to learn competence, and mathematical competence and basic competences in science are of leading importance in SPHE.  Absence of the communication in foreign languages competence in TSSC can be said as the most prominent difference between the ISSC and TSSC