Attitudes and motivations of Economics students: Some recent evidence

There is disagreement amongst economists regarding whether economics students are more self-interested than other students in economic and non-economic contexts. Econometric analysis of the choice to share in a Prisoner´s Dilemma game suggests that it may not be economics students per se that have a lower probability of choosing share rather than compete, but instead that individuals with attitudes, motivations and values similar to those assumed by standard economic theory have a lower probability of choosing share. The experimental evidence here of 1,701 students suggests that it is the motivations and attitudes of subjects that are important for determining economic choices rather than simply whether the individual studies economics. The results confirm that a higher proportion of economics students have motivations in a game theory context that are similar to those assumed by standard economic theory, yet that their related general attitudes and values are not significantly different. Overall the results suggest that the assumptions of standard economic theory are appropriate for a subset of individuals, and for many individuals who do not study economics

Are people ethical? An experimental approach

Do ethical motivations and attitudes affect behaviour? We examine this issue in six Prisoner´s Dilemma and Prisoner´s Dilemma related games using an online experiment where individuals were asked to make choices and subsequently to express the motivations for their choices and their general attitudes. The experimental evidence of 1,701 students suggests that the motivations and attitudes of respondents regarding altruism, inequality aversion, reciprocity and aversion to lying are important for determining economic choices as well as self-interest. Econometric analysis of the choice to share indicates that ethical and self-interested motives are more important for determining choices than personal characteristics

Incorporating Ethics into Economics: Problems and Possibilities

In traditional economics the decision-making process for individuals has effectively no role for ethics as individuals are self-interested. The key concepts in economics which determine the role of ethics in the decision-making process are utility, rationality and methodological individualism and hence how these can be and are formulated and combined determines different roles for ethics in economics. Amitai Etzioni, Amartya Sen and John Broome use different definitions of these concepts and hence find different problems and possibilities for a greater role for ethics in economics. This paper integrates the different approaches of these authors and suggests a general mono-utility framework for incorporating ethics into economics whereby the concept of utility requires adaptation

Common scale valuations across different preference-based measures: estimation using rank data

Background: Different preference-based measures (PBMs) used to estimate Quality Adjusted Life Years (QALYs) provide di¤erent utility values for the same patient. Differences are expected since values have been obtained using different samples, valuation techniques and descriptive systems. Previous studies have estimated the relationship between pairs of PBMs using patient self-reported data. However, there is a need for an approach capable of generating values directly on a common scale for a range of PBMs using the same sample of general population respondents and valuation technique but keeping the advantages of the different descriptive systems. Methods: General public survey data (n=501) where respondents ranked health states described using subsets of six PBMs were analysed. We develop a new model based on the mixed logit to overcome two key limitations of the standard rank ordered logit model, namely, the unrealistic choice pattern (Independence of Irrelevant Alternatives) and the independence of repeated observations. Results: There are substantial differences in the estimated parameters between the two models (mean di¤erence 0.07) leading to di¤erent orderings across the measures. Estimated values for the best states described by di¤erent PBMs are substantially and significantly di¤erent using the standard model, unlike our approach which yields more consistent results. Limitations: Data come from a exploratory study that is relatively small both in sample size and coverage of health states. Conclusions: This study develops a new, �exible econometric model specifically designed to reflect appropriately the features of rank data. Results support the view that the standard model is not appropriate in this setting and will yield very different and apparently inconsistent results. PBMs can be compared using a common scale by implementation of this new approach

Estimating a preference-based index from the Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM): valuation of CORE-6D

Background: The Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM) is used to evaluate the effectiveness of psychological therapies in people with common mental disorders. The objective of this study was to estimate a preference-based index for this population using CORE-6D, a health state classification system derived from CORE-OM consisting of a 5-item emotional component and a physical item, and to demonstrate a novel method for generating states that are not orthogonal. Methods: Rasch analysis was used to identify 11 plausible ‘emotional’ health states from CORE-6D (rather than conventional statistical design that would generate implausible states). By combining these with the 3 response levels of the physical item of CORE-6D, 33 plausible health states can be described, of which 18 were selected for valuation. An interview valuation survey of 220 members of public in South Yorkshire, UK, was undertaken using the time-trade-off method to value the 18 health states; regression analysis was subsequently used to predict values for all possible states described by CORE-6D. Results: A number of multivariate regression models were built to predict values for the 33 plausible health states of CORE-6D, using the Rasch logit value of the emotional health state and the response level of the physical item as independent variables. A cubic model with high predictive value (adjusted R squared 0.990) was finally selected, which can be used to predict utility values for all 927 states described by CORE-6D. Conclusion: The CORE-6D preference-based index will enable the assessment of cost-effectiveness of interventions for people with common mental disorders using existing and prospective CORE-OM datasets. The new method for generating states may be useful for other instruments with highly correlated dimensions

The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results

Background: Previous methods of empirical mapping involve using regressions on patient or general population self-report data from datasets involving 2 or more instruments. This approach relies on overlap in the descriptive systems of the measures, but key dimensions may not be present in both measures. Furthermore, this assumes it is appropriate to use different instruments on the same population, which may not be the case for all patient groups. The aim of the study described here is to develop a new method of mapping using general population preferences for hypothetical health states defined by the descriptive systems of different measures. This paper presents a description of the methods used in the study and reports on the results of the valuation study including details about the respondents, feasibility and quality (e.g. response rate, completion and consistency) and descriptive results on VAS and ranking data. The use of these results to estimate mapping functions between instruments will be presented in a companion paper. Methods: The study used interviewer administered versions of ranking and VAS techniques to value 13 health states defined by each of 6 instruments: EQ-5D (generic), SF-6D (generic), HUI2 (generic for children), AQL-5D (asthma specific), OPUS (social care specific), ICECAP (capabilities). Each interview involved 3 ranking and visual analogue scale (VAS) tasks with states from 3 different instruments where each task involves the simultaneous valuation of multiple instruments. The study includes 13 health and well-being states for each instrument (16 for EQ-5D) that reflect a range of health state values according to the published health state values for each instrument and each health state is valued approximately 75-100 times. Results: The sample consists of 499 members of the UK general population with a reasonable spread of background characteristics (response rate=55%). The study achieved a completion rate of 99% for all states included in the rank and rating tasks and 94.8% of respondents have complete VAS responses and 97.2% have complete rank responses. Interviewers reported that it is doubtful for 4.1% of respondents that they understood the tasks, and 29.3% of respondents stated that they found the tasks difficult. The results suggest important differences in the range of mean VAS and mean rank values per state across instruments; for example, mean VAS values for the worst state vary across instruments from 0.075 to 0.324. Respondents are able to change the ordering of states between the rank and VAS tasks and 12.0% of respondents have one or more differences in their rank and VAS orderings for every task. Conclusions: This study has demonstrated the feasibility of simultaneously valuing health states from different preference-based instruments. The preliminary analysis of the results presented here provides the basis for a new method of mapping between measures based on general population preferences

The simultaneous valuation of states from multiple instruments using ranking and VAS data: methods and preliminary results

Background: Previous methods of empirical mapping involve using regressions on patient or general population self-report data from datasets involving two or more instruments. This approach relies on overlap in the descriptive systems of the measures, but key dimensions may not be present in both measures. Furthermore this assumes it is appropriate to use different instruments on the same population, which may not be the case for all patient groups. The aim of the study described here is to develop a new method of mapping using general population preferences for hypothetical health states defined by the descriptive systems of different measures. This paper presents a description of the methods used in the study and reports on the results of the valuation study including details about the respondents, feasibility and quality (e.g. response rate, completion and consistency) and descriptive results on VAS and ranking data. The use of these results to estimate mapping functions between instruments will be presented in a companion paper. Methods: The study used interviewer administered versions of ranking and VAS techniques to value 13 health states defined by each of 6 instruments: EQ-5D (generic), SF-6D (generic), HUI2 (generic for children), AQL-5D (asthma specific), OPUS (social care specific), ICECAP (capabilities). Each interview involved 3 ranking and visual analogue scale (VAS) tasks with states from 3 different instruments where each task involves the simultaneous valuation of multiple instruments. The study includes 13 health and well-being states for each instrument (16 for EQ-5D) that reflect a range of health state values according to the published health state values for each instrument and each health state is valued approximately 75-100 times. Results: The sample consists of 499 members of the UK general population with a reasonable spread of background characteristics (response rate=55%). The study achieved a completion rate of 99% for all states included in the rank and rating tasks and 94.8% of respondents have complete VAS responses and 97.2% have complete rank responses. Interviewers reported that it is doubtful for 4.1% of respondents that they understood the tasks, and 29.3% of respondents stated that they found the tasks difficult. The results suggest important differences in the range of mean VAS and mean rank values per state across instruments, for example mean VAS values for the worst state vary across instruments from 0.075 to 0.324. Respondents are able to change the ordering of states between the rank and VAS tasks and 12.0% of respondents have one or more differences in their rank and VAS orderings for every task. Conclusions: This study has demonstrated the feasibility of simultaneously valuing health states from different preference-based instruments. The preliminary analysis of the results presented here provides the basis for a new method of mapping between measures based on general population preferences.preference-based measures of health; quality of life; mapping; visual analogue scale; ranking

Estimating a preference-based index from the clinical outcomes in routine evaluation-outcome measure (CORE-OM): Valuation of CORE-6D

Background. The Clinical Outcomes in Routine Evaluation–Outcome Measure (CORE-OM) is used to evaluate the effectiveness of psychological therapies in people with common mental disorders. The objective of this study was to estimate a preference-based index for this population using CORE-6D, a health state classification system derived from the CORE-OM consisting of a 5-item emotional component and a physical item, and to demonstrate a novel method for generating states that are not orthogonal. Methods. Rasch analysis was used to identify 11 emotional health states from CORE-6D that were frequently observed in the study population and are, thus, plausible (in contrast, conventional statistical design might generate implausible states). Combined with the 3 response levels of the physical item of CORE-6D, they generate 33 plausible health states, 18 of which were selected for valuation. A valuation survey of 220 members of the public in South Yorkshire, United Kingdom, was undertaken using the time tradeoff (TTO) method. Regression analysis was subsequently used to predict values for all possible states described by CORE-6D. Results. A number of multivariate regression models were built to predict values for the 33 health states of CORE-6D, using the Rasch logit value of the emotional state and the response level of the physical item as independent variables. A cubic model with high predictive value (adjusted R2 = 0.990) was selected to predict TTO values for all 729 CORE-6D health states. Conclusion. The CORE-6D preference-based index will enable the assessment of cost-effectiveness of interventions for people with common mental disorders using existing and prospective CORE-OM data sets. The new method for generating states may be useful for other instruments with highly correlated dimensions

Estimating informal care inputs associated with EQ-5D for use in economic evaluation.

OBJECTIVES: This paper estimates informal care need using the health of the patient. The results can be used to predict changes in informal care associated with changes in the health of the patient measured using EQ-5D. METHODS: Data was used from a prospective survey of inpatients containing 59,512 complete responses across 44,494 individuals. The number of days a friend or relative has needed to provide care or help with normal activities in the last 6 weeks was estimated using the health of the patient measured by EQ-5D, ICD chapter and other health and sociodemographic data. A variety of different regression models were estimated that are appropriate for the distribution of the informal care dependent variable, which has large spikes at 0 (zero informal care) and 42 days (informal care every day). RESULTS: The preferred model that most accurately predicts the distribution of the data is the zero-inflated negative binomial with variable inflation. The results indicate that improving the health of the patient reduces informal care need. The relationship between ICD chapter and informal care need is not as clear. CONCLUSIONS: The preferred zero-inflated negative binomial with variable inflation model can be used to predict changes in informal care associated with changes in the health of the patient measured using EQ-5D and these results can be applied to existing datasets to inform economic evaluation. Limitations include recall bias and response bias of the informal care data, and restrictions of the dataset to exclude some patient groups

Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: systematic review, statistical modelling and survey.

© Queen’s Printer and Controller of HMSO 2014Background: The National Institute for Health and Care Excellence recommends the use of generic preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However, these data may not be available or appropriate for all health conditions. Objectives: To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate. Design: The project was conducted in three stages: (1) A systematic review of the psychometric properties of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential modelling approaches to ‘map’ EQ-5D values from condition-specific and clinical measures of health [European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Functional Assessment of Cancer Therapy – General Scale (FACT-G)] are compared for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the EQ-5D are developed as ‘bolt-on’ items relating to hearing, tiredness and vision. They are valued using the time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without the vision bolt-on item in an additional sample of 300 people. Main outcome measures: Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30 and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness. A full valuation study was conducted for the EQ + vision. Results: (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3 performed well for hearing and vision disorders. It also performed well in cancers although evidence was limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a limited dependent variable mixture model performed better than an equivalent linear model. In the full analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and tiredness had a significant impact on values of the health states, but the direction and magnitude of differences depended on the severity of the health state. The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated. Conclusions: EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons provide a promising solution. More primary research into the psychometric properties of the generic preference-based measures is required, particularly in cancer and for the assessment of reliability. Further research is needed for the development and valuation of bolt-ons to EQ-5D.UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486