Preference analysis in adventure sport recreation: application of discrete choice experiments

Background Two previous systematic reviews have summarised the application of discrete choice experiments to value preferences for pharmacy services. These reviews identified a total of twelve studies and described how discrete choice experiments have been used to value pharmacy services but did not describe or discuss the application of methods used in the design or analysis. Aims (1) To update the most recent systematic review and critically appraise current discrete choice experiments of pharmacy services in line with published reporting criteria and; (2) To provide an overview of key methodological developments in the design and analysis of discrete choice experiments. Methods The review used a comprehensive strategy to identify eligible studies (published between 1990 and 2015) by searching electronic databases for key terms related to discrete choice and best-worst scaling (BWS) experiments. All healthcare choice experiments were then hand-searched for key terms relating to pharmacy. Data were extracted using a published checklist. Results A total of 17 discrete choice experiments eliciting preferences for pharmacy services were identified for inclusion in the review. No BWS studies were identified. The studies elicited preferences from a variety of populations (pharmacists, patients, students) for a range of pharmacy services. Most studies were from a United Kingdom setting, although examples from Europe, Australia and North America were also identified. Discrete choice experiments for pharmacy services tended to include more attributes than non-pharmacy choice experiments. Few studies reported the use of qualitative research methods in the design and interpretation of the experiments (n=9) or use of new methods of analysis to identify and quantify preference and scale heterogeneity (n=4). No studies reported the use of Bayesian methods in their experimental design. Conclusion Incorporating more sophisticated methods in the design of pharmacy-related discrete choice experiments could help researchers produce more efficient experiments which are better suited to valuing complex pharmacy services. Pharmacy-related discrete choice experiments could also benefit from more sophisticated analytical techniques such as investigations into scale and preference heterogeneity. Employing these sophisticated methods for both design and analysis could extend the usefulness of discrete choice experiments to inform health and pharmacy policy.

ObjectivesThe medical security of orphan drugs faces difficulty in basic medical insurance access in China. Conventional cost-effectiveness analysis in the access process lacks broader value concerns and a value assessment framework is needed. This study aims to construct a multicriteria decision analysis value assessment framework for orphan drugs using the discrete choice experiment method from the perspective of basic medical insurance access in China.MethodsThe attributes and levels of the framework were identified through literature and reports review. An unlabeled discrete choice experiment was employed to determine the relevance and relative importance weight of such attributes for decision-making. Questionnaire was designed based on D-efficient design. Survey was conducted anonymously using an online survey platform. A mixed logit model estimated the DCE responses.ResultsSeven attributes (disease severity, unmet needs, drug efficacy, improvement in health-related quality of life, drug safety, quality of drug evidence, and annual treatment cost per patient reimbursed by basic medical insurance) were selected with three levels for each. It formed three parallel questionnaires, each containing 11 paired choice sets. A total of 84 respondents completed the study, and 69 questionnaires were valid. The results showed that six of the seven attributes were significant, except for ‘Unmet needs’. Among all attributes and levels, the respondents exhibited the highest WTP (567,900 RMB/year) for ‘significant improvement in usual activities’. Based on discrete choice model, the most important attributes measured by their relative importance weights are: improvement in health-related quality of life (23.44%), disease severity (18.65%) and annual treatment cost per patient reimbursed by basic medical insurance (17.34%). Different types of respondents and weighting methods may lead to slight variations in the results.ConclusionOur study provides a new research perspective and methodological support for the value assessment of orphan drugs. When establishing a value assessment framework for orphan drugs in China, overall, the medical insurance access prioritized disease severity, and improvement in health-related quality of life. The application of discrete choice experiment proves to be a powerful tool for weighting criteria in healthcare multicriteria decision analysis framework and should be further explored for the value assessment of orphan drugs. Our findings offer a structured, evidence-based framework to support access and reimbursement decisions for orphan drugs.

This study aims to contribute to the existing literature by verifying whether the degree of liking of a new food product influences people’s preferences and willingness to pay from a discrete choice experiment when dealing with sustainable food products. To this purpose, we considered the case study of the introduction into the Italian market of a new food product: tinned Chianina meat. Among the attributes considered for this new product, two in particular were related to sustainability: organic breeding and the preservation of a traditional rural landscape. Half of the respondents underwent a sensory test before taking part in the hypothetical market (discrete choice experiment), while the remaining were administered the tests in reverse order. Tasting the product before the discrete choice experiment did not produce different willingness to pay (WTP) parameters as estimated by a taste factor interaction. However, separating the respondents into those who liked or disliked the product in the tasting condition revealed differences in willingness to pay results. The preferences are different for more than 50% of the attributes considered, and the magnitude of this difference is quite relevant. The WTP for one well known and certified sustainability related attribute—organic breeding—was not affected by the liking, while, for the other—the preservation of a traditional rural landscape—the effect of liking decreases the WTP. As a consequence, we suggest that tasting and liking studies should be routinely coupled with discrete choice studies when analyzing the introduction of new food products, especially when considering sustainable attributes in the experimental design. In the case of organic products where the expectations about taste are higher, neglecting to consider their sensory perception, along with the other discrete choice experiment attributes, could seriously undermine their long lasting success on the market.

This paper considers issues raised in the application of discrete choice experiments (DCEs) to estimating willingness to pay (WTP). The main issue addressed is the sensitivity of WTP estimates to the level of attributes. A DCE, concerned with preferences for alternative cervical screening programmes, was carried out with women in the Tayside area of Scotland. A split sample design was employed in which respondents were divided into two groups. Each group received a discrete choice questionnaire that varied with respect to the levels of three of the six attributes. The price attribute was one of the attributes that varied across questionnaires. Whilst estimated coefficients were not significantly different across five of the six attributes included in the experiment, mean WTP estimates were significantly different for four of the five welfare estimates. However, from a policy point of view, such a difference may not be important. Consideration is also given to other general methodological and policy issues that are raised when using DCEs to estimate WTP. The findings suggest the need for further research into the design and application of DCEs as a method for estimating WTP.

SF-6D utility weights are conventionally produced using a standard gamble (SG). SG-derived weights consistently demonstrate a floor effect not observed with other elicitation techniques. Recent advances in discrete choice methods have allowed estimation of utility weights. The objective was to produce Australian utility weights for the SF-6D and to explore the application of discrete choice experiment (DCE) methods in this context. We hypothesized that weights derived using this method would reflect the largely monotonic construction of the SF-6D. We designed an online DCE and administered it to an Australia-representative online panel (n = 1017). A range of specifications investigating nonlinear preferences with respect to additional life expectancy were estimated using a random-effects probit model. The preferred model was then used to estimate a preference index such that full health and death were valued at 1 and 0, respectively, to provide an algorithm for Australian cost-utility analyses. Physical functioning, pain, mental health, and vitality were the largest drivers of utility weights. Combining levels to remove illogical orderings did not lead to a poorer model fit. Relative to international SG-derived weights, the range of utility weights was larger with 5% of health states valued below zero. s. DCEs can be used to investigate preferences for health profiles and to estimate utility weights for multi-attribute utility instruments. Australian cost-utility analyses can now use domestic SF-6D weights. The comparability of DCE results to those using other elicitation methods for estimating utility weights for quality-adjusted life-year calculations should be further investigated.

Discrete choice experiments (DCEs) are a common method used to describe and quantitatively assess preferences in health applications. Increasingly, DCEs have been used to elicit preferences from children and adolescents and generate evidence to inform policies affecting this population. The aim of this review was to summarize and describe the application of DCEs conducted with children and adolescents and describe author-reported age-specific considerations in design, implementation, and analysis. A scoping review was conducted using a 'pearl-growing' technique whereby the reference lists of existing systematic reviews of DCEs were used to identify potential studies conducted with children or adolescents as respondents published between 1990 and 2017. This list was supplemented with an updated electronic search using the same strategy as the initial reviews to identify studies from 2017 to 2020. Of 480 studies identified, 19 were included; topics included vaccines (32%), drugs/medical devices (26%), treatment or health promotion interventions/programs (21%), warning labels on cigarettes/nicotine products (10%), and preferences for physical activity and healthy food choices (10%). The youngest reported age for independent DCE completion was 8 years. Approaches to assessing validity and reliability of choices were consistent with best practices for the conduct of DCEs. Reported age-specific considerations included use of visual aids, age-appropriate language, reducing task complexity and cognitive burden, and exploration of interpretation of willingness-to-pay. The number of DCEs conducted with children and adolescents has increased in recent years. Detailed explanation of why reported age-specific considerations were necessary, how they could be used to interpret results, or to understand the appropriateness of this methodology for different age groups was limited. Despite a recognition of the need for special consideration when conducting DCEs in this population, the unique issues in the context of age-specific considerations are largely unexplored, and further research is required. Moving forward, stated preference research conducted with children and adolescents should report in more detail methods of recruitment, results of validity assessments, and provide specific reflection on the extent to which modeled results are consistent with expectations and underlying theory.

ObjectivesUnderstanding young people’s preferences for healthcare is critical for reducing the negative effect of undesirable choices. This review aims to synthesise the evidence obtained from discrete choice experiments (DCEs) eliciting young people’s preferences for healthcare interventions and service deliveries, specifically, to (1) examine the methodology, including a selection of attributes and levels, experimental design, estimation procedure and validity; (2) evaluate similarities, differences and rigour of designs to the general population DCEs; and, (3) compare the DCEs’ application to the seven health priority areas defined by the World Health Organisation (WHO).MethodsA systematic review searching Medline, EconLIT, PsychINFO, Scopus, and Web of Science was performed up until May 2021. Inclusion criteria: a DCE, eliciting young peoples’ preferences (10–24 years of age), on a healthcare-related topic defined by WHO, peer-reviewed, full-text available in English. A bespoke checklist was used to assess the methodological quality of the included studies.ResultsEighteen DCE studies were included in the review, exploring interventions and service in sexual and reproductive health (n = 9; 50%), smoking cessation (n = 4; 22%), mental health (n = 1), nutrition (n = 1), unintentional injuries (n = 1), vaccination against severe but rare diseases (n = 1); and diabetes (n = 1). Compared to the general population, DCEs eliciting young people’s preferences had a high proportion of monetary measures and a smaller number of choices per respondent with the overwhelming number of surveys using fractional factorial design. The majority of studies were of moderate quality (50–75% of the criteria met).ConclusionsWhile identified DCEs touched on most health priority areas, the scope was limited. The conduct and reporting of DCEs with young people could be improved by including the state-of-the-art design, estimation procedures and analysis.

BackgroundDiscrete choice experiments have become a popular study design to study the labour market preferences of health workers. Discrete choice experiments in health, however, have been criticised for lagging behind best practice and there are specific methodological considerations for those focused on job choices. We performed a systematic review of the application of discrete choice experiments to inform health workforce policy.MethodsWe searched for discrete choice experiments that examined the labour market preferences of health workers, including doctors, nurses, allied health professionals, mid-level and community health workers. We searched Medline, Embase, Global Health, other databases and grey literature repositories with no limits on date or language and contacted 44 experts. Features of choice task and experimental design, conduct and analysis of included studies were assessed against best practice. An assessment of validity was undertaken for all studies, with a comparison of results from those with low risk of bias and a similar objective and context.ResultsTwenty-seven studies were included, with over half set in low- and middle-income countries. There were more studies published in the last four years than the previous ten years. Doctors or medical students were the most studied cadre. Studies frequently pooled results from heterogeneous subgroups or extrapolated these results to the general population. Only one third of studies included an opt-out option, despite all health workers having the option to exit the labour market. Just five studies combined results with cost data to assess the cost effectiveness of various policy options. Comparison of results from similar studies broadly showed the importance of bonus payments and postgraduate training opportunities and the unpopularity of time commitments for the uptake of rural posts.ConclusionsThis is the first systematic review of discrete choice experiments in human resources for health. We identified specific issues relating to this application of which practitioners should be aware to ensure robust results. In particular, there is a need for more defined target populations and increased synthesis with cost data. Research on a wider range of health workers and the generalisability of results would be welcome to better inform policy.Electronic supplementary materialThe online version of this article (doi:10.1186/1472-6963-14-367) contains supplementary material, which is available to authorized users.

Compared to many applied areas of economics, health economics has a strong tradition in eliciting and using stated preferences (SP) in policy analysis. Discrete choice experiments (DCEs) are one SP method increasingly used in this area. Literature on DCEs in health and more generally has grown rapidly since the mid-1990s. Applications of DCEs in health have come a long way, but to date few have been 'best practice', in part because 'best practice' has been somewhat of a moving target. The purpose of this paper is to briefly survey the history of DCEs and the state of current knowledge, identify and discuss knowledge gaps, and suggest potentially fruitful areas for future research to fill such gaps with the aim of moving the application of DCEs in health economics closer to best practice.

Discrete choice experiments are increasingly used to assess preferences for vaccines and vaccine service delivery. To synthesize and critically assess the application of discrete choice experiments in childhood/adolescent vaccines, to describe how discrete choice experiments have been applied to understand preferences, and to evaluate the use of discrete choice experiment data to inform estimates of vaccine uptake. We conducted a systematic review of six electronic databases. Included studies were discrete choice experiments and conjoint analyses published from 2000 to 2016 related to childhood/adolescent vaccines where respondents were parents, children/adolescents, or service providers. Validity assessment was used to assess study quality and risk of bias. In total, 27 articles were included, representing 21 different studies. A majority of articles were published between 2011 and 2016. Vaccines studied included human papillomavirus (24%), influenza (19%), meningococcal vaccines (14%), childhood vaccines (14%), hypothetical vaccines (10%), hepatitis B (5%), and diphtheria, tetanus, pertussis, hepatitis B, poliomyelitis, and Haemophilus influenzae type b (5%). Most studies assessed parent preferences (67%). The most common attributes were risk (24%), degree/duration of protection (21%), and cost (15%). Commonly reported outcome measures were estimates of uptake (33%), willingness-to-pay (22%), and other marginal rates of substitution (14%). Validity assessments yielded high scores overall. Areas of weakness included low response rates, inefficient experimental design, and failure to conduct formative qualitative work and a pilot of the discrete choice experiment. This is the first systematic review of childhood/adolescent vaccine-related discrete choice experiments. In future, special attention should be paid to ensuring that choice context and discrete choice experiment design are compatible to generate reliable estimates of uptake.

BackgroundOne of the key strategies to successful implementation of effective health-related interventions is targeting improvements in stakeholder engagement. The discrete choice experiment (DCE) is a stated preference technique for eliciting individual preferences over hypothetical alternative scenarios that is increasingly being used in health-related applications. DCEs are a dynamic approach to systematically measure health preferences which can be applied in enhancing stakeholder engagement. However, a knowledge gap exists in characterizing the extent to which DCEs are used in implementation science.MethodsWe conducted a systematic literature search (up to December 2016) of the English literature to identify and describe the use of DCEs in engaging stakeholders as an implementation strategy. We searched the following electronic databases: MEDLINE, Econlit, PsychINFO, and the CINAHL using mesh terms. Studies were categorized according to application type, stakeholder(s), healthcare setting, and implementation outcome.ResultsSeventy-five publications were selected for analysis in this systematic review. Studies were categorized by application type: (1) characterizing demand for therapies and treatment technologies (n = 32), (2) comparing implementation strategies (n = 22), (3) incentivizing workforce participation (n = 11), and (4) prioritizing interventions (n = 10). Stakeholders included providers (n = 27), patients (n = 25), caregivers (n = 5), and administrators (n = 2). The remaining studies (n = 16) engaged multiple stakeholders (i.e., combination of patients, caregivers, providers, and/or administrators). The following implementation outcomes were discussed: acceptability (n = 75), appropriateness (n = 34), adoption (n = 19), feasibility (n = 16), and fidelity (n = 3).ConclusionsThe number of DCE studies engaging stakeholders as an implementation strategy has been increasing over the past decade. As DCEs are more widely used as a healthcare assessment tool, there is a wide range of applications for them in stakeholder engagement. The DCE approach could serve as a tool for engaging stakeholders in implementation science.

Objective This paper describes the application of discrete choice experiments (DCEs), in the measurement of consumers' preferences for pharmacy services. Summary Patients' preferences for healthcare influence strongly their use of services. Quantifying revealed preferences for services (what services people use) is not always possible because either the service does not yet exist or the consumer has no experience of it. There is a need for tools that measure stated preference (what people say they will do) for healthcare, to allow development of new services. DCEs have been used in the valuation of preferences for healthcare services and interventions and can be applied usefully to the valuation of preferences for pharmacy services. DCEs assume that preferences are based on preferences for different attributes of a service, and that consumers are prepared to trade off one attribute against another, such as effectiveness versus side-effects. In a DCE study, respondents make hypothetical choices between scenarios of services with fixed attributes, but varying levels, revealing their strength of preference for attributes of that service. These data are analysed using regression, which generates coefficients that quantify the direction and magnitude of preferences. Marginal rates of substitution and willingness to pay for each attribute can be estimated, which provide powerful information for future service provision. For this approach to be applied in practice, key methodological issues must be handled explicitly, principally scenario design, attribute and level selection, orthogonality, level balance, minimal overlap and utility balance. A hypothetical example of a DCE designed for valuing consumers' preferences for a medication review service for the elderly is described.

The study of human behaviour has been cementing its place within economics for decades. The complexity of decisions in family farming, challenging agricultural markets, and climate change have drawn attention to human behaviour, namely risk perceptions and the decision-making process, with a focus on agricultural economics. This paper reviews current knowledge on risk management in agriculture from the behavioral perspective, and from the perspective experimental economics in particular, emphasizing a discrete choice experiment approach. A discrete choice experiment (DCE) elicits stated preferences through hypothetical choices and have been extensively applied in research on risk preferences and farmers’ willingness to apply different risk management strategies. The objective of this paper was to determine the frequency at which papers are published and their use in discrete choice experiments in general and in agriculture and emphasizes risk management in agriculture using bibliometric analysis. The PRISMA framework was used for a systematic literature review of the agricultural risk management publications that apply a DCE. The main steps to achieve the aforementioned goals are to define how many publications are primary research versus theoretical publications in the research area of agricultural risk management, which part of risk management in agriculture it covers, and how many attributes were used in each study. The authors reviewed 20 papers based on the following keyword criteria: discrete choice experiment, agriculture, risk management, and the period 2001–2021, using the Web of Science database. The results show an increase in DCE publications over the past 20 years. A comprehensive literature review of risk management in agriculture concluded that publications are primarily research focused, mainly consider on-farm strategies and smaller-scale risk-transfer strategies, and are predominantly conducted among farmers. The average number of attributes per publication is four to five. Limitations and directions for future research are discussed in the paper.

Discrete choice experiments are a robust technique for quantifying preferences. With this method, respondents are presented with a series of hypothetical comparisons described by attributes with varying levels. The aggregated choices from respondents can be used to infer the relative importance of the described attributes and acceptable trade-offs between attributes. The data generated from discrete choice experiments can aid surgeons in aligning patient values with treatment decisions and support the design of research that is responsive to patient preferences. This article summarizes the application of discrete choice experiments to orthopaedics. We share best practices for designing discrete choice experiments and options for reporting study results. Finally, we suggest opportunities for this method within our field.

The purpose of this study was to examine and compare parent preferences of before and after school physical activity program components in rural and suburban elementary schools. A discrete choice experiment was conducted to measure parent preferences for components of before/after school programs. A total of 183 parents (age = 37.2 [8.2]y, 155 females) sampled from 15 elementary schools (K-6 grades) in the Western United States took part in the study, half of which were from a rural community (n = 93, 50.8%). Results from the discrete choice experiment were analyzed using hierarchic Bayesian methodology, which estimated utility scores and was used to calculate important scores for program components. The specific goal of the before/after school program was the strongest determinant of parents' stated choice overall, followed by leaders, time of day, length, and main focus. Learning sports as the physical activity goal was the top-rated attribute. Subgroup analyses revealed discrepancies between suburban and rural parents and parents of boys and girls. This study extends the application of discrete choice experiments to school-based programming, providing a unique way to design empirically based, stakeholder informed school programs, specifically within before and after school settings.