Do labeled versus unlabeled treatments of alternatives' names influence stated choice outputs? Results from a mode choice study.
ABSTRACT: Discrete choice experiments have been widely applied to elicit behavioral preferences in the literature. In many of these experiments, the alternatives are named alternatives, meaning that they are naturally associated with specific names. For example, in a mode choice study, the alternatives can be associated with names such as car, taxi, bus, and subway. A fundamental issue that arises in stated choice experiments is whether to treat the alternatives' names as labels (that is, labeled treatment), or as attributes (that is, unlabeled treatment) in the design as well as the presentation phases of the choice sets. In this research, we investigate the impact of labeled versus unlabeled treatments of alternatives' names on the outcome of stated choice experiments, a question that has not been thoroughly investigated in the literature. Using results from a mode choice study, we find that the labeled or the unlabeled treatment of alternatives' names in either the design or the presentation phase of the choice experiment does not statistically affect the estimates of the coefficient parameters. We then proceed to measure the influence toward the willingness-to-pay (WTP) estimates. By using a random-effects model to relate the conditional WTP estimates to the socioeconomic characteristics of the individuals and the labeled versus unlabeled treatments of alternatives' names, we find that: a) Given the treatment of alternatives' names in the presentation phase, the treatment of alternatives' names in the design phase does not statistically affect the estimates of the WTP measures; and b) Given the treatment of alternatives' names in the design phase, the labeled treatment of alternatives' names in the presentation phase causes the corresponding WTP estimates to be slightly higher.
Project description:<h4>Background</h4>Dry powder inhalers (DPIs) are often used in asthma and chronic obstructive pulmonary disease (COPD) therapies. Using the discrete choice experiment (DCE) methodology, this study conducted in France was designed to assess patients' preferences for different attributes of DPIs.<h4>Methods</h4>Attributes of DPIs were defined based on a literature review, patient focus group discussions and interviews with healthcare professionals (qualitative phase of the study). An online survey was then conducted among French patients with asthma or COPD to elicit patient preferences and willingness to pay (WTP) for these attributes using the DCE methodology (quantitative phase). A fractional factorial design including three blocks of 12 choice sets was created. Each choice set comprised three alternatives: two fictitious inhalers and the patient's current inhaler. Marginal utilities were estimated using a ranked ordered logit model. Interactions between attributes and disease (asthma or COPD) were tested.<h4>Results</h4>Six DPI attributes were defined based on the qualitative phase: ease of use/fool-proof priming; accurate and easy-to-read dose counter; dose confirmation; hygiene of the mouthpiece; flexibility of the device handling; ability to use the inhaler with breathing difficulties. Overall, 201 patients with asthma and 93 with COPD were included in the online survey. Patients with asthma placed most value on an inhaler that requires one step for dose preparation (WTP €4.83 [95% CI: €3.77-€5.90], relative to an inhaler requiring four steps) and one that could be used during episodes of breathing difficulties (WTP €4.49 [95% CI: €2.95-€6.02]). Patients with COPD placed most value on an inhaler that could be used during episodes of breathing difficulties (WTP €7.70 [95% CI: €5.65-€9.76]) and on the accuracy of the dose counter (WTP €5.87 [95% CI: €3.98-€ 7.77]).<h4>Conclusion</h4>This study suggests that asthma and COPD patients would be willing to change their inhaler if they were offered the option of a new inhaler with improved characteristics and they place a high value on an inhaler with ease of use during breathing difficulty episodes.
Project description:Value-based decision making occurs when individuals choose between different alternatives and place a value on each alternative and its attributes. Marketing actions frequently manipulate product attributes, by adding, e.g., health claims on the packaging. A previous imaging study found that an emblem for organic products increased willingness to pay (WTP) and activity in the ventral striatum (VS). The current study investigated neural and behavioral processes underlying the influence of Fair Trade (FT) labeling on food valuation and choice. Sustainability is an important product attribute for many consumers, with FT signals being one way to highlight ethically sustainable production. Forty participants valuated products in combination with an FT emblem or no emblem and stated their WTP in a bidding task while in an MRI scanner. After that, participants tasted-objectively identical-chocolates, presented either as "FT" or as "conventionally produced". In the fMRI task, WTP was significantly higher for FT products. FT labeling increased activity in regions important for reward-processing and salience, that is, in the VS, anterior and posterior cingulate, as well as superior frontal gyrus. Subjective value, that is, WTP was correlated with activity in the ventromedial prefrontal cortex (vmPFC). We find that the anterior cingulate, VS and superior frontal gyrus exhibit task-related increases in functional connectivity to the vmPFC when an FT product was evaluated. Effective connectivity analyses revealed a highly probable directed modulation of the vmPFC by those three regions, suggesting a network which alters valuation processes. We also found a significant taste-placebo effect, with higher experienced taste pleasantness and intensity for FT labeled chocolates. Our results reveal a possible neural mechanism underlying valuation processes of certified food products. The results are important in light of understanding current marketing trends as well as designing future interventions that aim at positively influencing food choice.
Project description:We study the literature on willingness to pay (WTP) for local food by applying meta-regression analysis to a set of 35 eligible research papers that provide 86 estimates on consumers' WTP for the attribute "local." An analysis of the distribution of WTP measures suggests the presence of publication selection bias that favors larger and statistically significant results. The analyzed literature provides evidence for statistically significant differences among consumers' WTP for various types of product. Moreover, we find that the methodological approach (choice experiments vs. other approaches) and the analyzed country can have a significant influence on the generated WTP for local.
Project description:Both cisgenesis and transgenesis are plant breeding techniques that can be used to introduce new genes into plant genomes. However, transgenesis uses gene(s) from a non-plant organism or from a donor plant that is sexually incompatible with the recipient plant while cisgenesis involves the introduction of gene(s) from a crossable--sexually compatible--plant. Traditional breeding techniques could possibly achieve the same results as those from cisgenesis, but would require a much larger timeframe. Cisgenesis allows plant breeders to enhance an existing cultivar more quickly and with little to no genetic drag. The current regulation in the European Union (EU) on genetically modified organisms (GMOs) treats cisgenic plants the same as transgenic plants and both are mandatorily labeled as GMOs. This study estimates European consumers' willingness-to-pay (WTP) for rice labeled as GM, cisgenic, with environmental benefits (which cisgenesis could provide), or any combination of these three attributes. Data were collected from 3,002 participants through an online survey administered in Belgium, France, the Netherlands, Spain and the United Kingdom in 2013. Censored regression models were used to model consumers' WTP in each country. Model estimates highlight significant differences in WTP across countries. In all five countries, consumers are willing-to-pay a premium to avoid purchasing rice labeled as GM. In all countries except Spain, consumers have a significantly higher WTP to avoid consuming rice labeled as GM compared to rice labeled as cisgenic, suggesting that inserting genes from the plant's own gene pool is more acceptable to consumers. Additionally, French consumers are willing-to-pay a premium for rice labeled as having environmental benefits compared to conventional rice. These findings suggest that not all GMOs are the same in consumers' eyes and thus, from a consumer preference perspective, the differences between transgenic and cisgenic products are recommended to be reflected in GMO labeling and trade policies.
Project description:There is considerable evidence that labeling supports infants' object categorization. Yet in daily life, most of the category exemplars that infants encounter will remain unlabeled. Inspired by recent evidence from machine learning, we propose that infants successfully exploit this sparsely labeled input through "semi-supervised learning." Providing only a few labeled exemplars leads infants to initiate the process of categorization, after which they can integrate all subsequent exemplars, labeled or unlabeled, into their evolving category representations. Using a classic novelty preference task, we introduced 2-year-old infants (n = 96) to a novel object category, varying whether and when its exemplars were labeled. Infants were equally successful whether all exemplars were labeled (fully supervised condition) or only the first two exemplars were labeled (semi-supervised condition), but they failed when no exemplars were labeled (unsupervised condition). Furthermore, the timing of the labeling mattered: when the labeled exemplars were provided at the end, rather than the beginning, of familiarization (reversed semi-supervised condition), infants failed to learn the category. This provides the first evidence of semi-supervised learning in infancy, revealing that infants excel at learning from exactly the kind of input that they typically receive in acquiring real-world categories and their names.
Project description:To elicit prescribers' preferences for behavioural economics interventions designed to reduce inappropriate antibiotic prescribing, and compare these to actual behaviour.Discrete choice experiment (DCE).47 primary care centres in Boston and Los Angeles.234 primary care providers, with an average 20?years of practice.Results of a behavioural economic intervention trial were compared to prescribers' stated preferences for the same interventions relative to monetary and time rewards for improved prescribing outcomes. In the randomised controlled trial (RCT) component, the 3 computerised prescription order entry-triggered interventions studied included: Suggested Alternatives (SA), an alert that populated non-antibiotic treatment options if an inappropriate antibiotic was prescribed; Accountable Justifications (JA), which prompted the prescriber to enter a justification for an inappropriately prescribed antibiotic that would then be documented in the patient's chart; and Peer Comparison (PC), an email periodically sent to each prescriber comparing his/her antibiotic prescribing rate with those who had the lowest rates of inappropriate antibiotic prescribing. A DCE study component was administered to determine whether prescribers felt SA, JA, PC, pay-for-performance or additional clinic time would most effectively reduce their inappropriate antibiotic prescribing. Willingness-to-pay (WTP) was calculated for each intervention.In the RCT, PC and JA were found to be the most effective interventions to reduce inappropriate antibiotic prescribing, whereas SA was not significantly different from controls. In the DCE however, regardless of treatment intervention received during the RCT, prescribers overwhelmingly preferred SA, followed by PC, then JA. WTP estimates indicated that each intervention would be significantly cheaper to implement than pay-for-performance incentives of $200/month.Prescribing behaviour and stated preferences are not concordant, suggesting that relying on stated preferences alone to inform intervention design may eliminate effective interventions.NCT01454947; Results.
Project description:INTRODUCTION:Patient-reported experience measures (PREMs) are central to inform on the responsiveness of health systems to citizens' health care needs and expectations. At their current form, PREMs do not reflect the weights that patients assign to varying aspects of the care experience. We aimed to investigate patients' preferences and willingness to pay (WTP) for attributes of the care experience in outpatient settings. METHODS:A discrete choice experiment was conducted among a representative sample of the general adult population of Hungary (n = 1000). Choice set attributes and levels were defined based on OECD's standardized PREMs (e.g. a doctor spending enough time in consultation, providing easy to understand explanations, giving opportunity to ask questions, and involving in decision making) and a price attribute. Conditional and mixed logit analyses were conducted. WTP estimates were computed in preference and WTP space. RESULTS:The respondents most preferred attribute was that of a doctor spending enough time in consultation, followed by involvement in decision making. Moreover, waiting times had a less important effect on respondents' choice preference compared with aspects of the doctor-patient relationship. Estimates in the WTP space varied from €4.38 (2.85-5.90) for waiting an hour less at a doctor's office to €36.13 (32.07-40.18) for a consultation where a doctor spends enough time with a patient relative to a consultation where a doctor does not. CONCLUSIONS:A preference-based PREMs approach provide insight on the value patients assign to different aspects of their care experience. This can inform the decisions of policy-makers and other stakeholders to coordinate efforts and resource allocation in a more targeted manner, by acting on attributes of the care experience that have a greater impact on the implementation of patient-centered care.
Project description:Objective:Standards such as the Logical Observation Identifiers Names and Codes (LOINC®) are critical for interoperability and integrating data into common data models, but are inconsistently used. Without consistent mapping to standards, clinical data cannot be harmonized, shared, or interpreted in a meaningful context. We sought to develop an automated machine learning pipeline that leverages noisy labels to map laboratory data to LOINC codes. Materials and Methods:Across 130 sites in the Department of Veterans Affairs Corporate Data Warehouse, we selected the 150 most commonly used laboratory tests with numeric results per site from 2000 through 2016. Using source data text and numeric fields, we developed a machine learning model and manually validated random samples from both labeled and unlabeled datasets. Results:The raw laboratory data consisted of >6.5 billion test results, with 2215 distinct LOINC codes. The model predicted the correct LOINC code in 85% of the unlabeled data and 96% of the labeled data by test frequency. In the subset of labeled data where the original and model-predicted LOINC codes disagreed, the model-predicted LOINC code was correct in 83% of the data by test frequency. Conclusion:Using a completely automated process, we are able to assign LOINC codes to unlabeled data with high accuracy. When the model-predicted LOINC code differed from the original LOINC code, the model prediction was correct in the vast majority of cases. This scalable, automated algorithm may improve data quality and interoperability, while substantially reducing the manual effort currently needed to accurately map laboratory data.
Project description:Sedimentation velocity analytical ultracentrifugation (SV) is a powerful first-principle technique for the study of protein interactions, and allows a rigorous characterization of binding stoichiometry and affinities. A recently introduced commercial fluorescence optical detection system (FDS) permits analysis of high-affinity interactions by SV. However, for most proteins the attachment of an extrinsic fluorophore is an essential prerequisite for analysis by FDS-SV. Using the glutamate receptor GluA2 amino terminal domain as a model system for high-affinity homo-dimerization, we demonstrate how the experimental design and choice of fluorescent label can impact both the observed binding constants as well as the derived hydrodynamic parameter estimates for the monomer and dimer species. Specifically, FAM (5,6-carboxyfluorescein) was found to create different populations of artificially high-affinity and low-affinity dimers, as indicated by both FDS-SV and the kinetics of dimer dissociation studied using a bench-top fluorescence spectrometer and Förster Resonance Energy Transfer. By contrast, Dylight488 labeled GluA2, as well as GluA2 expressed as an EGFP fusion protein, yielded results consistent with estimates for unlabeled GluA2. Our study suggests considerations for the choice of labeling strategies, and highlights experimental designs that exploit specific opportunities of FDS-SV for improving the reliability of the binding isotherm analysis of interacting systems.
Project description:Biotechnology can provide innovative and efficient tools to support sustainable development of aquaculture. It is generally accepted that use of the term 'genetically modified' causes controversy and conflict among consumers, but little is known about how using the term 'biotechnology' as a salient feature on product packaging affects consumer preferences. In an online discrete choice experiment consisting of two treatments, a set of 1005 randomly chosen Swedish consumers were surveyed about use of hormone and triploidization sterilization techniques for salmonids. The information given to the treatment group included an additional sentence stating that the triploidization technique is an application of biotechnology, while the control group received the same text but without reference to biotechnology. Analysis using a hierarchical Bayes approach revealed significant consumer reactions to the term biotechnology. When the term was included in information, variation in consumer willingness-to-pay (WTP) estimates increased significantly. Moreover, some participants were dissuaded towards an option guaranteeing no biotechnological intervention in production of fish. These results have multiple implications for research and for the food industry. For research, they indicate the importance of examining the distribution of variation in WTP estimates for more complete characterization of the effects of information on consumer behavior. For the food industry, they show that associating food with biotechnology creates more variability in demand. Initiatives should be introduced to reduce the confusion associated with the term biotechnology among consumers.