Impact of Survey Administration Mode on the Results of a Health-Related Discrete Choice Experiment: Online and Paper Comparison.

BACKGROUND: Electronic data collection is increasingly being used for discrete choice experiments (DCEs). OBJECTIVES: To study whether paper or electronic administration results in measurement effects. METHODS: Respondents were drawn from the same sample frame (an Internet panel) and completed a nearly identical DCE survey either online or on paper during the same period. A DCE on preferences for basic health insurance served as a case study. We used panel mixed logit models for the analysis. RESULTS: In total, 898 respondents completed the survey: 533 respondents completed the survey online, whereas 365 respondents returned the paper survey. There were no significant differences with respect to sociodemographic characteristics between the respondents in both samples. The median response time was shorter for the online sample than for the paper sample, and a smaller proportion of respondents from the online sample were satisfied with the number of choice sets. Although some willingness- to-pay estimates were higher for the online sample, the elicited preferences for basic health insurance characteristics were similar between both modes of administration. CONCLUSIONS: We find no indication that online surveys yield inferior results compared with paper-based surveys, whereas the price per respondent is lower for online surveys. Researchers might want to include fewer choice sets per respondent when collecting DCE data online. Because our findings are based on a nonrandomized DCE that covers one health domain only, research in other domains is needed to support our findings.

Children's purchase behavior in the snack market: Can branding or lower prices motivate healthier choices?

BACKGROUND: Children's dietary-related diseases and their associated costs have expanded dramatically in many countries, making children's food choice a policy issue of increasing relevance. As children spend a considerable amount of money on energy-dense, nutrient-poor (EDNP) products, a better understanding of the main drivers of children's independent food purchase decisions is crucial to move this behavior toward healthier options. OBJECTIVE: The objective of the study is to investigate the role of branding and price in motivating children to choose healthier snack options. METHODS: The study investigates snack choices of children ages 8 to 11, using a survey and a purchase experiment. The research took place in after-school programs of selected schools in the Boston area. Participants included 116 children. Products in the choice experiment differed on three factors: product type, brand, and price. Data were analyzed using aggregated and mixed logit models. RESULTS: Children's purchase decisions are primarily determined by product type (Importance Value (IV) 56.6%), while brand (IV 22.8%) and price (IV 20.6%) prove to be of less relevance. Only those children who state that they like the familiar brand reveal a preference for the branded product in their purchase decision. Price is a significant predictor of choice when controlling for whether or not children obtain an allowance. CONCLUSION: It is not simple brand awareness but a child's liking of the brand that determines whether a brand is successful in motivating a child to choose a product. The extent of children's experience with money influences their price responsiveness. To the extent that children who receive an allowance are primarily the ones buying food snacks, higher prices for EDNP snacks could be successful in motivating children to choose a healthier option.

Women's choices of hospital for breast cancer surgery in Italy: Quality and equity implications.

This paper employs mixed logit regression to investigate the effects of providers characteristics on women's choice of hospital for breast surgery. Patient level data are used to model choices in Tuscany region, Italy. In particular, we focus on the effects of travel time and hospital quality indicators including quality standard (volumes of breast surgery), measurement of process (waiting times) and quality of surgical procedures. Variation in preferences related to individual characteristics such as age, education and travel distance from the hospital are also considered. Findings show that, on average, women prefer closer hospital with longer waiting times and higher quality (high volumes of interventions). We found preference heterogeneity associated to education: travel distance affects choice especially among less educated women (regardless of age), while among younger women (<65 years), less educated ones prefer shorter waiting times. These results could be used to optimize the allocation of resources toward breast cancer units that meet quality and efficacy standards to increase the efficiency and responsiveness of breast cancer care.

Exploring the factors contribute to the injury severities of vulnerable roadway user involved crashes.

The vehicle to pedestrian (V2P) applications will enable safety, mobility, and environmental advancements for the vulnerable roadway user (VRU) that current technologies are unable to provide. The present research aims to explore the use of random parameters in logit models to examine factors that significantly influence injury severity of VRU involved crashes. Two types of logit models, the mixed generalized ordered logit (MGOL) models and mixed logit models are proposed to provide insights on reducing injury severities of pedestrian and bicyclist involved crashes and benefit amending current V2P applications to address the special safety needs and challenges of these VRUs. Based on 9180 pedestrian involved crashes and 1402 bicyclist involved crashes from the Fatality Analysis Reporting System (FARS), the measure of injury severities - time-to-death is considered as the independent variables to capture a more comprehensive picture of events after a crash occurs. By comparing to the ordered logit models and the multinomial logit models, the effectiveness and appropriateness of the proposed models are verified through two perspectives - goodness of fit and predictive power. The modelling results show that the injury severity of VRU involved crashes is significantly associated with involved non-motorist characteristics (age and police reported alcohol involvement), involved motorist characteristics (drunk drivers, previous recorded crashes, number of occupants), involved vehicle characteristics (vehicle body type, vehicle model year, travel speed), roadway characteristics (interstate, junction, roadway profile), and environmental characteristics (light and weather condition). Among these significant factors, the number of occupants, vehicle body type, interstate, and junction result in random parameters, which capture and reflect the unobserved heterogeneity across sampled observations. The analyses of under-researched aspects of VRU involved crashes, that is time-to-death, help us develop a deeper understanding of the consequences of injury and ultimately health and social costs. The findings indicate that the proposed MGOL models and mixed logit models can account for the heterogeneity issues in crash data due to the unobserved factors. In addition, the injury severity models that incorporate the random parameter features can reveal new insights and have superior goodness of fit.