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To identify meaningful treatment attributes and quantify patient preferences for attributes of systemic atopic dermatitis (AD) treatments. Qualitative interviews were conducted with adults with moderate-to-severe AD (N = 21) to identify AD treatment attributes that patients consider most important and inform attribute selection for an online discrete-choice experiment (DCE) survey administered to patients in the United States with moderate-to-severe AD. Participants identified probability of clear/almost clear skin at 16 weeks, time to itch relief, mode of administration, and safety risks as very important. DCE data were analyzed using a random-parameters logit model to estimate the relative importance of treatment attributes and maximum acceptable risk. A total of 320 respondents completed the DCE survey (74% female; mean age, 35 years). Annual risk of malignancy was the most important attribute, followed by mode of administration, probability of clear skin at 16 weeks, and time to onset of itch relief. Respondents preferred daily oral treatment over injectable treatment. Respondents were willing to accept increases in adverse event risks for improvements in efficacy and mode of administration. The findings of this study can help inform joint patient-physician decision making in managing moderate-to-severe AD. [ABSTRACT FROM AUTHOR]

Objectives: Discrete choice experiments (DCEs) are increasingly used to elicit preferences for health and healthcare. Although many applications assume preferences are homogenous, there is a growing portfolio of methods to understand both explained (because of observed factors) and unexplained (latent) heterogeneity. Nevertheless, the selection of analytical methods can be challenging and little guidance is available. This study aimed to determine the state of practice in accounting for preference heterogeneity in the analysis of health-related DCEs, including the views and experiences of health preference researchers and an overview of the tools that are commonly used to elicit preferences.Methods: An online survey was developed and distributed among health preference researchers and nonhealth method experts, and a systematic review of the DCE literature in health was undertaken to explore the analytical methods used and summarize trends.Results: Most respondents (n = 59 of 70, 84%) agreed that accounting for preference heterogeneity provides a richer understanding of the data. Nevertheless, there was disagreement on how to account for heterogeneity; most (n = 60, 85%) stated that more guidance was needed. Notably, the majority (n = 41, 58%) raised concern about the increasing complexity of analytical methods. Of the 342 studies included in the review, half (n = 175, 51%) used a mixed logit with continuous distributions for the parameters, and a third (n = 110, 32%) used a latent class model.Conclusions: Although there is agreement about the importance of accounting for preference heterogeneity, there are noticeable disagreements and concerns about best practices, resulting in a clear need for further analytical guidance. [ABSTRACT FROM AUTHOR]

Objectives: Approximately 800 000 people die globally from colorectal cancer (CRC) every year. Prevention programs promote early detection, but for people with precancerous lesions, tailoring surveillance to include lifestyle-change programs could enhance prevention potential and improve outcomes.Methods: Those with intermediate or high-risk polyps removed during CRC screening colonoscopy within the Northern Ireland CRC Screening Programme were invited to complete 8 discrete choice questions about tailored surveillance, analyzed using random-parameters logit and a latent class modeling approach.Results: A total of 231 participants (77% male) self-reported comorbid hypertension (53%), high cholesterol (48%), and mean body mass index of 28.7 (overweight). Although 39% of participants were unaware of their CRC risk status, 30.9% indicated they were already making changes to reduce their risk. Although all respondents were significantly risk- and cost-averse, the latent class analysis identified 3 segments (classes): 1. Class 1 (26.8%) significantly favored phone or email support for a lifestyle change, a 17-month testing interval, and noninvasive testing. 2. Class 2 (48.4%) preferred the status quo. 3. Class 3 (24.7%) significantly favored further risk reduction and invasive testing.Conclusions: This is the first documented preference study focusing on postpolypectomy surveillance offering lifestyle interventions. Although current care is strongly preferred, risk and cost aversion are important for participants. Latent class analysis shows that some respondents are willing to change diet and lifestyle behaviors, reflecting a teachable moment, with opportunities to personalize and optimize surveillance. Significant discordance between perceived and known risk of recurrence and limited recall of risk information provided within current practice suggest necessary improvements to surveillance programs. [ABSTRACT FROM AUTHOR]

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as “good”; “sufficient”; or “corrective action needed” based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users. [ABSTRACT FROM AUTHOR]

While the repeated nature of discrete choice experiments is advantageous from a sampling efficiency perspective, patterns of choice may differ across the tasks, due, in part, to learning and fatigue. Using probabilistic decision process models, we find in a field study that learning and fatigue behavior may only be exhibited by a small subset of respondents. Most respondents in our sample show preference and variance stability consistent with rational pre-existent and well formed preferences. Nearly all of the remainder exhibit both learning and fatigue effects. An important aspect of our approach is that it enables learning and fatigue effects to be explored, even though they were not envisaged during survey design or data collection. [ABSTRACT FROM AUTHOR]