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Decision aids empower patients to understand how treatment options match their preferences. Choice experiments, a method to clarify values used within decision aids, present patients with hypothetical scenarios to reveal their preferences for treatment characteristics. Given the rise in research embedding choice experiments in decision tools and the emergence of novel developments in embedding methodology, a scoping review is warranted. This scoping review examines how choice experiments are embedded into decision tools and how these tools are evaluated, to identify best practices. This scoping review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Searches were conducted on MEDLINE, PsycInfo, and Web of Science. The methodology, development and evaluation details of decision aids were extracted and summarized using narrative synthesis. Overall, 33 papers reporting 22 tools were included in the scoping review. These tools were developed for various health conditions, including musculoskeletal (7/22, 32%), oncological (8/22, 36%), and chronic conditions (7/22, 32%). Most decision tools (17/22, 77%) were developed in the United States, with the remaining tools originating in the Netherlands, United Kingdom, Canada, and Australia. The number of publications increased, with 73% (16/22) published since 2015, peaking at 4 publications in 2019. The primary purpose of these tools (20/22, 91%) was to help patients compare or choose treatments. Adaptive conjoint analysis was the most frequently used design type (10/22, 45%), followed by conjoint analysis and discrete choice experiments (DCEs; both 4/22, 18%), modified adaptive conjoint analysis (3/22, 14%), and adaptive best-worst conjoint analysis (1/22, 5%). The number of tasks varied depending on the design (6-12 for DCEs and adaptive conjoint vs 16-20 for conjoint analysis designs). Sawtooth software was commonly used (14/22, 64%) to embed choice tasks. Four proof-of-concept embedding methods were identified: scenario analysis, known preference phenotypes, Bayesian collaborative filtering, and penalized multinomial logit model. After completing the choice tasks patients received tailored information, 73% (16/22) of tools provided attribute importance scores, and 23% (5/22) presented a \"best match\" treatment ranking. To convey probabilistic attributes, most tools (13/22, 59%) used a combination of approaches, including percentages, natural frequencies, icon arrays, narratives, and videos. The tools were evaluated across diverse study designs (randomized controlled trials, mixed methods, and cohort studies), with sample sizes ranging from 23 to 743 participants. Over 40 different outcomes were included in the evaluations, with the decisional conflict scale being the most frequently used in 6 tools. This scoping review provides an overview of how choice experiments are embedded into decision tools. It highlights the lack of established best practices for embedding methods, with only 4 proof-of-concept methods identified. Furthermore, the review reveals a lack of consensus on outcome measures, emphasizing the need for standardized outcome selection for future evaluations.

OBJECTIVE: Understanding employee workspace preferences is crucial for designing office work environments that meet their needs. This study investigated employee office design preferences within a mandated hybrid work model at a higher education institution. METHODS: In this discrete-choice experiment (DCE), operational support staff (N=433) at a university participated in evaluating 12 pairs of hypothetical office design options, each varying across seven workspace attributes from a DCE survey. Preference weights indicating the relative strength of preference for each workspace design attribute level were used to calculate the importance of each attribute, conditional on the range of levels considered and relative to all other attributes included in the survey. The conditional relative importance of each attribute was calculated as the difference in preference weights for the most- and least-preferred level of that attribute. Subgroup analysis was performed on predefined, mutually exclusive subgroups, with results reported only for those exhibiting statistically significant differences in preferences. RESULTS: The results showed that having a dedicated desk (ie, no desk sharing) was an important factor influencing preferences, followed by personalization and territoriality, opportunities for teamwork, and social interaction. Employees preferred having access to shared spaces for collaboration while also valuing dedicated desks for personal belongings. Private offices and quiet spaces were not strongly preferred. Preferences varied by demographic and work-related characteristics, including gender, age, commute distance, and home environment. CONCLUSIONS: This study shows that operational support staff in higher education prefer office designs that provide a dedicated desk, emphasize personalization, and social interaction. The strong preference for control over workspace and social connection highlights the office`s role in supporting psychosocial well-being in flexible work arrangements. These findings are crucial for informing occupational health and safety strategies and designing workspaces that balance individual and collective requirements.

The importance of patient-centered care in the management of type 2 diabetes mellitus (T2DM) is widely advocated. Understanding the attributes of T2DM medications important to patients is thus essential for effective management, in order to limit disease progression. This literature review aimed to identify studies comparing patient preferences, based on process and outcome attributes, between GLP1-receptor agonist (RA) profiles and between GLP1 RA and insulin profiles. MEDLINE, Embase, PsycINFO, and the Cochrane Library (2005-present) were searched for studies in patients with T2DM or the general population that compared preferences for GLP1 RAs or GLP1 RAs versus insulin using contingent valuation, conjoint analysis (discrete-choice experiments [DCEs], willingness to pay), rating-based approaches of specific attributes, standard gamble, or time trade-off. Studies comparing drug A versus drug B without explicit attribute valuation were excluded. Ten records met eligibility criteria. Eight studies compared preferences for GLP1 RA- profile attributes, one compared GLP1 RA versus insulin glargine profiles, and one addressed both comparisons. Important attributes driving patient preferences in DCEs were dose frequency, type of device, needle size, change in glycated hemoglobin, and adverse-event profile. Time trade-off evaluations demonstrated that weekly GLP1 RA injection-device attributes (reconstitution, waiting during preparation, needle handling) had a measurable impact on preference. Willingness-to-pay analysis showed that patients were more willing to pay extra for attributes of once-daily liraglutide over twice-weekly exenatide or insulin. Direct preference elicitation in DCEs revealed that patients preferred medication profiles representing GLP1 RAs with less frequent dosing and preferred GLP1 RA profiles over insulin. Process and outcome attributes are important drivers of patient preference for GLP1 RAs. Findings from patient-preference studies can inform clinical decision-making and help align care with patient values, which has the potential to improve medication adherence and outcomes.

Discontentment with a piped supply system of drinking water has become a significant concern in Bangladesh's urban areas in recent years, necessitating the improvement of different aspects of the system in question. Therefore, by conducting a discrete choice experiment on 115 households out of a systematically selected 161 households, this study aims to estimate the willingness to pay (WTP) for an improved safe drinking water supply by considering the trade-offs made by urban dwellers for the proposed improvements to an existing water supply system in the Khulna City Corporation (KCC) area of Bangladesh. The primary results show that the total WTP of households is estimated at BDT 243.6 (≈US$ 2.87) per month, implying that respondents are ready to pay for improvements to the water supply attributes of water quality, regularity of supply, water pressure in taps, and filtering. A revenue stream for an improved water supply system is also being developed, suggesting that investment in improving the system would be a ‘no-regret’ decision and economically sustainable.

The increased use of renewable energy is imperative as a countermeasure to climate change. As with conventional electricity generation technologies, public acceptance of renewables is an important issue, and willingness to pay (WTP) is a widely used indicator to assess such public attitudes. Unfortunately, the literature to date mostly covers developed countries, with few WTP surveys in developing countries. Tackling climate change is an urgent issue for these developing countries; therefore, understanding of public attitudes toward renewables in developing countries is crucial. This study conducted the first survey on WTP for introducing renewable energy in Myanmar. Although Myanmar boasts abundant renewable energy resources, including solar power and biomass in addition to large-scale hydro plants, its resources are not being properly utilized to generate electricity. This study surveyed WTP for power generation by solar photovoltaics, small hydropower, and biomass facilities. The results showed the highest WTP for solar power (USD 1.92) with 10% share in the energy mix, and lower WTP for biomass and small hydropower electricity generations (USD 1.13 and USD 1.17, respectively). Careful public communication is thus crucial for expanding biomass and small-scale hydro power plants.

The daily injection burden of recombinant human growth hormone (r-hGH) replacement therapy to treat growth hormone deficiency (GHD) may reduce compliance and limit treatment benefit. Research is needed to evaluate patient preferences for GHD injection regimen and device features. Quantitatively evaluate factors driving preferences for r-hGH injection regimen and device features among pediatric (3-17 years, and caregivers) and adult (≥25 years) patients with GHD using a discrete choice experiment (DCE) approach. The DCE was part of a broader, cross-sectional observational field study to develop clinical outcome assessments (COAs) that assess the experience of patients taking r-hGH injections. Following ethics approval, discrete choice data were collected through an online questionnaire from consented participants recruited from eight sites in the United States. Participants were presented with 20 choice tasks, each comprising different combinations of two profiles. Participants were then shown the same set of three hypothetical device and injection profiles (ie, storage, preparation, injection type device, maintenance, dose setting, injection schedule) and asked whether they would choose each profile over their current device and schedule. Choice-based conjoint analyses were used to estimate the marginal utilities and values for treatment attributes. Subject preferences were estimated at individual and aggregate levels. Two hundred and twenty-four participants completed the DCE (n=75 adults, n=79 adolescent/caregiver dyads, n=70 child/caregiver dyads). Injection schedule was the strongest predictor of choice for the total sample and each patient group. Less frequent injection schedules were more likely to be chosen by participants. A \"ready to use\" injection was preferred, with no preference for auto-injector versus needle-free device. Most participants would choose the hypothetical injection devices and less frequent dosing over their current daily administered device schedule. Patients prefer a less frequent injection regimen for treating GHD. Addressing patient preferences may improve compliance, adherence, and ultimately, clinical outcomes.

Despite the common intuition that similar products are stronger demand substitutes, this study shows a more nuanced relationship between perceived similarity and utility substitution. Using pile sorting, a method where items are sorted into groups according to their similarity, we conduct large‐scale consumer surveys on purchasing 21 foods for at‐home and away‐from‐home consumption. We find perceived similarities differ across settings: in grocery contexts, foods perceived as more similar tend to be utility complements, whereas in restaurants, more similar foods tend to be utility substitutes. Our findings provide a rich characterization of consumer food preferences that can aid marketing and strategy decision‐making.

For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multiattribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.

Policy Points  Public funding for mental health programs must compete with other funding priorities in limited state budgets.  Valuing state‐funded mental health programs in a policy‐relevant context requires consideration of how much benefit from other programs the public is willing to forgo to increase mental health program benefits and how much the public is willing to be taxed for such program benefits.  Taxpayer resistance to increased taxes to pay for publicly funded mental health programs and perceived benefits of such programs vary with state population size.  In all states, taxpayers seem to support increased public funding for mental health programs such as state Medicaid services, suggesting such programs are underfunded from the perspective of the average taxpayer. Context The direct and indirect impacts of serious mental illness (SMI) on health care systems and communities represents a significant burden. However, the value that community members place on alleviating this burden is not known, and SMI treatment must compete with a long list of other publicly funded priorities. This study defines the value of public mental health interventions as what the public would accept, either in the form of higher taxes or in reductions in nonhealth programs, in return for increases in the number of mental health program beneficiaries. Methods We developed and fielded a best‐practice discrete‐choice experiment survey to quantify respondents’ willingness to be taxed for increased spending among several competing programs, including a program for treating severe mental health conditions. A realistic decision frame was used to elicit respondents’ willingness to support expanded state budgets for mental health programs if that expansion required either cuts in the competing publicly financed programs or tax increases. The survey was administered to a general population national sample of 10,000 respondents. Findings Nearly half the respondents in our sample either chose “no budget increase” for all budget scenarios or had preferences that were too disordered to estimate trade‐off values. Including zero values for those respondents, we found that the mean (median) amount that all respondents were willing to be taxed annually for public mental health programs ranged between$156 ($ 99) per year for large‐population states and$343 ($ 181) per year for small‐population states. Respondents would accept reductions of between 1.6 and 3.4 beneficiaries in other programs in return for 1 additional mental health program beneficiary. Conclusions Our results are consistent with findings that a substantial portion of the US public is unwilling to pay higher taxes. Nevertheless, even including the substantial number of respondents who opposed any tax increase, the willingness of both the mean and median respondent to be taxed for mental health program expansions implies that programs providing mental health services such as state Medicaid are underfunded.

This study addresses the need to boost fruit and vegetable consumption amidst rising diet‐related health concerns. Blueberries, rich in phenolic phytochemicals, offer significant health benefits. Using a basket‐based choice experiment (BBCE), the study identifies sensory descriptors that enhance blueberry purchasing likelihood. Packaging with a “Stay Fresh” label reduces price sensitivity compared to others. Additionally, blueberries are commonly purchased alongside other berries rather than as substitutes. Demographic factors such as gender, age, education, employment, fitness, ethnicity, region, nutritional value perception, and budget influence blueberry selection. These insights can aid growers, retailers, and marketers in increasing fresh blueberry demand.