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BACKGROUND: Malnutrition remains a pressing public health concern for mothers and children in South Africa. Despite the government's multisectoral response, unaddressed social needs prevent some mothers getting full benefit from interventions, spanning financial planning, income stability, housing, access to government services, social support, and provision of affordable, nutritious foods. Engaging with mothers and prioritising their concerns is important if we wish to overcome obstacles to women benefiting from government nutrition interventions. This study aimed to identify the programmes that women perceived as a priority in addressing the social needs of mothers of young infants and pregnant women to enhance nutrition in a resource-constrained urban township in South Africa. METHODS: A cross-sectional study employed a quantitative preference elicitation survey, administered to 210 mothers and pregnant women from five primary healthcare facilities in Soweto. The survey tool was developed with the community to identify unmet social needs and potential solutions, which were synthesised with findings from the literature. The survey described 15 programmes, grouped into three delivery levels: clinics, community, and government. Participants were required to rank programme options in two stages. First, they selected their top two programmes within each delivery level. Subsequently, they allocated stickers to indicate the strength of their preference among the top programmes across the levels. Rankings were analysed using descriptive statistics. RESULTS: The highest priority was given to five programmes. Two delivered at the community level: Women's economic empowerment groups and Job search assistance, two at the clinic level: Social needs assessment and referral, and Prescription-based food, and one at the government level: Free quality childcare. The lowest-ranked programmes were two clinic-based programmes, specifically Maternal nutrition groups and Couple antenatal education. CONCLUSION: Women expressed strong views about which programmes should be prioritised to support mothers and pregnant women in addressing their social needs and improving nutrition. Key areas included providing support with job searching and entrepreneurship, accessing childcare and the healthy foods recommended at clinics, as well as finding information on available community and government services. Leveraging multisectoral collaboration, aligned policy objectives, efficient public financing, and strengthened implementation capacity will be pivotal in delivering these programmes.

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Purpose: To compare three methods for identifying patient preferences (MIPPs) at the point of decision-making: analysis of video-recorded patient-clinician encounters, post-encounter interviews, and post-encounter surveys. Patients and Methods: For the decision of whether to use a spinal cord stimulator device (SCS), a video coding scheme, interview guide, and patient survey were iteratively developed with 30 SCS decision-making encounters in a tertiary academic medical center pain clinic. Burke's grammar of motives was used to classify the attributed source or justification for a potential preference for each preference block. To compare the MIPPs, 13 patients' encounters with their clinician were video recorded and subsequently analyzed by 4 coders using the final video coding scheme. Six of these patients were interviewed, and 7 surveyed, immediately following their encounters. Results: For videos, an average of 66 (range 33-106) sets of utterances potentially indicating a patient preference (a preference block), surveys 33 (range 32-34), and interviews 25 (range 18-30) were identified. Thirty-eight unique themes (75 subthemes), each a preference topic, were identified from videos, surveys 19 themes (12 subthemes), and interviews 39 themes (54 subthemes). The proportion of preference blocks that were judged as expressing a preference that was clearly important to the patient or affected their decision was highest for interviews (72.8%), surveys (68.0%), and videos (27.0%). Videos mostly attributed preferences to the patient's situation (scene) (65%); interviews, the act of receiving or living with SCS (43%); surveys, the purpose of SCS (40%). Conclusion: MIPPs vary in the type of preferences identified and the clarity of expressed preferences in their data sets. The choice of which MIPP to use depends on projects' goals and resources, recognizing that the choice of MIPP may affect which preferences are found.

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BACKGROUND: A risk-stratified breast screening program could offer low-risk women less screening than is currently offered by the National Health Service. The acceptability of this approach may be enhanced if it corresponds to UK women's screening preferences and values. OBJECTIVES: To elicit and quantify preferences for low-risk screening options. METHODS: Women aged 40 to 70 y with no history of breast cancer took part in an online discrete choice experiment. We generated 32 hypothetical low-risk screening programs defined by 5 attributes (start age, end age, screening interval, risk of dying from breast cancer, and risk of overdiagnosis), the levels of which were systematically varied between the programs. Respondents were presented with 8 choice sets and asked to choose between 2 screening alternatives or no screening. Preference data were analyzed using conditional logit regression models. The relative importance of attributes and the mean predicted probability of choosing each program were estimated. RESULTS: Participants (N = 502) preferred all screening programs over no screening. An older starting age of screening, younger end age of screening, longer intervals between screening, and increased risk of dying had a negative impact on support for screening programs (P < 0.01). Although the risk of overdiagnosis was of low relative importance, a decreased risk of this harm had a small positive impact on screening choices. The mean predicted probabilities that risk-adapted screening programs would be supported relative to current guidelines were low (range, 0.18 to 0.52). CONCLUSIONS: A deintensified screening pathway for women at low risk of breast cancer, especially one that recommends a later screening start age, would run counter to women's breast screening preferences. Further research is needed to enhance the acceptability of offering less screening to those at low risk of breast cancer. HIGHLIGHTS: Risk-based breast screening may involve the deintensification of screening for women at low risk of breast cancer.Low-risk screening pathways run counter to women's screening preferences and values.Longer screening intervals may be preferable to a later start age.Work is needed to enhance the acceptability of a low-risk screening pathway.

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OBJECTIVES: The objective of this study is to elicit health care preferences of people with diabetes and identify classes of people with different preferences. METHODS: A discrete choice experiment was conducted among people with diabetes in Germany comprising attributes of role division in daily diabetes care planning, type of lifestyle education, support for correct medication intake, consultation frequency, emotional support, and time spent on self-management. A conditional logit model and a latent class model were used to elicit preferences toward diabetes care and analyze preference heterogeneity. RESULTS: A total of 76 people with diabetes, recruited in two specialized diabetes care centers in Germany (mean age 51.9 years, 37.3% women, 49.1% type 2 diabetes mellitus, 50.9% type 1 diabetes mellitus), completed the discrete choice experiment. The most important attributes were consultation frequency, division in daily diabetes care planning, and correct medication intake. The latent class model detected preference heterogeneity by identifying two latent classes which differ mainly with respect to lifestyle education and medication intake. CONCLUSION: While the majority of people with diabetes showed preferences in line with current health care provision in Germany, a relevant subgroup wished to strengthen lifestyle education and medication intake support with an aid or website.

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BACKGROUND: Particularly in rural regions, factors such as lower physician density and long travel distances complicate adequate outpatient care. However, urban regions can also be affected by deficits in care, for example, long waiting times. One model of care intending to improve the situation is the implementation of video consultations. The study protocol presents the methodology of the research project titled "Preference-based implementation of the video consultation in urban and rural regions" funded by the German Federal Joint Committee (funding number 01VSF20011). OBJECTIVE: This study aims to identify existing barriers to the use of video consultation and the preferences of insured individuals and physicians as well as psychotherapists in order to optimize its design and thus increase acceptance and use of video consultations in urban and rural regions. METHODS: Built on a mixed methods approach, this study first assesses the status quo of video consultation use through claims data analysis and carries out a systematic literature review on barriers and promoting factors for the use of video consultations. Based on this preliminary work, focus groups are conducted in order to prepare surveys with insureds as well as physicians and psychotherapists in the second study phase. The central element of the survey is the implementation of discrete choice experiments to elicit relevant preferences of (potential) user groups and service providers. The summarized findings are discussed in a stakeholder workshop and translated into health policy recommendations. RESULTS: The methodological approach used in this study is the focus of this paper. The study is still ongoing and will continue until March 2024. The first study phase has already been completed, in which preliminary work has been done on potential applications and hurdles for the use of video consultations. Currently, the survey is being conducted and analyses are being prepared. CONCLUSIONS: This study is intended to develop a targeted strategy for health policy makers based on actual preferences and perceived obstacles to the use of video consultations. The results of this study will contribute to further user-oriented development of the implementation of video consultations in German statutory health insurance. Furthermore, the iterative and mixed methods approach used in this study protocol is also suitable for a variety of other research projects. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50932.

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OBJECTIVES: Multiple methods are available for collecting health preference information. However, information on the design and analysis of novel methods is limited. This article aims to provide the first introduction into the design and analysis of multidimensional thresholding (MDT). METHODS: We introduce MDT as a 2-step approach: First, participants rank the largest possible improvements in all considered attributes by their importance. Second, participants complete a series of systematically combined trade-off questions. Hit-and-Run sampling is used for obtaining preference weights. We also use a computational experiment to compare different MDT designs. RESULTS: The outlined MDT can generate preference information suitable for specifying a multiattribute utility function at the individual level. The computational experiment demonstrates the method's ability to recover preference weights at a high level of precision. While all designs in the computation experiment perform comparably well on average, the design outlined in the paper stands out with a high level of precision even if differences in relative attribute importance are large. CONCLUSION: MDT is suitable for preference elicitation, in particular if sample sizes are small. Future research should help improve the methods (e.g., remove the need for an initial ranking) to increase the potential reach of MDT.

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Bundle recommendation aims to generate bundles of associated products that users tend to consume as a whole under certain circumstances. Modeling the bundle utility for users is a non-trivial task, as it requires to account for the potential interdependencies between bundle attributes. To address this challenge, we introduce a new preference-based approach for bundle recommendation exploiting the Choquet integral. This allows us to formalize preferences for coalitions of environmental-related attributes, thus recommending product bundles accounting for synergies among product attributes. An experimental evaluation of a dataset of local food products in Northern Italy shows how the Choquet integral allows the natural formalization of a sensible notion of environmental friendliness and that standard approaches based on weighted sums of attributes end up recommending bundles with lower environmental friendliness even if weights are explicitly learned to maximize it. We further show how preference elicitation strategies can be leveraged to acquire weights of the Choquet integral from user feedback in terms of preferences over candidate bundles, and show how a handful of queries allow to recommend optimal bundles for a diverse set of user prototypes.

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OBJECTIVES: This study generates VILL-UI (Vision Impairment in Low Luminance - Utility Index), a preference-weighted measure (PWM) derived from the VILL-33 measure for use in patients with age-related macular degeneration (AMD) and valued to generate United Kingdom and German preference weights. METHODS: A PWM consists of a classification system to describe health and utility values for every state described by the classification. The classification was derived using existing data collected as part of the MACUSTAR study, a low-interventional study on AMD, conducted at 20 clinical sites across Europe. Items were selected using psychometric and Rasch analyses, published criteria around PWM suitability, alongside instrument developer views and concept elicitation work that informed VILL-33 development. An online discrete choice experiment (DCE) with duration of the health state was conducted with the United Kingdom and German public. Responses were modeled to generate utility values for all possible health states. RESULTS: The classification system has 5 items across the 3 domains of VILL-33: reading and accessing information, mobility and safety, and emotional well-being. The DCE samples (United Kingdom: n = 1004, Germany: n = 1008) are broadly representative and demonstrate good understanding of the tasks. The final DCE analyses produce logically consistent and significant coefficients. CONCLUSIONS: This study enables responses to VILL-33 to be directly used to inform economic evaluation in AMD. The elicitation of preferences from both United Kingdom and Germany enables greater application of VILL-UI for economic evaluation throughout Europe. VILL-UI fills a gap in AMD in which generic preference-weighted measures typically lack sensitivity.

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Preference elicitation is widely used within health economic evaluations to inform coverage decisions. However, coverage decisions involve questions of social justice and it is unclear what role empirical evidence about preferences can play here. This study reviews the prevalent normative frameworks for using population-based preference elicitation and the criticisms they face, and proposes an alternative based on constitutional economics. The frameworks reviewed include a supposedly value-neutral framework of preferences as predictors of choice, preference utilitarian frameworks that aim to maximize preference satisfaction, and substantive consequentialist frameworks that aim to maximize happiness, health, or capabilities. The proposed alternative implements the idea that indices of social value are tools for conflict resolution, rather than tools for maximization. Preference elicitation is used for validating values generated by multi-criteria decision analysis results within representative processes of stakeholder deliberation.

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A new method has recently been developed for valuing health states, called 'Online elicitation of Personal Utility Functions' (OPUF). In contrast to established methods, such as time trade-off or discrete choice experiments, OPUF does not require hundreds of respondents, but allows estimating utility functions for small groups and even at the individual level. In this study, we used OPUF to elicit EQ-5D-5L health state preferences from a (not representative) sample of the UK general population, and then compared utility functions on the societal-, group-, and individual level. A demo version of the survey is available at: https://eq5d5l.me. Data from 874 respondents were included in the analysis. For each respondent, we constructed a personal EQ-5D-5L value set. These personal value sets predicted respondents' choices in three hold-out discrete choice tasks with an accuracy of 78%. Overall, preferences varied greatly between individuals. However, PERMANOVA analysis showed that demographic characteristics explained only a small proportion of the variability between subgroups. While OPUF is still under development, it has important strengths: it can be used to construct value sets for patient reported outcome instruments such as EQ-5D-5L, while also allowing examination of underlying preferences in an unprecedented level of detail. In the future, OPUF could be used to complement existing methods, allowing valuation studies in smaller samples, and providing more detailed insights into the heterogeneity of preferences across subgroups.

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OBJECTIVES: Limitations in conventional cost-effectiveness methods have led to calls for incorporation of additional value elements in assessments of health technologies. However, gaps remain in how additional value elements may inform decision making. This study aimed to prioritize additional value elements from the perspective of healthy individuals without a specific condition or indicated for a specific treatment in the United States among a multistakeholder panel and compare the importance of perspective-specific value elements. METHODS: Additional value elements were prioritized in 2 phases: (1) we identified and categorized additional value elements in a targeted literature review, and (2) we convened a multistakeholder group-based preference elicitation study (N = 28) to evaluate the description of each value element and rank and generate normalized weights of each value element for its significance in value assessment. The importance of additional value elements was also weighted relative to patient-centric value elements. RESULTS: The rank and weight of contextual value elements among 28 stakeholders were "severity of the disease" (26.2%), "disadvantaged and vulnerable target populations highly represented" (21.8%), "broader economic impact" (17.3%), "risk protection" (13.8%), "rarity of the disease" (11.3%), and "novel mechanism of action" (9.7%). Relative weight of the additional value elements versus patient-centric value elements was 52% and 48%, respectively. CONCLUSIONS: Study findings may inform priority setting for value frameworks and emerging US government assessments. The group-based elicitation method is repeatable and useful for structured deliberative processes in value assessment and may help improve the consistency and predictability of what is important to stakeholders.

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OBJECTIVES: Traditional preference elicitation methods, such as discrete choice experiments or time trade-off, usually require large sample sizes. This can limit their applicability in patient populations, where recruiting enough participants can be challenging. The objective of this study was to test a new method, called the Online elicitation of Personal Utility Functions (OPUF) approach, to derive an EQ-5D-5L value set from a relatively small sample of patients with rheumatic diseases. METHODS: OPUF is a new type of online survey that implements compositional preference elicitation techniques. Central to the method are 3 valuation steps: (1) dimension weighting, (2) level rating, and (3) anchoring. An English demo version of the OPUF survey can be accessed at https://valorem.health/eq5d5l. From the responses, a personal EQ-5D-5L utility function can be constructed for each participant, and a group-level value set can be derived by aggregating model coefficients across participants. RESULTS: A total of 122 patients with rheumatic disease from Germany completed the OPUF survey. The survey was generally well received; most participants completed the survey in less than 20 minutes and were able to derive a full EQ-5D-5L value set. The precision of mean coefficients was high, despite the small sample size. CONCLUSIONS: Our findings demonstrate that OPUF can be used to derive an EQ-5D-5L value set from a relatively small sample of patients. Although the method is still under development, we think that it has the potential to be a valuable preference elicitation tool and to complement traditional methods in several areas.

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BACKGROUND: Elicitation of patients' preferences is an integral part of shared decision-making, the recommended approach for prostate cancer decision-making. Existing decision aids for this population often do not specifically focus on patients' preferences. Healium is a brief interactive web-based decision aid that aims to elicit patients' treatment preferences and is designed for a low health literate population. OBJECTIVE: This study used a randomized controlled trial to evaluate whether Healium, designed to target preference elicitation, is as efficacious as Healing Choices, a comprehensive education and decision tool, in improving outcomes for decision-making and emotional quality of life. METHODS: Patients diagnosed with localized prostate cancer who had not yet made a treatment decision were randomly assigned to the brief Healium intervention or Healing Choices, a decision aid previously developed by our group that serves as a virtual information center on prostate cancer diagnosis and treatment. Assessments were completed at baseline, 6 weeks, and 3 months post baseline, and included decisional outcomes (decisional conflict, satisfaction with decision, and preparation for decision-making), and emotional quality of life (anxiety/tension and depression), along with demographics, comorbidities, and health literacy. RESULTS: A total of 327 individuals consented to participate in the study (171 were randomized to the Healium intervention arm and 156 were randomized to Healing Choices). The majority of the sample was non-Hispanic (272/282, 96%), White (239/314, 76%), married (251/320, 78.4%), and was on average 62.4 (SD 6.9) years old. Within both arms, there was a significant decrease in decisional conflict from baseline to 6 weeks postbaseline (Healium, P≤.001; Healing Choices, P≤.001), and a significant increase in satisfaction with one's decision from 6 weeks to 3 months (Healium, P=.04; Healing Choices, P=.01). Within both arms, anxiety/tension (Healium, P=.23; Healing Choices, P=.27) and depression (Healium, P=.001; Healing Choices, P≤.001) decreased from baseline to 6 weeks, but only in the case of depression was the decrease statistically significant. CONCLUSIONS: Healium, our brief decision aid focusing on treatment preference elicitation, is as successful in reducing decisional conflict as our previously tested comprehensive decision aid, Healing Choices, and has the added benefit of brevity, making it the ideal tool for integration into the physician consultation and electronic medical record. TRIAL REGISTRATION: ClinicalTrials.gov NCT05800483; https://clinicaltrials.gov/study/NCT05800483.

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OBJECTIVES: Physician preference items (PPIs) are high-cost medical devices for which clinicians express firm preferences with respect to a particular manufacturer or product. This study aims to identify the most important factors in the choice of new PPIs (hip or knee prosthesis) and infer about the existence of possible response biases in using 2 alternative stated preference techniques. METHODS: Six key attributes with 3 levels each were identified based on a literature review and clinical experts' opinions. An online survey was administered to Italian hospital orthopedists using type 1 best-worst scaling (BWS) and binary discrete choice experiment (DCE). BWS data were analyzed through descriptive statistics and conditional logit model. A mixed logit regression model was applied to DCE data, and willingness-to-pay (WTP) was estimated. All analyses were conducted using Stata 16. RESULTS: A sample of 108 orthopedists were enrolled. In BWS, the most important attribute was "clinical evidence," followed by "quality of products," while the least relevant items were "relationship with the sales representative" and "cost." DCE results suggested instead that orthopedists prefer high-quality products with robust clinical evidence, positive health technology assessment recommendation and affordable cost, and for which they have a consolidated experience of use and a good relationship with the sales representative. CONCLUSIONS: The elicitation of preferences for PPIs using alternative methods can lead to different results. The BWS of type 1, which is similar to a ranking exercise, seems to be more affected by acquiescent responding and social desirability than the DCE, which introduces tradeoffs in the choice task and is likely to reveal more about true preferences. HIGHLIGHTS: Physician preference items (PPIs) are medical devices particularly exposed to physicians' choice with regard to type of product and supplier.Some established techniques of collecting preferences can be affected by response biases such as acquiescent responding and social desirability.Discrete choice experiments, introducing more complex tradeoffs in the choice task, are likely to mitigate such biases and reveal true physicians' preferences for PPIs.

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People with metastatic breast cancer (MBC) have diverse medical, physical, and psychosocial needs that require multidimensional care. Understanding patient preferences is crucial to tailor treatments, services, and foster patient-centered care. A scoping review was performed to summarize the current evidence on the preferences of people with MBC regarding their care to identify knowledge gaps and key areas for future research. The Embase, MEDLINE, CINAHL and PsycInfo databases were searched. Twenty studies enrolling 3354 patients met the study eligibility criteria. Thirteen quantitative studies, four mixed methods studies, and three qualitative studies were included. Seven studies captured healthcare provider perspectives; thirteen studies evaluated patient preferences relating specifically to cancer treatments; three studies evaluated preferences relating to supportive care; and four studies evaluated communication and decision-making preferences. The current literature evaluating MBC patient preferences is heterogeneous with a focus on cancer treatments. Future research should explore patient preferences relating to multidisciplinary, multi-modal care that aims to improve quality of life. Understanding MBC patient preferences regarding their comprehensive care can help tailor healthcare delivery, enhance the patient experience, and improve outcomes.

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OBJECTIVES: A high-quality and widely accepted UK EQ-5D-5L value set is urgently required to enable the latest version of EQ-5D scored using recent UK public preferences to inform policy including health technology assessments submitted to the National Institute for Health and Care Excellence. This article outlines the study protocol for the generation of a new EQ-5D-5L UK value set. METHODS: Twelve hundred interviews will be undertaken using the composite time trade-off elicitation technique for 102 health states (86 from the international EQ-5D-5L valuation protocol, plus 16 with best predictive performance in an extended design used in the Native American EQ-5D-5L valuation). The sample will be UK adults (age ≥18 years) proportionately representative across England, Wales, Scotland, and Northern Ireland, representative for age, sex, ethnicity, and socioeconomic group, with inclusion of participants with/without health problems. Participants will choose to be interviewed via videoconference (by Zoom) or in-person in a central venue. Data quality will be rigorously assessed. RESULTS: The value set will be generated using tobit random effects and heteroscedastic tobit models (with censoring at -1) using all data, excluding time trade-off values highlighted by participants as ones they would reconsider and data from interviewers failing protocol compliance. Quality and acceptance will be achieved by public involvement, regular Steering Group meetings, independent assessment of data quality at 4 time points, and final endorsement of data and analyses. CONCLUSION: This study will produce a UK value set for the EQ-5D-5L for use in prospective and retrospective data sets containing EQ-5D-5L data.

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OBJECTIVE: To compare results of three preference elicitation methods for a cancer screening test. METHODS: Participants (undergraduate students) completed a discrete choice experiment (DCE) and a threshold technique (TT) task. Accuracy (false positives, false negatives), benefits (lives saved), and cost for a cancer screening test were used as attributes in the DCE and branching logic for the TT. Participants were also asked a direct elicitation question regarding a hypothetical screening test for breast (women) or prostate (men) cancer without mortality benefit. Correlations assessed the relationship between DCE and TT thresholds. Thresholds were standardized and ranked for both methods to compare. A logistic regression used the thresholds to predict results of the direct elicitation. RESULTS: DCE and TT estimates were not meaningfully correlated (max ρ = 0.17). Participant rankings of attributes matched only 20% of the time (58/292). Neither method predicted preference for being screened (ps > 0.21). CONCLUSIONS: The DCE and TT yielded different preference estimates (and rank orderings) for the same participant. Neither method predicted patients' desires for a screening test. PRACTICE IMPLICATIONS: Clinicians, patients, policy makers, and researchers should be aware that patient preference results may be sensitive to the method of eliciting preferences.

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BACKGROUND: The Mental Well-being Adjusted Life Year (MWALY) is an alternative outcome measure to the quality-adjusted life year (QALY) in economic evaluations of interventions aimed at improving mental well-being. However, there is a lack of preference-based mental well-being instruments for capturing population mental well-being preferences. OBJECTIVES: To derive a UK preference-based value set for the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS). METHODS: 225 participants that were interviewed between December 2020 and August 2021 completed 10 composite time trade-off (C-TTO) and 10 discrete choice experiment (DCE) interviewer-administered exercises. Heteroskedastic Tobit and conditional logit models were used to model C-TTO and DCE responses respectively. The DCE utility values were rescaled to a C-TTO comparable scale through anchoring and mapping. An inverse variance weighting hybrid model (IVWHM) was used to derive weighted-average coefficients from the modelled C-TTO and DCE coefficients. Model performance was assessed using statistical diagnostics. RESULTS: The valuation responses confirmed the feasibility and face validity of the C-TTO and DCE techniques. Apart from the main effects models, statistically significant associations were estimated between the predicted C-TTO value and participants' SWEMWBS scores, gender, ethnicities, education levels, and the interaction terms between age and useful feeling. The IVWHM was the most optimal model with the fewest logically inconsistent coefficients and the lowest pooled standard errors. The utility values generated by the rescaled DCE models and the IVWHM were generally higher than those of the C-TTO model. The predictive ability of the two DCE rescaling methods was similar according to the mean absolute deviation and root mean square deviation statistics. CONCLUSIONS: This study has produced the first preference-based value set for a measure of mental well-being. The IVWHM provided a desirable blend of both C-TTO and DCE models. The value set derived by this hybrid approach can be used for cost-utility analyses of mental well-being interventions.

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In recent years, transformer-based language representation models (LRMs) have achieved state-of-the-art results on difficult natural language understanding problems, such as question answering and text summarization. As these models are integrated into real-world applications, evaluating their ability to make rational decisions is an important research agenda, with practical ramifications. This article investigates LRMs' rational decision-making ability through a carefully designed set of decision-making benchmarks and experiments. Inspired by classic work in cognitive science, we model the decision-making problem as a bet. We then investigate an LRM's ability to choose outcomes that have optimal, or at minimum, positive expected gain. Through a robust body of experiments on four established LRMs, we show that a model is able to 'think in bets' if it is first fine-tuned on bet questions with an identical structure. Modifying the bet question's structure, while still retaining its fundamental characteristics, decreases an LRM's performance by more than 25%, on average, although absolute performance remains well above random. LRMs are also found to be more rational when selecting outcomes with non-negative expected gain, rather than optimal or strictly positive expected gain. Our results suggest that LRMs could potentially be applied to tasks that rely on cognitive decision-making skills, but that more research is necessary before these models can robustly make rational decisions.

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This essay explores the pitfalls and ambiguities in relying on preference elicitation to value health states, and it distinguishes preference elicitation, as a fallible method of measuring well-being, from public consultation, as an element of public deliberation. After distinguishing preference elicitation as a method of ascertaining opinions from preference elicitation as a method of measuring well-being, it points out that preferences depend on beliefs and the considerations speaking in favor of deferring to people's values do not carry over to deferring to their beliefs. Instead of valuing health states by their bearing on well-being, as measured by preferences, this essay argues for valuing health states by their bearing on activity limitations and suffering, as determined by public deliberation.