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.
CONCLUSIONS: 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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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%).
UNASSIGNED: 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.

UNASSIGNED: The objective of this study is to elicit health care preferences of people with diabetes and identify classes of people with different preferences.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

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.
UNASSIGNED: DERR1-10.2196/50932.

OBJECTIVE: 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.
CONCLUSIONS: 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.

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.

OBJECTIVE: 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.

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.

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.

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.
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.
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.
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.