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This work was supported by grants within the Biodiversity and Ecosystem Services Sustainability (BESS) programme. BESS was a 6-year programme (2011–2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Laurence Jones was supported by NERC grant ‘Location, Configuration, Distribution: the Role of Landscape Pattern and Diversity in Ecosystem Services' (NE/K015508/1). Other authors were supported by the following projects and grants: Fragments, Functions and Flows in Urban Ecosystem Services (F3UES) Project (NE/J015067/1), The DURESS project – Diversity of Upland Rivers for Ecosystem Service Sustainability (NE/J014818/1), Coastal Biodiversity and Ecosystem Services Sustainability – CBESS (NE/J015644/1) and Wessex BESS (NE/J014680/1). 1. Cultural ecosystem services (CES), a key aspect of nature's contributions to people, remain a challenge to incorporate into decision making. One contributing factor is the difficulty of defining and describing these, due partly to: ongoing poor understanding of what drives people to interact with nature, a lack of appropriate data to quantify these interactions, and basic difficulties in measuring and modelling the complex array of social, psychological and behavioural attributes which help explain people's actions. 2. In this study we present a framework which develops the concepts of cultural capital, social capital and human capital as specific forms of human-centred capital, in the context of their contribution to understanding CES. Each form of capital encompasses separate attributes of beneficiaries. 3. Testing the framework with data from a separate trans-disciplinary study illustrated that the framework was readily applicable to specific situations. A measure of cultural capital, EcoCentrism, explained more variation than a suite of seven demographic variables. 4. Applying the framework also showed that despite using a wide range of explanatory variables, a large proportion of observed variation remained unaccounted for. This suggests that more work is needed to understand and to develop metrics which can measure additional factors which underlie peoples? motivations to engage with nature. The framework is applicable to other types of ecosystem service, and may also be useful for exploring relational values. Publisher PDF

Objective: This study was undertaken to elicit patients' preferences for attributes characterizing antiseizure medication (ASM) monotherapy options before treatment consultation, and to explore the trade‐offs patients consider between treatment efficacy and risks of side effects. Further objectives were to explore how treatment consultation may affect patient preferences, to elicit physicians' preferences in selecting treatment, and to compare patient and physician preferences for treatment. Methods: This prospective, observational study (EP0076; VOTE) included adults with focal seizures requiring a change in their ASM monotherapy. Patients completed a discrete choice experiment (DCE) survey before and after treatment consultation. Physicians completed a similar survey after the consultation. The DCE comprised 12 choices between two hypothetical treatments defined by seven attributes. The conditional relative importance of each attribute was calculated. Results: Three hundred ten patients (mean [SD] age = 46.8 [18.3] years, 52.3% female) were enrolled from eight European countries, of whom 305 completed the survey before consultation and 273 completed the survey before and after consultation. Overall, this preference study in patients who intended to receive a new ASM monotherapy suggests that patient preferences were ordered as expected, with better outcomes being preferred to worse outcomes; patients preferred a higher chance of seizure freedom, lower risk of developing clinical depression, and fewer severe adverse events; avoiding moderate‐to‐severe “trouble thinking clearly” was more important than avoiding any other side effect. There were qualitative differences in what patients and physicians considered to be the most important aspects of treatment for patients; compared with patients, physicians had a qualitatively stronger preference for greater chance of seizure freedom and avoiding personality changes. Patients' preference weights were qualitatively similar before and after treatment consultation. Significance: For patients, seizure freedom and avoiding trouble thinking clearly were the most important treatment attributes. Physicians and patients may differ in the emphasis they place on specific attributes.

Lay abstract CAR-T therapy is a treatment option for patients with diffuse large B-cell lymphoma that has not responded to at least two other kinds of treatments. CAR-T therapies are manufactured from a patient’s white blood cells, modified to attack lymphoma cells. A CAR-T therapy takes time to manufacture after these cells are collected. CAR-T therapies can result in the reduction or disappearance of lymphoma tumors and can increase the chances of survival, but also cause serious side effects for a few patients. One of these is cytokine release syndrome (CRS), in which high levels of inflammation throughout the body may cause fever, heart problems or difficulty breathing. Another is the development of temporary but serious neurological problems such as confusion, seizures and memory problems. To understand how important physicians consider certain features of CAR-T therapies to be when deciding whether to recommend them, we asked physicians to choose between two treatment options resembling CAR-T therapies in a series of questions, with the CAR-T features varying in each question. Their answers indicated whether disappearance of tumors, a patient’s chances of survival after 1 and 2 years of treatment, manufacturing time, or the risk of CRS or neurological problems was the most important factor. Physicians most wanted to reduce manufacturing time from 113 to 16 days, but also were willing to accept a20% increase in risk of severe CRS and a 15% increase in risk of severe neurological events to increase a patient’s chance of survival from 40 to 55% at 2 years.

Background Making trials more patient-centred improves recruitment and retention, patient satisfaction and makes research accessible to a more representative population. We aimed to understand the factors that influence participation and engagement in clinical trials in cystic fibrosis (CF) trials to guide the rational design and delivery of patient-centred trials. Methods We used a Delphi process, supported by extensive literature review and 3 workshops, to determine which factors stakeholders think exert significant influence in participation and engagement in CF trials. Panellists were recruited from across the UK and the study was administered online. Results We had representation from 19 CF centres; 28 people with CF (pwCF), 26 parents and 30 healthcare professionals (HCPs). Panels were presented with a shortlist of 104 factors and asked which they thought influence participation and engagement in CF trials. After 3 iterations, 43 statements met consensus for pwCF, 48 for the parents and 69 for the HCPs. Conclusions We identified many targets to make trials more patient-centred. Whilst some require an overhaul of trial delivery, many are relatively easy to implement. We outline a list of ‘dos and don'ts’ for sponsors and research teams including: focus on good communication; recognise that lack of time is the greatest barrier to trial participation so minimise the frequency and length of visits; help participants fit trials around busy lives; remember trial participation can be a major life-event and support participants accordingly; and don't underestimate the impact of simple strategies e.g. on-site access to Wifi and cups of tea.

BACKGROUND Long-acting pre-exposure prophylaxis (LA-PrEP) formulated as implants and injections are promising prevention method strategies offering simplicity, discretion, and long dose duration. Men are important end users of LA-PrEP, and early assessment of their preferences could enhance downstream male engagement in HIV prevention. METHODS A discrete-choice experiment survey was conducted with 406 men, aged 18-24, in Cape Town, South Africa, to assess preferences for 5 LA-PrEP attributes with 2-4 pictorially-depicted levels: delivery form, duration, insertion location, soreness, and delivery facility. Latent class analysis was used to explore heterogeneity of preferences and estimate preference shares. RESULTS The median age was 21 (interquartile range 19-22), and 47% were men who have sex with men. Duration was the most important product attribute. Latent class analysis identified 3 classes: "duration-dominant decision makers" (46%) were the largest class, defined by significant preference for a longer duration product. "Comprehensive decision makers" (36%) had preferences shaped equally by multiple attributes and preferred implants. "Injection-dominant decision makers" (18%) had strong preference for injections (vs. implant) and were significantly more likely to be men who have sex with men. When estimating shares for a 2-month injection in the buttocks with mild soreness (HPTN regimen) vs. a 6-month implant (to arm) with moderate soreness (current target), 95% of "injection-dominant decision makers" would choose injections, whereas 79% and 63% of "duration-dominant decision makers" and "comprehensive decision makers" would choose implant. CONCLUSIONS Young South African men indicated acceptability for LA-PrEP. Preferences were shaped mainly by duration, suggesting a sizeable market for implants, and underscoring the importance of product choice. Further research into men's acceptability of LA PrEP strategies to achieve engagement in these HIV prevention tools constitutes a priority.

This technical note discusses how dummy and effects coding of categorical respondent characteristics in a class membership probability function should be interpreted by researchers employing a latent class analysis to explore preference heterogeneity in a discrete-choice experiment. Previous work highlighted issues arising from such coding when interpreting an alternative specific constant that represents an opt-out alternative or current situation in a discrete-choice experiment and did not fully address how this coding impacts the interpretation of parameters resulting from the membership probability function in a latent class analysis. Although latent class membership probability could be predicted separately for each respondent or subgroup of respondents, conclusions are often drawn directly from the model estimation using the full sample, which requires correctly interpreting the estimated parameters. In these cases, the misinterpretation that may arise if the problem is ignored could impact the policy conclusions and recommendations drawn based on the discrete-choice experiment results. This note provides an example comparing dummy and effects coding used to model respondent characteristics in the membership probability function in a discrete-choice experiment aimed to explore preferences for the treatment of chronic pain in the USA.

Background: Several pharmaceutical treatments for chronic pain caused by osteoarthritis (OA) and chronic low back pain (CLBP) are available or currently under development, each associated with different adverse events (AEs) and efficacy profiles. It is therefore important to understand what trade-offs patients are willing to make when choosing between treatments. Methods: A discrete-choice experiment (DCE) was conducted with 437 adults with chronic pain caused by OA and/or CLBP. Respondents were presented with a series of scenarios and asked to choose between pairs of hypothetical treatments, each defined by six attributes: level of symptom control; risks of heart attack, rapidly progressive osteoarthritis and dependency; frequency and mode of administration and cost. Attributes were based on known profiles of oral nonsteroidal anti-inflammatory drugs, opioids and injected nerve growth factor inhibitors, the last of which were under clinical development at the time of the study. Data were analysed using a latent class (LC) model to explore preference heterogeneity. Results: Overall, respondents considered improving symptom control and reducing risk of physical dependency to be the most important attributes. The LC analysis identified four participant classes: an ‘efficacy-focused’ class (33.7%), a ‘cost-averse’ class (29.4%), a ‘physical-dependence–averse’ class (19.6%) and a ‘needle-averse’ class (17.3%). Subgroup membership was incompletely predicted by participant age and their responses to comprehension questions. Conclusions: Preference heterogeneity across respondents indicates a need for a personalized approach to offering treatment options. Symptom improvement, cost, physical dependence and route of administration might be important to different patients. Significance: Multiple treatment options that differ substantially in terms of efficacy and adverse events are available for the management of chronic pain. With a growing emphasis on a patient-centred care model that incorporates patients’ priorities and values into treatment decisions, there is a need to understand how individuals with chronic musculoskeletal pain balance the benefits and risks of treatment and how treatment priorities vary among individuals. This study was designed to identify patient preferences for different characteristics of treatments for the management of chronic pain and to investigate how preferences differ among respondents.

Objectives: To identify meaningful treatment attributes and quantify patient preferences for attributes of systemic atopic dermatitis (AD) treatments. Materials and methods: 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. Results: 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. Conclusion: The findings of this study can help inform joint patient-physician decision making in managing moderate-to-severe AD.

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.

Purpose Teriparatide is used to treat patients with established osteoporosis but is often reserved for patients who have inadequate response to antiresorptive therapy. Biosimilar teriparatide, which is believed to have efficacy and safety similar to the originator product, is now available in Colombia. However, little is known about patients' preferences for originator biologic and biosimilar treatments. Our objective was to quantify the relative importance that patients in Colombia place on features of injectable osteoporosis treatments including whether the treatment is an originator biologic or a biosimilar. Patients and methods We used a discrete choice experiment (DCE) to elicit preferences of patients with osteoporosis treatment devices in Colombia. The survey was completed by 200 respondents at high risk of fracture, with or without teriparatide experience. Each treatment alternative within the DCE was characterized by five attributes: type of medicine (originator biologic, biosimilar), needle length, angle of injection, how to measure the medicine dose, and how long the medicine can be left unrefrigerated. A random parameters logit regression was used to estimate preferences and conditional relative attribute importance, while controlling for preference heterogeneity. Results A total of 200 patients (mean age = 58.3 years) completed the survey. Most were female (84.5%) and married (54.5%); 50.5% had secondary education or less, 21% had current teriparatide exposure. The attribute with the highest conditional relative importance estimate (standard error) was biologic versus biosimilar (10 [1.11]), followed by needle length (8.06 [1.11]), dose measurement (6.38 [0.87]), refrigeration (3.81 [1.18]), and angle of injection (1.30 [0.66]). Unobserved preference heterogeneity was present and controlled for in the analyses. Conclusion Despite the availability of biosimilar teriparatide in Colombia, patients expressed a strong preference for an originator biologic osteoporosis medicine over a biosimilar osteoporosis medicine, when the efficacy, safety, and cost of the two options were assumed to be the same.

Either a random-parameters logit (RPL) or latent class (LC) model can be used to model or explain preference heterogeneity in discrete-choice experiment (DCE) data. The former assumes continuous distribution of preferences across the sample, while the latter assumes a discrete distribution. This study compared RPL and LC models to explore preference heterogeneity when analyzing patient preferences for psoriasis treatments. Using DCE data collected from respondents with moderate-to-severe plaque psoriasis, we calculated and compared preference weights derived from RPL and LC models. We then compared how RPL and LC explain preference heterogeneity by exploring differences across subgroups defined by observed characteristics (i.e., country, age, gender, marital status, and psoriasis severity). While RPL and LC models resulted in the same mean preference weights, different preference-heterogeneity patterns emerged from the two approaches. In both models, country of residence and self-reported disease severity could be linked to systematic differences in preferences. The RPL also identified gender and marital status, but not age, as sources of heterogeneity; the LC membership probability model indicated that age was a significant factor, but not gender or marital status. Using data from a psoriasis patient survey to compare two widely used methods for exploring heterogeneity identified differences in results between stated-preferences: subgroup analysis in the RPL model and inclusion of subgroup characteristics in the class membership probability function of the LC model. Researchers should model data using the most adaptable approach to address the initial study question.

Background Antibiotics have led to considerable increases in life expectancy. However, over time, antimicrobial resistance has accelerated and is now a significant global public health concern. Understanding societal preferences for the use of antibiotics as well as eliciting the willingness to pay for future research is crucial. Objective To investigate preferences for different strategies to optimize antibiotic use and to understand the willingness to pay for future research in antimicrobial resistance and antimicrobial drug development. Methods A discrete-choice experiment was administered to a sample of the UK general population. Respondents were asked to make nine choices, each offering three options—two hypothetical “doctor and antibiotics” and one “no doctor—no antibiotics”—defined by five attributes: treatment, days needed to recover, risk of bacterial infection that needs antibiotics, risk of common side effects, and risk of antimicrobial resistance by 2050. Data were analyzed using random parameters logit models. A double-bounded contingent valuation was also included in the survey to explore the willingness to pay for policies to contain antimicrobial resistance. Results Among the 2579 respondents who completed the survey, 1151 always selected “no doctor—no antibiotics” and 57 never varied their choices; therefore, 1371 responses were used in the analysis. Risk of antimicrobial resistance by 2050 was the most important attribute and the “treatment” was the least important attribute, although this was sensitive to a higher risk of bacterial infection. The aggregate annual willingness to pay for containing antimicrobial resistance was approximately £8.35 billion (~£5–£10 billion). Conclusions The antimicrobial resistance risk is relevant and important to the general public. The high willingness to pay suggests that large investments in policies or interventions to combat antimicrobial resistance are justified. Supplementary Information The online version contains supplementary material available at 10.1007/s40273-021-01076-9.

This study aimed to quantify preferences and risk tolerance for a tick-borne encephalitis (TBE) vaccination. A stated-preference survey instrument was administered to international travelers living in the United States to elicit preferences for a no-cost TBE vaccine when planning an international trip, conditional upon four different qualitative levels of endemic TBE risk. The likelihood of choosing the vaccine increased with a destination’s level of endemic risk. Most respondents (94%) would choose to receive the vaccine at the highest risk level presented in the survey (i.e. when multiple TBE cases among humans are reported year after year); 6% of the sample would choose not to receive the vaccine at any risk level. Respondents who engage in outdoor activities were twice as likely as the average respondent to choose vaccination rather than opting out of vaccination, and were one-third more likely than the average respondent to choose to receive the vaccine at the lowest risk level. Respondents were highly interested in a TBE vaccine, assuming no cost, and most were willing to be vaccinated at all qualitative TBE risk levels. Respondents who participated in outdoor activities were more likely than the average respondent to choose the vaccine.

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.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.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.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.

Purpose To quantify rheumatology patient preferences and willingness to pay (WTP) for features differentiating enhanced from standard self-injection devices and to investigate differences among subgroups. Patients and methods Patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA) were recruited in the UK. A discrete-choice experiment was used to elicit preferences; respondents were presented with 10 choices between 3 different devices: a free standard disposable device, and 2 hypothetical reusable devices characterized by presence/absence of skin sensor, injection speed control, on-screen instructions, injection reminders, electronic log, and large grip. Every hypothetical device included a cost component to assess WTP for each enhanced feature. A random-parameters logit model was used to estimate preference weights and WTP. Results Data were collected from 323 respondents by electronic survey (15/11/2017-15/02/2018; RA: 108; PsA: 103; axSpA: 112). On average, the skin sensor was the most preferred feature (£30), followed by injection speed control, injection reminders, electronic log (~£20 each), on-screen instructions (~£12), and a device with a small, rather than large grip (~£7). Similar preferences for attributes were observed across condition subgroups except for grip size: axSpA patients preferred small grip (~£27); PsA patients preferred large grip (~£19). Overall, respondents preferred reusable devices with all enhanced features (WTP value: £85) over the standard device. RA patients exhibited a higher WTP (£145) than PsA (£102) or axSpA (£62) for the same enhanced device. Conclusion Patients positively valued reusable self-injection devices with enhanced features, which may improve patient experience, potentially improving treatment adherence, clinical, and economic outcomes.

Purpose: This study aimed to elicit patient and physician preferences for ulcerative colitis (UC) treatments in the United States (US). Patients and methods: The following UC treatment attributes included in the discrete-choice experiment (DCE) were identified during qualitative interviews with both patients and physicians: time to symptom improvement, chance of long-term symptom control, risks of serious infection and malignancy, mode and frequency of administration, and need for steroids. The DCE survey instruments were developed and administered to patients and physicians. A random-parameters logit model was used to estimate preference weights and conditional relative importance for these attributes. Results: A total of 200 patients with moderate to severe UC (status determined using self-reported medication history) and 200 gastroenterologists completed the survey. Patients' average age was 42 years; most (59%) were female. Patients considered symptom control 2.5 times as important as time to symptom improvement and 5-year risk of malignancy almost as important as long-term symptom control (relative importance, 0.79 vs 0.96 for long-term symptom control); they preferred oral to subcutaneous or intravenous administration (relative importance, 0.47 vs 0.11 and 0.18, respectively). For physicians, symptom control was the most important attribute and was five times as important as the risk of malignancy. Conclusion: Both patients and physicians considered long-term symptom control the most important attribute relative to others; however, risk of malignancy was of almost-equal importance to patients but not physicians. Differences between patients' and physicians' preferences highlight the need for improved communication about the relevant benefits and risks of different UC treatments to improve therapeutic decision-making.

Background: Discrete-choice experiments (DCEs) are increasingly conducted to quantify risk tolerance by computing maximum acceptable risk (MAR) for improvements in efficacy or other benefits gained from new medical treatments. To compute MARs from DCE data, respondents are asked to make choices under uncertainty between treatments. Specific treatment-related harms are included in the choice questions as probabilistic adverse events (AEs), and choice variation with the probability of these outcomes is assumed to indicate their effect on the expected utility of treatments. With a limited number of comparisons between profiles, calculation of MARs requires understanding how outcome probabilities that are not explicitly considered in the DCE can change the value of medical technologies. This study aims to examine how various assumptions on the expected disutility of these excluded probabilities can result in different MAR measures. Methods: We summarize commonly used empirical specifications for the expected disutility of AEs and derive the resulting MAR functions. We then discuss an empirical application on treatments to delay bone metastases in oncology patients with solid tumors. Results: A total of 187 respondents completed the DCE. Results show the impact of making various assumptions about the expected disutility of AEs, and the resulting MAR values for specific health benefits. As expected, different assumptions resulted in variations in MAR values for specific health benefits. Even with small differences in MAR measures, our results suggest that the assumptions evaluated here can lead to different conclusions about the acceptability of a medical technology. Conclusion: Results show possible systematic variations in MARs caused by the assumed form of the effect of changes in the probability of AEs. Furthermore, we find that different assumptions can lead to different conclusions about the acceptability of a medical technology, even when MAR distributions overlap. This result suggests that researchers should evaluate the assumptions they are making for these effects and use sensitivity analysis to evaluate the robustness of risk-tolerance measures from stated-preference data.

Background Biologic psoriasis treatments are differentiated by efficacy, side effects, and other attributes. Objective Determine attributes of biologic psoriasis treatments that drive patients' treatment choices. Methods Respondents (USA: n = 300; Germany: n = 300) with moderate-to-severe psoriasis completed a discrete-choice-experiment survey, choosing between hypothetical treatments characterized by attributes with varying levels: chance of clear skin after 1 year, number of first-year treatments, first-year risks of mild-to-moderate injection site reaction (ISR) and serious infection, and years of proven efficacy/safety. Results U.S. respondents most valued clear skin (conditional relative importance, 1.88; p Limitations Respondents evaluated hypothetical treatments and were recruited from web panels. Conclusions Clear skin and ISR risk are stronger drivers of treatment choice than injection frequency and infection risk.

Objectives This study aimed to elicit preferences for psoriasis treatment features and to test for preference heterogeneity across groups of respondents. Materials and methods A discrete-choice experiment was employed to elicit preferences of patients with plaque psoriasis in multiple countries. The survey instrument included a series of choice questions between three hypothetical treatments, each characterized by varying levels of six attributes (namely, lesion reduction, risk of impairing side effects, time to reach results, mode and frequency of administration, itching reduction, and side effects). Random parameters logit was used to model the data. Results were compared across a total of 18 subgroup sets. Results The data analysis from 1,123 respondents showed that, on average, respondents receive more utility gain from higher levels of lesion reduction and lower risks of impairing side effects than changes in other attributes included in the study. Systematic differences were detected for 13 sets; the most pronounced differences were observed based on disease severity, nail psoriasis, biologic experience, and quality-of-life scores. Conclusion These many sources of preference heterogeneity identified by our analysis suggest that to improve patient satisfaction and, probably, adherence and persistence, clinicians should discuss options with patients when prescribing their treatment.

BACKGROUND: Literature reviews show stated-preference studies, used to understand the values individuals place on health and health care, are increasingly administered online, potentially maximising respondent access and allowing for enhanced response quality. Online respondents may often choose whether to use a desktop or laptop personal computer (PC), tablet or smartphone, all with different screen sizes and modes of data entry, to complete the survey. To avoid differences in measurement errors, frequently respondents are asked to complete the surveys on a PC despite evidence that handheld devices are increasingly used for internet browsing. As yet, it is unknown if or how the device used to access the survey affects responses and/or the subsequent valuations derived.METHOD: This study uses data from a discrete choice experiment (DCE) administered online to elicit preferences of a general population sample of females for a national breast screening programme. The analysis explores differences in key outcomes such as completion rates, engagement with the survey materials, respondent characteristics, response time, failure of an internal validity test and health care preferences for (1) handheld devices and (2) PC users. Preferences were analysed using a fully correlated random parameter logit (RPL) model to allow for unexplained scale and preference heterogeneity.RESULTS: One thousand respondents completed the survey in its entirety. The most popular access devices were PCs (n = 785), including Windows (n = 705) and Macbooks (n = 69). Two-hundred and fifteen respondents accessed the survey on a handheld device. Most outcomes related to survey behaviour, including failure of a dominance check, 'flat lining', self-reported attribute non-attendance (ANA) or respondent-rated task difficulty, did not differ by device type (p > 0.100). Respondents accessing the survey using a PC were generally quicker (median time to completion 14.5 min compared with 16 min for those using handheld devices) and were significantly less likely to speed through a webpage. Although there was evidence of preference intensity (taste) or variability (scale) heterogeneity across respondents in the sample, it was not driven by the access device.CONCLUSION: Overall, we find that neither preferences nor choice behaviour is associated with the type of access device, as long as respondents are presented with question formats that are easy to use on small touchscreens. Health preference researchers should optimise preference instruments for a range of devices and encourage respondents to complete the surveys using their preferred device. However, we suggest that access device characteristics should be gathered and included when reporting results.

Literature reviews show stated-preference studies, used to understand the values individuals place on health and health care, are increasingly administered online, potentially maximising respondent access and allowing for enhanced response quality. Online respondents may often choose whether to use a desktop or laptop personal computer (PC), tablet or smartphone, all with different screen sizes and modes of data entry, to complete the survey. To avoid differences in measurement errors, frequently respondents are asked to complete the surveys on a PC despite evidence that handheld devices are increasingly used for internet browsing. As yet, it is unknown if or how the device used to access the survey affects responses and/or the subsequent valuations derived.This study uses data from a discrete choice experiment (DCE) administered online to elicit preferences of a general population sample of females for a national breast screening programme. The analysis explores differences in key outcomes such as completion rates, engagement with the survey materials, respondent characteristics, response time, failure of an internal validity test and health care preferences for (1) handheld devices and (2) PC users. Preferences were analysed using a fully correlated random parameter logit (RPL) model to allow for unexplained scale and preference heterogeneity.One thousand respondents completed the survey in its entirety. The most popular access devices were PCs (n = 785), including Windows (n = 705) and Macbooks (n = 69). Two-hundred and fifteen respondents accessed the survey on a handheld device. Most outcomes related to survey behaviour, including failure of a dominance check, 'flat lining', self-reported attribute non-attendance (ANA) or respondent-rated task difficulty, did not differ by device type (p 0.100). Respondents accessing the survey using a PC were generally quicker (median time to completion 14.5 min compared with 16 min for those using handheld devices) and were significantly less likely to speed through a webpage. Although there was evidence of preference intensity (taste) or variability (scale) heterogeneity across respondents in the sample, it was not driven by the access device.Overall, we find that neither preferences nor choice behaviour is associated with the type of access device, as long as respondents are presented with question formats that are easy to use on small touchscreens. Health preference researchers should optimise preference instruments for a range of devices and encourage respondents to complete the surveys using their preferred device. However, we suggest that access device characteristics should be gathered and included when reporting results.

Summary Objective To quantify preferences for attributes of potential analgesic treatments for moderate-to-severe pain associated with osteoarthritis (OA) and/or chronic low back pain (CLBP) as relevant to injectable nerve growth factor (NGF)–inhibitors, nonsteroidal anti-inflammatory drugs (NSAIDs), and opioids. Methods We used a discrete-choice experiment (DCE) to elicit preferences for attributes of OA and CLBP pharmaceutical treatments, and a best-worst scaling (BWS) exercise to further characterize the relative importance of treatment-related side-effect risks. The survey was completed online by 602 US residents with self-reported chronic, moderate-to-severe OA pain and/or CLBP who had tried, had contraindications for, or were unwilling to take currently available pharmaceutical therapies. In the DCE, respondents repeatedly chose between two hypothetical treatments defined by six attributes (symptom control; treatment-related risks of (1) severe joint problems, (2) heart attack, and (3) physical dependence; mode/frequency of administration; and cost). In the BWS exercise, respondents evaluated ten side-effect risks. Random-parameters logit models were estimated; conditional relative attribute importance, maximum acceptable risks, and willingness to pay were calculated. Results The most important DCE attributes were improving symptom control (scaled conditional relative importance, 10.00) and reducing risk of physical dependence (6.99). The three most important BWS attributes were, in rank order, risks of stroke, physical dependence, and heart attack. Respondents were willing to accept a > 4% treatment-related risk of severe joint problems for even modest symptom improvement. Conclusion A pharmaceutical treatment with a risk of severe joint problems was viewed as an acceptable alternative to other treatments with comparable efficacy but risks associated with NSAIDs or opioids.

Introduction: Existing biomedical HIV prevention options, though highly effective, present substantial adherence challenges. End-user input on early-stage design of new HIV prevention approaches is critical to yielding products that achieve high uptake and adherence. The iPrevent Study examined youths’ preferences for key attributes of long-acting Pre-Exposure Prophylaxis (PrEP), with a focus on characteristics pertinent to product delivery alongside key modifiable product attributes. Methods: A discrete choice experiment was conducted with female and male youth aged 18 to 24 in two high-density communities in Cape Town, South Africa during the period July 2017 to January 2019. Sexually active, PrEP-naïve youth were recruited using population-based sampling; targeted sampling was used to enrol men who have sex with men (MSM). In a series of nine questions, participants were asked to choose between two hypothetical products composed of five attributes (form, dosing frequency, access, pain, insertion site). We used a random-parameters logit model to estimate preference weights and trade-offs among product alternatives. We examined differences across three subgroups: females, men who have sex with only women (MSW) and MSM. Results: A total of 807 participants (401 female) were enrolled with a median age of 21 years. Males included 190 MSM. Most youth had tested for HIV (95%) and reported being HIV-negative (91%). Across all groups, duration of effectiveness was the most important attribute, with strong preference for less frequent dosing. Injections were favoured over implants, though these preferences were strongest for females and MSM. Females preferred a product offered at a health clinic and disliked pharmacy access; all groups preferred the arm as the insertion site. Youth were willing to trade their preferred product form for longer duration. Conclusions: Youth indicated strong preferences for longer duration products. Each attribute nonetheless influenced preferences, offering insight into trade-offs that inform long-acting PrEP development.

As new female-initiated HIV prevention products enter development, it is crucial to incorporate women’s preferences to ensure products will be desired, accepted, and used. A discrete-choice experiment was designed to assess the relative importance of six attributes to stated choice of a vaginally delivered HIV prevention product. Sexually active women in South Africa and Zimbabwe aged 18–30 were recruited from two samples: product-experienced women from a randomized trial of four vaginal placebo forms and product-naïve community members. In a tablet-administered survey, 395 women chose between two hypothetical products over eight choice sets. Efficacy was the most important, but there were identifiable preferences among other attributes. Women preferred a product that also prevented pregnancy and caused some wetness (p

Purpose Teriparatide is used to treat patients with established osteoporosis but is often reserved for patients who have inadequate response to antiresorptive therapy. Biosimilar teriparatide, which is believed to have efficacy and safety similar to the originator product, is now available in Colombia. However, little is known about patients’ preferences for originator biologic and biosimilar treatments. Our objective was to quantify the relative importance that patients in Colombia place on features of injectable osteoporosis treatments including whether the treatment is an originator biologic or a biosimilar. Patients and Methods We used a discrete choice experiment (DCE) to elicit preferences of patients with osteoporosis treatment devices in Colombia. The survey was completed by 200 respondents at high risk of fracture, with or without teriparatide experience. Each treatment alternative within the DCE was characterized by five attributes: type of medicine (originator biologic, biosimilar), needle length, angle of injection, how to measure the medicine dose, and how long the medicine can be left unrefrigerated. A random parameters logit regression was used to estimate preferences and conditional relative attribute importance, while controlling for preference heterogeneity. Results A total of 200 patients (mean age = 58.3 years) completed the survey. Most were female (84.5%) and married (54.5%); 50.5% had secondary education or less, 21% had current teriparatide exposure. The attribute with the highest conditional relative importance estimate (standard error) was biologic versus biosimilar (10 [1.11]), followed by needle length (8.06 [1.11]), dose measurement (6.38 [0.87]), refrigeration (3.81 [1.18]), and angle of injection (1.30 [0.66]). Unobserved preference heterogeneity was present and controlled for in the analyses. Conclusion Despite the availability of biosimilar teriparatide in Colombia, patients expressed a strong preference for an originator biologic osteoporosis medicine over a biosimilar osteoporosis medicine, when the efficacy, safety, and cost of the two options were assumed to be the same.

BACKGROUND: In discrete-choice experiments (DCEs), respondents are presented with a series of scenarios and asked to select their preferred choice. In clinical decision making, DCEs allow one to calculate the maximum acceptable risk (MAR) that a respondent is willing to accept for a one-unit increase in treatment efficacy. Most published studies report the average MAR for the whole sample, without conveying any information about heterogeneity. For a sample of psychiatrists prescribing drugs for a series of hypothetical patients with schizophrenia, this article demonstrates how heterogeneity accounted for in the DCE modeling can be incorporated in the derivation of the MAR.METHODS: Psychiatrists were given information about a group of patients' responses to treatment on the Positive and Negative Syndrome Scale (PANSS) and the weight gain associated with the treatment observed in a series of 26 vignettes. We estimated a random parameters logit (RPL) model with treatment choice as the dependent variable.RESULTS: Results from the RPL were used to compute the MAR for the overall sample. This was found to be equal to 4%, implying that, overall, psychiatrists were willing to accept a 4% increase in the risk of an adverse event to obtain a one-unit improvement of symptoms - measured on the PANSS. Heterogeneity was then incorporated in the MAR calculation, finding that MARs ranged between 0.5 and 9.5 across the sample of psychiatrists.LIMITATIONS: We provided psychiatrists with hypothetical scenarios, and their MAR may change when making decisions for actual patients.CONCLUSIONS: This analysis aimed to show how it is possible to calculate physician-specific MARs and to discuss how MAR heterogeneity could have implications for medical practice.

This study provides a methodologically rigorous attempt to disentangle the impact of various factors – unobserved heterogeneity, information and environmental attitudes – on the inclination of individuals to exhibit either a utility maximization or a regret minimization behaviour in a discrete choice experiment for renewable energy programmes described by four attributes: greenhouse gas emissions, power outages, employment in the energy sector, and electricity bill. We explore the ability of different models – multinomial logit, random parameters logit, and hybrid latent class – and of different choice paradigms – utility maximization and regret minimization – in explaining people's choices for renewable energy programmes. The “pure” random regret random parameters logit model explains the choices of our respondents better than other models, indicating that regret is an important choice paradigm, and that choices for renewable energy programmes are mostly driven by regret, rather than by rejoice. In particular, we find that our respondents' choices are driven more by changes in greenhouse gas emissions than by reductions in power outages. Finally, we find that changing the level of information to one attribute has no effect on choices, and that being a member of an environmental organization makes a respondent more likely to be associated with the utility maximization choice framework.

Health researchers design discrete choice experiments (DCEs) to elicit preferences over attributes that define treatments. A DCE can accommodate a limited number of attributes selected by researchers based on numerous factors (e.g., respondent comprehension, cognitive burden, and sample size). For situations where researchers want information about the possible impact of an attribute excluded from the DCE, we propose a method to use a question after the DCE. This follow-up question includes the attributes in the DCE with fixed levels and an additional attribute originally excluded from the DCE. The DCE data can be used to predict the probability that respondents would select one treatment profile over another without the additional attribute. Comparing the prediction to the percentage of the sample who selected each profile when it includes the additional attribute provides information on the potential impact of the additional attribute. We provide an example using data from a DCE on treatments for chronic lymphocytic leukemia. Cost was excluded from the DCE, but the survey included a follow-up question with two fixed treatment profiles, similar to two treatments currently on the market, and a cost for each. Preferences were sensitive to modest changes in cost, highlighting the importance of gathering this information.

We examine the effect of energy efficiency incentives on household energy efficiency home improvements. Starting in February 2007, Italian homeowners have been able to avail themselves of tax credits on the purchase and installation costs of certain types of energy efficiency renovations. We examine two such renovations—door/window replacements and heating system replacements—using multi-year cross-section data from the Italian Consumer Expenditure Survey and focusing on a narrow period around the introduction of the tax credits. Our regressions control for dwelling and household characteristics and economy-wide factors likely to influence the replacement rates. The effects of the policy are different for the two types of renovations. With window replacements, the policy is generally associated with a 30 % or stronger increase in the renovation rates and number of renovations. In the simplest econometric models, the effect is not statistically significant, but the results get stronger when we allow for heterogeneous effects across the country. With heating system replacements, simpler models suggest that the tax credits policy had no effect whatsoever or that free riding was rampant, i.e., people are now accepting subsidies for replacements that they would have done anyway. Further examination suggests a strong degree of heterogeneity in the effects across warmer and colder parts of the country, and effects in the colder areas that are even more pronounced than those for window replacements. These results should, however, be interpreted with caution due to the low rates of renovations, which imply that the effects are estimated relatively imprecisely. ISSN:1570-646X ISSN:1570-6478