Making Use of Technology to Improve Stated Preference Studies.

The interest in quantifying stated preferences for health and healthcare continues to grow, as does the technology available to support and improve health preference studies. Technological advancements in the last two decades have implications and opportunities for preference researchers designing, administering, analysing, interpreting and applying the results of stated preference surveys. In this paper, we summarise selected technologies and how these can benefit a preference study. We discuss empirical evaluations of the technology in preference research, with examples from health where possible. The technologies reviewed include serious games, virtual reality, eye tracking, innovative formats and decision aids with values clarification components. We conclude with a critical reflection on the benefits and limitations of implementing (often costly) technology alongside stated preference studies.

Understanding the Impact of Different Modes of Information Provision on Preferences for a Newborn Bloodspot Screening Program in the United Kingdom.

Introduction. This study aimed to understand the impact of alternative modes of information provision on the stated preferences of a sample of the public for attributes of newborn bloodspot screening (NBS) in the United Kingdom. Methods. An online discrete choice experiment survey was designed using 4 attributes to describe NBS (effect of treatment on the condition, time to receive results, whether the bloodspot is stored, false-positive rate). Survey respondents were randomized to 1 of 2 survey versions presenting the background training materials using text from a leaflet (leaflet version) or an animation (animation version). Heteroskedastic conditional logistic regression was used to estimate the effect of mode of information provision on error variance. Results. The survey was completed by 1,000 respondents (leaflet = 525; animation = 475). Preferences for the attributes in the DCE were the same in both groups, but the group receiving the animation version had 9% less error variance in their responses. Respondents completing the animation version gave higher ratings compared with the leaflet version in terms of ease of perceived understanding. Subgroup analysis suggested that the animation was particularly effective at reducing error variance for women (20%), people with previous children (16.5%), and people between the ages of 35 and 45 y (11.8%). Limitations. This study used simple DCE with 4 attributes, and the results may vary for more complex choice questions. Conclusion. This study provides evidence that that supplementing the information package offered to parents choosing to take part in NBS with an animation may aid them their decision making. Further research would be needed to test the animation in the health system. Implications. Researchers designing DCE should carefully consider the design of their training materials to improve the quality of data collected. Highlights: Prior to completing a discrete choice experiment about newborn bloodspot screening, respondents were shown information using either a leaflet-based or animated format.Respondents receiving information using an animation version reported that the information was slightly easier to understand and exhibited 9% less error variance in expressing their preferences for a newborn screening program.Using the animation version to present information appeared to have a larger impact in reducing the error variance of responses for specific respondents including women, individuals with children, individuals between the ages of 35 and 45 y, and individuals educated to degree level.

How to Present a Decision Object in Health Preference Research: Attributes and Levels, the Decision Model, and the Descriptive Framework.

In health preference research (HPR) studies, data are generated by participants'/subjects' decisions. When developing an HPR study, it is therefore important to have a clear understanding of the components of a decision and how those components stimulate participant behavior. To obtain valid and reliable results, study designers must sufficiently describe the decision model and its components. HPR studies require a detailed examination of the decision criteria, detailed documentation of the descriptive framework, and specification of hypotheses. The objects that stimulate subjects' decisions in HPR studies are defined by attributes and attribute levels. Any limitations in the identification and presentation of attributes and levels can negatively affect preference elicitation, the quality of the HPR data, and study results. This practical guide shows how to link the HPR question to an underlying decision model. It covers how to (1) construct a descriptive framework that presents relevant characteristics of a decision object and (2) specify the research hypotheses. The paper outlines steps and available methods to achieve all this, including the methods' advantages and limitations.

Adolescent and caregiver preferences for juvenile idiopathic arthritis treatment: a discrete-choice experiment.

BACKGROUND: This study aimed to elicit and quantify preferences for treatments for juvenile idiopathic arthritis (JIA). METHODS: We conducted a discrete-choice experiment among adolescents with JIA in the United States (US) (n = 197) and United Kingdom (UK) (n = 100) and caregivers of children with JIA in the US (n = 207) and UK (n = 200). In a series of questions, respondents chose between experimentally designed profiles for hypothetical JIA treatments that varied in efficacy (symptom control; time until next flare-up), side effects (stomachache, nausea, and vomiting; headaches), mode and frequency of administration, and the need for combination therapy. Using a random-parameters logit model, we estimated preference weights for these attributes, from which we derived their conditional relative importance. RESULTS: On average, respondents preferred greater symptom control; greater time until the next flare-up; less stomachache, nausea, and vomiting; and fewer headaches. However, adolescents and caregivers in the US were generally indifferent across varying modes and frequencies of administration. UK adolescents and caregivers preferred tablets, syrup, or injections to intravenous infusions. US and UK adolescents were indifferent between treatment with monotherapy or combination therapy; caregivers in the UK preferred treatment with combination therapy to monotherapy. Subgroup analysis showed preference heterogeneity across characteristics including gender, treatment experience, and symptom experience in both adolescents and caregivers. CONCLUSIONS: Improved symptom control, prolonged time to next flare-up, and avoidance of adverse events such as headache, stomachache, nausea, and vomiting are desirable characteristics of treatment regimens for adolescents with JIA and their caregivers.

Discrete choice experiment to investigate preferences for psychological intervention in cardiac rehabilitation.

OBJECTIVE: Cardiac rehabilitation (CR) is offered to people who recently experienced a cardiac event, and often comprises of exercise, education and psychological care. This stated preference study aimed to investigate preferences for attributes of a psychological therapy intervention in CR. METHODS: A discrete choice experiment (DCE) was conducted and recruited a general population sample and a trial sample. DCE attributes included the modality (group or individual), healthcare professional providing care, information provided prior to therapy, location and the cost to the National Health Service (NHS). Participants were asked to choose between two hypothetical designs of therapy, with a separate opt-out included. A mixed logit model was used to analyse preferences. Cost to the NHS was used to estimate willingness to pay (WTP) for aspects of the intervention design. RESULTS: Three hundred and four participants completed the DCE (general public sample (n=262, mean age 47, 48% female) and trial sample (n=42, mean age 66, 45% female)). A preference for receiving psychological therapy was demonstrated by both samples (general population WTP £1081; 95% CI £957 to £1206). The general population appeared to favour individual therapy (WTP £213; 95% CI £160 to £266), delivered by a CR professional (WTP £48; 9% % CI £4 to £93) and with a lower cost (ß=-0.002; p<0.001). Participants preferred to avoid options where no information was received prior to starting therapy (WTP -£106; 95% CI -£153 to -£59). Results for the location attribute were variable and challenging to interpret. CONCLUSIONS: The study demonstrates a preference for psychological therapy as part of a programme of CR, as participants were more likely to opt-in to therapy. Results indicate that some aspects of the delivery which may be important to participants can be tailored to design a psychological therapy. Preference heterogeneity is an issue which may prevent a 'one-size-fits-all' approach to psychological therapy in CR.

How do women want to receive information about non-invasive prenatal testing? Evidence from a discrete choice experiment.

OBJECTIVE: Non-invasive prenatal testing (NIPT) identifies the risk of abnormalities in pregnancy, potentially reducing the risk of miscarriage associated with invasive tests. This study aimed to understand the preferences of current and future mothers about the content, format and timing of information provision about NIPT. METHODS: An online discrete choice experiment was designed comprising four attributes: when in the pregnancy information is provided (4 levels); degree of detail (2 levels); information format (6 levels); cost to women for gathering information (5 levels). Respondents included women identified by an online-panel company in Sweden. The mathematical design was informed by D-efficient criteria. Choice data were analysed using uncorrelated random parameters logit and latent class models. RESULTS: One thousand Swedish women (56% current mothers) aged 18-45 years completed the survey. On average, women preferred extensive information provided at/before 9 weeks of pregnancy. There was heterogeneity in preferences about the desired format of information provision (website, mobile app or individual discussion with a midwife) in the population. CONCLUSION: Women had clear preferences about the desired content, format and timing of information provision about NIPT. It is important to tailor information provision to enable informed choices about NIPT.

Current Practices for Accounting for Preference Heterogeneity in Health-Related Discrete Choice Experiments: A Systematic Review.

BACKGROUND: Accounting for preference heterogeneity is a growing analytical practice in health-related discrete choice experiments (DCEs). As heterogeneity may be examined from different stakeholder perspectives with different methods, identifying the breadth of these methodological approaches and understanding the differences are major steps to provide guidance on good research practices. OBJECTIVES: Our objective was to systematically summarize current practices that account for preference heterogeneity based on the published DCEs related to healthcare. METHODS: This systematic review is part of the project led by the Professional Society for Health Economics and Outcomes Research (ISPOR) health preference research special interest group. The systematic review conducted systematic searches on the PubMed, OVID, and Web of Science databases, as well as on two recently published reviews, to identify articles. The review included health-related DCE articles published between 1 January 2000 and 30 March 2020. All the included articles also presented evidence on preference heterogeneity analysis based on either explained or unexplained factors or both. RESULTS: Overall, 342 of the 2202 (16%) articles met the inclusion/exclusion criteria for extraction. The trend showed that analyses of preference heterogeneity increased substantially after 2010 and that such analyses mainly examined heterogeneity due to observable or unobservable factors in individual characteristics. Heterogeneity through observable differences (i.e., explained heterogeneity) is identified among 131 (40%) of the 342 articles and included one or more interactions between an attribute variable and an observable characteristic of the respondent. To capture unobserved heterogeneity (i.e., unexplained heterogeneity), the studies largely estimated either a mixed logit (n = 205, 60%) or a latent-class logit (n = 112, 32.7%) model. Few studies (n = 38, 11%) explored scale heterogeneity or heteroskedasticity. CONCLUSIONS: Providing preference heterogeneity evidence in health-related DCEs has been found as an increasingly used practice among researchers. In recent studies, controlling for unexplained preference heterogeneity has been seen as a common practice rather than explained ones (e.g., interactions), yet a lack of providing methodological details has been observed in many studies that might impact the quality of analysis. As heterogeneity can be assessed from different stakeholder perspectives with different methods, researchers should become more technically pronounced to increase confidence in the results and improve the ability of decision makers to act on the preference evidence.

Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report.

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

Factors that impact on women's decision-making around prenatal genomic tests: An international discrete choice survey.

OBJECTIVE: We conducted a survey-based discrete-choice experiment (DCE) to understand the test features that drive women's preferences for prenatal genomic testing, and explore variation across countries. METHODS: Five test attributes were identified as being important for decision-making through a literature review, qualitative interviews and quantitative scoring exercise. Twelve scenarios were constructed in which respondents choose between two invasive tests or no test. Women from eight countries who delivered a baby in the previous 24 months completed a DCE presenting these scenarios. Choices were modeled using conditional logit regression analysis. RESULTS: Surveys from 1239 women (Australia: n = 178; China: n = 179; Denmark: n = 88; Netherlands: n = 177; Singapore: n = 90; Sweden: n = 178; UK: n = 174; USA: n = 175) were analyzed. The key attribute affecting preferences was a test with the highest diagnostic yield (p < 0.01). Women preferred tests with short turnaround times (p < 0.01), and tests reporting variants of uncertain significance (VUS; p < 0.01) and secondary findings (SFs; p < 0.01). Several country-specific differences were identified, including time to get a result, who explains the result, and the return of VUS and SFs. CONCLUSION: Most women want maximum information from prenatal genomic tests, but our findings highlight country-based differences. Global consensus on how to return uncertain results is not necessarily realistic or desirable.

A General Public Study on Preferences and Welfare Impacts of Antimicrobial Resistance in the United Kingdom.

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.

Towards Personalising the Use of Biologics in Rheumatoid Arthritis: A Discrete Choice Experiment.

INTRODUCTION: There have been promising developments in technologies and associated algorithm-based prescribing ('stratified approach') to target biologics to sub-groups of people with rheumatoid arthritis (RA). The acceptability of using an algorithm-guided approach in practice is likely to depend on various factors. OBJECTIVE: This study quantified preferences for an algorithm-guided approach to prescribing biologics (termed 'biologic calculator'). METHODS: An online discrete choice experiment (DCE) was designed to elicit preferences from patients and the public for using a 'biologic calculator' compared with conventional prescribing. Treatment approaches were described by five attributes: delay to starting treatment; positive and negative predictive value (PPV/NPV); risk of infection; and cost saving to the UK national health service. Each survey contained six choice sets asking respondents to select their preferred option from two hypothetical biologic calculators or conventional prescribing. Background questions included sociodemographics, health status and healthcare experiences. DCE data were analysed using mixed logit models. RESULTS: Completed choice data were collected from 292 respondents (151 patients with RA and 142 members of the public). PPV, NPV and risk of infection were the most highly valued attributes to respondents deciding between prescribing strategies. CONCLUSION: Respondents were generally receptive to personalised medicine in RA, but researchers developing personalised approaches should pay close attention to generating evidence on both the PPV and the NPV of their technologies.

Mobilising the Next Generation of Stated-Preference Studies: the Association of Access Device with Choice Behaviour and Data Quality.

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.

Utilising Patient and Public Involvement in Stated Preference Research in Health: Learning from the Existing Literature and a Case Study.

Publications reporting discrete choice experiments of healthcare interventions rarely discuss whether patient and public involvement (PPI) activities have been conducted. This paper presents examples from the existing literature and a detailed case study from the National Institute for Health Research-funded PATHWAY programme that comprehensively included PPI activities at multiple stages of preference research. Reflecting on these examples, as well as the wider PPI literature, we describe the different stages at which it is possible to effectively incorporate PPI across preference research, including the design, recruitment and dissemination of projects. Benefits of PPI activities include gaining practical insights from a wider perspective, which can positively impact experiment design as well as survey materials. Further benefits included advice around recruitment and reaching a greater audience with dissemination activities, amongst others. There are challenges associated with PPI activities; examples include time, cost and outlining expectations. Overall, although we acknowledge practical difficulties associated with PPI, this work highlights that it is possible for preference researchers to implement PPI across preference research. Further research systematically comparing methods related to PPI in preference research and their associated impact on the methods and results of studies would strengthen the literature.

Public preferences regarding data linkage for research: a discrete choice experiment comparing Scotland and Sweden.

BACKGROUND: There are increasing examples of linking data on healthcare resource use and patient outcomes from different sectors of health and social care systems. Linked data are generally anonymised, meaning in most jurisdictions there are no legal restrictions to their use in research conducted by public or private organisations. Secondary use of anonymised linked data is contentious in some jurisdictions but other jurisdictions are known for their use of linked data. The publics' perceptions of the acceptability of using linked data is likely to depend on a number of factors. This study aimed to quantify the preferences of the public to understand the factors that affected views about types of linked data and its use in two jurisdictions. METHOD: An online discrete choice experiment (DCE) previously conducted in Scotland was adapted and replicated in Sweden. The DCE was designed, comprising five attributes, to elicit the preferences from a representative sample of the public in both jurisdictions. The five attributes (number of levels) were: type of researcher using linked data (four); type of data being linked (four); purpose of the research (three); use of profit from using linked data (four); who oversees the research (four). Each DCE contained 6 choice-sets asking respondents to select their preferred option from two scenarios or state neither were acceptable. Background questions included socio-demographics. DCE data were analysed using conditional and heteroskedastic conditional logit models to create forecasts of acceptability. RESULTS: The study sample comprised members of the public living in Scotland (n = 1004) and Sweden (n = 974). All five attributes were important in driving respondents' choices. Swedish and Scottish preferences were mostly homogenous with the exception of 'who oversees the research using linked data', which had relatively less impact on the choices observed from Scotland. For a defined 'typical' linked data scenario, the probability (on average) of acceptance was 85.7% in Sweden and 82.4% in Scotland. CONCLUSION: This study suggests that the public living in Scotland and Sweden are open to using anonymised linked data in certain scenarios for research purposes but some caution is advisable if the anonymised linked data joins health to non-health data.

Frameworks and guidance to support ethical public health practice.

This article reports and reflects on an element of a recent survey of UK public health professionals, specifically in relation to the Public Health Knowledge and Skills Framework (PHSKF) and the ethical requirements that underpin public health practice. Only 38.4% of respondents reported accessing the PHKSF and a mere 13.7% reported accessing the accompanying background paper on ethical public health practice. Given that ethical practice underpins the PHSKF, it is concerning that so few respondents are familiar with the PHSKF and one of the source documents. While issuing frameworks and guidance is one way to support public health practice, there is a further need for greater integration of skills and knowledge around ethical public health practice within education and training initiatives.

Reporting Formative Qualitative Research to Support the Development of Quantitative Preference Study Protocols and Corresponding Survey Instruments: Guidelines for Authors and Reviewers.

BACKGROUND: Formative qualitative research is foundational to the methodological development process of quantitative health preference research (HPR). Despite its ability to improve the validity of the quantitative evidence, formative qualitative research is underreported. OBJECTIVE: To improve the frequency and quality of reporting, we developed guidelines for reporting this type of research. The guidelines focus on formative qualitative research used to develop robust and acceptable quantitative study protocols and corresponding survey instruments in HPR. METHODS: In December 2018, a steering committee was formed as a means to accumulate the expertise of the HPR community on the reporting guidelines (21 members, seven countries, multiple settings and disciplines). Using existing guidelines and examples, the committee constructed, revised, and refined the guidelines. The guidelines underwent beta testing by three researchers, and further revisions to the guidelines were made based on their feedback as well as on comments from members of the International Academy of Health Preference Research (IAHPR) and the editorial board of The Patient: Patient-Centered Outcomes Research. RESULTS: The guidelines have five components: introductory material (4 domains), methods (12), results/findings (2), discussion (2), and other (2). They are concordant with existing guidelines, published examples, beta-testing results, and expert comments. CONCLUSIONS: Publishing formative qualitative research is a necessary step toward strengthening the foundation of any quantitative study, enhancing the relevance of its preference evidence. The guidelines should aid researchers, reviewers, and regulatory agencies and promote transparency within HPR more broadly.

Opening the 'Black Box': An Overview of Methods to Investigate the Decision-Making Process in Choice-Based Surveys.

The desire to understand the preferences of patients, healthcare professionals and the public continues to grow. Health valuation studies, often in the form of discrete choice experiments, a choice based survey approach, proliferate as a result. A variety of methods of pre-choice process analysis have been developed to investigate how and why people make their decisions in such experiments and surveys. These techniques have been developed to investigate how people acquire and process information and make choices. These techniques offer the potential to test and improve theories of choice and/or associated empirical models. This paper provides an overview of such methods, with the focus on their use in stated choice-based healthcare studies. The methods reviewed are eye tracking, mouse tracing, brain imaging, deliberation time analysis and think aloud. For each method, we summarise the rationale, implementation, type of results generated and associated challenges, along with a discussion of possible future developments.

A Picture is Worth a Thousand Words: The Role of Survey Training Materials in Stated-Preference Studies.

BACKGROUND: Online survey-based methods are increasingly used to elicit preferences for healthcare. This digitization creates an opportunity for interactive survey elements, potentially improving respondents' understanding and/or engagement. OBJECTIVE: Our objective was to understand whether, and how, training materials in a survey influenced stated preferences. METHODS: An online discrete-choice experiment (DCE) was designed to elicit public preferences for a new targeted approach to prescribing biologics ("biologic calculator") for rheumatoid arthritis (RA) compared with conventional prescribing. The DCE presented three alternatives, two biologic calculators and a conventional approach (opt out), described by five attributes: delay to treatment, positive predictive value, negative predictive value, infection risk, and cost saving to the national health service. Respondents were randomized to receive training materials as plain text or an animated storyline. Training materials contained information about RA and approaches to treatment and described the biologic calculator. Background questions included sociodemographics and self-reported measures of task difficulty and attribute non-attendance. DCE data were analyzed using conditional and heteroskedastic conditional logit (HCL) models. RESULTS: In total, 300 respondents completed the DCE, receiving either plain text (n = 158) or the animated storyline (n = 142). The HCL showed the estimated coefficients for all attributes aligned with a priori expectations and were statistically significant. The scale term was statistically significant, indicating that respondents who received plain-text materials had more random choices. Further tests suggested preference homogeneity after accounting for differences in scale. CONCLUSIONS: Using animated training materials did not change the preferences of respondents, but they appeared to improve choice consistency, potentially allowing researchers to include more complex designs with increased numbers of attributes, levels, alternatives or choice sets.

Education, training, and experience in public health ethics and law within the UK public health workforce.

BACKGROUND: Public health ethics and law (PHEL) is a core professional competency for the public health workforce. However, few data are available describing the extent to which UK public health workforce members experience ethical and legal issues or have sufficient educational and/or training background to adequately deal with such issues. METHODS: An anonymous online survey was developed for dissemination via member mailing lists of the: Faculty of Public Health, Royal Society of Public Health, and UK Public Health Register. Public Health England also included a link to the survey in their newsletter. The survey included questions about education, training, and experience in relation to PHEL. The survey was deployed from October 2017 to January 2018. RESULTS: The survey was completed by a diverse sample of five hundred and sixty-two individuals. The majority of respondents reported: (i) regularly encountering ethical issues, (ii) resolving ethical issues through personal reflection, (iii) having little or no education and training in PHEL, and (iv) questioning whether they have dealt with ethical issues encountered in practice in the best way. CONCLUSIONS: The results suggest that there is a need to develop and support wider PHEL capacity within the UK public health workforce through the provision of PHEL education, training, guidance, and mentoring.

The role of information provision in economic evaluations of non-invasive prenatal testing: a systematic review.

BACKGROUND: Technological progress has led to changes in the antenatal screening programmes, most significantly the introduction of non-invasive prenatal testing (NIPT). The availability of a new type of testing changes the type of information that the parent(s) require before, during and after screening to mitigate anxiety about the testing process and results. OBJECTIVES: To identify the extent to which economic evaluations of NIPT have accounted for the need to provide information alongside testing and the associated costs and health outcomes of information provision. METHODS: A systematic review of economic evaluations of NIPTs (up to February 2018) was conducted. Medline, Embase, CINAHL and PsychINFO were searched using an electronic search strategy combining a published economic search filter (from NHS economic evaluations database) with terms related to NIPT and screening-related technologies. Data were extracted using the Consolidated Health Economic Evaluation Reporting Standards framework and the results were summarised as part of a narrative synthesis. RESULTS: A total of 12 economic evaluations were identified. The majority of evaluations (n = 10; 83.3%) involved cost effectiveness analysis. Only four studies (33.3%) included the cost of providing information about NIPT in their economic evaluation. Two studies considered the impact of test results on parents' quality of life by allowing utility decrements for different outcomes. Some studies suggested that the challenges of valuing information prohibited their inclusion in an economic evaluation. CONCLUSION: Economic evaluations of NIPTs need to account for the costs and outcomes associated with information provision, otherwise estimates of cost effectiveness may prove inaccurate.