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.

word count: 198 2 ABSTRACT Purpose:Broadening access to genomic testing and counselling will be necessary to realise the benefits of personalised healthcare. This study aimed to assess the feasibility of delivering a standardised genomic care model for inherited retinal dystrophy (IRD) and of using selected measures to quantify its impact on patients. Methods:A pre-post prospective cohort study recruited 98 patients affected by IRD to receive standardised multidisciplinary care. A checklist was used to assess the fidelity of the care process. Patient-reported outcome measures -the Genetic Counselling Outcome Scale (GCOS-24), ICEpop CAPability measure for Adults (ICECAP-A), and the EuroQol 5-dimension questionnaire (EQ-5D) -and a resource-use questionnaire were administered to investigate rates of missingness, ceiling effects, and changes over time. Results:The care model was delivered consistently. Higher rates of missingness were found for the genetic-specific measure (GCOS-24). Considerable ceiling effects were observed for the generic measure (EQ-5D). The ICECAP-A yielded less missing data, without significant ceiling effects. It was feasible to use telephone interviews for follow-up data collection. Conclusion:The study highlighted challenges and solutions associated with efforts to standardise genomic care for IRD. The study identified appropriate methods 3 for a future definitive study to assess the clinical and costeffectiveness of the care model.

This study offers important insights into the factors influencing current prescribing practice for first-line biological therapies for people with psoriasis. It provides baseline data to inform the evaluation of future potential changes that may affect prescribing behaviour, such as stratified medicine.

Whole-genome sequencing (WGS) is being applied within research settings across Europe to develop genomic WGS-based diagnostic tests. The focus of this perspective paper is to describe if, and how, current approaches of health technology assessment could be applied to WGS-based diagnostic tests. This perspective draws on the collective view from a trans-European multidisciplinary consortium of methodologists, clinicians and scientists. Specific challenges can be described by using the PICO (population, intervention, comparator, outcome) framework to inform health technology assessment. Practical solutions are suggested which require joined-up, multidisciplinary working across healthcare systems using existing expert networks so that emergent issues for the health technology assessment of WGS can be met in a timely fashion.