Preferences for interventions designed to increase cervical screening uptake in non-attending young women: how findings from a discrete choice experiment compare with observed behaviours in a trial

Background Young women’s attendance at cervical screening in the UK is continuing to fall and the incidence of invasive cervical cancer has begun to rise. Objectives We assessed the preferences of non-attending young women for alternative ways of delivering cervical screening. Design Postal discrete choice experiment (DCE) conducted during the STRATEGIC study of interventions for increasing cervical screening uptake. Attributes included action required to arrange a test, location of the test, availability of a nurse navigator and cost to the NHS. Setting and participants Non-attending young women in two UK regions. Main outcome measures Responses were analysed using a mixed multinomial logit model. A predictive analysis identified the most preferable strategy compared to current screening. Preferences from the DCE were compared with women’s observed behaviours during the STRATEGIC trial. Results The DCE response rate was 5.5% (222/4000) and 94% of respondents agreed screening is important. Preference heterogeneity existed around all attributes with strong evidence for test location. Relative to current screening, unsolicited self-sampling kits for home use appeared most preferable. The STRATEGIC trial showed this same intervention to be most effective although many women who received it and were screened attended for conventional cytology instead. Conclusions The DCE and trial identified the unsolicited self-sampling kit as the most preferred / effective intervention. Data from the DCE suggested that the decision of some women receiving the kit in the trial to attend for conventional cytology may be due to anxieties around home testing coupled with a knowledge that ignoring the kit could potentially have life changing consequences. Keywords: cervical cancer; screening uptake; young women; preferences; discrete choice experiments; heterogeneity; United Kingdo

Framing and signalling effects of taxes on sugary drinks: a discrete choice experiment among households in Great Britain

Taxes on sugar-sweetened beverages (SSBs) are in place in many countries to combat obesity with emerging evidence that these are effective in reducing purchases of SSBs. In this study, we tested whether signalling and framing the price increase from an SSB tax explicitly as a health-related, earmarked measure reduces the demand for SSBs more than an equivalent price increase. We measured the demand for non-alcoholic beverages with a discrete choice experiment (DCE) administered online to a randomly selected group of n = 603 households with children in Great Britain (GB) who regularly purchase SSBs. We find a suggestive evidence that a price increase leads to a larger reduction in the probability of choosing SSBs when it is signalled as a tax and framed as a health-related and earmarked policy. Respondents who did not support a tax on SSBs, who were also more likely to choose SSBs in the first place, were on average more responsive to a price increase framed as an earmarked tax than those who supported the tax. The predictive validity of the DCE, to capture preferences for beverages, was confirmed using actual purchase data. The findings imply that a well-signalled and earmarked tax on SSBs could improve its effectiveness at reducing the demand

Understanding the formation and influence of attitudes in patients' treatment choices for lower back pain: Testing the benefits of a hybrid choice model approach

A growing number of studies across different fields are making use of a new class of choice models, labelled variably as hybrid model structures or integrated choice and latent variable models, and incorporating the role of attitudes in decision making. To date, this technique has not been used in health economics. The present paper looks at the formation of such attitudes and their role in patients' treatment choices in the context of low back pain. We use stated choice data collected from a sample of 561 patients with 348 respondents referred to a regional spine centre in Middelfart, Denmark in spring/summer 2012. We show how the hybrid model structure is able to make a link between attitudinal questions and treatment choices, and also explains variation of these attitudes across key socio-demographic groups. However, we also show how, in this case, only a small share of the overall heterogeneity is linked to the latent attitude construct. Despite their growing popularity, the key findings of the advanced model, despite a greater insight into the drivers of attitudes and small gains in efficiency, are no different from standard approaches which remain easier to apply

A cluster randomised trial of strategies to increase cervical screening uptake at first invitation (STRATEGIC)

Acknowledgements The STRATEGIC study research team thanks Sara Rodgers and Laura Clark at the University of York for their input conducting qualitative interviews. We are grateful to Maggie Redshaw at the National Perinatal Epidemiology Unit (NPEU) for helpful suggestions to attempt to improve the response rate in our study. We also would like to thank the NPEU design team who significantly improved the look of our final questionnaire, and the NPEU administration team for their assistance preparing the mail-out material. Special thanks are given to our data entry team Sissi Hernandez-Quesada, Jacob Stevens and Pamela White. The authors would also like to thank Zeinab Abbas for her valuable assistance in the economic evaluation. We would like to express our gratitude to the teams at the English and Scottish screening agencies for their willingness to collaborate in this study. Finally, we thank all women who participated and completed the DCE survey. Any errors or omissions are entirely our own. We are indebted to the support provided by the Lancashire and South Cumbria Agency, without whom we could not have provided the interventions. We also wish to thank Linsey Nelson for her painstaking work in helping to compile this report. Funding Funding for this study was provided by the Health Technology Assessment programme of the National Institute for Health Research.Peer reviewedPublisher PD

Consumer Preferences Regarding Country of Origin for Multiple Meat Products

Despite the growing use of country of origin (CoO) information and labels on food, the extent to which consumers really value this information is unclear. In an effort to understand this issue we present results of a hypothetical discrete choice experiment examining consumer willingness-to-pay for CoO information about meat and meat products. Our results reveal that CoO information is positively valued for all the food products we consider. However, it is relatively less important compared to other food attributes for a large number of products such as bacon, pizza and ready meals. Our results suggest that consumers do not value very highly CoO information for many of the food products examined. Therefore, if the associated costs of mandatory CoO implementation are sufficiently high this raises questions about the inclusion of this information on food labels

Logit Mixed Logit Under Asymmetry and Multimodality of WTP: a Monte Carlo Evaluation

The logit‐mixed logit (LML) model advances choice modeling by generalizing previous parametric and semi‐nonparametric specifications and allowing retrieval of flexible taste distributions. Using standard operating conditions in the field, we report results from Monte Carlo experiments designed to assess the finite sample bias‐variance tradeoff for the LML using as a benchmark conventional Mixed logit models (MXL) under asymmetric and multimodal taste distributions. The LML specification always outperforms the MXL in terms of bias, but when the variance around modes is high the mean squared error (MSE) is lower than that of MXL only at sample sizes larger than usual and with some nuances. D‐error minimizing experimental design predicated on multinomial logit significantly reduces MSE, but no clear winner is found between polynomial, step, and spline functions for the multidimensional grid function. Analysis of empirical data from a choice experiment on tap water shows that multimodality emerges only if higher number of node parameters are used in the LML