scholarly journals Public acceptability of non-pharmaceutical interventions to control a pandemic in the United Kingdom: a discrete choice experiment

2021 ◽  
Author(s):  
Luis Enrique Loria-Rebolledo ◽  
Mandy Ryan ◽  
Verity Watson ◽  
Mesfin G Genie ◽  
Ruben Andreas Sakowsky ◽  
...  
Keyword(s):  
United Kingdom ◽  
Northern Ireland ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Survey Design ◽  
Media Analysis ◽  
The United Kingdom ◽  
Trade Offs ◽  
Excess Deaths

Objective To understand how individuals make trade-offs between features of lockdown interventions to control a pandemic across the four nations of the United Kingdom. Design Survey that included a Discrete Choice Experiment (DCE). The survey design was informed using policy documents, social media analysis and with input from remote think aloud interviews with members of the public (n=23). Setting Nation-wide survey across the four nations of the United Kingdom. Representative sample in terms of age and sex for each of the nations recruited using an online panel between 29th October and 12th December 2020. Participants Individuals who are over 18 years old. A total of 4120 adults completed the survey (1112 in England, 848 in Northern Ireland, 1143 in Scotland and 1098 in Wales). Primary outcome measure Adult preferences for, and trade-offs between, type of lockdown restrictions, length of lockdown, postponement of routine healthcare, excess deaths, impact on ability to buy things and unemployment. Results In all four countries, one out of five respondents were willing to reduce excess deaths at all costs. The majority of adults are willing to accept higher excess deaths if this means lockdowns that are less strict, shorter and do not postpone routine healthcare. On average, respondents in England were willing to accept a higher increase in excess deaths to have less strict lockdown restrictions introduced compared to Scotland, Northern Ireland, and Wales, respectively. Conclusions The majority of the UK population is willing to accept the increase in excess deaths associated with introducing less strict lockdown restrictions. The acceptability of different restriction scenarios varies according to the features of the lockdown and across countries. Authorities can use information about trade-off preferences to inform the introduction of different lockdown restriction levels, and design compensation policies that maximise societal welfare.

scholarly journals Understanding public preferences and trade-offs for government responses during a pandemic: a protocol for a discrete choice experiment in the UK

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e043477
Author(s):  
Mesfin G Genie ◽  
Luis Enrique Loría-Rebolledo ◽  
Shantini Paranjothy ◽  
Daniel Powell ◽  
Mandy Ryan ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Online Survey ◽  
Research Unit ◽  
Media Analysis ◽  
Moral Foundation ◽  
Trade Offs ◽  
Ethics Research ◽  
The Uk

IntroductionSocial distancing and lockdown measures are among the main government responses to the COVID-19 pandemic. These measures aim to limit the COVID-19 infection rate and reduce the mortality rate of COVID-19. Given we are likely to see local lockdowns until a treatment or vaccine for COVID-19 is available, and their effectiveness depends on public acceptability, it is important to understand public preference for government responses.Methods and analysisUsing a discrete choice experiment (DCE), this study will investigate the public’s preferences for pandemic responses in the UK. Attributes (and levels) are based on: (1) lockdown measures described in policy documents; (2) literature on preferences for lockdown measures and (3) a social media analysis. Attributes include: lockdown type; lockdown length; postponement of usual non-urgent medical care; number of excess deaths; number of infections; impact on household spending and job losses. We will prepilot the DCE using virtual think aloud interviews with respondents recruited via Facebook. We will collect preference data using an online survey of 4000 individuals from across the four UK countries (1000 per country). We will estimate the relative importance of the attributes, and the trade-offs individuals are willing to make between attributes. We will test if respondents’ preferences differ based on moral attitudes (using the Moral Foundation Questionnaire), socioeconomic circumstances (age, education, economic insecurity, health status), country of residence and experience of COVID-19.Ethics and disseminationThe University of Aberdeen’s College Ethics Research Board (CERB) has approved the study (reference: CERB/2020/6/1974). We will seek CERB approval for major changes from the developmental and pilot work. Peer-reviewed papers will be submitted, and results will be presented at public health and health economic conferences nationally and internationally. A lay summary will be published on the Health Economics Research Unit blog.

scholarly journals Discrete choice experiment for eliciting preference for health services for patients with ALS and their informal caregivers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katy Tobin ◽  
Sinead Maguire ◽  
Bernie Corr ◽  
Charles Normand ◽  
Orla Hardiman ◽  
...  
Keyword(s):  
Health Services ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Strong Preference ◽  
Multidisciplinary Teams ◽  
Relative Importance ◽  
Trade Offs ◽  
Als Patients ◽  
The Impact

Abstract Background Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative condition with a mean life expectancy of 3 years from first symptom. Understanding the factors that are important to both patients and their caregivers has the potential to enhance service delivery and engagement, and improve efficiency. The Discrete Choice Experiment (DCE) is a stated preferences method which asks service users to make trade-offs for various attributes of health services. This method is used to quantify preferences and shows the relative importance of the attributes in the experiment, to the service user. Methods A DCE with nine choice sets was developed to measure the preferences for health services of ALS patients and their caregivers and the relative importance of various aspects of care, such as timing of care, availability of services, and decision making. The DCE was presented to patients with ALS, and their caregivers, recruited from a national multidisciplinary clinic. A random effects probit model was applied to estimate the impact of each attribute on a participant’s choice. Results Patients demonstrated the strongest preferences about timing of receiving information about ALS. A strong preference was also placed on seeing the hospice care team later rather than early on in the illness. Patients also indicated their willingness to consider the use of communication devices. Grouping by stage of disease, patients who were in earlier stages of disease showed a strong preference for receipt of extensive information about ALS at the time of diagnosis. Caregivers showed a strong preference for engagement with healthcare professionals, an attribute that was not prioritised by patients. Conclusions The DCE method can be useful in uncovering priorities of patients and caregivers with ALS. Patients and caregivers have different priorities relating to health services and the provision of care in ALS, and patient preferences differ based on the stage and duration of their illness. Multidisciplinary teams must calibrate the delivery of care in the context of the differing expectations, needs and priorities of the patient/caregiver dyad.

scholarly journals Understanding uptake of digital health products: Methodology tutorial for a Discrete Choice Experiment using a Bayesian efficient design (Preprint)

2021 ◽  
Author(s):  
Dorothy Szinay ◽  
Rory Cameron ◽  
Felix Naughton ◽  
Jennifer A. Whitty ◽  
Jamie Brown ◽  
...  
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Stated Preference ◽  
Digital Health ◽  
Revealed Preferences ◽  
Quantitative Methodology ◽  
Efficient Design ◽  
Trade Offs ◽  
Health Products

UNSTRUCTURED Understanding the preferences of potential users of digital health products is beneficial for digital health policy and planning. Stated preference methods could help elicit individuals’ preferences in the absence of observational data. A discrete choice experiment (DCE) is a commonly used stated preference method; a quantitative methodology that argues that individuals make trade-offs when engaging in a decision by choosing an alternative of a product or service that offers the greatest utility, or benefit. This methodology is widely used in health economics in situations where revealed preferences are difficult to collect but is much less used in the field of digital health. This article outlines the stages involved in developing a discrete choice experiment. As a case study, it uses the application of a DCE for revealing preferences in targeting the uptake of smoking cessation apps. It describes the establishment of attributes, the construction of choice tasks of two or more alternatives, and the development of the experimental design. This tutorial offers a guide for researchers with no prior knowledge of this research technique.

scholarly journals An assessment of students’ job preference using a discrete choice experiment: a postgraduate case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Henry Gyarteng-Mensah ◽  
De-Graft Owusu-Manu ◽  
David Edwards ◽  
Isaac Baidoo ◽  
Hatem El-Gohary
Keyword(s):  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Negative Impact ◽  
Employment Decisions ◽  
Content Type ◽  
Postgraduate Students ◽  
Trade Offs ◽  
Job Preference

Purpose Using a discrete choice experiment (DCE), this study aims to better understand the job preference of postgraduate students studying at the Kwame Nkrumah University of Science and Technology-Institute of Distance Learning, Ghana and also rank the attributes of a job they deem important. Design/methodology/approach The research adopted a positivist epistemological design contextualised within a deductive approach and case study strategy. Primary survey data was collected from a stratified random sample of 128 postgraduate students with multi-sectorial career prospects. Sample students were subjected to a DCE in which their stated preferences were collected using closed-ended questionnaires with 28 pairs of hypothetical job profiles. Respondents’ preferences from the DCE data were then modelled using the conditional logit. Findings The research reveals that: salary in the range GHC 2,800.00 to GHC 3,400.00 ($1 = GHS 5.3); supportive management; very challenging jobs; and jobs located in the city were the top attributes that were significant and had the most impact in increasing the utility of selecting a particular job. Interestingly, jobs with no extra hours workload were not significant hence, had a negative impact upon student preferences. Originality/value This novel research is the first to use a DCE to better elicit preference and trade-offs of postgraduate students in a developing country towards varying job characteristics that have an impact on their future employment decisions. Knowledge advancements made provide invaluable insight to employers and policymakers on the key criteria that should be implemented to retain the best candidate.

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