Energy policy trade-offs in Poland: A best-worst scaling discrete choice experiment

Energy Policy ◽  
2021 ◽  
Vol 156 ◽  
pp. 112465
Author(s):  
Kentaka Aruga ◽  
Timothy Bolt ◽  
Przemysław Pest
Keyword(s):  
Energy Policy ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Trade Offs ◽  
Best Worst Scaling

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 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 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.

scholarly journals Finding the best fit: examining the decision-making of augmentative and alternative communication professionals in the UK using a discrete choice experiment

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e030274
Author(s):  
Edward J D Webb ◽  
Yvonne Lynch ◽  
David Meads ◽  
Simon Judge ◽  
Nicola Randall ◽  
...  
Keyword(s):  
Decision Making ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Augmentative And Alternative Communication ◽  
Mixed Logit ◽  
Information Criterion ◽  
Alternative Communication ◽  
Trade Offs ◽  
The Uk

ObjectivesMany children with varied disabilities, for example, cerebral palsy, autism, can benefit from augmentative and alternative communication (AAC) systems. However, little is known about professionals’ decision-making when recommending symbol based AAC systems for children. This study examines AAC professionals’ preferences for attributes of AAC systems and how they interact with child characteristics.DesignAAC professionals answered a discrete choice experiment survey with AAC system and child-related attributes, where participants chose an AAC system for a child vignette.SettingThe survey was administered online in the UK.Participants155 UK-based AAC professionals were recruited between 20 October 2017 and 4 March 2018.OutcomesThe study outcomes were the preferences of AAC professionals’ as quantified using a mixed logit model, with model selection performed using a step-wise procedure and the Bayesian Information Criterion.ResultsSignificant differences were observed in preferences for AAC system attributes, and large interactions were seen between child attributes included in the child vignettes, for example, participants made more ambitious choices for children who were motivated to communicate using AAC, and predicted to progress in skills and abilities. These characteristics were perceived as relatively more important than language ability and previous AAC experience.ConclusionsAAC professionals make trade-offs between attributes of AAC systems, and these trade-offs change depending on the characteristics of the child for whom the system is being provided.

scholarly journals How do surgeons’ trade-off between patient outcomes and risk of complications in total knee arthroplasty? a discrete choice experiment in Australia

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e029406 ◽  
Author(s):  
Sandie Szawlowski ◽  
Peter F M Choong ◽  
Jinhu Li ◽  
Elizabeth Nelson ◽  
Mandana Nikpour ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Night Time ◽  
Trade Off ◽  
Orthopaedic Surgeons ◽  
Trade Offs ◽  
Total Knee ◽  
And Function

ObjectiveTo measure the trade-off between risk of complications versus patient improvement in pain and function in orthopaedic surgeons’ decisions about whether to undertake total knee arthroplasty (TKA).MethodsA discrete choice experiment asking surgeons to make choices between experimentally-designed scenarios describing different levels of operative risk and dimensions of pain and physical function. Variation in preferences and trade-offs according to surgeon-specific characteristics were also examined.ResultsThe experiment was completed by a representative sample of 333 orthopaedic surgeons (n=333): median age 52 years, 94% male, 91% fully qualified. Orthopaedic surgeons were willing to accept substantial increases in absolute risk associated with TKA surgery for greater improvements in a patient’s pain and function. The maximum risk surgeons were willing to accept was 40% for reoperation and 102% for the need to seek further treatment from a general practitioner or specialist in return for a change from postoperative severe night-time pain at baseline to no night-time pain at 12 months. With a few exceptions, surgeon-specific characteristics were not associated with how much risk a surgeon is willing to accept in a patient undergoing TKA.ConclusionThis is the first study to quantify risk-benefit trade-offs among orthopaedic surgeons performing TKA, using a discrete choice experiment. This study provides insight into the risk tolerance of surgeons.

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