ArticleBMC health services research2023
A discrete choice experiment to elicit preferences for a liver screening programme in Queensland, Australia: a mixed methods study to select attributes and levels.
Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Discrete Choice Experiments and Conjoint Analyses in Health Screening Programs for Type 2 Diabetes and Liver Disease: A Scoping Review.Canadian liver journal · 2025Pooled it
- Implementation of a nurse-delivered, community-based liver screening and assessment program for people with metabolic dysfunction-associated steatotic liver disease (LOCATE-NAFLD trial).BMC health services research · 2025Trial
- Public preferences for primary healthcare services in Hong Kong: a discrete choice experiment.BMC primary care · 2026Article
- Patterns in Attribute Selection and Development Reporting in Patient Preference Studies Between 2007-2024: A Systematic Literature Review.Journal of health economics and outcomes research · 2026Article
- Consumer Preferences for a Healthcare Appointment Reminder in Australia: A Discrete Choice Experiment.The patient · 2024Article
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundIn Australia, the overall prevalence of liver disease is increasing. Maximising uptake of community screening programmes by understanding patient preferences is integral to developing consumer-centred care models for liver disease. Discrete choice experiments (DCEs) are widely used to elicit preferences for various healthcare services. Attribute development is a vital component of a well-designed DCE and should be described in sufficient detail for others to assess the validity of outcomes. Hence, this study aimed to create a list of potential attributes and levels which can be used in a DCE study to elicit preferences for chronic liver disease screening programmes.
methodsKey attributes were developed through a multi-stage, mixed methods design. Focus groups were held with consumers and health care providers on attributes of community screening programmes for liver disease. Stakeholders then prioritised attributes generated from the focus group in order of importance via an online prioritisation survey. The outcomes of the prioritisation exercise were then reviewed and refined by an expert panel to ensure clinically meaningful levels and relevance for a DCE survey.
resultsFifteen attributes were generated during the focus group sessions deemed necessary to design liver disease screening services. Outcomes of the prioritisation exercise and expert panel stages recognised five attributes, with three levels each, for inclusion in a DCE survey to elicit consumer preferences for community screening for liver disease. This study also highlights broader social issues such as the stigma around liver disease that require careful consideration by policy makers when designing or implementing a liver screening programme.
conclusionsThe attributes and levels identified will inform future DCE surveys to understand consumer preferences for community screening programmes for liver disease. In addition, the outcomes will help inform the implementation of the LOCATE-NAFLD programme in real-world practice, and could be relevant for other liver and non-liver related chronic disease screening programmes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.