Evidence map›Paper›PMID 24566923›Full record

SynthesisThe patient2014

Risk as an attribute in discrete choice experiments: a systematic review of the literature.

Mark Harrison, Dan Rigby, Caroline Vass, Terry Flynn, Jordan Louviere, Katherine Payne

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in The patient, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 7 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity.The European journal of health economics : HEPAC : health economics in prevention and care · 2018
    Pooled it
  5. Pooled it
  6. Pooled it
  7. The Role of Qualitative Research Methods in Discrete Choice Experiments.Medical decision making : an international journal of the Society for Medical Decision Making · 2017
    Pooled it
  8. Using Separate Single-Outcome Risk Presentations Instead of Integrated Multioutcome Formats Improves Comprehension in Discrete Choice Experiments.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
    Trial
  9. Trial
  10. Trial
  11. Trial
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Preferences for using the London Underground during the COVID-19 pandemic.Transportation research. Part A, Policy and practice · 2022
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mark HarrisonCentre for Health Economics, Institute of Population Health, 4th floor, Jean McFarlane Building, University Place, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK, mark.harrison@manchester.ac.uk.
Dan Rigby
Caroline Vass
Terry Flynn
Jordan Louviere
Katherine Payne

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiscrete choice experiments (DCEs) are used to elicit preferences of current and future patients and healthcare professionals about how they value different aspects of healthcare. Risk is an integral part of most healthcare decisions. Despite the use of risk attributes in DCEs consistently being highlighted as an area for further research, current methods of incorporating risk attributes in DCEs have not been reviewed explicitly.

objectivesThis study aimed to systematically identify published healthcare DCEs that incorporated a risk attribute, summarise and appraise methods used to present and analyse risk attributes, and recommend best practice regarding including, analysing and transparently reporting the methodology supporting risk attributes in future DCEs. DATA SOURCES: The Web of Science, MEDLINE, EMBASE, PsycINFO and Econlit databases were searched on 18 April 2013 for DCEs that included a risk attribute published since 1995, and on 23 April 2013 to identify studies assessing risk communication in the general (non-DCE) health literature. STUDY ELIGIBILITY CRITERIA: Healthcare-related DCEs with a risk attribute mentioned or suggested in the title/abstract were obtained and retained in the final review if a risk attribute meeting our definition was included. STUDY APPRAISAL AND SYNTHESIS

methodsExtracted data were tabulated and critically appraised to summarise the quality of reporting, and the format, presentation and interpretation of the risk attribute were summarised.

resultsThis review identified 117 healthcare DCEs that incorporated at least one risk attribute. Whilst there was some evidence of good practice incorporated into the presentation of risk attributes, little evidence was found that developing methods and recommendations from other disciplines about effective methods and validation of risk communication were systematically applied to DCEs. In general, the reviewed DCE studies did not thoroughly report the methodology supporting the explanation of risk in training materials, the impact of framing risk, or exploring the validity of risk communication. LIMITATIONS: The primary limitation of this review was that the methods underlying presentation, format and analysis of risk attributes could only be appraised to the extent that they were reported.

conclusionsImprovements in reporting and transparency of risk presentation from conception to the analysis of DCEs are needed. To define best practice, further research is needed to test how the process of communicating risk affects the way in which people value risk attributes in DCEs.

Indexed as

Decision MakingResearch DesignRiskPatient Preference

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.