Evidence map›Paper›PMID 36002895›Full record

ArticleBMC health services research2022

Methodology to derive preference for health screening programmes using discrete choice experiments: a scoping review.

David Brain, Amarzaya Jadambaa, Sanjeewa Kularatna

Abstract readScoping Review
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. 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

3 authors.

David BrainAustralian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Kelvin Grove, 4059, QLD, Australia.ORCID http://orcid.org/0000-0002-6612-348X
Amarzaya JadambaaAustralian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Kelvin Grove, 4059, QLD, Australia.ORCID http://orcid.org/0000-0003-0862-1154
Sanjeewa KularatnaAustralian Centre for Health Services Innovation, Centre for Healthcare Transformation, School of Public Health and Social Work, Faculty of Health, Queensland University of Technology, Kelvin Grove, 4059, QLD, Australia. Sanjeewa.Kularatna@qut.edu.au.ORCID http://orcid.org/0000-0001-5650-154X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhile involving users in healthcare decision-making has become increasingly common and important, there is a lack of knowledge about how to best design community-based health screening programs. Reviews of methods that incorporate discrete choice experiments (DCEs) are scarce, particularly for non-cancer illnesses like cardiovascular disease, diabetes and liver disease. We provide an overview of currently available applications and methods available by using DCEs in health screening programs, for chronic conditions.

methodsA scoping review was undertaken, where four electronic databases were searched for key terms to identify eligible DCE studies related to community health screening. We included studies that met a pre-determined criteria, including being published between 2011 and 2021, in English and reported findings on human participants. Data were systematically extracted, tabulated, and summarised in a narrative review.

resultsA total of 27 studies that used a DCE to elicit preferences for cancer (n = 26) and cardiovascular disease screening (n = 1) programmes were included in the final analysis. All studies were assessed for quality, against a list of 13 criteria, with the median score being 9/13 (range 5-12). Across the 27 studies, the majority (80%) had the same overall scores. Two-thirds of included studies reported a sample size calculation, approximately half (13/27) administered the survey completely online and over 75% used the general public as the participating population.

conclusionOur review has led to highlighting several areas of current practice that can be improved, particularly greater use of sample size calculations, increased use of qualitative methods, better explanation of the chosen experimental design including how choice sets are generated, and methods for analysis.

Indexed as

Cardiovascular DiseasesPatient PreferenceChoice BehaviorHumansResearch DesignSurveys and QuestionnairesChronic diseaseCommunity screening programDiscrete choice experimentPreferences

Identifiers

PMID36002895
PMCPMC9400308

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.