Evidence map›Paper›PMID 34671946›Full record

SynthesisThe patient2022

Attributes Used for Cancer Screening Discrete Choice Experiments: A Systematic Review.

Rebekah Hall, Antonieta Medina-Lara, Willie Hamilton, Anne E Spencer

Erratum issuedAbstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in The patient, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 4 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

20 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments.Medical decision making : an international journal of the Society for Medical Decision Making · 2024
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  13. Patient preferences for investigating cancer-related symptoms in Australian general practice: a discrete-choice experiment.The British journal of general practice : the journal of the Royal College of General Practitioners · 2024
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  17. Public Preferences for Determining Eligibility for Screening in Risk-Stratified Cancer Screening Programs: A Discrete Choice Experiment.Medical decision making : an international journal of the Society for Medical Decision Making · 2023
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Rebekah HallCollege of Medicine and Health, University of Exeter, South Cloisters, St Luke's Campus, Heavitree, Exeter, EX1 2LU, UK. rh591@exeter.ac.uk.ORCID 0000-0003-1804-993X
Antonieta Medina-LaraCollege of Medicine and Health, University of Exeter, South Cloisters, St Luke's Campus, Heavitree, Exeter, EX1 2LU, UK.ORCID 0000-0001-7325-8246
Willie HamiltonCollege of Medicine and Health, University of Exeter, South Cloisters, St Luke's Campus, Heavitree, Exeter, EX1 2LU, UK.ORCID 0000-0003-1611-1373
Anne E SpencerCollege of Medicine and Health, University of Exeter, South Cloisters, St Luke's Campus, Heavitree, Exeter, EX1 2LU, UK.ORCID 0000-0002-8163-3103

Funding

Cancer Research UK C8640/A23385
6 · The paper itself

Abstract

backgroundEvidence from discrete choice experiments can be used to enrich understanding of preferences, inform the (re)design of screening programmes and/or improve communication within public campaigns about the benefits and harms of screening. However, reviews of screening discrete choice experiments highlight significant discrepancies between stated choices and real choices, particularly regarding willingness to undergo cancer screening. The identification and selection of attributes and associated levels is a fundamental component of designing a discrete choice experiment. Misspecification or misinterpretation of attributes may lead to non-compensatory behaviours, attribute non-attendance and responses that lack external validity.

objectivesWe aimed to synthesise evidence on attribute development, alongside an in-depth review of included attributes and methodological challenges, to provide a resource for researchers undertaking future studies in cancer screening.

methodsA systematic review was conducted to identify discrete choice experiments estimating preferences towards cancer screening, dated between 1990 and December 2020. Data were synthesised narratively. In-depth analysis of attributes led to classification into four categories: test specific, service delivery, outcomes and monetary. Attribute significance and relative importance were also analysed. The International Society for Pharmacoeconomics and Outcomes Research conjoint analysis checklist was used to assess the quality of reporting.

resultsForty-nine studies were included at full text. They covered a range of cancer sites: over half (26/49) examined colorectal screening. Most studies elicited general public preferences (34/49). In total, 280 attributes were included, 90% (252/280) of which were significant. Overall, test sensitivity and mortality reduction were most frequently found to be the most important to respondents.

conclusionsImprovements in reporting the identification, selection and construction of attributes used within cancer screening discrete choice experiments are needed. This review also highlights the importance of considering the complexity of choice tasks when considering risk information or compound attributes. Patient and public involvement and stakeholder engagement are recommended to optimise understanding of unavoidably complex choice tasks throughout the design process. To ensure quality and maximise comparability across studies, further research is needed to develop a risk-of-bias measure for discrete choice experiments.

Indexed as

Early Detection of CancerNeoplasmsChoice BehaviorData CollectionHumansMass ScreeningPatient Preference

Identifiers

What Socratic 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 Socratic graph.