Evidence map›Paper›PMID 41371772›Full record

ArticleRespirology (Carlton, Vic.)2026

Maximising Participation in the Australian National Lung Cancer Screening Program: A Discrete Choice Experiment of Eligible, High-Risk Individuals.

Peiwen Jiang, Caitlin Paton, Richard Norman, Marianne Weber, Henry M Marshall, Fraser Brims, Kuan Pim Lim, Sarah York, Georgia Bartlett, Richard De Abreu Lourenco and 1 more

Abstract read
In one paragraph

Article in Respirology (Carlton, Vic.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Peiwen JiangCentre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia.ORCID 0009-0000-4173-3487
Caitlin PatonEvaluation and Implementation Science Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
Richard NormanSchool of Population Health, Curtin University, Perth, Australia.
Marianne WeberSydney School of Public Health, The University of Sydney, Sydney, Australia.
Henry M MarshallUniversity of Queensland Thoracic Research Centre and Department of Thoracic Medicine, The Prince Charles Hospital, Chermside, Brisbane, Australia.
Fraser BrimsCurtin Medical School, Curtin University, Perth, Australia.ORCID 0000-0002-6725-7535
Kuan Pim LimDepartment of Respiratory Medicine, St John of God Subiaco Hospital, Perth, Australia.
Sarah YorkAlbury Private Hospital Clinical Trials Unit, Ramsay Health Care Limited, Albury, Australia.
Georgia BartlettEvaluation and Implementation Science Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.
Richard De Abreu LourencoCentre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia.
Nicole M RankinEvaluation and Implementation Science Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia.

Funding

National Health and Medical Research Council APP1185390National Health and Medical Research Council: Investigator Grant APP1178331Queensland Government, Australia
6 · The paper itself

Abstract

BACKGROUND AND

objectiveRelatively little is known about how to maximise participation in lung cancer screening for Australians at high risk of developing the disease. A discrete choice experiment was conducted to elicit and quantify preferences of Australians eligible for lung cancer screening (LCS) to maximise participation in the National Lung Cancer Screening Program (NLCSP) and estimate likely participation.

methodsRespondents completed an online survey of six LCS factors or 'attributes' (invitation to screen, eligibility assessment, appointment booking, model of care, health care worker support and out-of-pocket costs). Results were analysed using mixed logit (MIXL), multinomial logit (MNL) and latent class analysis to explore heterogeneity in respondents' choices. Willingness to pay (WTP) for screening attributes were estimated based on the ratio of the coefficient on attributes to cost.

resultsRespondents (n = 757) were aged 50-70 years with smoking histories (> 30 pack-year history and either currently smoke or quit ≤ 10 years). The MIXL showed that participants preferred support from a program navigator, with the highest estimated WTP of $24, plus personalised invitations and lower screening costs. The results identified participation rates that could be achieved through optimal LCS program design, across the most optimistic screening program scenario (87.4%), the scenario proposed in the NLCSP (51.5%) and the least preferred scenario (35.0%).

conclusionThe results are highly relevant for the NLCSP, which commenced on 1 July 2025. Potential participants place significant value on program navigators, a role not funded within the program, which could significantly improve uptake.

Indexed as

Choice BehaviorEarly Detection of CancerLung NeoplasmsMass ScreeningAgedAustraliaFemaleHumansMaleMiddle AgedSurveys and Questionnairesdiscrete choice experimentinvitation strategieslung cancer screeninglung neoplasmspatient navigationpatient preferences

Identifiers

PMID41371772
PMCPMC13050626

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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.