Evidence map›Paper›PMID 38819825›Full record

ArticleJAMA network open2024

Patient Lung Cancer Screening Decisions and Environmental and Psychosocial Factors.

Jennifer Richmond, Jessica R Fernandez, Kemberlee Bonnet, Ashley Sellers, David G Schlundt, Allana T Forde, Consuelo H Wilkins, Melinda C Aldrich

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Diagnostic performance of [European journal of nuclear medicine and molecular imaging · 2026
    Article
  5. Impact of social determinants on the development, diagnosis, and treatment of cancer: recommended public health interventions.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Screening for Lung Cancer, Overdiagnosis, and Healthcare Utilization: A Nationwide Population-Based Study.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2025
    Article
  12. Review
  13. Article
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Jennifer RichmondDivision of Public Health Sciences, Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Jessica R FernandezDivision of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
Kemberlee BonnetDepartment of Psychology, Vanderbilt University, Nashville, Tennessee.
Ashley SellersDepartment of Psychology, Vanderbilt University, Nashville, Tennessee.
David G SchlundtDepartment of Psychology, Vanderbilt University, Nashville, Tennessee.
Allana T FordeDivision of Intramural Research, National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, Maryland.
Consuelo H WilkinsDivision of Geriatric Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Melinda C AldrichDivision of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding

The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Learning Health System training program: PROgRESS--Patient/ pRactice Outcomes and Research in Effectiveness and Systems ScienceT32HS026122 · AHRQ · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GRIJALVA, CARLOS G, ROUMIE, CHRISTIANNE L. · 2018 to 2024
$3.5M
Addressing racial disparities in lung cancer screeningR01CA251758 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ALDRICH, MELINDA, BLUME, JEFFREY D. · 2021 to 2025
$2.4M
Stressors and Health Disparities Research ProgramZIAMD000019 · NIMHD · NATIONAL INSTITUTE ON MINORITY HEALTH AND HEALTH DISPARITIES · PI FORDE, ALLANA · 2020 to 2025
$964k
Developing a Trustworthy Multilevel Intervention to Improve Lung Cancer ScreeningR00CA277366 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI RICHMOND, JENNIFER ANN · 2023 to 2025
$701k
Developing a Trustworthy Multilevel Intervention to Improve Equity in Lung Cancer ScreeningK99CA277366 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RICHMOND, JENNIFER ANN · 2023 to 2023
$109k
AHRQ HHS T32 HS026122NCATS NIH HHS UL1 TR000445NCI NIH HHS K99 CA277366NCI NIH HHS L60 CA264691NCI NIH HHS R00 CA277366
6 · The paper itself

Abstract

Importance: Screening for lung cancer using low-dose computed tomography is associated with reduced lung cancer-specific mortality, but uptake is low in the US; understanding how patients make decisions to engage with lung cancer screening is critical for increasing uptake. Prior research has focused on individual-level psychosocial factors, but environmental factors (eg, historical contexts that include experiencing racism) and modifying factors-those that can be changed to make it easier or harder to undergo screening-also likely affect screening decisions. Objective: To investigate environmental, psychosocial, and modifying factors influencing lung cancer screening decision-making and develop a conceptual framework depicting relationships between these factors. Design, Setting, and Participants: This multimethod qualitative study was conducted from December 2021 to June 2022 using virtual semistructured interviews and 4 focus groups (3-4 participants per group). All participants met US Preventive Services Task Force eligibility criteria for lung cancer screening (ie, age 50-80 years, at least a 20 pack-year smoking history, and either currently smoke or quit within the past 15 years). Screening-eligible US participants were recruited using an online panel. Main Outcomes and Measures: Key factors influencing screening decisions (eg, knowledge, beliefs, barriers, and facilitators) were the main outcome. A theory-informed, iterative inductive-deductive approach was applied to analyze data and develop a conceptual framework summarizing results. Results: Among 34 total participants (interviews, 20 [59%]; focus groups, 14 [41%]), mean (SD) age was 59.1 (4.8) years and 20 (59%) identified as female. Half had a household income below $20 000 (17 [50%]). Participants emphasized historical and present-day racism as critical factors contributing to mistrust of health care practitioners and avoidance of medical procedures like screening. Participants reported that other factors, such as public transportation availability, also influenced decisions. Additionally, participants described psychosocial processes involved in decisions, such as perceived screening benefits, lung cancer risk appraisal, and fear of a cancer diagnosis or harmful encounters with practitioners. In addition, participants identified modifying factors (eg, insurance coverage) that could make receiving screening easier or harder. Conclusions and Relevance: In this qualitative study of patient lung cancer screening decisions, environmental, psychosocial, and modifying factors influenced screening decisions. The findings suggest that systems-level interventions, such as those that help practitioners understand and discuss patients' prior negative health care experiences, are needed to promote effective screening decision-making.

Indexed as

Decision MakingEarly Detection of CancerLung NeoplasmsQualitative ResearchAgedAged, 80 and overFemaleFocus GroupsHumansMaleMiddle AgedTomography, X-Ray ComputedUnited States

Identifiers

PMID38819825
PMCPMC11143466

What OpenQuestion holds

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LicenceCC BY
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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.