Evidence map›Paper›PMID 37128415›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022

Capturing Demographic, Health-Related, and Psychosocial Variables in a Standardized Manner: Towards Improving Cancer Screening Adherence.

Yannan Lin, Ruiwen Ding, Ashley E Prosper, Denise R Aberle, Alex A T Bui, William Hsu

Abstract read

In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Yannan LinDepartment of Bioengineering, University of California, Los Angeles, CA, USA.

Ruiwen DingDepartment of Bioengineering, University of California, Los Angeles, CA, USA.

Ashley E ProsperMedical & Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA, USA.

Denise R AberleDepartment of Bioengineering, University of California, Los Angeles, CA, USA.

Alex A T BuiDepartment of Bioengineering, University of California, Los Angeles, CA, USA.

William HsuDepartment of Bioengineering, University of California, Los Angeles, CA, USA.

Funding

Molecular and Imaging Biomarkers for Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary NodulesR01CA210360 · NCI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ABERLE, DENISE R., LENBURG, MARC ELLIOTT · 2016 to 2021

$3.1M

Individually-tailored clinical decision support for management of indeterminate pulmonary nodulesR01CA226079 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ABERLE, DENISE R., BUI, ALEX · 2019 to 2023

$2.3M

NCI NIH HHS R01 CA210360NCI NIH HHS R01 CA226079

6 · The paper itself

Abstract

Determining factors influencing patient participation in and adherence to cancer screening recommendations is key to successful cancer screening programs. However, the collection of variables necessary to anticipate patient behavior in cancer screening has not been systematically examined. Using lung cancer screening as a representative example, we conducted an exploratory analysis to characterize the current representations of 18 demographic, health-related, and psychosocial variables collected as part of a conceptual model to understand factors for lung cancer screening participation and adherence. Our analysis revealed a lack of standardization in controlled terminologies and common data elements for these variables. For example, only eight (44%) demographic and health-related variables were recorded consistently in the electronic health record. Multiple survey instruments could collect the remaining variables but were highly inconsistent in how variables were represented. This analysis suggests opportunities to establish standardized data formats for psychological, cognitive, social, and environmental variables to improve data collection.

Indexed as

Early Detection of CancerLung NeoplasmsData CollectionDemographyHumansPatient Participation

Identifiers

PMID37128415

PMCPMC10148364

What OpenQuestion holds

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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.