Evidence map›Paper›PMID 37456269›Full record

ArticleJournal of clinical and translational science2023

Understanding men's beliefs and concerns about linking health data in the context of precision medicine.

Caitlin G Allen, Melanie Jefferson, Gayenell Magwood, Cathy Melvin, Oluwole Adeyemi Babatunde, Chanita Hughes Halbert

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2023. 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

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

6 authors.

Caitlin G AllenDepartment of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.ORCID https://orcid.org/0000-0002-6288-3529
Melanie JeffersonDepartment of Psychiatry and Behavioral Sciences, Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.
Gayenell MagwoodDepartment of Biobehavioral Health and Nursing Science, College of Nursing, University of South Carolina, Charleston, SC, USA.
Cathy MelvinDepartment of Public Health Sciences, College of Medicine, Medical University of South Carolina, Charleston, SC, USA.
Oluwole Adeyemi BabatundeDepartment of Psychiatry and Behavioral Sciences, Hollings Cancer Center, Medical University of South Carolina, Charleston, SC, USA.
Chanita Hughes HalbertDepartment of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background/Objective: Linking data is a critical feature of precision medicine initiatives that involves integrating information from multiple sources to improve researchers' and clinicians' ability to deliver care. We have limited understanding of how individuals perceive linking data as it relates to precision medicine. The aim of this study was to identify how sociodemographics, comorbidities, and beliefs about precision medicine influence two outcomes related to linking data: beliefs about linking data and concerns about linking data among men. Methods: We recruited 124 adult men from primary care practices at a large clinical research university to complete a cross-sectional survey that included questions about sociodemographic characteristics, comorbidities, beliefs, benefits, and limitations of precision medicine, and two outcomes of interest: beliefs about the value of linking data and concerns about linking data. Descriptive statistics, bivariate associations, and multivariable regression were conducted. Results: Participants had positive beliefs about linking data for precision medicine (M = 4.05/5) and average concern about linking data (M = 2.1/5). Final multivariable models revealed that higher levels of loneliness are associated with more positive beliefs about linking data (β = 0.41, Conclusion: Our results advance the literature about perceptions of linking data for use in clinical and research studies among men. Better understanding of factors associated with more positive perceptions of data linkages could help improve how researchers recruit and engage participants.

Indexed as

health beliefslinking datamen’s healthPrecision medicinetranslational science

Identifiers

PMID37456269
PMCPMC10346034

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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.