Evidence map›Paper›PMID 29317809›Full record

ArticleClinical interventions in aging2018

Best strategies to recruit and enroll elderly Blacks into clinical and biomedical research.

Lennox A Graham, Julius Ngwa, Oyonumo Ntekim, Oludolapo Ogunlana, Saba Wolday, Steven Johnson, Megan Johnson, Chimene Castor, Thomas V Fungwe, Thomas O Obisesan

Abstract read
In one paragraph

Article in Clinical interventions in aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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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

10 authors.

Lennox A GrahamDepartment of Health Management, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA.
Julius NgwaDivision of Cardiovascular Medicine, College of Medicine, Howard University, Washington, DC, USA.
Oyonumo NtekimDepartment of Nutritional Sciences, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA.
Oludolapo OgunlanaDepartment of Internal Medicine, Howard University Teaching Hospital, Washington, DC, USA.
Saba WoldayDepartment of Internal Medicine, Howard University Teaching Hospital, Washington, DC, USA.
Steven JohnsonDepartment of Nutritional Sciences, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA.
Megan JohnsonDepartment of Internal Medicine, Howard University Teaching Hospital, Washington, DC, USA.
Chimene CastorDepartment of Nutritional Sciences, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA.
Thomas V FungweDepartment of Nutritional Sciences, College of Nursing and Allied Health Sciences, Howard University, Washington, DC, USA.
Thomas O ObisesanDepartment of Internal Medicine, Howard University Teaching Hospital, Washington, DC, USA.

Funding

Maternal Morbidity and Mortality: Risk Factors, Early Detection and Personalized InterventionUL1TR001409 · NCATS · GEORGETOWN UNIVERSITY · PI GONDRE-LEWIS, MARJORIE C, MELLMAN, THOMAS A · 2015 to 2024
$37.8M
Georgetown-Howard Universities Center for Clinical and Translational Science (GHUUL1TR000101 · NCATS · GEORGETOWN UNIVERSITY · PI MELLMAN, THOMAS A, VERBALIS, JOSEPH G · 2012 to 2015
$19.3M
Genes, Exercise, Neurocognitive and Neurodegeneration: Community-Based ApproachR01AG045058 · NIA · HOWARD UNIVERSITY · PI OBISESAN, THOMAS O · 2014 to 2018
$2.9M
Effects of Standardized Aerobic Exercise-Training on Neurocognitive and NeurodegeR01AG031517 · NIA · HOWARD UNIVERSITY · PI OBISESAN, THOMAS O · 2009 to 2010
$2.0M
NCATS NIH HHS UL1 TR000101NCATS NIH HHS UL1 TR001409NIA NIH HHS R01 AG031517NIA NIH HHS R01 AG045058
6 · The paper itself

Abstract

backgroundHistorically, Blacks have been disproportionately underrepresented in clinical trials. Outcomes associated with low Blacks' participation in research include poor understanding of the predictors and treatment of the disease, increasing health disparities, poor health equity, and suboptimal wellness of the nation as a whole. To address this gap in research participation, we analyzed our recruitment data to identify the most effective strategies for enrolling older Blacks in clinical trials.

methodsData used in these analyses were obtained from 3,266 potential volunteers, ages 50 or older, who completed a Mini-Mental State Exam as part of recruitment and screening for various clinical studies on Alzheimer's disease. In order to determine the most effective strategies for engaging Blacks in clinical research, we used tests of proportion to assess significant differences in recruitment sources, counts, and percentages for optimal recruitment strategies by gender. Finally, we employed regression analyses to confirm our findings.

resultsOf the total 3,266 screened, 2,830 Black volunteers were identified for further analysis. Overall, more women than men (73.8% vs 26.2%) participated in our recruitment activities. However, a significantly higher proportion of men than women were engaged through family (3.86% vs 1.30%,

conclusionOur findings indicate Black men and women in our sample were predominantly recruited from health fairs and through advertisements tailored to their health needs and interests. Conversely, we mostly engaged Black men through family referrals and persons known to them, indicating a need for trust in their decision to engage study personnel and/or participate in clinical trials.

Indexed as

Biomedical ResearchBlack or African AmericanPatient SelectionAgedFemaleHumansMaleMental Status and Dementia TestsMiddle AgedUnited StatesBlacksclinical trialscommunity outreachrecruitment strategiesscreening

Identifiers

PMID29317809
PMCPMC5743176

What OpenQuestion holds

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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.