Evidence map›Paper›PMID 31032065›Full record

ArticleInternational journal of human rights in healthcare2018

Reducing Cancer Health Disparities among U.S. Latinos: A Freireian Approach.

Yonaira M Rivera

Abstract read
In one paragraph

Article in International journal of human rights in healthcare, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 88% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Yonaira M RiveraDepartment of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA, 787-529-9015, yrivera2@jhu.edu.
Johns Hopkins University · US

Funding

INSTITUTIONAL RESEARCH CANCER EPIDEMIOLOGY FELLOWSHIPT32CA009314 · NCI · JOHNS HOPKINS UNIVERSITY · PI Corinne E. Joshu, Meghan Bridgid Moran · 1985 to 2026
$11.2M
NCI NIH HHS T32 CA009314
6 · The paper itself

Abstract

PURPOSE –: This paper applies Paulo Freire's writings from DESIGN/METHODOLOGY/APPROACH –: Freire's writings on oppression, critical consciousness, FINDINGS –: Freireian teachings can provide insight on ways to engage Latino communities in culturally sensitive conversations that respect deeply rooted beliefs, and address the political and socioeconomic inequities many continue to face. Programs must revisit Freire's political and transformative roots to ensure efforts to reduce CHDs also promote health equity and community empowerment. PRACTICAL IMPLICATIONS –: Public health initiatives should incorporate Freireian principles of dialogical education and critical consciousness in the development of cancer prevention and screening programs tailored to Latinos in the U.S. to ensure program longevity and success. SOCIETAL IMPLICATIONS –: Approaching conversations and interactions dialogically can foster critical engagement and empower collective action among Latino communities in efforts to improve their environments and reduce health disparities. ORIGINALITY/VALUE –: This is a multi-layered analysis of different social and structural factors influencing CHDs among Latinos in the U.S., and is coupled with a historical overview of colonialism and oppression in Latin America. It culminates in suggestions on ways to improve future public health efforts that embrace Freireian approaches and promote health equity. CLASSIFICATION –: Conceptual paper.

Indexed as

Cancer health disparitiesDialogical educationHealth equityLatinosPaulo FreirePraxisPromotoresPublic health

Identifiers

PMID31032065
PMCPMC6485949
OpenAlexW2811132515

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.