Evidence map›Paper›PMID 35707717›Full record

ArticleJournal of visual political communication2020

Decolonial visual resistance as a public health strategy in post-María Puerto Rico.

Nelson Varas-Díaz, Mark Padilla, Sheilla Rodríguez Madera, Kevin Grove, Violeta Contreras Ramírez, Sergio Rivera Rodríguez, Ricardo L Vargas-Molina, Melissa Marzán

Abstract read
In one paragraph

Article in Journal of visual political communication, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

8 authors.

Nelson Varas-DíazFlorida International University.ORCID 0000-0003-4695-1146
Mark PadillaFlorida International University.ORCID 0000-0002-2532-6280
Sheilla Rodríguez MaderaFlorida International University.ORCID 0000-0003-1967-1341
Kevin GroveFlorida International University.ORCID 0000-0001-9114-5050
Violeta Contreras RamírezUniversity of Puerto Rico.ORCID 0000-0002-5899-324X
Sergio Rivera RodríguezCity University of New York.ORCID 0000-0002-4903-7205
Ricardo L Vargas-MolinaUniversity of Puerto Rico.ORCID 0000-0003-2854-2365
Melissa MarzánPonce Health Sciences University.ORCID 0000-0003-4932-0702

Funding

A Multi-Level Health Systems Study of Collapse and Resilience in Puerto Rico s Response to Hurricane MariaR21AG063453 · NIA · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI PADILLA, MARK B, RODRIGUEZ MADERA, SHEILLA LEE · 2018 to 2019
$424k
NIA NIH HHS R21 AG063453
6 · The paper itself

Abstract

In this article, we explore the use of the image as a strategy to understand how natural disasters and coloniality impact the health of marginalized communities. We focus on the aftermath of Hurricane María in Puerto Rico and aim to describe how local people used the image as a strategy to challenge the invisibility fostered by coloniality and advocate for a more humane, equitable and effective public health response. We implemented a mixed methods research design including: (1) ethnographic observations, (2) qualitative in-depth interviews with 67 representatives of the health care system, (3) photographs they had taken as part of their experiences during and after the hurricane and (4) images from local newspapers and social media. In light of the findings we argue that Puerto Ricans engaged in decolonial visual resistance to manage the aftermath of the hurricane. Thus, while surviving the natural disaster, they challenged the traditional use of the image in public health endeavours.

Indexed as

colonialitydecolonialityHurricane Maríanatural disastersPuerto Ricovisual resistance

Identifiers

PMID35707717
PMCPMC9194790

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.