Evidence map›Paper›PMID 33233949›Full record

ArticleAccountability in research2021

Using the concept of "deserved trust" to strengthen the value and integrity of biomedical research.

Mark Yarborough

Abstract read
In one paragraph

Article in Accountability in research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. "Do they REALLY trust us"?: Lessons from a volunteer research registry.Journal of clinical and translational science · 2024
    Article
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.

Mark YarboroughBioethics Program, University of California Davis Health, Sacramento, CA, USA.ORCID 0000-0001-8188-4968

Funding

UC Davis Clinical and Translational Science CenterUL1TR001860 · NCATS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI KENYON, NICHOLAS J., LYLES, COURTNEY REES · 2016 to 2025
$47.3M
CTSA Administrative Supplement for Informatics Core: A novel AI/ML system to predict respiratory failure and ARDS in Covid-19 patientsUL1TR002556 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI KELLER, MARLA J, KIM, MIMI Y · 2018 to 2022
$26.7M
Clinical and Translational Science Award (UL1)UL1TR000086 · NCATS · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI SHAMOON, HARRY · 2012 to 2013
$5.5M
NCATS NIH HHS UL1 TR000086NCATS NIH HHS UL1 TR001860NCATS NIH HHS UL1 TR002556
6 · The paper itself

Abstract

It is commonplace for science leaders and others to claim that the future of biomedical research rests in large part upon the public's trust. If true, it behooves the biomedical research community to understand how it avoids taking chances with that trust. This commentary, which builds upon comments of noted trust scholar Russell Hardin about how best to enjoy trust, assumes that the key to being trusted is deserving to be trusted. Thus, it proposes using "deserved trust" to identify ways that the public's trust in biomedical research could be better supported. Employing deserved trust to support the public's trust leads us to consider what it is that the biomedical research community should be trusted to do, examine the evidence about the effectiveness of current safeguards meant to assure that those things routinely get done, and identify new ways to equip individual researchers, research teams, and research institutions to assure that the public's trust in their research is deserved rather than misplaced.

Indexed as

Biomedical ResearchTrustHumansPublic trustresearch integrityresponsible conduct of researchtranslational research

Identifiers

PMID33233949
PMCPMC8233402

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.