Evidence map›Paper›PMID 41161845›Full record

ReviewBMJ open2025

Five Nested Dolls Framework: enhancing transparency and collaboration in community-engaged research through researcher's reflexivity and disclosure.

Saya Kakim, Jasmine K Cooper, C Daniel Mullins

Abstract readReview
In one paragraph

Review in BMJ open, 2025. 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

3 authors.

Saya KakimThe PATIENTS Program, University of Maryland School of Pharmacy, Baltimore, MD, USA skakim@rx.umaryland.edu.ORCID http://orcid.org/0009-0006-1607-9296
Jasmine K CooperThe PATIENTS Program, University of Maryland School of Pharmacy, Baltimore, MD, USA.
C Daniel MullinsThe PATIENTS Program, University of Maryland School of Pharmacy, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDespite the widespread use of community-engaged research (CEnR) in public health, there is a lack of practical guidance for ensuring research transparency while fostering collaboration between researchers and patient communities.

objectiveIn this article, we propose the Five Nested Dolls Community-Engaged Research Framework (Five Dolls CEnR) as a tool to assist researchers in enhancing the transparency of CEnR and fostering collaboration between researchers and patient communities throughout all phases of CEnR. FRAMEWORK: Each of the five dolls represents a meaningful aspect of CEnR, such as patient engagement in research, conceptual framework, research design, findings and researchers' positionality. In alignment with feminist standpoint theory, Five Dolls CEnR is based on a nesting design principle to demonstrate the influence of researchers' experiences, perspectives, values, beliefs and assumptions on a research process.To ensure transparency of the research process and foster collaboration in CEnR, the authors have described self-reflexivity and self-disclosure, two multidisciplinary concepts, as strategies. This framework consists of a series of steps and questions to promote self-reflexivity and self-disclosure of researchers at each doll level.

conclusionAs a multidisciplinary framework, Five Dolls CEnR can be used across disciplines and throughout the planning, implementation and dissemination phases of a study.

Indexed as

Community-Based Participatory ResearchCooperative BehaviorDisclosureResearch PersonnelHumansPatient ParticipationResearch DesignCommunity-Based Participatory ResearchCommunity ParticipationPatient Participation

Identifiers

PMID41161845
PMCPMC12574416

What OpenQuestion holds

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LicenceCC BY-NC
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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.