ArticleInternational journal for equity in health2022
Shifting the narrative: equity, evidence, effectiveness, and innovation in the era of Ending the HIV Epidemic.
Article in International journal for equity in health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
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Who cites it
1 citing paper in PubMed.
- Co-Designing Person- and Family-Centered Care for Older Adults Living With HIV: Protocol for a Community-Based Participatory Study.JMIR research protocols · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe use of evidence-based (EB) and evidence-informed (EI) criteria in determining the effectiveness of health interventions has been widely adopted by national and international agencies in their attempt to address health gaps, particularly around Ending the HIV Epidemic (EHE) initiatives. Utilization of these rigorous standards has proven critical in making progress towards achieving EHE goals, yet many communities remain unreached and underserved despite widespread adoption of EB/EI standards in public health research and practice. Although a crucial tool for innovative healthcare delivery, emphasis on the use of EB/EI parameters has created bias within the cycle of knowledge creation that favors well-resourced institutions given their capacity to meet the rigorous evaluation standards required of EB/EI science. This bias can systematically exclude institutions more aligned with community needs, such as community-based organizations and other grass-roots initiatives, which may have long-standing interventions that more effectively engage marginalized groups but do not have the capacity to meet EB/EI standards. MAIN BODY: This paper will explore the manifestation of systematic bias and research inequity in the process of identifying and assessing EB/EI HIV care interventions through the lens of a Health Resources and Services Administration funded initiative, coined the Center for Innovation and Engagement, which supports people living with HIV in the United States. An overview of the initiative is provided along with examples of how promising interventions with positive outcomes for members of marginalized communities are excluded in place of interventions that meet traditional standards of scientific rigor but are not novel or particularly innovative. Themes around academic imperialism and power hierarchies will be considered along with key barriers, lessons learned, and recommendations for promoting more equitable EB/EI research practice.
conclusionsIt is crucial for entities supporting public health interventions to prioritize equity and inclusion in all stages of funding, design, and implementation. This is particularly true for conditions, such as HIV, that disproportionally impact the most marginalized. This will require approaching EB/EI research with a critical lens towards power and a willingness to dismantle historical dynamics that perpetuate inequities as a way of encouraging truly innovative solutions to support those who need it most.
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Registered trials
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.