Evidence map›Paper›PMID 34407849›Full record

ArticleHealth research policy and systems2021

Fundamental challenges in assessing the impact of research infrastructure.

Sana Zakaria, Jonathan Grant, Jane Luff

Abstract readLetter
In one paragraph

Article in Health research policy and systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Using data to improve the health of coastal communities: The Coda Network.International journal of population data science · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  9. Article
  10. Article
  11. Status of Research and Development Within Dental Institutes of Pakistan.Inquiry : a journal of medical care organization, provision and financing
    Article
  12. Review
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.

Sana ZakariaCentral Commissioning Facility, National Institute of Health Research, 15 Church Street, TW1 3NL, Twickenham, United Kingdom. sana.zakaria@nihr.ac.uk.
Jonathan GrantPolicy Institute, King's College London, SE1 8WA, London, United Kingdom.
Jane LuffCentral Commissioning Facility, National Institute of Health Research, 15 Church Street, TW1 3NL, Twickenham, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical research infrastructure is one of the unsung heroes of the scientific response to the current COVID-19 pandemic. The extensive, long-term funding into research support structures, skilled people, and technology allowed the United Kingdom research response to move off the starting blocks at pace by utilizing pre-existing platforms. The increasing focus from funders on evaluating the outcomes and impact of research infrastructure investment requires both a reframing and progression of the current models in order to address the contribution of the underlying support infrastructure. The majority of current evaluation/outcome models focus on a "pipeline" approach using a methodology which follows the traditional research funding route with the addition of quantitative metrics. These models fail to embrace the complexity caused by the interplay of previous investment, the coalescing of project outputs from different funders, the underlying infrastructure investment, and the parallel development across different parts of the system. Research infrastructure is the underpinning foundation of a project-driven research system and requires long-term, sustained funding and capital investment to maintain scientific and technological expertise. Therefore, the short-term focus on quantitative metrics that are easy to collect and interpret and that can be assessed in a roughly 5-year funding cycle needs to be addressed. The significant level of investment in research infrastructure necessitates investment to develop bespoke methodologies that develop fit-for-purpose, longer-term/continual approach(es) to evaluation. Real-world research should reflect real-world evaluation and allow for the accrual of a narrative of value indicators that build a picture of the contribution of infrastructure to research outcomes. The linear approach is not fit for purpose, the research endeavour is a complex, twisted road, and the evaluation approach needs to embrace this complexity through the development of realist approaches and the rapidly evolving data ecosystem. This paper sets out methodological challenges and considers the need to develop bespoke methodological approaches to allow a richer assessment of impact, contribution, attribution, and evaluation of research infrastructure. This paper is the beginning of a conversation that invites the community to "take up the mantle" and tackle the complexity of real-world research translation and evaluation.

Indexed as

COVID-19EcosystemHumansPandemicsSARS-CoV-2United KingdomCOVID-19EvaluationImpact assessmentImpact frameworksNIHR BRCPipelinePlatformRealist evaluationResearch infrastructureTime lags

Identifiers

PMID34407849
PMCPMC8371591

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.