Evidence map›Paper›PMID 40011059›Full record

ArticleBMJ open quality2025

Concept analysis of health research translation nomenclature.

Lucylynn Lizarondo, Zoe Jordan, Ecushla Linedale, Craig Lockwood

Abstract read
In one paragraph

Article in BMJ open quality, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

4 authors.

Lucylynn LizarondoJBI, School of Public Health, University of Adelaide, North Adelaide, South Australia, Australia lucylynn.lizarondo@adelaide.edu.au.ORCID http://orcid.org/0000-0003-4902-7610
Zoe JordanJBI, School of Public Health, University of Adelaide, North Adelaide, South Australia, Australia.
Ecushla LinedaleSAHMRI, Adelaide, South Australia, Australia.
Craig LockwoodJBI, School of Public Health, University of Adelaide, North Adelaide, South Australia, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTranslating health research into clinical practice is a complex process aimed at enhancing healthcare quality and patient outcomes. The terminology surrounding this process is varied and often used interchangeably, leading to minimal consensus on the activities encompassed by each term.

objectivesThis study aims to examine existing taxonomies and websites for operational definitions related to health research translation, culminating in a comprehensive synopsis of terms specific to this field.

designIn 2019, a literature search was conducted using databases such as PubMed and CINAHL, along with relevant government and non-governmental organisation (NGO) websites, including grey literature. The search focused on English-language publications defining health research translation from 2000 onward and was updated in 2023. One author conducted the search, employing a mix of free-text and database-specific terms. Two authors independently evaluated the results for inclusion. Relevant data were extracted to aid in sorting and prioritising terminology based on frequency. A concept analysis approach, developed by Foley and Davis and informed by Rodgers' seven phases, was used to map the nomenclature.

resultsA total of 51 papers were analysed, revealing that the most frequently used terms for health research translation were knowledge translation (KT), implementation and translational research. Both evidence-based healthcare and KT describe the process of integrating evidence into practice, positioning them as analogous. Two major domains were identified: practice and science, with practice-related language further categorised into people-focused, process-focused and outcome-focused.

conclusionsThis paper presents a conceptual nomenclature map that serves as a foundation for developing a consensus-driven ontology for health research translation. The framework highlights how language can be categorised into common domains, fostering meaningful communication across diverse groups and entities.

Indexed as

Concept FormationTerminology as TopicTranslational Research, BiomedicalHumansEvidence-Based PracticeHealthcare quality improvementHealth services research

Identifiers

PMID40011059
PMCPMC11865793

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.