ArticleBMJ open2023
Potential social marketing applications for knowledge translation in healthcare: a scoping review protocol.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Gaining market share for health: A social marketing framework for implementation science.Health marketing quarterly · 2026Article
- Applications of social marketing for implementation science: a scoping review.Implementation science : IS · 2025Article
- The challenges of epidemiologic translation: communicating with physicians, policymakers, and the public.Frontiers in public health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionKnowledge translation has emerged as a practice and a science to bridge the gap between evidence and practice in healthcare. While the field has appropriately borrowed from other related fields to advance its science, there remain fields less mined. One such field with potential relevance to knowledge translation, but limited application to date, is social marketing. This review aims to determine elements of social marketing interventions that could be applied to knowledge translation science. Our objectives are to: (1) summarise the types of studies that have tested social marketing interventions in controlled intervention study designs; (2) describe the social marketing interventions and their effects; and (3) propose strategies for the integration of social marketing interventions into knowledge translation science. METHODS AND ANALYSIS: This scoping review will be conducted using the Joanna Briggs Institute Methodological Guidance. For the first and second objectives, all English-language studies published from 1971 onwards will be included if they (1) used a randomised or non-randomised controlled intervention design, and (2) tested a social marketing intervention as defined by five essential social marketing criteria. The research team will address the third objective through discussion and consensus. All screening and extraction will be performed independently by two reviewers. Variables extracted will include intervention details using essential and desirable social marketing criteria and the context, mechanism and outcomes of the interventions. ETHICS AND DISSEMINATION: This project is a secondary analysis of published papers and does not require ethics approval. We will disseminate our review outputs in knowledge translation journals and present at relevant conferences across the spectrum of the field. We will produce a short and long version of a plain language summary that will be tailored to various groups including implementation scientists and quality improvement researchers. REGISTRATION DETAILS: Open Science Framework Registration link: osf.io/6q834.
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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.