Evidence map›Paper›PMID 42729485›Full record

ArticleFrontiers in public health2026

Implementation and knowledge translation of health promotion programs at scale: "a perspective article".

Hatem H Alsaqqa

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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

1 author.

Hatem H AlsaqqaFaculty of Public Health and Deanship of Scientific Research, Al-Quds University, Jerusalem, Palestine.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Health promotion decision-makers must decide which evidence-based health programs will advance the health of a target population regarding a specific health concern. A key component of evidence-based implementation is the complexity of health programs, which means that numerous factors affect their outcomes. However, the level to which the results of a successful health program assessed in a primary context can be attained in a target context is known as transferability. Even when there is evidence of their value or efficacy, the strategies for large-scale public health program implementation received much less attention. Thus, understanding how successful interventions are expanded from research settings into more general policy and practice is made easier with the help of theoretical frameworks. Therefore, the drivers and challenges that can affect the translation and adoption of research evidence in health policy and practice are highlighted in this perspective paper. Effective legislation and practice depend on pertinent and useful evidence, which decision-makers integrate into plans and programs to increase health system coverage and enhance health outcomes. Although numerous health promotion interventions have demonstrated effectiveness, the translation of research evidence into large-scale implementation remains fragmented. This perspective proposes ontology-based knowledge as an innovative approach to strengthen evidence synthesis, knowledge translation, reusable implementation knowledge. Ontologies offer unifying frameworks that can promote more efficient knowledge accumulation by supporting the synthesis of researchers' empirical work in a knowledge base, ultimately facilitating the translation of this evidence into actionable health policies and practices.

Indexed as

Health PromotionTranslational Research, BiomedicalHealth PolicyHumanshealth promotionimplementationknowledge translationontologyprogramscale

Identifiers

PMID42729485
PMCPMC13562038

What OpenQuestion holds

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Registered trials

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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.