Evidence map›Paper›PMID 41851803›Full record

ArticleImplementation science communications2026

Rethinking barriers and facilitators in implementation science: conceptual, methodological, and practical challenges, and ways forward.

Per Nilsen

Abstract read
In one paragraph

Article in Implementation science communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

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

Per NilsenDepartment of Health, Medicine and Health Sciences, Linköping University, Linköping, Sweden. per.nilsen@liu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Implementation science has long relied on the concepts of barriers and facilitators (B&F) to explain why evidence-based practices succeed or fail. Determinant frameworks such as the Consolidated Framework for Implementation Research and Theoretical Domains Framework have standardized this terminology, offering a common vocabulary to describe influences on implementation processes. However, the increasing maturity of the field exposes conceptual and methodological limitations of the traditional B&F approach. This article critically examines eight interrelated challenges in the identification, measurement, and application of B&F, drawing on theoretical, empirical, and methodological literature.The analysis highlights that B&F are not simple opposites, that they are often based on perceptions rather than mechanisms, and that exhaustive identification may not be feasible or conceptually coherent. Further, measurement and prioritization remain inconsistent, and the dynamic, multi-level, and temporal dimensions of implementation are frequently overlooked. The persistent gap between identifying B&F and linking them to implementation strategies constrains progress toward explanatory and actionable science.Moving beyond descriptive checklists, the paper suggests reconceptualizing B&F as dynamic system properties and adopting methods that capture complexity, mechanisms, and contextual interaction. Strengthening theory-method alignment will enable implementation research to evolve from enumerating determinants toward explaining how change unfolds in real-world systems.

Indexed as

BarriersContextDeterminant frameworksFacilitatorsImplementation strategiesMechanismsTheoretical development

Identifiers

PMID41851803
PMCPMC13045074

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.