Evidence map›Paper›PMID 29935136›Full record

ArticleInternational journal of health policy and management2018

From Linear to Complicated to Complex Comment on "Using Complexity and Network Concepts to Inform Healthcare Knowledge Translation".

Jo Rycroft-Malone

Abstract readComment
In one paragraph

Article in International journal of health policy and management, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Jo Rycroft-MaloneSchool of Healthcare Sciences, Bangor University, Bangor, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attention to collaborative approaches to encouraging evidence use in healthcare practice are gaining traction. The inherent complexities in collaborative and networked approaches to knowledge translation (KT) have been embraced by Kitson and colleagues in their complexity network model. In this commentary, the potential of complexity as presented by Kitson et al within their model is considered. The utility of such a model will be contingent upon how easy users find it to understand and apply to their challenge, and doing so in a way that is useful to not only help with explanation, but also with prediction.

Indexed as

Delivery of Health CareTranslational Research, BiomedicalHumansOrganizationsCollaborationComplexityFrameworkKnowledge TranslationModel

Identifiers

PMID29935136
PMCPMC6015516

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.