Evidence map›Paper›PMID 30400942›Full record

ArticleHealth research policy and systems2018

Advancing the evaluation of integrated knowledge translation.

Sara A Kreindler

Abstract read
In one paragraph

Article in Health research policy and systems, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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

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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.

Sara A KreindlerDepartment of Community Health Sciences, University of Manitoba, 451-753 McDermot Ave., Winnipeg, MB, R3E 0T6, Canada. skreindler@wrha.mb.ca.ORCID http://orcid.org/0000-0001-9499-2853

Funding

Canadian Institutes of Health Research FDN #143247
6 · The paper itself

Abstract

backgroundIntegrated knowledge translation (IKT) flows from the premise that knowledge co-produced with decision-makers is more likely to inform subsequent decisions. However, evaluations of manager/policy-maker-focused IKT often concentrate on intermediate outcomes, stopping short of assessing whether research findings have contributed to identifiable organisational action. Such hesitancy may reflect the difficulty of tracing the causes of this distal, multifactorial outcome. This paper elucidates how an approach based on realistic evaluation could advance the field. MAIN TEXT: Realistic evaluation views outcomes as a joint product of intervention mechanisms and context. Through identification of context-mechanism-outcome configurations, it enables the systematic testing and refinement of 'mid-range theory' applicable to diverse interventions that share a similar underlying logic of action. The 'context-sensitive causal chain' diagram, a tool adapted from the broader theory-based evaluation literature, offers a useful means of visualising the posited chain from activities to outcomes via mechanisms, and the context factors that facilitate or disrupt each linkage (e.g. activity-mechanism, mechanism-outcome). Drawing on relevant literature, this paper proposes a context-sensitive causal chain by which IKT may generate instrumental use of research findings (i.e. direct use to make a concrete decision) and identifies an existing tool to assess this outcome, then adapts the chain to describe a more subtle, indirect pathway of influence. Key mechanisms include capacity- and relationship-building among researchers and decision-makers, changes in the (perceived) credibility and usability of findings, changes in decision-makers' beliefs and attitudes, and incorporation of new knowledge in an actual decision. Project-specific context factors may impinge upon each linkage; equally important is the organisation's absorptive capacity, namely its overall ability to acquire, assimilate and apply knowledge. Given a sufficiently poor decision-making environment, even well-implemented IKT that triggers important mechanisms may fall short of its desired outcomes. Further research may identify additional mechanisms and context factors.

conclusionBy investigating 'what it is about an intervention that works, for whom, under what conditions', realistic evaluation addresses questions of causality head-on without sacrificing complexity. A realist approach could contribute greatly to our ability to assess - and, ultimately, to increase - the value of IKT.

Indexed as

Decision MakingDelivery of Health CareEvaluation Studies as TopicHealth PolicyPolicy MakingTranslational Research, BiomedicalAdministrative PersonnelCapacity BuildingCooperative BehaviorGoalsHumansKnowledgeOrganizationsResearch PersonnelStakeholder ParticipationEvidence-informed decision-makingKnowledge translationRealistic evaluationResearch methods

Identifiers

PMID30400942
PMCPMC6218993

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.