Evidence map›Paper›PMID 29169364›Full record

ArticleHealth research policy and systems2017

Policymakers' experience of a capacity-building intervention designed to increase their use of research: a realist process evaluation.

Abby Haynes, Sue Brennan, Sally Redman, Anna Williamson, Steve R Makkar, Gisselle Gallego, Phyllis Butow

Open access · goldAbstract read
In one paragraph

Article in Health research policy and systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

8 citing papers in PubMed, 39 citations in OpenAlex.

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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

7 authors at 4 institutions in 1 country.

Abby HaynesSax Institute, 235 Jones Street, Ultimo, NSW, 2007, Australia. abby.haynes@saxinstitute.org.au.ORCID http://orcid.org/0000-0001-5703-5683
Sue BrennanAustralasian Cochrane Centre, School of Public Health and Preventive Medicine, Monash University, 553 St Kilda Road, Melbourne, Victoria, 3004, Australia.
Sally RedmanSax Institute, 235 Jones Street, Ultimo, NSW, 2007, Australia.
Anna WilliamsonSax Institute, 235 Jones Street, Ultimo, NSW, 2007, Australia.
Steve R MakkarSax Institute, 235 Jones Street, Ultimo, NSW, 2007, Australia.
Gisselle GallegoSchool of Medicine, University of Notre Dame, 160 Oxford St, Darlinghurst, NSW, 2010, Australia.
Phyllis ButowCentre for Medical Psychology & Evidence-based Decision-making, University of Sydney, The Lifehouse, 119-143 Missenden Rd, Camperdown, NSW, 2006, Australia.
Sax Institute · AUThe University of Sydney · AUMonash University · AUThe University of Notre Dame Australia · AU

Funding

National Health and Medical Research Council 1001436National Health and Medical Research Council 1093096
6 · The paper itself

Abstract

backgroundAn intervention's success depends on how participants interact with it in local settings. Process evaluation examines these interactions, indicating why an intervention was or was not effective, and how it (and similar interventions) can be improved for better contextual fit. This is particularly important for innovative trials like Supporting Policy In health with Research: an Intervention Trial (SPIRIT), where causal mechanisms are poorly understood. SPIRIT was testing a multi-component intervention designed to increase the capacity of health policymakers to use research.

methodsOur mixed-methods process evaluation sought to explain variation in observed process effects across the six agencies that participated in SPIRIT. Data collection included observations of intervention workshops (n = 59), purposively sampled interviews (n = 76) and participant feedback forms (n = 553). Using a realist approach, data was coded for context-mechanism-process effect configurations (retroductive analysis) by two authors.

resultsIntervention workshops were very well received. There was greater variation of views regarding other aspects of SPIRIT such as data collection, communication and the intervention's overall value. We identified nine inter-related mechanisms that were crucial for engaging participants in these policy settings: (1) Accepting the premise (agreeing with the study's assumptions); (2) Self-determination (participative choice); (3) The Value Proposition (seeing potential gain); (4) 'Getting good stuff' (identifying useful ideas, resources or connections); (5) Self-efficacy (believing 'we can do this!'); (6) Respect (feeling that SPIRIT understands and values one's work); (7) Confidence (believing in the study's integrity and validity); (8) Persuasive leadership (authentic and compelling advocacy from leaders); and (9) Strategic insider facilitation (local translation and mediation). These findings were used to develop tentative explanatory propositions and to revise the programme theory.

conclusionThis paper describes how SPIRIT functioned in six policy agencies, including why strategies that worked well in one site were less effective in others. Findings indicate a complex interaction between participants' perception of the intervention, shifting contextual factors, and the form that the intervention took in each site. Our propositions provide transferable lessons about contextualised areas of strength and weakness that may be useful in the development and implementation of similar studies.

Indexed as

Administrative PersonnelAttitudeCapacity BuildingHealth PolicyPolicy MakingResearchFeedbackHumansProgram EvaluationSurveys and QuestionnairesHealth policyParticipant perspectivesProcess evaluationRealist evaluationResearch utilisation

Identifiers

PMID29169364
PMCPMC5701502
OpenAlexW2770676046

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.