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Record W2297168878 · doi:10.1186/s13012-016-0399-1

Integrated knowledge translation (IKT) in health care: a scoping review

2015· review· en· W2297168878 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImplementation Science · 2015
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsDalhousie UniversityWestern UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsKnowledge translationGeneral partnershipPsychological interventionHealth services researchMedicineRelevance (law)Health informaticsMEDLINEHealth administrationKnowledge managementCINAHLMedical educationCochrane LibraryNursingPublic healthComputer scienceAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Integrated knowledge translation (IKT) refers to collaboration between researchers and decision-makers. While advocated as an approach for enhancing the relevance and use of research, IKT is challenging and inconsistently applied. This study sought to inform future IKT practice and research by synthesizing studies that empirically evaluated IKT and identifying knowledge gaps. METHODS: We performed a scoping review. We searched MEDLINE, EMBASE, and the Cochrane Library from 2005 to 2014 for English language studies that evaluated IKT interventions involving researchers and organizational or policy-level decision-makers. Data were extracted on study characteristics, IKT intervention (theory, content, mode, duration, frequency, personnel, participants, timing from initiation, initiator, source of funding, decision-maker involvement), and enablers, barriers, and outcomes reported by studies. We performed content analysis and reported summary statistics. RESULTS: Thirteen studies were eligible after screening 14,754 titles and reviewing 106 full-text studies. Details about IKT activities were poorly reported, and none were formally based on theory. Studies varied in the number and type of interactions between researchers and decision-makers; meetings were the most common format. All studies reported barriers and facilitators. Studies reported a range of positive and sub-optimal outcomes. Outcomes did not appear to be associated with initiator of the partnership, dedicated funding, partnership maturity, nature of decision-maker involvement, presence or absence of enablers or barriers, or the number of different IKT activities. CONCLUSIONS: The IKT strategies that achieve beneficial outcomes remain unknown. We generated a summary of IKT approaches, enablers, barriers, conditions, and outcomes that can serve as the basis for a future review or for planning ongoing primary research. Future research can contribute to three identified knowledge gaps by examining (1) how different IKT strategies influence outcomes, (2) the relationship between the logic or theory underlying IKT interventions and beneficial outcomes, and (3) when and how decision-makers should be involved in the research process. Future IKT initiatives should more systematically plan and document their design and implementation, and evaluations should report the findings with sufficient detail to reveal how IKT was associated with outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.838
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.010
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.937
GPT teacher head0.829
Teacher spread0.107 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it