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Record W2012974981 · doi:10.1186/s12911-014-0121-7

Scoping review of toolkits as a knowledge translation strategy in health

2014· article· en· W2012974981 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

VenueBMC Medical Informatics and Decision Making · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of TorontoSickKids FoundationDalhousie UniversityShriners Hospitals for Children - CanadaHospital for Sick Children
Fundersnot available
KeywordsKnowledge translationGrey literatureDisseminationHealth informaticsHealth careKnowledge managementInformation DisseminationKnowledge baseComputer scienceMedical educationMedicineMEDLINEWorld Wide WebPublic healthNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: Significant resources are invested in the production of research knowledge with the ultimate objective of integrating research evidence into practice. Toolkits are becoming increasingly popular as a knowledge translation (KT) strategy for disseminating health information, to build awareness, inform, and change public and healthcare provider behavior. Toolkits communicate messages aimed at improving health and changing practice to diverse audiences, including healthcare practitioners, patients, community and health organizations, and policy makers. This scoping review explores the use of toolkits in health and healthcare. METHODS: Using Arksey and O'Malley's scoping review framework, health-based toolkits were identified through a search of electronic databases and grey literature for relevant articles and toolkits published between 2004 and 2011. Two reviewers independently extracted data on toolkit topic, format, target audience, content, evidence underlying toolkit content, and evaluation of the toolkit as a KT strategy. RESULTS: Among the 253 sources identified, 139 met initial inclusion criteria and 83 toolkits were included in the final sample. Fewer than half of the sources fully described the toolkit content and about 70% made some mention of the evidence underlying the content. Of 83 toolkits, only 31 (37%) had been evaluated at any level (27 toolkits were evaluated overall relative to their purpose or KT goal, and 4 toolkits evaluated the effectiveness of certain elements contained within them). CONCLUSIONS: Toolkits used to disseminate health knowledge or support practice change often do not specify the evidence base from which they draw, and their effectiveness as a knowledge translation strategy is rarely assessed. To truly inform health and healthcare, toolkits should include comprehensive descriptions of their content, be explicit regarding content that is evidence-based, and include an evaluation of the their effectiveness as a KT strategy, addressing both clinical and implementation 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)0.013
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.639
GPT teacher head0.698
Teacher spread0.058 · 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