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Record W2940916865 · doi:10.1186/s40900-019-0139-1

Patient and Public Engagement in Integrated Knowledge Translation Research: Are we there yet?

2019· article· en· W2940916865 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueResearch Involvement and Engagement · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of OttawaMcMaster UniversityPopulation Health Research InstituteOttawa HospitalUniversity of Northern British Columbia
FundersCanadian Institutes of Health Research
KeywordsKnowledge translationPublic engagementKnowledge managementMedicinePsychologyComputer sciencePublic relationsPolitical science

Abstract

fetched live from OpenAlex

PLAIN ENGLISH SUMMARY: There have been many attempts to improve how healthcare services are developed and delivered. Despite this, we know that there are many gaps and differences in practice and that these can lead to poor patient outcomes. In addition, there are also concerns that research is being undertaken that does not reflects the realities or needs of those using healthcare services, and that the use of research findings in practice is slow. As such, shared approaches to research, such as integrated knowledge translation, are being used.Integrated knowledge translation (IKT) is a research approach that brings together researchers, along with other stakeholders that have knowledge about a particular healthcare issue. Stakeholders may include healthcare providers and policy-makers. More recently, there has been a growing awareness of the need to include patients and members of the public within research processes. These collaborative and patient-oriented research approaches are seen as a way to develop research that tackles ongoing gaps in practice and reflect the insights, needs and priorities of those most affected by health research outcomes. Despite great support, little is known about how these major research approaches are connected, or how they may bring about improvements in the development and use of research evidence. In this paper, we examine how IKT and patient engagement processes are linked, as well as exploring where differences exist. Through this, we highlight opportunities for greater patient engagement in IKT research and to identify areas that need to be understood further. ABSTRACT: Healthcare organizations across the world are being increasingly challenged to develop and implement services that are evidence-based and bring about improvement in patient and health service outcomes. Despite an increasing emphasis upon evidence-based practice, large variations in practice remain and gaps pervade in the creation and application of knowledge that improves outcomes. More collaborative models of health research have emerged over recent years, including integrated knowledge translation (IKT), whereby partnerships with key knowledge users are developed to enhance the responsiveness and application of the findings. Likewise, the meaningful engagement of patients, in addition to the inclusion of patient-reported outcomes and priorities, has been hailed as another mechanism to improve the relevance, impact and efficiency of research.Collectively, both IKT and patient engagement processes provide a vehicle to support research that can address health disparities and improve the delivery of effective and responsive healthcare services. However, the evidence to support their impact is limited and while these approaches are inextricably connected through their engagement focus, it is unclear how IKT and patient engagement processes are linked conceptually, theoretically, and practically. In this paper, we will begin to critically examine some of the linkages and tensions that exist between IKT and patient-engagement for research and will examine potential opportunities for IKT researchers as they navigate and enact meaningful partnerships with patients and the public.

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)0.024
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.003
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 head0.784
GPT teacher head0.541
Teacher spread0.243 · 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