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Exploring patient engagement practices and resources within a health care system: Applying a multi-phased mixed methods knowledge mobilization approach

2014· article· en· W2031008668 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Multiple Research Approaches · 2014
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsAlberta Health ServicesUniversity of Alberta
Fundersnot available
KeywordsProject commissioningResource (disambiguation)Health careNursingPatient careMedicineKnowledge managementMedical educationBusinessPublic relationsPublishingPolitical scienceComputer science

Abstract

fetched live from OpenAlex

A Canadian health authority developed a patient engagement framework, but had no standard resources or supports to prepare staff, leaders or patients/families for meaningful patient engagement. A study was conducted to determine what resources, preparation and supports were needed for patients, providers and leaders to be meaningfully engaged in patient-centred care decisions, and for the contents of a resource ‘kit.’ A multi-phased mixed methods approach included a needs assessment with patients, providers and leaders on what was essential for the patient engagement experience; a scoping literature review on appropriate resources; a patient engagement ‘Resource Kit’ based on findings; and a pilot and evaluation of the kit. This integrated approach resulted in a resource kit that was relevant in terms of content, comprehensive in the volume of resources, and tailored to the unique needs of patients/families, providers and leaders. Continuing evolution and evaluation of the kit was seen as critical.

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)0.021
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.681
GPT teacher head0.577
Teacher spread0.104 · 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