Exploring patient engagement practices and resources within a health care system: Applying a multi-phased mixed methods knowledge mobilization approach
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.123 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".