Knowledge Translation for Effective Consumers
Bibliographic record
Abstract
With the emergence of patient-centered care, consumers are becoming more effective managers of their care--in other words, "effective consumers." To support patients to become effective consumers, a number of strategies to translate knowledge to action (KTA) have been used with varying success. The use of a KTA framework can be helpful to researchers and implementers when framing, planning, and evaluating knowledge translation activities and can potentially lead to more successful activities. This article briefly describes the KTA framework and its use by a team based out of the University of Ottawa to translate evidence-based knowledge to consumers. Using the framework, tailored consumer summaries, decision aids, and a scale to measure consumer effectiveness were created in collaboration with consumers. Strategies to translate the products into action then were selected and implemented. Evaluation of the knowledge tools and products indicates that the products are useful to consumers. Current research is in place to monitor the use of these products, and future research is planned to evaluate the effect of using the knowledge on health outcomes. The KTA framework provides a useful and valuable approach to knowledge translation.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
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 teacher head, 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".