An integrated knowledge translation approach to co-create and evaluate patient education tools on cholesterol management
Bibliographic record
Abstract
Context: The objective of CHOICES (Community Heart Outcomes Improvement and Cholesterol Education Study) is to understand how evidence-informed cholesterol management can prevent cardiovascular disease (CVD) in 14 health regions at higher risk in Ontario, Canada using a suite of educational interventions. An integrated knowledge translation (IKT) approach was used to co-create an educational tool on CVD risk, behaviour modifications for cholesterol management, and cholesterol-lowering medications. In order to further understand the needs of Ontario residents related to CVD prevention, a process evaluation was conducted through engagement with the public. Objective: To evaluate implementation quality including reach, responsiveness and usability of the patient-targeted educational tool for cholesterol management. Study Design: A 10-minute online survey was administered to users of the tool. Population: Adults aged 40-75 years who reside in one of the 14 identified regions in Ontario with higher-than-average CVD risk. The tool and survey were shared broadly in the targeted regions and participants were recruited through social media, stakeholder involvement, and market research organizations. Outcome Measures: Reach was measured by the number of participants who received the tool and completed the survey. The survey measured perceived usability of organization, layout and applicability of the tool (6-items). Responsiveness was measured by the level of receptivity and interest in sharing the tool (4-items). Respondents ranked their level of agreement to each question on a likert scale from 1 (Strongly Disagree) to 7 (Strongly Agree). Results: 230 users of the tool were recruited to participate, of which 104 completed the survey (response rate= 45.2%). Respondents indicated that the tool's content was clear (M = 6.00, SD = 1.05) and would support them as a patient seeking cholesterol related information (M = 6.00, SD = 0.99). Respondents indicated their high likelihood to recommend the tool to their personal networks (M = 5.37, SD = 1.19) and preference to receive similar information from their family physician (M = 5.92, SD = 1.15). Conclusion: Overall, participant responsiveness and receptivity to the co-created patient educational tool was high. This work enhances understanding of the benefits of co-created patient-targeted interventions to improve cholesterol management and ultimately inform the implementation of similar scalable strategies across Ontario.
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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 | 0.087 | 0.117 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".