Evaluation of an integrated knowledge translation approach used for updating the Cochrane Review of Patient Decision Aids: a pre-post mixed methods study
Bibliographic record
Abstract
BACKGROUND: When people who can use or benefit from research findings are engaged as partners on study teams, the quality and impact of findings are better. These people can include patients/consumers and clinicians who do not identify as researchers. They are referred to as "knowledge users". This partnered approach is called integrated knowledge translation (IKT). We know little about knowledge users' involvement in the conduct of systematic reviews. We aimed to evaluate team members' degree of meaningful engagement and their perceptions of having used an IKT approach when updating the Cochrane Review of Patient Decision Aids. METHODS: We conducted a pre-post mixed methods study. We surveyed all team members at two time points. Before systematic review conduct, all participating team members indicated their preferred level of involvement within each of the 12 steps of the systematic review process from "Screen titles/abstracts" to "Provide feedback on draft article". After, they reported on their degree of satisfaction with their achieved level of engagement across each step and the degree of meaningful engagement using the Patient Engagement In Research Scale (PEIRS-22) across 7 domains scored from 100 (extremely meaningful engagement) to 0 (no meaningful engagement). We solicited their experiences with the IKT approach using open-ended questions. We analyzed quantitative data descriptively and qualitative data using content analysis. We triangulated data at the level of study design and interpretation. RESULTS: Of 21 team members, 20 completed the baseline survey (95.2% response rate) and 17/20 (85.0% response rate) the follow-up survey. There were 11 (55%) researchers, 3 (15%) patients/consumers, 5 (25%) clinician-researchers, and 1 (5%) graduate student. At baseline, preferred level of involvement in the 12 systematic review steps varied from n = 3 (15%) (search grey literature sources) to n = 20 (100%) (provide feedback on the systematic review article). At follow-up, 16 (94.1%) participants were totally or very satisfied with the extent to which they were involved in these steps. All (17, 100%) agreed that the process was co-production. Total PEIRS-22 scores revealed most participants reported extremely (13, 76.4%) or very (2, 11.8%) meaningful degree of engagement. Triangulated data revealed that participants indicated benefit to having been engaged in an authentic research process that incorporated diverse perspectives, resulting in better and more relevant outputs. Reported challenges were about time, resources, and the logistics of collaborating with a large group. CONCLUSION: Following the use of an IKT approach during the conduct of a systematic review, team members reported high levels of meaningful engagement. These results contribute to our understanding of ways to co-produce systematic reviews.
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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 | 0.305 | 0.416 |
| Meta-epidemiology (narrow) | 0.002 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".