Unique and shared partner priorities for supporting engagement in knowledge mobilization in pediatric pain: a best–worst scaling experiment
Bibliographic record
Abstract
Abstract Background Engaging in partnerships is key to the success of knowledge mobilization (KM) activities; however, how best to engage partners in KM activities in the context of paediatric pain and children’s health more broadly is not well understood. There is limited guidance on what supports the development of effective partnerships in KM activities with a variety of partner types. The purpose of this study was to examine the preferences and priorities of three partner groups (i.e. health professionals, researchers and patient/caregiver partners) when it comes to supporting their engagement in KM activities within paediatric pain and children’s health. Methods We used a case 1 (object case) best–worst scaling (BWS) experiment, a stated preferences method to assess priorities and relative importance of factors related to supporting engagement in KM activities and compare their importance across the three partner groups. Participants completed 12 tasks requiring them to select items that were most and least important to supporting their engagement in KM activities. A total of 11 items, generated through a previous elicitation task, were included in the balanced incomplete block experimental design for the BWS. Difference scores and ratio values were calculated for each group and relative comparisons were observed across groups. Results A total of 127 participants completed the BWS experiment. All partner groups agreed that items related to relationships within teams were among the most important, while pragmatic items related to executing KM were amongst the least important. While there was relative similarity in the items ranked as important, varying priorities also emerged for each group; fit of KM activities in the clinical context was particularly important among researchers, while flexible communication was relatively more important within the patient/caregiver group. Health professionals differed the least from the other groups. Conclusions Different partner groups prioritized strong relationships when it comes to supporting engagement in KM activities, reinforcing the importance of connections in KM processes. There was nuance, however, around how partner groups valued various aspects of relationships. Individuals leading KM initiatives in paediatric pain and children’s health should discuss relationships and pragmatics with partners to ensure successful collaboration and impactful activities.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".