RE-AIMing conferences: a reach, effectiveness, and maintenance evaluation of the Rick Hansen Institute’s Praxis 2016
Bibliographic record
Abstract
This article reported on the reach, effectiveness, and maintenance dimensions of a RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) analysis to evaluate Praxis 2016, a conference aimed to develop solutions to overcome challenges to translating research into practice in the spinal cord injury (SCI) community. Reach indicators were collected from the Praxis 2016 organizing committee. For effectiveness and maintenance, attendees (n = 106) completed a questionnaire pre-, post-, and 9-month post-Praxis 2016 assessing (a) capability (e.g., knowledge), (b) motivation, (c) opportunities, and (d) the groups they currently, need to, and/or plan to work with to develop solutions to overcome the challenges of translating SCI research into practice. They also reported their satisfaction with Praxis 2016. Qualitative interviews with attendees and organizers post-Praxis 2016 were conducted. Praxis 2016 reached 28% of their intended audience. For effectiveness, attendees' knowledge significantly increased (t(59)= 3.83, p < .001), they reported a greater need to work with members within the SCI community from pre- to post-Praxis 2016, and were generally satisfied with Praxis 2016. Regarding maintenance, more attendees reported needing to work with researchers, clinicians and SCI community organizations at 9-month post-Praxis 2016. The interviewees reported increased knowledge and capacity to network with the SCI community, but highlighted concerns for the long-term impact of Praxis 2016. Praxis 2016 was an effective approach to create short-term change in knowledge, and to expand knowledge translation networks. Further efforts could build on Praxis 2016 to foster long-term success in overcoming the challenges in translating SCI research into practice.
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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 | 0.078 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".