“From All, To All”: Implementing a collaborative online conference to reflect on the daily living of individuals with cerebral palsy
Bibliographic record
Abstract
BACKGROUND: Translating knowledge to improve paediatric rehabilitation has become a research area of interest. This study describes the development and evaluation of an online conference that brought together perspectives of individuals with cerebral palsy (CP), families, health care professionals, and researchers to discuss the daily living of individuals with CP. METHODS: We anchored the development and implementation of the online conference in the action cycle of the Knowledge to Action Framework. To develop the meeting, we included representatives from each stakeholder group in the programme committee. The conference programme was designed having the lifespan perspective of individuals with CP, from birth to adulthood, as its central core, with themes related to daily living (e.g., self-care, mobility, and continuing education). Participants' satisfaction with the conference was assessed using an anonymized online survey sent to all participants. RESULTS: The conference had 1656 attendees, of whom 675 answered the online satisfaction survey. Most participants rated the structure of the conference (i.e., quality of the technical support, audio and video, and online platform) and discussed topics (i.e., relevance, content, discussion, speakers, and available time) positively. CONCLUSION: Collaborative conferences that include stakeholders throughout the planning and implementation are a viable, effective knowledge translation strategy that allows for sharing experiences and disseminating knowledge among families and individuals with CP, health care professionals, and researchers.
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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 | 0.057 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".