Principles to guide spinal cord injury research partnerships: a Delphi consensus study
Bibliographic record
Abstract
Purpose To establish consensus regarding principles that should be used to guide spinal cord injury (SCI) research partnerships between researchers and research users.Materials and methods A three-round Delphi consensus exercise was carried out with researchers and/or research users involved in one or more SCI research partnerships. Participants considered a list of 125 partnership principles. In rounds 1 and 2, participants rated their agreement that a principle should guide SCI research partnerships on an 11-point Likert scale. After each round, principles that received a mean score of ≥8.0 or 70% of participants rated the principle ≥8.0 were retained. In round 3, participants categorized principles as essential, desirable, irrelevant, or unsure.Results At least 20 individuals participated in each round. In round 1, 103 principles met consensus criteria and eight principles were added. In round 2, 93 principles met the criteria. In round 3, 29 principles were categorized as essential and eight as desirable. Recommended principles focused on the interpersonal, relational, and logistical aspects of partnerships. Principles that did not reach consensus related to social justice and actionable impact.Conclusions Findings provide insight into 37 principles that could be used to combat tokenism and inform future guidance to meaningfully engage partners in SCI research.Implications for RehabilitationConsensus-based research partnership principles (i.e., norms or beliefs) were identified and could be prioritized to help support spinal cord injury (SCI) researchers and research users combat tokenism and meaningfully engage research users as partners in the co-creation of knowledge.The resulting list of recommended research partnership principles was used to inform the development of guidance to support quality partnerships between SCI researchers and research users within and outside the rehabilitation context (www.IKTprinciples.com).Guidance supporting meaningful research partnerships may accelerate the time between discovery and use of research in 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 | 0.269 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".