Prioritization of rehabilitation Domains for establishing spinal cord injury high performance indicators using a modification of the Hanlon method: SCI-High Project
Bibliographic record
Abstract
Objectives: To prioritize Domains of SCI Rehabilitation Care (SCI-Care) based on clinical importance and feasibility to inform the development of indicators of quality SCI-Care for adults with SCI/D in Canada.Methods: A 17-member external advisory committee, comprised of key stakeholders, ranked 15/37 Domains of rehabilitation previously flagged by the E-scan project team for gaps between knowledge generation and clinical implementation. Priority scores (D) were calculated using the Hanlon formula: D=[A+(2×B)]×C, where A is prevalence, B is seriousness, and C is the effectiveness of available interventions. A modified “EAARS” (Economic, Acceptability, Accessibility, Resources, and Simplicity) criterion was used to rank feasibility on a scale of 0–4 (4 is high). The product of these two scores determined the initial Domain ranking. Following the consensus process, further changes were made to the Domain rankings.Results: Despite a low feasibility score, Sexual Health was ranked as high priority; and, the Community Participation and Employment Domains were merged. The 11 final prioritized Domains in alphabetic order were: Cardiometabolic Health; Community Participation and Employment; Emotional Well-Being; Reaching, Grasping, and Manipulation; Self-Management; Sexual Health; Tissue Integrity; Urinary Tract Infection; Urohealth; Walking, and Wheeled Mobility.Conclusions: The modified Hanlon method was used to facilitate prioritization of 11 of 37 Domains to advance the quality of SCI-care by 2020. In future, the Spinal Cord Injury Rehabilitation Care High Performance Indicators (SCI-High) Project Team will develop structure, process and outcome indicators for each prioritized Domain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".