Models of Care Delivery from Rehabilitation to Community for Spinal Cord Injury: A Scoping Review
Bibliographic record
Abstract
Spinal cord injury (SCI) is a chronic condition that results in high healthcare utilization and lifetime cost across the care continuum. In the absence of a standardized model of care delivery for SCI in western countries such as Canada, a scoping review of the literature was performed to identify and summarize existing international SCI models of care delivery. Four databases were searched using key words and subject headings for concepts such as: "spinal cord injury," "delivery of healthcare," "model of care," "patient care planning," and "care pathway." Title, abstract, and full text review were competed by two independent reviewers. A combined total of 46 peer-reviewed and gray literature articles were included. No single SCI model of care has been adopted across different countries internationally. However, optimal attributes of models of care were identified, including the importance of having multidisciplinary SCI specialty care providers along the continuum, provision of rural SCI services and outreach, integration of primary care, peer mentoring, and using a hub and spokes model of care. These findings inform the future development of an SCI model of care, which ideally would serve all geographical locations and span the continuum of care, improving the health status and quality of life of persons with SCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".