A Narrative Literature Review to Direct Spinal Cord Injury Patient Education Programming
Bibliographic record
Abstract
PURPOSE: To summarize the evidence on SCI-related education literature, while looking at potential barriers, solutions, benefits, and patient preferences regarding SCI patient education. METHOD: A literature review was conducted using 5 electronic databases. Quality appraisal instruments were designed to determine the methodological rigor of the quantitative and qualitative studies found. Selected articles were read in their entirety and themes were abstracted. RESULTS: Fourteen articles met the inclusion criteria for this narrative literature review, all of which were based on research studies. Seven of these 14 were quantitative studies, 3 were qualitative studies, and 4 were mixed-methods studies. CONCLUSION: To improve SCI education during rehabilitation, programs should maximize the receptiveness of newly injured patients to SCI-related information, optimize the delivery of SCI education, increase the number of opportunities for learning, promote and support lifelong learning, and include patient and program evaluation. How these strategies are specifically implemented needs to be determined by program management in consultation with various stakeholders, whilst considering the unique characteristics of the rehabilitation facility.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".