International Comparison of Vocational Rehabilitation for Persons With Spinal Cord Injury: Systems, Practices, and Barriers
Bibliographic record
Abstract
Background: Employment rates among people with spinal cord injury or spinal cord disease (SCI/D) show considerable variation across countries. One factor to explain this variation is differences in vocational rehabilitation (VR) systems. International comparative studies on VR however are nonexistent. Objectives: To describe and compare VR systems and practices and barriers for return to work in the rehabilitation of persons with SCI/D in multiple countries. Methods: A survey including clinical case examples was developed and completed by medical and VR experts from SCI/D rehabilitation centers in seven countries between April and August 2017. Results: Location (rehabilitation center vs community), timing (around admission, toward discharge, or after discharge from clinical rehabilitation), and funding (eg, insurance, rehabilitation center, employer, or community) of VR practices differ. Social security services vary greatly. The age and preinjury occupation of the patient influences the content of VR in some countries. Barriers encountered during VR were similar. No participant mentioned lack of interest in VR among team members as a barrier, but all mentioned lack of education of the team on VR as a barrier. Other frequently mentioned barriers were fatigue of the patient (86%), lack of confidence of the patient in his/her ability to work (86%), a gap in the team's knowledge of business/legal aspects (86%), and inadequate transportation/accessibility (86%). Conclusion: VR systems and practices, but not barriers, differ among centers. The variability in VR systems and social security services should be considered when comparing VR study results.
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 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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".