Rural and Urban Living in Persons with Spinal Cord Injury and Comparing Environmental Barriers, Their Health, and Quality-of-Life Outcomes
Bibliographic record
Abstract
There is worldwide geographic variation in the epidemiology of traumatic spinal cord injury (tSCI). The aim of this study was to determine whether environmental barriers, health status, and quality-of-life outcomes differ between patients with tSCI living in rural or urban settings, and whether patients move from rural to urban settings after tSCI. A cohort review of the Rick Hansen SCI Registry (RHSCIR) was undertaken from 2004 to 2012 for one province in Canada. Rural/urban setting was determined using postal codes. Outcomes data at 1 year in the community included the Short Form-36 Version 2 (SF36v2™), Life Satisfaction Questionnaire, Craig Hospital Inventory of Environmental Factors-Short Form (CHIEF-SF), Functional Independent Measure® Instrument, and SCI Health Questionnaire. Statistical methodologies used were t test, Mann-Whitney U test, and Fisher's exact or χ2 test. In the analysis, 338 RHSCIR participants were included; 65 lived in a rural setting and 273 in an urban setting. Of the original patients residing in a rural area at discharge,10 moved to an urban area by 1 year. Those who moved from a rural to urban area reported a lower SF-36v2™ Mental Component Score (MCS; p = 0.04) and a higher incidence of depression at 1 year (p = 0.04). Urban patients also reported a higher incidence of depression (p = 0.02) and a lower CHIEF-SF total score (p = 0.01) indicating fewer environmental barriers. No significant differences were found in other outcomes. Results suggest that although the patient outcomes are similar, some patients move from rural to urban settings after tSCI. Future efforts should target screening mental health problems early, especially in urban settings.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".