Spinal Cord Injury Community Survey: Understanding the Needs of Canadians with SCI
Bibliographic record
Abstract
BACKGROUND: There is a lack of literature regarding service needs of people with SCI living in the community. Better assessment of expressed and met and unmet needs would help in the development of effective service delivery. OBJECTIVE: From a national SCI Community Survey in Canada, the aim was to identify the most critical service needs of people living in the community at least 1 year post discharge from rehabilitation and the support they received to meet their needs. METHOD: Data were collected mainly through a secure Web site and encompassed demographics, personal and household income, an SCI severity measure, and an SCI community needs measure containing information on 13 SCI-related needs. RESULTS: A total of 1,549 persons with SCI (traumatic lesion, n = 1,137; nontraumatic lesion, n = 412) across Canada completed the survey. Most critical needs for community integration were expressed by a substantial proportion of survey participants, but significantly more expressed and met needs were reported by persons with a traumatic than a nontraumatic lesion. Personal and environmental characteristics influenced the probability of expressing and meeting needs (eg, severity of injury and household income). Help and support to meet expressed needs were received from government agencies, community organizations, and friends or family. CONCLUSION: Better assessment of expressed and met or unmet needs for services remains a challenge but will serve as a tool to optimize service delivery in the community. Environmental barriers to services, particularly the process of getting needs met and associated costs, remain an issue that requires a reconsideration of some aspects of access to services.
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 | 0.005 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".