Falls Occurring After a Spinal Cord Injury: A Scoping Review
Bibliographic record
Abstract
IMPORTANCE: Falls have a considerable physical and psychological impact on people with spinal cord injury (SCI). Occupational therapy practitioners require evidence to support the timely development of occupation-based programs that can be applied to fall prevention in daily life. OBJECTIVE: To determine what is known about falls after SCI, including wheelchair users and people who are ambulatory, and to understand elements of fall prevention to be addressed by occupational therapy practitioners. We applied the Canadian Measure of Occupational Performance and Engagement to understand elements to be addressed in fall education and prevention with this population. DATA SOURCES: We searched eight databases using the key words falls and spinal cord injury with no limit set on dates. Study Selection and Data Collection: Studies were included that reported on falls among adults with SCI and measured one or more of the following: incidence of falls, consequences of falls, contributing factors for falls, the person's experience of falls, and strategies to prevent falls. FINDINGS: Thirty-five articles were included. The majority of the articles included information on the incidence (n = 20), consequences (n = 26), and contributing factors (n = 30) of falls. Two articles analyzed the person's experience of falls, and 1 study reviewed a fall prevention program for people with SCI specifically. CONCLUSIONS AND RELEVANCE: Research on participants' experience of falls and fall prevention programs used in spinal cord rehabilitation is extremely limited. Future research on the lived experience of falls for people with SCI is warranted. What This Article Adds: This review of evidence on falls after SCI highlights gaps in the current available evidence.
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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".