The experience of falls and fall risk during the subacute phase of spinal cord injury: a mixed methods study
Bibliographic record
Abstract
Purpose: To understand the circumstances, causes and consequences of falls experienced by individuals with subacute SCI, and to explore their perspectives on how falls/fall risk impacted their transition to community living.Materials and methods: Sixty adults with subacute SCI participated. A sequential explanatory mixed methods design was adopted. In Phase I, falls were monitored for six months post-inpatient rehabilitation discharge through a survey. In Phase II, a qualitative focus group (n = 5) was held to discuss participants’ perspectives on Phase I results and falls/fall risk. Descriptive statistics and thematic analysis were used to analyze Phase I and II data, respectively.Results: Falls commonly occurred in the daytime, at home and about half resulted in minor injury. Three themes reflecting participants’ perspectives were identified in Phase II. 1) Lack of preparedness to manage fall risk upon returning home from inpatient rehabilitation. 2) Adjusting to increased fall risk following discharge from inpatient rehabilitation. 3) Psychological impact of the transition to living at home with an increased fall risk.Conclusions: The findings highlight the need for fall prevention initiatives during subacute SCI, when individuals are learning to manage their increased fall risk.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".