Knowledge and awareness assessment of bone loss and fracture risk after spinal cord injury
Bibliographic record
Abstract
Bone loss at skeletal sites predominantly below the neurological lesion is a known secondary complication following spinal cord injury (SCI); however, patient awareness of post-SCI bone loss and treatment is unknown. Therefore, the purpose of this study was to explore and describe current education and awareness of bone loss among adults with SCI.Methods A cross-sectional analysis was conducted on a convenience sample of 138 adults with SCI, who completed a survey regarding knowledge and awareness of post-SCI bone health as part of a larger study. Self-reported demographic information and assessments of bone health knowledge were analyzed.Results Approximately 20% (n = 28) of participants had never heard of bone mineral density (BMD), 25% (n = 34) only vaguely remembered that BMD was mentioned during their hospitalization/rehabilitation after SCI, 36% (n = 50) clearly remembered that BMD was mentioned during their hospitalization/rehabilitation, and 17% (n = 24) reported having an individual or group education session on causes and management of low BMD during rehabilitation. Only 30% (n = 42) of participants believed they had adequate knowledge on the subject, while 70% (n = 96) believed their knowledge was inadequate or were unsure. Most participants (73%, n = 101) reported being concerned about the risks of low BMD after SCI and were interested in learning more about prevention (76%, n = 105) and treatment options (78%, n = 108).Conclusions While results suggest that most participants received some information regarding bone health in post-SCI care, over 70% of participants reported wanting more information about bone loss prevention and treatment, indicating bone health education is a patient priority in this population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".