An Exploratory Analysis of the Potential Association Between SCI Secondary Health Conditions and Daily Activities
Bibliographic record
Abstract
BACKGROUND: Secondary health conditions (SHCs) are common following traumatic spinal cord injury (tSCI) and are believed to influence a person's ability to participate in daily activities (DAs). This association should be understood so that health care providers may target interventions with clarity and purpose to manage SHCs and facilitate DAs to maximal effect. OBJECTIVE: To explore the association between SHCs and DAs expressed as the increased chance of not participating as much as wanted in a DA when an SHC is present. METHODS: Community-dwelling persons with tSCI (n = 1,137) responded to the SCI Community Survey. The occurrence and frequency of 21 SHCs were determined. The extent of participation in 26 DAs was measured. The relative risk (RR) of not participating as much as wanted in a DA when a SHC is present was calculated. RESULTS: When some SHC were present, the RR of not participating as much as wanted increased significantly (range, 15%-153%; P < .001). Certain SHCs (light-headedness/dizziness, fatigue, weight problems, constipation, shoulder problems) were associated with a greater chance of not participating in many DAs. No single SHC was associated with every DA and conversely not every DA was associated with an SHC. CONCLUSIONS: Maximizing participation in DAs requires minimizing SHCs in every instance. Understanding the association between SHCs and DAs may facilitate targeted care resulting in less severe SHCs, greater participation in DAs, and benefits to both the individual and society.
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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".