COVID-19 and travel for people with spinal cord injury
Bibliographic record
Abstract
Background: Individuals who participate in adaptive fitness or activity-based therapy programs with SCI do adaptive fitness activities to maintain and increase health and well-being. Impacts from COVID-19 affected access to community-based programs for all individuals. Objective: To seek understanding of how the COVID-19 pandemic affected access to community based adaptive health effects access to adaptive/ activity-based therapy/ wellness centers, and how inactivity affects health impacts with individuals who normally participate in adaptive fitness/ activity-based therapy activities with SCI. Design: Initial cross-sectional findings from a longitudinal study Methods: Data was collected between June to September 2020 (N=64) by a self-reported online survey, from individuals with SCI in the USA and Canada who normally participate in adaptive fitness programs. Primary outcomes were to observe health outcomes among individuals with SCI who have been unable to participate in adaptive fitness programs due to the COVID-19 pandemic social distancing guidelines. Ordinal logic, averages, standard deviation, and generalized observations were used to analyze the data. Results Observed: There was a significant decline of exercise for individuals who normally participate in adaptive fitness programs as a result of the COVID-19 pandemic during the summer of 2020. Moderate negative health impacts were observed with function in regard to mobility/ movement related skills, ability to complete ADLs, Typical endurance levels with daily activities, pain, weight, and need for new assistive equipment. Conclusions: The COVID-19 pandemic has decreased physical activity for participants in exercise/ therapy programs with SCI. Individuals with SCI who stop or decrease participation may have moderate negative impacts in their health and well-being.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".