Exploring the Lived Experiences of Individuals With Spinal Cord Injury During the COVID-19 Pandemic
Bibliographic record
Abstract
The global spread of severe acute respiratory syndrome coronavirus 2019 (COVID-19) has affected over 100 countries and has led to the tragic loss of life, overwhelmed health care systems and severely impacted the global economy. Specifically, individuals living with spinal cord injury (SCI) are particularly vulnerable during the COVID-19 pandemic as they often face adverse impacts on their health, emotional well-being, community participation, and life expectancy. The objective of this study was to investigate the lived experience of individuals with SCI during the COVID-19 pandemic in Ontario, Canada. An exploratory design with a qualitative descriptive approach was used to address the study objective. Nine semi-structured interviews were conducted with individuals with traumatic and non-traumatic SCI (37-69 years, C3-L5, AIS A-D, and 5-42 years post-injury). Using reflexive thematic analysis, the following themes were created: (1) Caregiver exposure to COVID-19; (2) Staying physically active in quarantine; (3) Living in social isolation; (4) Difficulty obtaining necessary medical supplies; (5) Access to health services and virtual care during COVID-19; and (6) Fighting COVID-19 misinformation. This is one of the first studies to explore the impact of COVID-19 on individuals living with SCI in Ontario. This study contributes to a greater understanding of the challenges faced by individuals living with SCI and provides insight into how to better support and respond to the specific and unique needs of individuals with SCI and their families during a national emergency or pandemic.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".