Navigating the Pandemic: Exploring Perspectives of Individuals with Spinal Cord Injury on COVID-19 Resources
Bibliographic record
Abstract
The COVID-19 pandemic severely impacted vulnerable populations, such as individuals with spinal cord injury (SCI). Concerns within this group have escalated regarding access to essential services, including caregiver support, equipment maintenance, and medical care during the pandemic. In response, multiple COVID-19 online resources tailored for individuals with SCI were developed and provided. This study aimed to investigate the perspectives of individuals with SCI (n=12) on available COVID-19 online resources and to examine the perceived usability, clarity, and applicability of the resources. In this qualitative description study, we used an online survey and semi-structured interviews to collect data. Survey results indicated that 70% of participants found the resources useful, 65% found them easy to navigate, and 60% were likely to use the information provided, with specific feedback revealing generally positive responses for prevention infographics and text-based mental health resources, mixed feedback for mental health and physical activity videos, and varied responses for caregiver resources. Based on the data from qualitative interviews, three main themes emerged, namely “Quality of information”, “Presentation” and “Delivery of Resources”. Findings highlight the need for more specific, realistic, and actionable information tailored to the SCI community, emphasizing the importance of detailed, visually appealing, and regularly updated resources to effectively support individuals with SCI during health crises.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".