Patient Perceptions of the Impact of the COVID Pandemic on the Quality of Their Gastrointestinal Cancer Care
Bibliographic record
Abstract
We surveyed patients who had a received care for a gastrointestinal cancer between 03/2020 and 05/2021 to understand their perceptions of the impact of the Covid pandemic on cancer care delivery and quality of care. Three-hundred fifty-eight respondents provided evaluable responses (response rate: 17.3%). Approximately half of respondents (46.4%) perceived that they had experienced a pandemic-related cancer care modification; most changes were initiated by a clinician or the cancer center (44.6%). Relative to White patients those from Racialized Groups (OR: 1.91, 95% CI: 1.03-3.54) were more likely to report a cancer treatment change. Additionally, relative to patients in follow-up, those who were newly diagnosed (OR: 2.39; 95% CI: 1.21-4.71) were more likely to report a change. Compared to White patients, patients from Racialized Groups were approximately twice as likely to report perceiving that virtual visits during Covid negatively impacted the quality of their care (OR: 2.21; 95% CI: 0.96-5.08). These findings potentially reflect pre-existing systemic disparities in quality of and access to care, as well as differences in how care is experienced by patients from Racialized Groups.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".