Virtual Care Access and Health Equity during the COVID-19 Pandemic, a qualitative study of patients with chronic diseases from Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The COVID-19 pandemic has led to the widespread uptake of virtual care in Canada; however, virtual care may also create new barriers to health care. The purpose of this paper was to explore patient perceptions and concerns around virtual care access. METHODS: Between February and April 2020, we conducted semi-structured interviews with participants from four chronic disease clinics (stroke, epilepsy, amyotrophic lateral sclerosis, obstetrics medicine) in a mid-sized academic hospital in Southern Ontario, Canada. Consecutive sampling was done by including the patients receiving virtual care in those months. Caregivers were invited to participate in the event that patients were unable to participate in the interview. Thematic analysis was employed to identify overarching themes, and codes were reviewed and refined using a consensus process. RESULTS: We interviewed 31 participants (27 patients, four caregivers) that had taken part in virtual care. Our findings suggested that the COVID-19 pandemic served to isolate participants and had negatively impacted their access to health care. However, virtual care did provide a safe avenue for patients to receive care and served as a reassuring option during the pandemic. Low technological literacy and access were identified as barriers to virtual care. Greater awareness and patient engagement is needed in future research to improve access. CONCLUSION: Certain populations can be disproportionately affected by differential access to virtual care. Future studies should examine how social determinants intersect to impact virtual health care access in different patient populations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it