Patients’ and caregivers’ experiences of virtual care in a primary care setting during the COVID-19 pandemic: A patient-oriented research study
Bibliographic record
Abstract
Objective: This study explored patient and caregiver expectations and experiences of virtual primary care in Manitoba, Canada. This study focused on accessibility of care, acceptability and perceptions of quality from 'users' of primary healthcare services. Due to the rapid implementation of virtual primary care during the COVID-19 pandemic in Canada, patient/public input was largely bypassed. Methods: A mixed method was conducted in collaboration with Patient and Caregiver Community Advisors. Data was obtained from 696 surveys and 9 focus groups (n = 41 patients and caregivers). Results: Data suggest good acceptance of virtual visits, although considered a new experience despite almost exclusive use of the telephone. Participants preferred more input for choosing the type of visit but experienced less stress, time and inconvenience by using virtual care. There were mixed opinions of quality. More complex visits were associated with incomplete consultations and serve as one exemplar of the limitations due to lack of physical presence or contact. Unique communication skills were required to convey health concerns adequately and accurately. A more transactional approach was perceived from the lack of visual cues and the awkwardness associated with pauses during the phone conversation. Virtual care may be better used for certain circumstances but should encompass patient-centred decision making for when and how. Many expressed interests in video options; technology access and user ability are additional considerations for advancing virtual care. Conclusions: The experiences and recommendations from patients and caregivers provide an important contribution to decision-making and integrating and sustaining quality virtual care for patient-centered healthcare service delivery. Keywords: Virtual care experiences, primary care, patient-oriented research, mixed methods, COVID-19.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".