Understanding how virtual care has shifted primary care interactions and patient experience: A qualitative analysis
Bibliographic record
Abstract
INTRODUCTION: The widespread and rapid implementation of virtual care has introduced evolutionary changes in the context, process, and way primary care is delivered. The objectives of this study were to: (1) understand whether and how virtual care has shifted the therapeutic relationship; (2) describe the core components of compassionate care from the patient perspective and (3) identify how and in what circumstances compassionate care might be amplified. METHODS: Participants living in Ontario, Canada were eligible if they had interacted with their primary care clinician following the rapid implementation of virtual care in March 2020, irrespective of virtual care use. One-on-one semi-structured interviews were conducted with all participants and data were analyzed using inductive thematic analysis. RESULTS: Four themes emerged across 36 interviews: (1) Virtual care shifts communication patterns but the impact on the therapeutic relationship is unclear; (2) Rapid implementation of virtual care limited perceived quality and access among those who did not have the option to utilize it; (3) Patients perceive five key elements as central to compassion in a virtual context; and (4) Leveraging technology to fill gaps within and beyond the visit is a step towards improving experiences for all. DISCUSSION: Virtual care has transformed the ways in which patient-clinician communication operates in primary care. Patients with access to virtual care described largely positive experiences, while those whose interactions were limited to phone visits experienced decreased quality and access to care. Attention must shift to identifying effective strategies to support the health workforce in building virtual compassion competencies.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".