“I don’t know how we would have coped without it.” Understanding the Importance of a Virtual Hospital Visiting Program During the COVID-19 Pandemic
Bibliographic record
Abstract
As the COVID-19 pandemic reached Canada in full strength, the concept of allowing visiting to patients became an impossibility in most healthcare organizations. In March 2020, hospitals across Canada made the decision to close to visitors. This was a complicated decision which left admitted patients with very little option for connecting with family and friends other than through the telephone. In response, North York General Hospital launched a virtual family visiting (VFV) program across all inpatient units. Here we report the findings of a qualitative study of the program informed by an interpretive descriptive approach. Interviews were conducted with families who participated in the VFV program at North York General Hospital in Toronto, Canada during the first wave of the COVID pandemic. A total of 24 family members were interviewed. As anticipated, the family members were all extremely pleased with the opportunity to connect virtually and very satisfied with the VFV program. What was less anticipated was the anxiety and distress that families experienced in being separated from their loved ones. Our data analysis revealed 4 key themes which we have labeled (a) the unforeseen consequences of separation trauma, (b) increased vulnerability of patients and family, (c) a lifeline of human connection, and (d) the role of the facilitator as a connector. This work contributes significantly to a system-level understanding of the impact of imposed separation, increased vulnerability, and the importance of providing an alternative way for families to be present with their loved ones in these unprecedented times.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".