Reducing social isolation during the COVID-19 pandemic: Assessing the contribution of courtesy phone calls by volunteers
Bibliographic record
Abstract
CONTEXT: During the COVID-19 pandemic, restrictions were imposed on visits in hospitals in the province of Quebec, Canada in an effort to reduce the risk of viral exposure by minimizing face-to-face contact in order to protect patients, visitors and staff. These measures led to social isolation for patients. In order to reduce this isolation, CHUM (the Centre hospitalier de l'Université de Montréal, a teaching hospital) shifted from in-person visits to courtesy telephone calls delivered by volunteers from CHUM's Volunteers, Recreation and Leisure Department. OBJECTIVES: To study: (1) the contribution made by these calls to reducing isolation and their limitations, (2) how the calls can be improved, and (3) whether they should be maintained, based on the views of patients and volunteers. METHODOLOGY: This study examined two populations. The first one consisted of 189 adult patients hospitalized at CHUM who received a courtesy phone call from a volunteer and the second one consisted of the 25 CHUM volunteers who made these calls. Quantitative data were collected from patients and volunteers through questionnaires and a Smartsheet. The patient questionnaire evaluated isolation, the courtesy phone calls, the relationship of trust with the volunteer and sociodemographic questions. The volunteer questionnaire evaluated the appropriateness of the technology for the intervention, the support and training received, the impacts of the courtesy phone call on both the patients and the volunteers, an experience report and sociodemographic information. In addition, a focus group was held with 7 volunteers. Then the verbatim were transcribed and analyzed using QDA miner software. RESULTS: From April 27, 2020 to September 5, 2020 more than 11,800 calls were made, mainly concerning hospitalization conditions or home follow-ups (n = 83), and relationships with relatives, friends, and family (n = 79). For 73.6% of hospitalized patients, the courtesy calls from volunteers were a good response to their needs, and 72% of volunteers agreed. 64.5% of patients felt less isolated and 40% of volunteers felt useful. CONCLUSION: Our data suggest that patients felt less isolated during their hospitalization because of the courtesy calls made by the volunteers, that smartphones could also be used for video calls and, finally, that maintaining this type of service seems as relevant after as during a pandemic to provide social interactions to people isolated for medical reasons.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".