Patient Engagement With and Perceptions of the COVIDA Project, a Volunteer-Led Telemonitoring and Teleorientation Service for COVID-19 Community Management: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: During the pandemic in Peru, the COVIDA (Collaboration Network of Volunteer Brigade Members for the Investigation, Detection, and Primary Management of Community Cases Affected by COVID-19) project proposed an innovative way to provide telemonitoring and teleorientation to COVID-19 patients, led by health care student volunteers. However, it has not been described how this interaction is perceived from the patient's perspective and which factors increase their engagement with this service. OBJECTIVE: The aim of this study is to describe the perceptions of patients about COVIDA and identify factors associated with their engagement with this service. METHODS: A mixed methods study was conducted to evaluate perceptions of patients that participated in the COVIDA project. This telehealth intervention organized by the National University of San Marcos was implemented in Peru from August to December 2020. The service involved daily phone calls by volunteer students to monitor registered COVID-19 patients until the completion of the 14th day of the illness or if a warning sign was identified. The volunteers also provided teleorientation to address the patients' needs and concerns. Quantitative analysis was performed to describe the characteristics of the patients and to assess the factors related to their engagement with the service, which was defined by the percentage of participants who completed the follow-up according to their individual schedule. Qualitative analysis through semistructured interviews evaluated the patients' perceptions of the service regarding the aspects of communication, interaction, and technology. RESULTS: Of the 770 patients enrolled in COVIDA, 422 (55.7%) were female; the median age was 39 (IQR 28-52) years. During the monitoring, 380 patients (49.4%) developed symptoms, and 471 (61.2%) showed warning signs of COVID-19. The overall median for engagement was 93% (IQR 35.7%-100%). Among those patients who did not develop warning signs, engagement was associated with the presence of symptoms (OR 3.04, 95% CI 2.22-4.17), a positive COVID-19 test at the start of follow-up (OR 1.97, 95% CI 1.48-2.61), and the presence of comorbidities (OR 1.83, 95% CI 1.29-2.59). Patients reported that the volunteers provided clear and valuable information and emotional support. Communication via phone calls took place smoothly and without interruptions. CONCLUSIONS: COVIDA represents a well-accepted and well-perceived alternative model for student volunteers to provide telemonitoring, teleorientation, and emotional support to patients with COVID-19 in the context of overwhelmed demand for health care services. The deployment of this kind of intervention should be prioritized among patients with symptoms and comorbidities, as they show more engagement with these services.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".