The impact of COVID‐19 on patient engagement in the health system: Results from a Pan‐Canadian survey of patient, family and caregiver partners
Bibliographic record
Abstract
INTRODUCTION: The COVID-19 pandemic has had an impact on all aspects of the health system. Little is known about how the activities and experiences of patient, family and caregiver partners, as a large group across a variety of settings within the health system, changed due to the substantial health system shifts catalysed by the pandemic. This paper reports on the results of a survey that included questions about this topic. METHODS: Canadian patient, family and caregiver partners were invited to participate in an online anonymous survey in the Fall of 2020. A virtual snowballing approach to recruitment was used. Survey invitations were shared on social media and emailed to health system and governmental organizations with the request that they share the survey with patient partners. This paper focuses on responses to two questions related to patient partner experiences during the COVID-19 pandemic. RESULTS: The COVID-19 questions were completed by 533 respondents. Over three quarters of respondents (77.9%, n = 415) indicated their patient engagement activities had been impacted by COVID-19. The majority (62.5%, n = 230) experienced at least a temporary or partial reduction in their patient engagement activities. Some respondents did see increases in their patient engagement activities (11.4%, n = 42). Many respondents provided insights into their experience with virtual platforms for engagement (n = 194), most expressed negative or mixed experiences with this shift. CONCLUSIONS: This study provides a snapshot of Canadian patient, family and caregiver partners' perspectives on the impact of COVID-19 on their engagement activities. Understanding how engagement unfolded during a crisis is critical for our future planning if patient engagement is to be fully integrated into the health system. Identifying how patient partners were engaged and not engaged during this time period, as well as the benefits and challenges of virtual engagement opportunities, offers instructive lessons for sustaining patient engagement, including the supports needed to engage with a more diverse set of patient, family and caregiver partners. PATIENT CONTRIBUTION: Patient partners were important members of the Canadian Patient Partner Study research team. They were engaged from the outset, participating in all stages of the research project. Additional patient partners were engaged to develop and pilot test the survey, and all survey respondents were patient, family or caregiver partners. The manuscript is coauthored by two patient partners.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".