The Impact of COVID-19 on Older Adults’ Perceptions of Virtual Care: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: In response to the COVID-19 pandemic, older adults worldwide have increasingly received health care virtually, and health care organizations and professional bodies have indicated that virtual care is "here to stay." As older adults are the highest users of the health care system, virtual care implementation can have a significant impact on them and may pose a need for additional support. OBJECTIVE: This research aims to understand older adults' perspectives and experiences of virtual care during the pandemic. METHODS: As part of a larger study on older adults' technology use during the pandemic, we conducted semistructured interviews with 20 diverse older Canadians (mean age 76.9 years, SD 6.5) at 2 points: summer of 2020 and winter/early spring of 2021. Participants were asked about their technology skills, experiences with virtual appointments, and perspectives on this type of care delivery. Interviews were digitally recorded and transcribed. A combination of team-based and framework analyses was used to interpret the data. RESULTS: Participants described their experiences with both in-person and virtual care during the pandemic, including issues with accessing care and long gaps between appointments. Overall, participants were generally satisfied with the virtual care they received during the pandemic. Participants described the benefits of virtual care (eg, increased convenience, efficiency, and safety), the limitations of virtual care (eg, need for physical examination and touch, lack of nonverbal communication, difficulties using technology, and systemic barriers in access), and their perspectives on the future of virtual care. Half of our participants preferred a return to in-person care after the COVID-19 pandemic, while the other half preferred a combination of in-person and virtual services. Many participants who preferred to access in-person services were not opposed to virtual care options, as needed; however, they wanted virtual care as an option alongside in-person care. Participants emphasized a need for training and support to be meaningfully implemented to support both older adults and providers in using virtual care. CONCLUSIONS: Overall, our research identified both perceived benefits and perceived limitations of virtual care, and older adult participants emphasized their wish for a hybrid model of virtual care, in which virtual care is viewed as an addendum, not a replacement for in-person care. We recognize the limitations of our sample (small, not representative of all older Canadians, and more likely to use technology); this body of literature would greatly benefit from more research with older adults who do not/cannot use technology to receive care. Findings from this study can be mobilized as part of broader efforts to support older patients and providers engaged in virtual and in-person care, particularly post-COVID-19.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".