Communication With Older Adults in Times of a Pandemic: Practical Suggestions for the Health Care Professionals
Bibliographic record
Abstract
In order to limit the spread of the coronavirus, several protective measures have been put in place in the community, in private and public residences and in health care centers. Some measures have a negative impact on communication. They include physical distancing, the use of face masks and shields as well as the increased use of telephone and videoconferencing for distance communication. The effects of COVID-19 are particularly harsh on older adults. Consequently, older adults, especially those with hearing loss, are particularly at risk of experiencing communication breakdowns and increased social isolation. Health care professionals should learn about and be encouraged to use communication strategies to maintain good interactions with their patients. This article proposes practical suggestions to health professionals who interact with older adults, especially those who have difficulty understanding speech. The goal of this article is to inform on the prevalence of hearing loss, the hearing difficulties experienced by older adults, the manifestations of hearing problems, the effects of pandemic protection measures on communication and the strategies that can be used to optimize professional-patient communication during a pandemic.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".