The meaning of dignity in care during the COVID-19 pandemic: a qualitative study in acute and intensive care
Bibliographic record
Abstract
BACKGROUND: The pandemic Era has forced palliative care professionals to use a dignity-in-care approach in different settings from the classic ones of palliative care: acute and intensive care. We explored the meanings of dignity for patients, their family members, and clinicians who have experienced COVID-19 in the acute and intensive care setting. METHODS: A qualitative, prospective study by means of semi-structured interviews with patients hospitalized for COVID-19, family members, and clinicians who care for them. FINDINGS: Between March 2021 and October 2021, we interviewed 16 participants: five physicians, three nurses, and eight patients. None of the patients interviewed consented for family members to participate: they considered it important to protect them from bringing the painful memory back to the period of their hospitalization. Several concepts and themes arose from the interviews: humanity, reciprocity, connectedness, and relationship, as confirmed by the literature. Interestingly, both healthcare professionals and patients expressed the value of informing and being informed about clinical conditions and uncertainties to protect dignity. CONCLUSIONS: Dignity should be enhanced by all healthcare professionals, not only those in palliative care or end-of-life but also in emergency departments.
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 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 | 0.020 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.019 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".