Nursing care for hospitalized patients with COVID-19 in light of Fundamental Care
Bibliographic record
Abstract
OBJECTIVES: to analyze how the COVID-19 pandemic affected the Fundamental Care provided by nurses to hospitalized patients in a public hospital. METHODS: qualitative, descriptive, exploratory research. Twenty-four nurses were interviewed who cared for patients with COVID-19 in a public hospital in the capital city of the state of Paraná, from January to February 2022. Creswell Content Analysis was applied to the data, operationalized by the MaxQda software and in light of the Fundamental Care theory. RESULTS: three categories were obtained with their respective dimensions: Physical Care (Personal Hygiene; Comfort and Mobilization; Eating and drinking; Rest and sleep; Safety and Medication Management), Psychosocial Care (Communication; Privacy; Dignity, respect and beliefs; Emotional well-being) and Relational Care (Active listening; Empathy and compassion; Engagement, support and involvement with families and caregivers and work with patients). FINAL CONSIDERATIONS: the pandemic period may have provided an opportunity to look at the nurse-patient-care relationship, especially based on the theory of Fundamental Care.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".