Impact of the COVID-19 Pandemic on the Experiences of Hospitalized Patients: A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: This study aimed to identify the factors that exerted an impact on the experiences of hospitalized patients during the COVID-19 pandemic from the quality and safety perspectives. METHOD: A scoping review that followed the 5 stages described by Arksey and O'Malley was used. A systematized search of original studies was conducted in 9 databases: PubMed/MEDLINE, BDENF, CINAHL, LILACS, SciELO, Embase, Scopus, Web of Science, and Google Scholar. The factors that exerted an impact on patients' experiences were summarized, considering the perspective of quality and patient safety in health institutions. The factors were categorized using the Content Analysis technique. RESULTS: A total of 6950 studies were screened, and 32 met the eligibility criteria. The main factors that exerted an impact on the patients' experience were as follows: caregiver/family concern with the patients' well-being during hospitalization, search for alternative communication and interaction means between the patients and their family, and changes in health care organization. The restrictions inherent to the policy regarding visits and companions exerted a negative impact on the experiences, increasing the patients' feelings of loneliness and isolation. Negative impacts were also evidenced in the hospital admission and discharge process and in the limitation of treatment possibilities offered to the patients, because of contact restrictions. CONCLUSIONS: The factors that exerted an impact on the patients' experiences permeate communication between professionals, patients, and family members, with implications for health care quality.
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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 | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it