COVID-19 pandemic through the eyes of general nurses in the South Bohemian Region: a qualitative study
Bibliographic record
Abstract
E -manuscript Preparation, F -literature Search, G -Funds CollectionBackground. the CoViD-19 pandemic brought about significant changes for healthcare professionals, which led to a new situation and challenges in patient care.Objectives. the aim of this study was to examine the opinion and experiences of general nurses in the South bohemian region of the Czech republic on the impact of the CoViD-19 pandemic.Material and methods.to meet this goal, qualitative research was chosen in the form of semi-structured interviews with 15 nurses across the healthcare system in the South bohemian region in the Czech republic.the research was carried out from 1.6.2021-30.9.2021.Data analysis was carried out using the embedded theory.Results. the central category was "nurse".related categories were identified as a pandemic, nurse personality, nurse's job description, the impact of the pandemic, mental hygiene, information and media, patient responses, professional demands, the functioning of health and healthcare facilities, the future and pandemics.the pandemic had a positive and negative impact on all these categories.the positive impact was connected mainly with the development of skills and the competence of nurses.the negative effect was primarily associated with stress, rapid changes in practice, doubt about knowledge and skills and fear.Conclusions.interviews with nurses showed that for effective management of the increased burden placed on nurses during a pandemic, it is essential in the future to pay attention to the saturation of the basic, lower and higher needs of nurses.the importance of support in work, family and social life, access to quality information and the opportunity to expand knowledge and skills was also evident.
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 | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".