Impact of pandemic by covid-19 on portuguese rehabilitation nurses
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has had a significant global impact on health and socioeconomic status. At the same time, it has caused an overload on health systems and their professionals, including rehabilitation nurses. The real expression of this impact at the level of rehabilitation nurses is unknown. Objective: To assess the impact of the COVID19 pandemic on Portuguese rehabilitation nurses. Method: Observational, descriptive and cross-sectional study, with a non-probabilistic sample of Portuguese rehabilitation nurses who performed functions in any type of service in the three months prior to data collection. Data collection took place at the beginning of the third quarter of 2020 through an online questionnaire provided by email. Results: Sample consisting of 146 nurses specialized in Rehabilitation Nursing (EEER), of which 31% (n = 45) had to cease providing specialized care during the pandemic (increase of 2.7x). Regarding satisfaction with the quality of care provided, the average before the start of the pandemic was 3.95 (SD ± 0.75) and during the pandemic it dropped to 2.9 (SD ± 1.11) (scale of 5-point Likert). Of the participants. 73.3% (n = 107) refer that they had, at some point, to follow institutional guidelines in disagreement with their ethical and deontological principles, with 69.9% (n = 102) reporting having had a need, at least a situation, to prioritize which sick people to care for. During the pandemic, the EEER relied on expert colleagues and online resources to increase knowledge and skills regarding the care inherent in the pandemic. Conclusion: During the first pandemic peak by COVID 19, a significant part of the EEERs had to ensure only general care. The main challenges faced by EEER were in the field of organization and management of care due to the greater complexity of patients, the greater bureaucratic burden, changes in the relationship with co-workers and the need to balance professional and personal life. There was a decrease in satisfaction with the quality of care provided, as well as a high percentage of EEER who experienced ethical and deontological challenges. In order to ensure their continuous training and to update their skills and guarantee the quality and safety of nursing care, the EEERs have shown dynamism and a willingness to use information and communication technologies.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".