Psychological Stress on Nursing Community in the Face of the COVID-19 Pandemic
Bibliographic record
Abstract
Healthcare became priority due to COVID-19 pandemic. The role of healthcare workers like nurses in serving COVID-19 patients is exuberant. They have direct contact with COVID-19 patients and must spend longer hours in and around the patients. The way nurses rendered services under extreme lockdown conditions is quite palpable. They do have lot of stress in discharging duties during the pandemic. This paper addresses the challenges and issues of nurses serving COVID-19 patients and provides measures to overcome stress during the pandemic. The study is empirical and descriptive in nature. Afraid of viral infection, longer shifts, heavy workload, inadequate PPE, social stigma, maintaining social distance with loved ones of family members, relatives, and friends, lack of appreciation and recognition from the doctors, helplessness towards colleagues, and lack of awareness of safety protocols among COVID-19 positive patients caused psychological stress among nurses. They have adapted a coping mechanism with belief in God.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".