Preparedness, Risk Perception, Concerns, and Risk Acceptance Among Hospital Health Care Workers in Facing the Emerging COVID-19 Outbreak in Najran Hospitals, Saudi Arabia, at the Early Phase of the Pandemic
Bibliographic record
Abstract
Background The COVID-19 pandemic extended to reach most countries in the world during a few months. The preparedness of health care institutions and health care workers (HCWs) is crucial for applying effective prevention and control measures. Objective This study aims to assess HCWs’ and institutional preparedness in facing the new emerging COVID-19 infection at the early phase of the pandemic and to explore HCWs’ risk perception, concerns, and risk acceptance. Methods A cross-sectional survey was conducted among hospital HCWs in King Khalid and New Najran hospitals, Saudi Arabia, at the early phase of the pandemic, during March and April 2020. Results Overall, 563 completed questionnaires were received (n=382, 67.9% from King Khalid and n=181, 32.1% from New Najran). The majority were female participants (78.6%); nurses constituted 74.7% of the sample. The age range of the participants was 20-63 years, with the mean age of physicians and nurses being 36.5 (SD 9.15) years and 31.8 (SD 7.48) years, respectively. Among participants, 65.8% attended training programs for COVID-19 infection, of whom 69.9% were satisfied with this training. Almost all (97.4%) of the participants reported reading the official circulars assigned for guidelines, case definition, and infection control measures regarding COVID-19 infection; 97.1% received basic infection control training; 98.9% checked for the best-fitted size of an N95 mask; and 89.4% were influenza vaccinated. Of the participants, 82.6% reported that they have sufficient knowledge about the COVID-19 pandemic, 82.0% reported being confident that they can protect themselves and their patients when dealing with COVID-19 cases, 92.9% reported that they understand the risk of COVID-19 infection for patients and health care staff, and 83.2% reported agreement of accepting the risk of getting the infection being a part of their job. The study participants attained a mean 20.26 (SD 2.60) knowledge score on a scale of 26 maximum points (77.9%); of them, 74.5% attained 20 points or more (>75%), indicating good working knowledge about the COVID-19 pandemic. Exploring the participants’ perception about the preparedness of their institutions toward the COVID-19 pandemic, 70.8% agreed that institutional precautionary measures to COVID-19 in the workplace are sufficient, 71.6% agreed that all personal protective equipment is provided and always available in the workplace, and 90.6% mentioned that the staff in their institutions have had adequate training. Exploring risk perception and the affective aspect of the pandemic on HCWs, 79.0%, 35.2%, and 64.2% of the participants felt that they, their families, and the Najran community are at high risk of getting an infection of COVID-19, respectively, and 54.7% and 55.1% were concerned about their personal and family health, respectively. Conclusions The findings revealed good knowledge about the COVID-19 pandemic among HCWs in Najran hospitals, Saudi Arabia. Concerns and worries were expressed regarding working with the highly infectious patients with COVID-19. Participants appreciated important aspects of institutional preparedness. Experience gained from the previous Middle East respiratory syndrome–related coronavirus outbreak may explain good knowledge, risk acceptance, self-efficacy, and good and rapid institutional preparedness at the early stage of the pandemic.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".