Perception of the COVID-19 Pandemic Among Members of Saudi Society: Solidarity, Humility, and Connectivity
Bibliographic record
Abstract
Background and purpose The magnitude of the coronavirus disease 2019 (COVID-19) pandemic on the healthcare system, economy, education, and social networking is dreadful, the least to say. Surprisingly, and unlike previous epidemics, the impact has been universal, and even top-ranking countries with solid economies were not immune. The purpose of this study is to develop a better understanding of the Saudi community's response and reaction to the preventative measures implemented by the government to combat the COVID-19 pandemic. Methodology A cross-sectional study using a self-administered online-based questionnaire was conducted among 920 participants from March 2020 to February 2021 among the Saudi community across the Kingdom. Results Among the studied participants, the majority (60%) are always committed to washing their hands according to the Ministry of Health (MoH) instructions, and 74% indicated that they were always compliant with the sneezing etiquette outlined by the MoH. Studied participants were affected through different influencers of life aspects. Moreover, 63% of them gained new skills and behaviors during the pandemic curfew. Additionally, many studied participants assumed that "life will not return to what it used to be" as a future perception. Conclusion In conclusion, the present findings proved the importance and power of the Saudi Vision (2030) represented by the National Transformation Program on enhancing the healthcare system, facilitating access to healthcare, and integrating technology among government parties addressed during the COVID-19 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".