The Effect of the Knowledge, Attitude, and Behavior of Workers Regarding COVID-19 Precautionary Measures on Food Safety at Foodservice Establishments in Jordan
Bibliographic record
Abstract
The novel coronavirus (COVID-19) pandemic has caused sequential ripples of public health concern worldwide. Restaurant owners and workers have been significantly affected by safety regulations which have governed the activities of both employees and consumers. The objective of this study was to investigate the knowledge, attitude, and practices (KAP) of restaurant owners and workers in the context of COVID-19 and assess the effect of COVID-19 precautions on the implementation of food safety measures at foodservice establishments in Jordan. A cross-sectional survey was conducted that involved 605 participants from 91 restaurants and catering establishments in Jordan. The questionnaire was filled out during a face-to-face interview or via online platforms. Most (77%) of the respondents were male and under 35 years old (79%), with 42% of them having a high educational level (bachelor’s degree or postgraduate studies) and 46% having 1–5 years of work experience. It was found that only 20% of workers possessed good knowledge (scores above 75%), 56% had positive attitudes, and 55% had good practices, with a mean of 47% being compliant with the KAP levels expected. In total, 19 to 34% of participants observed that the precautions and preventive measures put in place during the pandemic improved the application of key food safety regulations within their workplaces. It is evident that more training is required for both employees and employers to ensure the effective implementation of the regulations required to prevent the spread of COVID-19 and food-borne pathogens via the application of good hygienic practices that improve food safety, reducing illnesses and food waste while maintaining food security and economic sustainability.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".