3.2 Knowledge, Attitude, and Practices of Respondents
Table 1 shows the knowledge of participants regarding COVID-19. About 89.7% of respondents provided the correct answer with a score of 17.9 (SD=0.08). Questions about general COVID-19 knowledge received 91.6% accurate responses, while questions concerning food safety received 87.9% correct answers. Workers had sufficient knowledge on most of the issues. But when it came to the survival and destruction condition of the coronavirus, they seemed to have some problems. Whether the virus can survive at freezing temperatures or whether UV can kill it got less than 80% correct responses. About two in ten workers failed to answer comorbidity risk or zoonoses questions and were not sure if there is any registered medication available in the market.
The results related to the attitude are summarized in Table 2 . With an excellent 9.3 (SD=0.04) score, more than 90% of people showed a positive attitude towards different issues of COVID-19. More than a few of 10% of participants didn’t think that they could get affected while working, while almost the same number of people were not interested in training on COVID-19. Nearly 13% didn’t believe that washing one’s hands for a minimum of 20 seconds was required.
Like knowledge and attitude, the respondents from the food industry’s practices also showed desirable outcomes (Table 3 ). On average, about 88% of workers maintained commendable and appropriate practices during the pandemic. However, some issues, like staying away from crowded places, not touching eyes, nose, or mouth during food handling, and avoiding frequent use of public transportation, were not regularly practiced by nearly 20% of the workers.
Table 1. Knowledge of respondents regarding COVID-19.
Table 2. Attitude of respondents towards COVID-19.
Table 3. Practices of respondents during COVID-19.
Scores on knowledge, attitude, and practices have been tested by different demographic characteristics, i.e., gender, age group, education, experience, field of work in current company, and source of information on COVID-19 (Table 4 ). The null hypothesis of the Mann‐Whitney U and the Wilcoxon test stipulates that each group’s distribution was the same. In the case of knowledge, all demographic characteristics showed significant differences in central tendencies for each distribution. When it comes to attitude, all demographic characteristics other than the job area showed significant differences. Education was the only factor that showed a significant difference in the test for practices score. Therefore, the demographic characteristics lead to varying the individual score, while education possesses significant results in all three KAP elements.
Other than the individual score on KAP elements, in the regression model, we have determined underlying factors that enhanced the total KAP score. The R-square value indicates the global check for the model that the model explains 81.2% of the variance in total score on knowledge, attitude, and practices (Table 5 ). F value is very close to zero, which indicates that the regression model is statistically significant and predicts the outcome variable. In this regression model, education and experience significantly associate the knowledge and practices of COVID-19 among the food industry workers. Age, gender, and field of work have no significant association with the knowledge, attitude, and practices towards COVID-19. Those attending primary school have 7.4 times more knowledge of COVID-19 in comparison to those who did not attend school, and it is 6.9 times higher among the high school attending employees, 7.4 times more for those with a university degree, and a slightly lower 6.7 times higher among the technical education holders in comparison to the non-school-attending participants. Experience is also statistically significant at a 5% level of confidence, but unexpectedly the coefficient is negative in value, although very minimal. That shows that those in the profession who are younger are more cautious or knowledgeable about COVID-19 than the older employees.
Table 4. Differences in KAP scores according to the demographic characteristics.
Table 5. Regression of total KAP scores.