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.