Answer:
The p-value of the test is of 0.1922 > 0.02, which means that there is not significant evidence to reject the null hypothesis, that is, there is not significant evidence to conclude that the proportion is of less than 40%.
Step-by-step explanation:
Test if the proportion is less than 40%:
At the null hypothesis, we test if the proportion is of at least 0.4, that is:

At the alternative hypothesis, we test if the proportion is of less than 0.4, that is:

The test statistic is:
In which X is the sample mean,
is the value tested at the null hypothesis,
is the standard deviation and n is the size of the sample.
0.4 is tested at the null hypothesis:
This means that 
74 out of the 200 workers sampled said they would return to work
This means that 
Value of the test statistic:

P-value of the test and decision:
The p-value of the test is the probability of finding a sample proportion below 0.37, which is the p-value of z = -0.87.
Looking at the z-table, z = -0.87 has a p-value of 0.1922.
The p-value of the test is of 0.1922 > 0.02, which means that there is not significant evidence to reject the null hypothesis, that is, there is not significant evidence to conclude that the proportion is of less than 40%.