Answer:
1. Inclusive bias
2. Over-estimated
Step-by-step explanation:
Inclusive bias involves selecting samples for convenience. This occurs in situations where for instance, the volunteer group is the only group available.
Results including this type of bias, cannot be interpreted to fit into an entire population and should only be limited to the narrowed down demographic range provided by the bias.
The association between diabetes and smoking in this study, is likely to be over-estimated as the employees are guided by rules set by the hospital and are controlled by them. This rule could involve prohibiting smoking at work and while running long shifts, employees may not get breaks to smoke. On the other hand, patients don't get to be controlled by the hospital and are much freer to lead their lives as they deem fit.