To ensure clarity and manageability in survey programming, what should be done with multiple conditions in logic?

Separating multiple conditions using new logic sets is an effective strategy for ensuring clarity and manageability in survey programming. By creating distinct logic sets for different conditions, you can help maintain a clear structure in your survey logic. This means that each logic set operates independently, allowing you to troubleshoot or adjust one set without inadvertently affecting another. This separation reduces complexity, making it easier for survey developers and analysts to understand how different conditions interact and ensuring that the logic flows logically.

For instance, if multiple conditions are all mixed together within a single logic set, it can lead to confusion about how the various conditions are interrelated. When they are separated, it's simpler to visualize and follow the survey's branching paths. This approach aids in maintaining a clear overview, which is especially important in large, complex surveys where many conditions might exist.

While the other options, such as using descriptive titles or utilizing nested conditions, can contribute to clarity in their own right, they do not offer the same level of structural clarity that separating conditions into new logic sets provides. Grouping conditions logically may also help, but without separate logic sets, the logic can still become entangled and complex. Thus, choosing to separate them is the most effective method for achieving clarity and manageability.