The following algorithm is to search for a specific user's data in a database and update it if certain conditions are met. The algorithm works as follows:

The database is represented as a list of records, where each record contains a user ID$,$ a timestamp, and a status.

The algorithm searches for a particular user ID$.$

If the user's record is found and the timestamp is within the last $30$ days, the algorithm updates the status to "Active."

If no record is found for the user, it appends a new record for the user with the current timestamp and sets the status to "Active."

UpdateUserStatus$($database$,$ userID, currentTimestamp$)$:

found $=$ False

for each record in database:

if record.userID $=$ userID:

found $=$ True

if currentTimestamp $-$ record.timestamp $<=30$:

record.status $=$ "Active"

break

if found $=$ False:

newRecord $=$ CreateRecord$($userID$,$ currentTimestamp, "Active"$)$

database.append$($newRecord$)$

Analyze the time complexity of the given algorithm. Your analysis should:

Identify the key operations in the algorithm.

Calculate the worst$-$case time complexity of the algorithm in terms of $$n$,$ where $$n$$ is the number of records in the database.

Justify whether this algorithm is efficient for large databases.