Better approach for "LIKE OR LIKE, OR LIKE, OR LIKE, OR LIKE"
Full text indexes generally aren't a magic bullet, and require additional maintenance, disk space, and fairly intrusive changes to query patterns. 

Unless you're truly in need of indexing large documents (think email bodies, PDFs, Word docs, etc.), they're overkill (and if we're being honest, I'd take that process out of SQL Server entirely and use Elasticsearch or something similar).

For smaller use-cases, computed columns are generally a better approach.

Here's a quick demo setup:

use tempdb

CREATE TABLE #fulltextindexesarestupid (Id INT PRIMARY KEY CLUSTERED, StopAbusingFeatures VARCHAR(100))

INSERT #fulltextindexesarestupid (Id)
SELECT TOP 1000000 ROW_NUMBER() OVER (ORDER BY (@@ROWCOUNT))
FROM sys.messages AS m
CROSS JOIN sys.messages AS m2

UPDATE #fulltextindexesarestupid
SET StopAbusingFeatures = CASE WHEN Id % 15 = 0 THEN 'Bad'
                               WHEN Id % 3 = 0 THEN 'Idea'
                               WHEN Id % 5 = 0 THEN 'Jeans'
                               END


ALTER TABLE #fulltextindexesarestupid 
ADD LessBad AS CONVERT(BIT, CASE WHEN StopAbusingFeatures LIKE '%Bad%' THEN 1
                    WHEN StopAbusingFeatures LIKE '%Idea%' THEN 1
                    ELSE 0 END)

CREATE UNIQUE NONCLUSTERED INDEX ix_whatever ON #fulltextindexesarestupid (LessBad, Id)


Querying based on even a non-persisted column gives us a plan that 'uses indexes' and everything :)

SELECT COUNT(*)
FROM #fulltextindexesarestupid AS f
WHERE LessBad = 1