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This will result in a "questionnaire_response_items" table that looks like this:

id questionnaire patient_id authored item_link_id item_text answer_value_string answer_value_integer answer_value_boolean answer_value_date
1 http://example.org/q/phq9 101 2024-03-15T10:30:00+10:00 q1 Little interest... null 2 null null
1 http://example.org/q/phq9 101 2024-03-15T10:30:00+10:00 q2 Feeling down... null 1 null null
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 demographics Demographics null null null null
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 name Full name John Smith null null null
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 dob Date of birth null null null 1980-05-22
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 conditions Medical conditions null null null null
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 diabetes Diabetes null null true null
2 http://example.org/q/health-history 102 2024-03-16T14:20:00+10:00 hypertension Hypertension null null false null
{:.table-data}

Note how all items are flattened into a single table regardless of their nesting depth. The "demographics" and "conditions" items are group items (with no answer values), while items like "name", "dob", "diabetes", and "hypertension" are nested within those groups but appear as separate rows in the output.