diff --git a/doc/source/user_guide/boolean.rst b/doc/source/user_guide/boolean.rst
index 3c361d4de17e5..7de0430123fd2 100644
--- a/doc/source/user_guide/boolean.rst
+++ b/doc/source/user_guide/boolean.rst
@@ -37,6 +37,19 @@ If you would prefer to keep the ``NA`` values you can manually fill them with ``
 
    s[mask.fillna(True)]
 
+If you create a column of ``NA`` values (for example to fill them later)
+with ``df['new_col'] = pd.NA``, the ``dtype`` would be set to ``object`` in the
+new column. The performance on this column will be worse than with
+the appropriate type. It's better to use
+``df['new_col'] = pd.Series(pd.NA, dtype="boolean")``
+(or another ``dtype`` that supports ``NA``).
+
+.. ipython:: python
+
+   df = pd.DataFrame()
+   df['objects'] = pd.NA
+   df.dtypes
+
 .. _boolean.kleene:
 
 Kleene logical operations
diff --git a/doc/source/user_guide/integer_na.rst b/doc/source/user_guide/integer_na.rst
index 1a727cd78af09..76a2f22b7987d 100644
--- a/doc/source/user_guide/integer_na.rst
+++ b/doc/source/user_guide/integer_na.rst
@@ -84,6 +84,19 @@ with the dtype.
    In the future, we may provide an option for :class:`Series` to infer a
    nullable-integer dtype.
 
+If you create a column of ``NA`` values (for example to fill them later)
+with ``df['new_col'] = pd.NA``, the ``dtype`` would be set to ``object`` in the
+new column. The performance on this column will be worse than with
+the appropriate type. It's better to use
+``df['new_col'] = pd.Series(pd.NA, dtype="Int64")``
+(or another ``dtype`` that supports ``NA``).
+
+.. ipython:: python
+
+   df = pd.DataFrame()
+   df['objects'] = pd.NA
+   df.dtypes
+
 Operations
 ----------