diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index d80c80fa5d0ab..dbbe2c0751f3a 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4757,6 +4757,14 @@ def insert(
         if not isinstance(loc, int):
             raise TypeError("loc must be int")
 
+        if isinstance(value, DataFrame) and len(value.columns) > 1:
+            raise ValueError(
+                f"Expected a one-dimensional object, got a DataFrame with "
+                f"{len(value.columns)} columns instead."
+            )
+        elif isinstance(value, DataFrame):
+            value = value.iloc[:, 0]
+
         value = self._sanitize_column(value)
         self._mgr.insert(loc, column, value)
 
@@ -4843,11 +4851,9 @@ def _sanitize_column(self, value) -> ArrayLike:
         """
         self._ensure_valid_index(value)
 
-        # We can get there through isetitem with a DataFrame
-        # or through loc single_block_path
-        if isinstance(value, DataFrame):
-            return _reindex_for_setitem(value, self.index)
-        elif is_dict_like(value):
+        # Using a DataFrame would mean coercing values to one dtype
+        assert not isinstance(value, DataFrame)
+        if is_dict_like(value):
             return _reindex_for_setitem(Series(value), self.index)
 
         if is_list_like(value):
diff --git a/pandas/tests/frame/indexing/test_insert.py b/pandas/tests/frame/indexing/test_insert.py
index d084f841f9e19..5d0a51ea0d462 100644
--- a/pandas/tests/frame/indexing/test_insert.py
+++ b/pandas/tests/frame/indexing/test_insert.py
@@ -100,6 +100,8 @@ def test_insert_frame(self):
         # GH#42403
         df = DataFrame({"col1": [1, 2], "col2": [3, 4]})
 
-        msg = r"Expected a 1D array, got an array with shape \(2, 2\)"
+        msg = (
+            "Expected a one-dimensional object, got a DataFrame with 2 columns instead."
+        )
         with pytest.raises(ValueError, match=msg):
             df.insert(1, "newcol", df)