diff --git a/xarray/core/indexing.py b/xarray/core/indexing.py
index 82ee4ccb0e4..92ace8573b8 100644
--- a/xarray/core/indexing.py
+++ b/xarray/core/indexing.py
@@ -1680,13 +1680,29 @@ def _convert_scalar(self, item):
         # a NumPy array.
         return to_0d_array(item)
 
-    def _oindex_get(self, indexer: OuterIndexer):
-        return self.__getitem__(indexer)
+    def _prepare_key(self, key: tuple[Any, ...]) -> tuple[Any, ...]:
+        if isinstance(key, tuple) and len(key) == 1:
+            # unpack key so it can index a pandas.Index object (pandas.Index
+            # objects don't like tuples)
+            (key,) = key
 
-    def _vindex_get(self, indexer: VectorizedIndexer):
-        return self.__getitem__(indexer)
+        return key
 
-    def __getitem__(
+    def _handle_result(
+        self, result: Any
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        if isinstance(result, pd.Index):
+            return type(self)(result, dtype=self.dtype)
+        else:
+            return self._convert_scalar(result)
+
+    def _get_item(
         self, indexer: ExplicitIndexer
     ) -> (
         PandasIndexingAdapter
@@ -1695,11 +1711,7 @@ def __getitem__(
         | np.datetime64
         | np.timedelta64
     ):
-        key = indexer.tuple
-        if isinstance(key, tuple) and len(key) == 1:
-            # unpack key so it can index a pandas.Index object (pandas.Index
-            # objects don't like tuples)
-            (key,) = key
+        key = self._prepare_key(indexer.tuple)
 
         if getattr(key, "ndim", 0) > 1:  # Return np-array if multidimensional
             indexable = NumpyIndexingAdapter(np.asarray(self))
@@ -1707,10 +1719,40 @@ def __getitem__(
 
         result = self.array[key]
 
-        if isinstance(result, pd.Index):
-            return type(self)(result, dtype=self.dtype)
-        else:
-            return self._convert_scalar(result)
+        return self._handle_result(result)
+
+    def _oindex_get(
+        self, indexer: OuterIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        return self._get_item(indexer)
+
+    def _vindex_get(
+        self, indexer: VectorizedIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        return self._get_item(indexer)
+
+    def __getitem__(
+        self, indexer: ExplicitIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        return self._get_item(indexer)
 
     def transpose(self, order) -> pd.Index:
         return self.array  # self.array should be always one-dimensional
@@ -1766,6 +1808,34 @@ def _convert_scalar(self, item):
             item = item[idx]
         return super()._convert_scalar(item)
 
+    def _oindex_get(
+        self, indexer: OuterIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        result = super()._oindex_get(indexer)
+        if isinstance(result, type(self)):
+            result.level = self.level
+        return result
+
+    def _vindex_get(
+        self, indexer: VectorizedIndexer
+    ) -> (
+        PandasIndexingAdapter
+        | NumpyIndexingAdapter
+        | np.ndarray
+        | np.datetime64
+        | np.timedelta64
+    ):
+        result = super()._vindex_get(indexer)
+        if isinstance(result, type(self)):
+            result.level = self.level
+        return result
+
     def __getitem__(self, indexer: ExplicitIndexer):
         result = super().__getitem__(indexer)
         if isinstance(result, type(self)):