diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 5674c118f63d6..c5faa432cb494 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -107,7 +107,6 @@
     ensure_platform_int,
     infer_dtype_from_object,
     is_1d_only_ea_dtype,
-    is_1d_only_ea_obj,
     is_bool_dtype,
     is_dataclass,
     is_datetime64_any_dtype,
@@ -913,7 +912,7 @@ def _values(  # type: ignore[override]
         mgr = self._mgr
 
         if isinstance(mgr, ArrayManager):
-            if len(mgr.arrays) == 1 and not is_1d_only_ea_obj(mgr.arrays[0]):
+            if len(mgr.arrays) == 1 and not is_1d_only_ea_dtype(mgr.arrays[0].dtype):
                 # error: Item "ExtensionArray" of "Union[ndarray, ExtensionArray]"
                 # has no attribute "reshape"
                 return mgr.arrays[0].reshape(-1, 1)  # type: ignore[union-attr]
@@ -10050,7 +10049,7 @@ def func(values: np.ndarray):
 
         def blk_func(values, axis=1):
             if isinstance(values, ExtensionArray):
-                if not is_1d_only_ea_obj(values) and not isinstance(
+                if not is_1d_only_ea_dtype(values.dtype) and not isinstance(
                     self._mgr, ArrayManager
                 ):
                     return values._reduce(name, axis=1, skipna=skipna, **kwds)
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 467da586f604d..d4aa6ae9f4059 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -45,7 +45,7 @@
     ensure_float64,
     ensure_int64,
     ensure_platform_int,
-    is_1d_only_ea_obj,
+    is_1d_only_ea_dtype,
     is_bool_dtype,
     is_categorical_dtype,
     is_complex_dtype,
@@ -601,7 +601,7 @@ def cython_operation(
             raise NotImplementedError("number of dimensions is currently limited to 2")
         elif values.ndim == 2:
             assert axis == 1, axis
-        elif not is_1d_only_ea_obj(values):
+        elif not is_1d_only_ea_dtype(values.dtype):
             # Note: it is *not* the case that axis is always 0 for 1-dim values,
             #  as we can have 1D ExtensionArrays that we need to treat as 2D
             assert axis == 0
diff --git a/pandas/core/internals/concat.py b/pandas/core/internals/concat.py
index 50b12f5365964..991e4bbf4fbdb 100644
--- a/pandas/core/internals/concat.py
+++ b/pandas/core/internals/concat.py
@@ -27,7 +27,6 @@
 )
 from pandas.core.dtypes.common import (
     is_1d_only_ea_dtype,
-    is_1d_only_ea_obj,
     is_datetime64tz_dtype,
     is_dtype_equal,
 )
@@ -478,7 +477,7 @@ def _concatenate_join_units(join_units: list[JoinUnit], copy: bool) -> ArrayLike
             else:
                 concat_values = concat_values.copy()
 
-    elif any(is_1d_only_ea_obj(t) for t in to_concat):
+    elif any(is_1d_only_ea_dtype(t.dtype) for t in to_concat):
         # TODO(EA2D): special case not needed if all EAs used HybridBlocks
         # NB: we are still assuming here that Hybrid blocks have shape (1, N)
         # concatting with at least one EA means we are concatting a single column
@@ -487,7 +486,9 @@ def _concatenate_join_units(join_units: list[JoinUnit], copy: bool) -> ArrayLike
         # error: No overload variant of "__getitem__" of "ExtensionArray" matches
         # argument type "Tuple[int, slice]"
         to_concat = [
-            t if is_1d_only_ea_obj(t) else t[0, :]  # type: ignore[call-overload]
+            t
+            if is_1d_only_ea_dtype(t.dtype)
+            else t[0, :]  # type: ignore[call-overload]
             for t in to_concat
         ]
         concat_values = concat_compat(to_concat, axis=0, ea_compat_axis=True)