diff --git a/exploration/expl_esm.py b/exploration/expl_esm.py
index 6934b58..9cfd90f 100644
--- a/exploration/expl_esm.py
+++ b/exploration/expl_esm.py
@@ -61,7 +61,7 @@ df_esm_preprocessed.columns
 # One approach would be to count distinct session IDs which are incremented for each group of EMAs. However, since not every question answered counts as a fulfilled EMA, some unique session IDs should be eliminated first.
 
 # %%
-session_counts = df_esm_preprocessed.groupby(["participant_id", "esm_session"]).count()[
+session_counts = df_esm_preprocessed.groupby(["participant_id", "device_id", "esm_session"]).count()[
     "id"
 ]
 
@@ -82,7 +82,7 @@ df_session_counts = pd.DataFrame(session_counts).rename(
 )
 df_session_1 = df_session_counts[(df_session_counts["esm_session_count"] == 1)]
 df_esm_unique_session = df_session_1.join(
-    df_esm_preprocessed.set_index(["participant_id", "esm_session"])
+    df_esm_preprocessed.set_index(["participant_id", "device_id", "esm_session"])
 )
 
 # %%
@@ -141,6 +141,13 @@ df_esm_preprocessed.query("participant_id == 31 & esm_session == 77")[
     ["esm_trigger", "esm_instructions", "esm_user_answer"]
 ]
 
+# %%
+df_esm_2 = df_session_counts[
+    df_session_counts["esm_session_count"] == 2
+].reset_index().merge(df_esm_preprocessed, how="left", on=["participant_id", "device_id", "esm_session"])
+with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also
+    display(df_esm_2)
+
 # %% [markdown]
 # ### Long sessions
 
@@ -208,7 +215,7 @@ df_session_counts.count()
 # %%
 non_session = session_group_by.apply(
     lambda x: (
-        (x.esm_user_answer == "DayFinished3421") | (x.esm_user_answer == "DayOff3421")
+        (x.esm_user_answer == "DayFinished3421") | (x.esm_user_answer == "DayOff3421") | (x.esm_user_answer == "DayFinishedSetEvening")
     ).any()
 )
 df_session_counts.loc[non_session, "session_response"] = "day_finished"
diff --git a/features/esm.py b/features/esm.py
index fc43581..3263b31 100644
--- a/features/esm.py
+++ b/features/esm.py
@@ -89,8 +89,9 @@ def classify_sessions_adherence(df_esm_preprocessed: pd.DataFrame) -> pd.DataFra
 
     non_session = sessions_grouped.apply(
         lambda x: (
-            (x.esm_user_answer == "DayFinished3421")
-            | (x.esm_user_answer == "DayOff3421")
+            (x.esm_user_answer == "DayFinished3421")  # I finished working for today.
+            | (x.esm_user_answer == "DayOff3421")  # I am not going to work today.
+            | (x.esm_user_answer == "DayFinishedSetEvening")  # When would you like to answer the evening EMA?
         ).any()
     )
     df_session_counts.loc[non_session, "session_response"] = "day_finished"