diff --git a/features/esm_SAM.py b/features/esm_SAM.py
index f59282c..e4c5adc 100644
--- a/features/esm_SAM.py
+++ b/features/esm_SAM.py
@@ -39,13 +39,22 @@ def extract_stressful_events(df_esm: pd.DataFrame) -> pd.DataFrame:
     # 2.
     df_esm_event_stress = detect_stressful_event(df_esm_sam_clean)
 
-    # Join all the features related to the events.
+    # Join to the previously calculated features related to the events.
     df_esm_events = df_esm_event_threat_challenge_mean_wide.join(
         df_esm_event_stress[
             GROUP_QUESTIONNAIRES_BY + ["event_present", "event_stressfulness"]
         ].set_index(GROUP_QUESTIONNAIRES_BY)
     )
 
+    # 3.
+    df_esm_event_time = convert_event_time(df_esm_sam_clean)
+
+    df_esm_events = df_esm_events.join(
+        df_esm_event_time[GROUP_QUESTIONNAIRES_BY.append("event_time")].set_index(
+            GROUP_QUESTIONNAIRES_BY
+        )
+    )
+
     return df_esm_events
 
 
@@ -98,3 +107,14 @@ def detect_stressful_event(df_esm_sam_clean: pd.DataFrame) -> pd.DataFrame:
         event_stressfulness=lambda x: x.esm_user_answer_numeric,
     )
     return df_esm_event_stress
+
+
+def convert_event_time(df_esm_sam_clean: pd.DataFrame) -> pd.DataFrame:
+    df_esm_event_time = df_esm_sam_clean[
+        df_esm_sam_clean["questionnaire_id"] == QUESTIONNAIRE_ID_SAM.get("event_time")
+    ].assign(
+        event_time=lambda x: pd.to_datetime(
+            x.esm_user_answer, errors="coerce", infer_datetime_format=True, exact=True
+        )
+    )
+    return df_esm_event_time