diff --git a/features/esm_SAM.py b/features/esm_SAM.py
index 0c5ba21..f59282c 100644
--- a/features/esm_SAM.py
+++ b/features/esm_SAM.py
@@ -36,8 +36,17 @@ def extract_stressful_events(df_esm: pd.DataFrame) -> pd.DataFrame:
     df_esm_event_threat_challenge_mean_wide = calculate_threat_challenge_means(
         df_esm_sam_clean
     )
+    # 2.
+    df_esm_event_stress = detect_stressful_event(df_esm_sam_clean)
 
-    return df_esm_event_threat_challenge_mean_wide
+    # Join all the 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)
+    )
+
+    return df_esm_events
 
 
 def calculate_threat_challenge_means(df_esm_sam_clean: pd.DataFrame) -> pd.DataFrame:
@@ -78,3 +87,14 @@ def calculate_threat_challenge_means(df_esm_sam_clean: pd.DataFrame) -> pd.DataF
         values=["esm_numeric_mean"],
     )
     return df_esm_event_threat_challenge_mean_wide
+
+
+def detect_stressful_event(df_esm_sam_clean: pd.DataFrame) -> pd.DataFrame:
+    df_esm_event_stress = df_esm_sam_clean[
+        df_esm_sam_clean["questionnaire_id"] == QUESTIONNAIRE_ID_SAM.get("event_stress")
+    ]
+    df_esm_event_stress = df_esm_event_stress.assign(
+        event_present=lambda x: x.esm_user_answer_numeric > 0,
+        event_stressfulness=lambda x: x.esm_user_answer_numeric,
+    )
+    return df_esm_event_stress