Symptom Patterns in Young Adults with Cancer: An App-Based Study

OBJECTIVES: To investigate symptom patterns in young adults with cancer using a smartphone-based app. The authors sought to explore symptom frequency and severity, cluster patients based on their symptom severity, investigate the co-occurrence of severe symptoms, and explore the relationship between symptoms and activities.

DATA SOURCES: Data were collected, using a mobile app, from 161 young adults with cancer (mean age 25.5 years, 75% female, 59% with solid cancer). Symptom frequency/severity was investigated with descriptive statistics. K-means clustering technique was used to cluster patients based on the average symptom severity. Co-occurrence of severe symptoms was investigated with the association rule technique. The relationship between symptom severity and likelihood of performing a physical/social activity was explored with mixed-effects logistic regression.

CONCLUSION: The most frequently reported symptom was mood disturbance, followed by fatigue, which was also the most severe one. Two clusters of patients were identified, experiencing higher and lower severity for all symptoms. Severe appetite disturbances were frequently reported together with severe lack of energy and nausea. Severe lack of energy, either alone or together with mood disturbance, was often reported together with severe fatigue. Higher mood disturbance was associated with lower probability of performing physical and social activities. This study provides new insights into the symptom experience of young adults with cancer.

IMPLICATIONS FOR NURSING PRACTICE: Using a symptoms-tracking app may be a valid strategy for healthcare professionals, nurses, and researchers to support patients in symptom monitoring and, consequently, to identify and implement tailored symptom-management strategies.