Background: In recent years, the incidence of cancer has been on the rise worldwide due to environmental pollution, poor lifestyle habits, and increasing medical diagnoses. In China, the incidence and mortality of lung cancer both rank first among malignant tumors. In the process of cancer diagnosis and treatment, patients with lung cancer experience a serious symptom burden. Inadequate symptom management will aggravate the physical and mental pain of patients, and even delay or interrupt the treatment of the disease. Therefore, it is urgent to provide scientific symptom management programs for medical staff and patients with lung cancer.
Objective: To construct the core symptom cluster management program for patients with lung cancer undergoing chemotherapy.
Methods: Under the guidance of Symptom Management Theory, the draft program was formed through the literature supplement and clinical expert meeting based on the best evidence summary, and the final program was formed after two rounds of Delphi with 17 experts.
Results: The draft program contains 35 entries in 3 time dimensions and 16 intervention dimensions. The final program, formed after two rounds of Delphi, consists of 12 entries in 7 different dimensions. In both rounds, Delphi issued and recovered 17 questionnaires, and the recovery rate was 100%. The expert authority coefficient was 0.888. The submission rate of expert opinions was 82.35% and 58.82%. The mean values of importance were 3.765-4.647 and 4.410-4.820. The full score frequency was 23.5-76.5 and 58.8-88.2. The coefficient of variation was 0.130-0.280 and 0.110-0.197. The Kendall’s W was 0.467 and 0.523, P < 0.05. The expert approval rate for the clinical usability of each item was 94.1%-100%.
Conclusion: Under the guidance of Symptom Management Theory, the core symptom cluster management program for patients with lung cancer undergoing chemotherapy established in this study is scientific and credible, with clinical operability, and can guide medical staff and patients with lung cancer to carry out symptom management in complex clinical environments.