Lung Cancer (Diagnosis)
Conditions
Keywords
Artificial Intelligence, Personalized Discharge Education, Postoperative Recovery, Discharge Teaching, Self-Efficacy, Quality of Life
Brief summary
This randomized controlled trial evaluates the effect of artificial intelligence (AI)-personalized discharge education on discharge teaching quality and recovery outcomes in patients after lung cancer surgery. Eligible participants will be randomly assigned in a 1:1 ratio to either an intervention group or a control group. The control group will receive routine discharge education, including verbal instructions and a standardized printed discharge booklet. The intervention group will receive the same routine education plus an AI-generated personalized discharge guidance plan based on individual clinical and care-related information. All AI-generated content will be reviewed by a responsible nurse before being provided to participants. The primary outcome is the quality of discharge teaching measured on the day of discharge. Secondary outcomes include self-efficacy for postoperative rehabilitation management and quality of life assessed one month after discharge.
Detailed description
This is a single-center, prospective, single-blind randomized controlled trial designed to evaluate whether AI-personalized discharge education can improve discharge teaching quality and postoperative recovery outcomes among patients undergoing surgery for lung cancer. A total of 156 eligible participants will be randomly assigned in a 1:1 ratio to an intervention group or a control group. Participants in the control group will receive routine discharge care, including verbal education provided by nursing staff and a standardized printed discharge education booklet covering medication use, wound care, respiratory exercises, physical activity, diet, follow-up, and other routine postoperative care. Participants in the intervention group will receive routine discharge care plus AI-personalized discharge education. Within 24 hours before discharge, relevant patient information will be entered into a structured system, including surgical approach, extent of lung resection, pain score, dyspnea score, comorbidities, discharge medications, home care conditions, educational level, smoking history, and postoperative complications. A large language model will then generate an individualized discharge guidance document. The guidance will include medication instructions, respiratory rehabilitation exercises, wound and activity management, follow-up planning, and warning signs requiring medical attention. All AI-generated content will be reviewed and approved by a responsible nurse before being delivered to the participant or caregiver. The primary outcome is discharge teaching quality, assessed using the Quality of Discharge Teaching Scale (QDTS) on the day of discharge after the intervention. Secondary outcomes include self-efficacy for postoperative rehabilitation management, assessed using the SESPRM-LC scale, and quality of life, assessed using the Functional Assessment of Cancer Therapy-Lung (FACT-L) scale, both measured one month after discharge. The study will also explore the relationships among discharge teaching quality, self-efficacy, and quality of life, including the potential mediating role of self-efficacy.
Interventions
BEHAVIORALAI-Personalized Discharge Education
Participants receive an individualized discharge guidance plan generated by an artificial intelligence system based on clinical and care-related information, including surgical approach, extent of lung resection, pain and dyspnea scores, comorbidities, discharge medications, home care conditions, educational level, smoking history, and postoperative complications. The guidance includes medication instructions, respiratory exercises, wound and activity management, follow-up planning, and warning signs requiring medical attention. All AI-generated content is reviewed by a responsible nurse before being provided to the participant or caregiver.
BEHAVIORALRoutine Discharge Education
Participants receive routine discharge education provided by nursing staff, including verbal instructions and a standardized printed discharge booklet covering medication use, wound care, respiratory exercises, physical activity, diet, follow-up, and other routine postoperative care.
Sponsors
Xiamen University
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
SINGLE (Outcomes Assessor)
Masking description
Outcome assessors are blinded to group assignment. Due to the nature of the intervention, participants and nurses delivering the discharge education cannot be blinded. Data analysts will also remain unaware of group allocation during the primary analysis.
Intervention model description
Participants are randomly assigned in a 1:1 ratio to either the AI-personalized discharge education group or the routine discharge education group.
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
1. Pathologically confirmed primary lung cancer and underwent radical lung cancer surgery by thoracoscopic or open approach, including lobectomy, pneumonectomy, or wedge resection. 2. Age 18 to 80 years. 3. Clinical stage I to III. 4. No distant organ metastasis. 5. Clinically stable after surgery, conscious, and able to perform basic listening, speaking, and reading activities, with planned discharge to home for recovery. 6. The participant or primary caregiver is able to use a smartphone and WeChat. 7. Able and willing to provide informed consent and voluntarily participate in the study.
Exclusion criteria
1. Recurrent lung cancer or previous treatment with targeted therapy, chemotherapy, or radiotherapy. 2. Severe aphasia, cognitive impairment (MMSE \<24), or psychiatric disorders that prevent independent completion of study questionnaires. 3. Severe cardiac, hepatic, or renal dysfunction, or another malignant tumor. 4. Severe postoperative complications requiring prolonged hospitalization, such as bronchopleural fistula or major bleeding. 5. Participation in another interventional clinical study. 6. Unable to complete the 1-month follow-up because of travel or residence outside the study area after discharge.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Quality of Discharge Teaching Scale (QDTS) Total Score | On the day of discharge, immediately after the intervention | Discharge teaching quality will be assessed using the Quality of Discharge Teaching Scale (QDTS). The QDTS contains 24 items scored from 0 to 10, with a total score ranging from 0 to 240. Higher scores indicate better quality of discharge teaching. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Self-Efficacy for Postoperative Rehabilitation Management (SESPRM-LC) Total Score | 1 month after discharge | Self-efficacy for postoperative rehabilitation management will be assessed using the SESPRM-LC scale. The scale contains 27 items scored from 1 to 5, with a total score ranging from 27 to 135. Higher scores indicate greater self-efficacy. |
| Quality of Life Measured by the Functional Assessment of Cancer Therapy-Lung (FACT-L) | 1 month after discharge | Quality of life will be assessed using the Functional Assessment of Cancer Therapy-Lung (FACT-L). Higher scores indicate better quality of life. |
Countries
China
Contacts
CONTACTWeiguang Zhou, Master's
PRINCIPAL_INVESTIGATORYang Liu, PhD
Xiamen University
Outcome results
None listed