Lung Cancer (Diagnosis)AI-LUNGNCT07827183
AI-Personalized Discharge Education for Patients After Lung Cancer Surgery
A study testing AI-Personalized Discharge Education and Routine Discharge Education in people with Lung Cancer (Diagnosis), run by Xiamen University at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Lung Cancer (Diagnosis)
- What is being tested?
- AI-Personalized Discharge Education and Routine Discharge Education
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 156 participants
- Where
- 1 siteChina
- Study dates
- 15 Aug 2026to 15 Nov 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Pathologically confirmed primary lung cancer and underwent radical lung cancer surgery by thoracoscopic or open approach, including lobectomy, pneumonectomy, or wedge resection.
- Age 18 to 80 years.
- Clinical stage I to III.
- No distant organ metastasis.
- Clinically stable after surgery, conscious, and able to perform basic listening, speaking, and reading activities, with planned discharge to home for recovery.
- The participant or primary caregiver is able to use a smartphone and WeChat.
- Able and willing to provide informed consent and voluntarily participate in the study.
Who cannot join
- Recurrent lung cancer or previous treatment with targeted therapy, chemotherapy, or radiotherapy.
- Severe aphasia, cognitive impairment (MMSE <24), or psychiatric disorders that prevent independent completion of study questionnaires.
- Severe cardiac, hepatic, or renal dysfunction, or another malignant tumor.
- Severe postoperative complications requiring prolonged hospitalization, such as bronchopleural fistula or major bleeding.
- Participation in another interventional clinical study.
- Unable to complete the 1-month follow-up because of travel or residence outside the study area after discharge.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
Siping Central People's Hospital
Siping, Jilin, 136000
Weiguang Zhou, Master's, +86 13624449503, 254402969@qq.com
Yang Liu, PhD
About this study
Official title: Effect of AI-Personalized Discharge Education on the Quality of Discharge Teaching and Recovery Outcomes in Patients After Lung Cancer Surgery: A Randomized Controlled Trial
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.
Read the 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.
- Conditions
- Lung Cancer (Diagnosis)
- Being tested
- AI-Personalized Discharge Education, Routine Discharge Education
- Keywords
- Artificial Intelligence, Personalized Discharge Education, Postoperative Recovery, Discharge Teaching, Self-Efficacy, Quality of Life
- Medical subject headings
- Lung Neoplasms, Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Personalized Discharge EducationBehavioural
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.
Routine Discharge EducationBehavioural
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.
| Study group | Role | What they receive |
|---|---|---|
| AI-Personalized Discharge Education | Experimental | Participants receive routine discharge education plus AI-personalized discharge guidance. The personalized guidance is generated based on individual clinical and care-related information and is reviewed by a responsible nurse before being provided to the participant or caregiver. Receives: Behavioral: AI-Personalized Discharge Education; Behavioral: Routine Discharge Education |
| Routine Discharge Education | Active comparator | Participants receive routine discharge education, including verbal instructions from nursing staff and a standardized printed discharge education booklet covering medication use, wound care, respiratory exercises, physical activity, diet, follow-up, and related postoperative care. Receives: Behavioral: Routine Discharge Education |
What is being measured
The primary outcome is the main question the study is designed to answer.
Quality of Discharge Teaching Scale (QDTS) Total Score
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.
Measured: On the day of discharge, immediately after the intervention
Secondary outcomes (2)
Self-Efficacy for Postoperative Rehabilitation Management (SESPRM-LC) Total Score
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.
Measured: 1 month after discharge
Quality of Life Measured by the Functional Assessment of Cancer Therapy-Lung (FACT-L)
Quality of life will be assessed using the Functional Assessment of Cancer Therapy-Lung (FACT-L). Higher scores indicate better quality of life.
Measured: 1 month after discharge
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted18 Sep 2026
- Study start15 Aug 2026
- Primary completion15 Oct 2026 (estimated)
- Study completion15 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung Cancer (Diagnosis)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- 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.
- Masking
- Single blind
- Who is masked
- Outcomes assessor
- Enrolment
- 156 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Xiamen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Xi Huang, Xiamen University
- Investigators
- Yang Liu, PhD, Principal investigator, Xiamen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07827183
- Sponsor's protocol ID
- AI-LUNG-RCT-2026-01
- Other IDs
- SKJT2026-003
- Acronym
- AI-LUNG
- Status last verified
- Sep 2026
- First submitted
- 14 Sep 2026
- Last updated
- 18 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data are not planned to be shared.
Study at a glance
From the registry record, last updated by the sponsor on 18 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of AI-Personalized Discharge Education on the Quality of Discharge Teaching and Recovery Outcomes in Patients After Lung Cancer Surgery: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07827183
- Acronym / sponsor ID
- AI-LUNG / AI-LUNG-RCT-2026-01
- Conditions
- Lung Cancer (Diagnosis)
- Keywords
- Artificial Intelligence, Personalized Discharge Education, Postoperative Recovery, Discharge Teaching, Self-Efficacy, Quality of Life
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 156 participants (estimated)
- Lead sponsor
- Xiamen UniversityUniversity, hospital or other
- Study start
- 15 Aug 2026 (actual)
- Primary completion
- 15 Oct 2026 (estimated)
- Study completion
- 15 Nov 2026 (estimated)
- First posted
- 18 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Single blind (outcomes assessor)
- Number of arms
- 2
- 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.
| Arm | Type | Receives |
|---|---|---|
| AI-Personalized Discharge Education | Experimental | Behavioral: AI-Personalized Discharge Education, Behavioral: Routine Discharge EducationParticipants receive routine discharge education plus AI-personalized discharge guidance. The personalized guidance is generated based on individual clinical and care-related information and is reviewed by a responsible nurse before being provided to the participant or caregiver. |
| Routine Discharge Education | Active comparator | Behavioral: Routine Discharge EducationParticipants receive routine discharge education, including verbal instructions from nursing staff and a standardized printed discharge education booklet covering medication use, wound care, respiratory exercises, physical activity, diet, follow-up, and related postoperative care. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- Pathologically confirmed primary lung cancer and underwent radical lung cancer surgery by thoracoscopic or open approach, including lobectomy, pneumonectomy, or wedge resection.
- Age 18 to 80 years.
- Clinical stage I to III.
- No distant organ metastasis.
- Clinically stable after surgery, conscious, and able to perform basic listening, speaking, and reading activities, with planned discharge to home for recovery.
Key exclusion criteria (6 listed)
- Recurrent lung cancer or previous treatment with targeted therapy, chemotherapy, or radiotherapy.
- Severe aphasia, cognitive impairment (MMSE <24), or psychiatric disorders that prevent independent completion of study questionnaires.
- Severe cardiac, hepatic, or renal dysfunction, or another malignant tumor.
- Severe postoperative complications requiring prolonged hospitalization, such as bronchopleural fistula or major bleeding.
- Participation in another interventional clinical study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Personalized Discharge EducationParticipants 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. | Behavioural | AI-Personalized Discharge Education |
| Routine Discharge EducationParticipants 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. | Behavioural | AI-Personalized Discharge Education, Routine Discharge Education |
Primary outcome
Quality of Discharge Teaching Scale (QDTS) Total Score
Time frame: 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.
2 secondary outcomes
Self-Efficacy for Postoperative Rehabilitation Management (SESPRM-LC) Total Score
Time frame: 1 month after discharge
Quality of Life Measured by the Functional Assessment of Cancer Therapy-Lung (FACT-L)
Time frame: 1 month after discharge
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Sep 2026.
- Individual participant dataSharing planned: No. Individual participant data are not planned to be shared.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Yang Liu, PhD principal investigator
Xiamen University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Personalized Discharge Education and Routine Discharge Education in people with Lung Cancer (Diagnosis), run by Xiamen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 18 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Weiguang Zhou, Master's (+86 13624449503, 254402969@qq.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Quality of Discharge Teaching Scale (QDTS) Total Score (time frame: On the day of discharge, immediately after the intervention). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Sep 2026; AzTrials last refreshed its copy on 7 Nov 2026.