AI-Personalized Discharge Education for Patients After Lung Cancer Surgery (AI-LUNG)
2026년 9월 14일 업데이트: Xi Huang, Xiamen University
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.
연구 개요
상태
상태
모병
정황
정황
개입 / 치료
개입 / 치료
상세 설명
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.
연구 유형
연구 유형
중재적
등록 (추정된)
등록
156
단계
단계
- 해당 없음
연락처 및 위치
이 섹션에서는 연구를 수행하는 사람들의 연락처 정보와 이 연구가 수행되는 장소에 대한 정보를 제공합니다.
연구 연락처
연구 연락처
- 이름: Weiguang Zhou, Master's
- 전화번호: +86 13624449503
- 이메일: 254402969@qq.com
연구 장소
-
-
Jilin
-
Siping, Jilin, 중국, 136000
- 모병
- Siping Central People's Hospital
-
수석 연구원:
- Yang Liu, PhD
-
연락하다:
- Weiguang Zhou, Master's
- 전화번호: +86 13624449503
- 이메일: 254402969@qq.com
-
-
참여기준
연구원은 적격성 기준이라는 특정 설명에 맞는 사람을 찾습니다. 이러한 기준의 몇 가지 예는 개인의 일반적인 건강 상태 또는 이전 치료입니다.
자격 기준
자격 기준
공부할 수 있는 나이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
아니
설명
Inclusion Criteria:
- 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.
Exclusion Criteria:
- 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.
공부 계획
이 섹션에서는 연구 설계 방법과 연구가 측정하는 내용을 포함하여 연구 계획에 대한 세부 정보를 제공합니다.
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 지지 요법
- 할당: 무작위
- 중재 모델: 병렬 할당
- 마스킹: 하나의
팔의 수
2
무기와 개입
참가자 그룹 / 팔참가자 그룹 / 팔 |
개입 / 치료개입 / 치료 |
|---|---|
|
실험적: AI-Personalized Discharge Education
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.
|
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.
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.
|
|
활성 비교기: Routine Discharge Education
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.
|
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.
|
연구는 무엇을 측정합니까?
주요 결과 측정
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
Quality of Discharge Teaching Scale (QDTS) Total Score
기간: 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.
|
On the day of discharge, immediately after the intervention
|
2차 결과 측정
2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
Self-Efficacy for Postoperative Rehabilitation Management (SESPRM-LC) Total Score
기간: 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.
|
1 month after discharge
|
|
Quality of Life Measured by the Functional Assessment of Cancer Therapy-Lung (FACT-L)
기간: 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.
|
1 month after discharge
|
공동 작업자 및 조사자
여기에서 이 연구와 관련된 사람과 조직을 찾을 수 있습니다.
수사관
수사관
- 수석 연구원: Yang Liu, PhD, Xiamen University
연구 기록 날짜
이 날짜는 ClinicalTrials.gov에 대한 연구 기록 및 요약 결과 제출의 진행 상황을 추적합니다. 연구 기록 및 보고된 결과는 공개 웹사이트에 게시되기 전에 특정 품질 관리 기준을 충족하는지 확인하기 위해 국립 의학 도서관(NLM)에서 검토합니다.
연구 주요 날짜
연구 시작 (실제)
연구 시작
2026년 8월 15일
기본 완료 (추정된)
기본 완료
2026년 10월 15일
연구 완료 (추정된)
연구 완료
2026년 11월 15일
연구 등록 날짜
최초 제출
최초 제출
2026년 9월 14일
QC 기준을 충족하는 최초 제출
QC 기준을 충족하는 최초 제출
2026년 9월 14일
처음 게시됨 (실제)
처음 게시됨
2026년 9월 18일
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
마지막 업데이트 게시됨
2026년 9월 18일
QC 기준을 충족하는 마지막 업데이트 제출
QC 기준을 충족하는 마지막 업데이트 제출
2026년 9월 14일
마지막으로 확인됨
마지막으로 확인됨
2026년 9월 1일
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
기타 연구 ID 번호
- AI-LUNG-RCT-2026-01
- SKJT2026-003 (기타 식별자: Ethics Committee of Siping Central People's Hospital)
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
아니요
IPD 계획 설명
Individual participant data are not planned to be shared.
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
아니
미국 FDA 규제 기기 제품 연구
아니
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .