| Unique ID issued by UMIN | UMIN000060705 |
|---|---|
| Receipt number | R000069406 |
| Scientific Title | A Randomized Controlled Trial on the Use of AI Avatars for Pre-Discharge Patient Education: Effects on Workflow Efficiency, Patient Understanding, and Satisfaction |
| Date of disclosure of the study information | 2026/04/26 |
| Last modified on | 2026/03/04 20:10:21 |
A study to examine whether AI avatar-based pre-discharge explanations improve patients' understanding and satisfaction
Patient impact of AI avatar-based pre-discharge explanation
A Randomized Controlled Trial on the Use of AI Avatars for Pre-Discharge Patient Education: Effects on Workflow Efficiency, Patient Understanding, and Satisfaction
Efficiency and patient impact of AI avatar-based pre-discharge education: RCT
| Japan |
Adult patients with gastrointestinal diseases scheduled for hospital discharge
| Gastroenterology | Hepato-biliary-pancreatic medicine | Gastrointestinal surgery |
| Hepato-biliary-pancreatic surgery |
Malignancy
NO
The aim of this study is to prospectively and quantitatively evaluate the effects of three pre-discharge education methods - traditional face-to-face instruction, conventional video-based education, and AI avatar-based video education - on nursing workflow efficiency, patient understanding, and patient satisfaction. In a subset of participants, electroencephalographic measurements will be conducted using an affective analyzer to objectively assess the acceptability of the AI avatar-based video.
Efficacy
- Time required for healthcare providers' explanations (minutes)
- Number of explanations provided by healthcare providers (count)
- Patient understanding at the end of the first educational session
(objective assessment by healthcare providers using a five-item Likert scale, and subjective assessment using a comprehension test)
- Time required until the start of the intervention
- Patient satisfaction (questionnaire adapted from the CSQ-8)
- Need for additional explanations (presence/absence and content)
- Patient understanding at the first post-discharge outpatient visit
(objective assessment by healthcare providers using a five-item Likert scale, and subjective assessment using a comprehension test)
- Electroencephalographic measurements using an affective analyzer (affective values)
- Nurses' perceived workload (three-item short version of the NASA-TLX)
Interventional
Parallel
Randomized
Individual
Open -no one is blinded
Active
3
Treatment
| Other |
AI avatar video + face-to-face instruction
Conventional video + face-to-face instruction
Face-to-face instruction only
| 18 | years-old | <= |
| Not applicable |
Male and Female
- Patients in the Department of Gastrointestinal Surgery or Gastroenterology who have a gastrointestinal drain or catheter in place at the time of discharge
- No age restrictions
- Patients who can understand explanations provided in Japanese
- Patients without dementia or severe cognitive impairment based on cognitive function assessment
(For patients aged 75 years or older, the OLD will be administered, and the MMSE will be performed as needed)
- Patients with no prior experience of having a drain or catheter placed
- Patients who do not have a gastrointestinal drain or catheter in place at the time of discharge
- Patients suspected of having dementia or severe cognitive impairment
- Patients aged 75 years or older who score 4 or more out of 12 items on the OLD, and additionally score 23 or lower on the MMSE
- Patients with visual or hearing impairments that make it difficult to watch videos or understand explanations
- Patients for whom sufficient time for instruction cannot be secured due to reasons such as urgent discharge
- Patients who have previous experience with a drain or catheter and may already understand self-management methods
90
| 1st name | Sanae |
| Middle name | |
| Last name | Sasaki |
Keio University Hospital
nursing department
1608582
35 Shinanomachi, Shinjuku-ku, Tokyo
0333531211
sanae.sasaki@adst.keio.ac.jp
| 1st name | Saori |
| Middle name | |
| Last name | Tanebe |
Keio University Hospital
nursing department
1608582
35 Shinanomachi, Shinjuku-ku, Tokyo
0333531211
saori.tanabe@adst.keio.ac.jp
Keio University Hospital
none
Self funding
Keio University School of Medicine Ethics Committee
35 Shinanomachi, Shinjuku-ku, Tokyo
03-5363-3503Ext.62014
med-rinri-jimu@adst.keio.ac.jp
NO
| 2026 | Year | 04 | Month | 26 | Day |
Unpublished
Preinitiation
| 2026 | Year | 03 | Month | 01 | Day |
| 2026 | Year | 04 | Month | 27 | Day |
| 2028 | Year | 03 | Month | 31 | Day |
| 2026 | Year | 02 | Month | 18 | Day |
| 2026 | Year | 03 | Month | 04 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000069406