Pain, PostoperativeNCT06456853
Comparison of AI-Generated Pain Scoring Visuals With Visual Analog Scale (VAS) for Pain Assessment
An observational study of Pain, Postoperative, run by Kanuni Sultan Suleyman Training and Research Hospital at 1 site in Turkey (Türkiye).
Trial summary
This prospective study will be conducted in surgical wards, assessing postoperative patients. Initially, patients will be evaluated using the VAS method. Subsequently, they will be shown five AI-generated images depicting different pain levels and will select the image that best represents their pain. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Pain, Postoperative
- What is being tested?
- Pain assesment
- How many people
- 400 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 14 Jun 2024to 2 Feb 2025
- How long will I take part?
- 1 Day
- Phase
- Observational
- Are there results?
- None posted in the registry
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 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: VAS scoring and pain assessment using visuals will be conducted on at least 398 patients aged 18 and above who have undergone any surgery, at any time within the first 24 hours postoperatively.
Who may be able to join
- 18 years old and above
- Underwent surgery for any reason
- Consented to participate in the study and signed the informed consent form
Who cannot join
- Patients under 18 years old
- Patients who did not sign the informed consent form
- Patients with visual impairments
- Patients whose level of consciousness is not sufficient to complete the survey
- Patients with a history of psychiatric disorders
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
Istanbul, 34303
About this study
This prospective study will be conducted in surgical wards, assessing postoperative patients. Initially, patients will be evaluated using the VAS method. Subsequently, they will be shown five AI-generated images depicting different pain levels and will select the image that best represents their pain. A follow-up survey will assess the effectiveness of each method.
Using ChatGPT-4/DALL-E, images corresponding to VAS scores of 1-2, 3-4, 5-6, 7-8, and 9-10 will be created. Patients will choose the image that best describes their pain, aiming to determine if AI-supported visuals offer a more accurate alternative to VAS for pain assessment.
Read the detailed description
Study Objective The primary objective of this study is to compare and evaluate the effectiveness of AI-generated pain visuals in assisting patients to express their pain levels with the Visual Analog Scale (VAS). By allowing patients to more accurately depict their pain through AI-supported visuals, the study aims to enhance pain management practices in clinical settings.
Study Significance Pain management is a critical component of healthcare, directly impacting patient well-being and treatment success. The VAS is a widely used tool for subjective pain assessment but can be challenging for some patients due to its abstract nature. AI-generated visuals offer a potentially more precise and understandable way for patients to communicate their pain, potentially leading to more accurate and personalized pain assessments and management.
This study aims to measure the contribution of AI-generated pain visuals to more accurate pain assessment and to explore the potential applications of this technology. Additionally, the study seeks to understand the advantages and limitations of this approach compared to traditional methods like VAS, thereby enhancing the role of AI in pain management practices.
Expected Benefits and Risks
Expected Benefits:
Improved Pain Expression: AI-generated visuals may help patients articulate their pain more clearly, leading to better pain management in clinical settings.
Personalized Treatment Approaches: Enhanced pain expression can provide healthcare providers with opportunities to create more personalized treatment plans, especially beneficial for chronic pain patients.
Enhanced Clinical Decision-Making: The use of AI visuals may facilitate more objective and reproducible pain assessments, improving overall pain management strategies.
Potential Risks:
Misinterpretation Risk: AI-generated visuals might misinterpret patient pain in certain cases, especially if the visuals are misleading or complex.
Dependence on Technology: Over-reliance on AI tools may overlook the importance of human judgment and the subjective nature of pain assessment.
Study Design This prospective study will be conducted in surgical wards, assessing postoperative patients. Initially, patients will be evaluated using the conventional VAS method, which involves marking their pain on a 0-10 scale. Subsequently, patients will be shown five AI-generated images depicting different pain levels and asked to select the image that best represents their pain. A follow-up survey will assess which method the patients found more effective for expressing their pain.
VAS Scoring:
Patients will mark their pain level on a line ranging from 0 (no pain) to 10 (worst pain).
AI-Generated Visuals:
Using ChatGPT-4/DALL-E, images corresponding to VAS scores of 1-2, 3-4, 5-6, 7-8, and 9-10 will be created. These images will specifically depict facial expressions reflecting the respective pain levels. Patients will choose the image that best describes their pain.
This study aims to identify whether AI-supported visuals provide a more accurate and user-friendly alternative to traditional VAS scoring for pain assessment.
VAS Score Descriptions VAS Score 1-2: A middle-aged man showing signs of mild discomfort.
VAS Score 3-4: A young female athlete on a soccer field expressing moderate pain.
VAS Score 5-6: A man in a kitchen environment displaying severe pain from a cut.
VAS Score 7-8: A young male feeling severe shoulder pain.
VAS Score 9-10: A young woman experiencing intense pain.
- Conditions
- Pain, Postoperative
- Being tested
- Pain assesment
- Keywords
- Postoperative Pain, Artificial Intelligence, Pain assesment
- Medical subject headings
- Pain, Postoperative
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Pain assesmentOther
We will ask patients about their pain and will try to asses their pain scores. Then we will ask them to which methot is more suitable for assesment.
| Study group | Role | What they receive |
|---|---|---|
| Visual Analog Scale Score | The Visual Analog Scale (VAS) pain score is a simple and effective method used to measure patients' pain levels. This method is typically represented by a line ranging from 0 to 10, where 0 indicates no pain and 10 indicates the most severe pain. Patients are asked to mark a point on the line that corresponds to their level of pain. Receives: Other: Pain assesment | |
| Images maded by Artificial Intelligence | Pain assesment maded by images which is created from ChatGPT/DALLE Receives: Other: Pain assesment |
What is being measured
The primary outcome is the main question the study is designed to answer.
Pain assesment
The primary outcome for this research is to compare the effectiveness of AI-generated pain assessment visuals with the traditional Visual Analog Scale (VAS) in accurately evaluating and expressing patients' pain levels. This will be measured through patient-reported ease of use, clarity, and usefulness of both methods, as well as patient preference for either method in pain assessment.
Measured: 10 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jun 2024
- Study start14 Jun 2024
- Primary completion1 Feb 2025
- Study completion2 Feb 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pain, PostoperativeStudies 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
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 400 participants (actual)
- Target duration
- 1 Day
Sponsor and investigators
- Lead sponsor
- Kanuni Sultan Suleyman Training and Research Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Engin Ihsan Turan, Kanuni Sultan Suleyman Training and Research Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06456853
- Sponsor's protocol ID
- AI Images
- Status last verified
- Feb 2025
- First submitted
- 8 Jun 2024
- Last updated
- 21 Feb 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: All patients IPD will delete and we will give randomised patient number to them
Study at a glance
From the registry record, last updated by the sponsor on 21 Feb 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Comparison of AI-Generated Pain Scoring Visuals With Visual Analog Scale (VAS) for Pain Assessment
- ClinicalTrials.gov ID
- NCT06456853
- Acronym / sponsor ID
- AI Images
- Conditions
- Pain, Postoperative
- Keywords
- Postoperative Pain, Artificial Intelligence, Pain assesment
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 400 participants (actual)
- Lead sponsor
- Kanuni Sultan Suleyman Training and Research HospitalUniversity, hospital or other
- Study start
- 14 Jun 2024 (actual)
- Primary completion
- 1 Feb 2025 (actual)
- Study completion
- 2 Feb 2025 (actual)
- First posted
- 13 Jun 2024 (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 prospective study will be conducted in surgical wards, assessing postoperative patients. Initially, patients will be evaluated using the VAS method. Subsequently, they will be shown five AI-generated images depicting different pain levels and will select the image that best represents their pain. A follow-up survey will assess the effectiveness of each method.
Using ChatGPT-4/DALL-E, images corresponding to VAS scores of 1-2, 3-4, 5-6, 7-8, and 9-10 will be created. Patients will choose the image that best describes their pain, aiming to determine if AI-supported visuals offer a more accurate alternative to VAS for pain assessment.
Detailed description
Study Objective The primary objective of this study is to compare and evaluate the effectiveness of AI-generated pain visuals in assisting patients to express their pain levels with the Visual Analog Scale (VAS). By allowing patients to more accurately depict their pain through AI-supported visuals, the study aims to enhance pain management practices in clinical settings.
Study Significance Pain management is a critical component of healthcare, directly impacting patient well-being and treatment success. The VAS is a widely used tool for subjective pain assessment but can be challenging for some patients due to its abstract nature. AI-generated visuals offer a potentially more precise and understandable way for patients to communicate their pain, potentially leading to more accurate and personalized pain assessments and management.
This study aims to measure the contribution of AI-generated pain visuals to more accurate pain assessment and to explore the potential applications of this technology. Additionally, the study seeks to understand the advantages and limitations of this approach compared to traditional methods like VAS, thereby enhancing the role of AI in pain management practices.
Expected Benefits and Risks
Expected Benefits:
Improved Pain Expression: AI-generated visuals may help patients articulate their pain more clearly, leading to better pain management in clinical settings.
Personalized Treatment Approaches: Enhanced pain expression can provide healthcare providers with opportunities to create more personalized treatment plans, especially beneficial for chronic pain patients.
Enhanced Clinical Decision-Making: The use of AI visuals may facilitate more objective and reproducible pain assessments, improving overall pain management strategies.
Potential Risks:
Misinterpretation Risk: AI-generated visuals might misinterpret patient pain in certain cases, especially if the visuals are misleading or complex.
Dependence on Technology: Over-reliance on AI tools may overlook the importance of human judgment and the subjective nature of pain assessment.
Study Design This prospective study will be conducted in surgical wards, assessing postoperative patients. Initially, patients will be evaluated using the conventional VAS method, which involves marking their pain on a 0-10 scale. Subsequently, patients will be shown five AI-generated images depicting different pain levels and asked to select the image that best represents their pain. A follow-up survey will assess which method the patients found more effective for expressing their pain.
VAS Scoring:
Patients will mark their pain level on a line ranging from 0 (no pain) to 10 (worst pain).
AI-Generated Visuals:
Using ChatGPT-4/DALL-E, images corresponding to VAS scores of 1-2, 3-4, 5-6, 7-8, and 9-10 will be created. These images will specifically depict facial expressions reflecting the respective pain levels. Patients will choose the image that best describes their pain.
This study aims to identify whether AI-supported visuals provide a more accurate and user-friendly alternative to traditional VAS scoring for pain assessment.
VAS Score Descriptions VAS Score 1-2: A middle-aged man showing signs of mild discomfort.
VAS Score 3-4: A young female athlete on a soccer field expressing moderate pain.
VAS Score 5-6: A man in a kitchen environment displaying severe pain from a cut.
VAS Score 7-8: A young male feeling severe shoulder pain.
VAS Score 9-10: A young woman experiencing intense pain.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Target follow-up
- 1 Day
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Visual Analog Scale Score | – | Other: Pain assesmentThe Visual Analog Scale (VAS) pain score is a simple and effective method used to measure patients' pain levels. This method is typically represented by a line ranging from 0 to 10, where 0 indicates no pain and 10 indicates the most severe pain. Patients are asked to mark a point on the line that corresponds to their level of pain. |
| Images maded by Artificial Intelligence | – | Other: Pain assesmentPain assesment maded by images which is created from ChatGPT/DALLE |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- VAS scoring and pain assessment using visuals will be conducted on at least 398 patients aged 18 and above who have undergone any surgery, at any time within the first 24 hours postoperatively.
Key inclusion criteria (3 listed)
- 18 years old and above
- Underwent surgery for any reason
- Consented to participate in the study and signed the informed consent form
Key exclusion criteria (5 listed)
- Patients under 18 years old
- Patients who did not sign the informed consent form
- Patients with visual impairments
- Patients whose level of consciousness is not sufficient to complete the survey
- Patients with a history of psychiatric disorders
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 |
|---|---|---|
| Pain assesmentWe will ask patients about their pain and will try to asses their pain scores. Then we will ask them to which methot is more suitable for assesment. | Other | Images maded by Artificial Intelligence, Visual Analog Scale Score |
Primary outcome
Pain assesment
Time frame: 10 minutes
The primary outcome for this research is to compare the effectiveness of AI-generated pain assessment visuals with the traditional Visual Analog Scale (VAS) in accurately evaluating and expressing patients' pain levels. This will be measured through patient-reported ease of use, clarity, and usefulness of both methods, as well as patient preference for either method in pain assessment.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Feb 2025.
- Individual participant dataSharing planned: No. All patients IPD will delete and we will give randomised patient number to them
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pain, Postoperative, run by Kanuni Sultan Suleyman Training and Research Hospital at 1 site in Turkey (Türkiye).
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 3 inclusion and 5 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: finished, as of the sponsor's last update on 21 Feb 2025. 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 Turkey (Türkiye). 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Pain assesment (time frame: 10 minutes). 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 21 Feb 2025; AzTrials last refreshed its copy on 2 Nov 2026.