Comparison of AI-Generated Pain Scoring Visuals With Visual Analog Scale (VAS) for Pain Assessment

NCT06456853 | Completed

• 1 other identifier: AI Images
• Study Type: observational
• Target: 400
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Pain, Postoperative

Keywords

Postoperative Pain; Artificial Intelligence; Pain assesment

Outcome Measures

Primary Outcomes (1)

• 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.

  10 minutes

Study Arms (2)

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.

Other: Pain assesment

Images maded by Artificial Intelligence

Pain assesment maded by images which is created from ChatGPT/DALLE

Other: Pain assesment

Interventions

Pain assesment OTHER

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.

Images maded by Artificial Intelligence; Visual Analog Scale Score

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

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.

You may qualify if:

• years old and above
• Underwent surgery for any reason
• Consented to participate in the study and signed the informed consent form

You may not qualify if:

• 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

Sponsors & Collaborators

• Kanuni Sultan Suleyman Training and Research Hospital: lead

Study Sites (1)

Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital

Istanbul, 34303, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Pain, Postoperative

Condition Hierarchy (Ancestors)

Postoperative Complications; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Pain; Neurologic Manifestations; Signs and Symptoms

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Day
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: anesthesiology and reanimation specialist

Study Record Dates

• First Submitted: June 8, 2024
• First Posted: June 13, 2024
• Study Start: June 14, 2024
• Primary Completion: February 1, 2025
• Study Completion: February 2, 2025
• Last Updated: February 21, 2025

Record last verified: 2025-02

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)