EndometriosisNCT07393568
The Influence of Patient Use of Artificial Intelligence on Doctor-Patient Interaction and Clinical Outcomes in Endometriosis Consultations
An observational study of Endometriosis, run by Hadassah Medical Organization.
Trial summary
Generative artificial intelligence (AI), including large language models such as ChatGPT, Gemini, and Copilot, is increasingly used by patients to obtain medical information and prepare for clinical encounters. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Endometriosis
- What is being tested?
- using Chat gpt before outpatient clinic visit
- How many people
- 94 participants
- Where
- No sites listed yet
- Study dates
- 1 Feb 2026to 1 Jan 2027
- Phase
- Observational
- 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 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Study population: The study population will consist of adult women (aged ≥18 years) attending a specialized gynecology outpatient clinic for evaluation or management of endometriosis-related complaints. Eligible participants must be able to provide informed consent and complete study questionnaires independently. Participants will include both new and returning patients with suspected or confirmed endometriosis. Individuals with cognitive impairment or psychiatric conditions that significantly interfere with communication or the ability to provide informed consent will be excluded. Following enrollment, participants will be categorized based on self-reported use of generative artificial intelligence (AI) tools to prepare for their clinical visit. Demographic and baseline clinical characteristics-including age, ethnicity, body mass index, smoking status, medical comorbidities, reproductive history, and prior surgical history-will be collected to characterize the study population and allow for compariso
Who may be able to join
- Women aged ≥18.
- Attending clinic for endometriosis-related complaints.
- Able to give informed consent.
Who cannot join
- Cognitive impairment or psychiatric conditions that affect communication or the ability to provide informed consent
About this study
Generative artificial intelligence (AI), including large language models such as ChatGPT, Gemini, and Copilot, is increasingly used by patients to obtain medical information and prepare for clinical encounters. Although these tools often provide guideline-consistent information, their responses may be incomplete, inaccurate, or lack personalization, potentially influencing patient expectations and clinical interactions. The impact of patient AI use on satisfaction, adherence, and physician-patient communication remains poorly understood.
This prospective comparative study will evaluate the effects of patient AI use prior to gynecologic consultations for endometriosis. Women attending a specialized endometriosis clinic will be categorized as AI users or non-users based on their preparation for the visit. Patient-reported outcomes, including satisfaction, expectations, adherence to physician recommendations, and pain during physical examination, will be assessed using validated questionnaires and visual analogue scales. Physicians, blinded to AI use, will independently assess patient engagement, trust, and compliance. Visit duration will also be recorded.
The primary objective is to determine whether AI use affects patient satisfaction and adherence to treatment recommendations. Secondary objectives include evaluating physician-perceived interaction quality and concordance between AI-generated guidance and physician recommendations. Findings from this study will provide critical evidence on how AI influences patient behavior and clinical care in endometriosis, informing best practices for integrating AI-informed patients into routine clinical encounters.
Read the detailed description
Generative artificial intelligence (AI), including large language models, is increasingly used by patients to obtain medical information prior to clinical encounters. These tools provide rapid access to health-related content and may influence patient knowledge, expectations, communication style, and decision-making during physician consultations. The effect of patient use of AI tools on the doctor-patient interaction and short-term clinical outcomes in the context of endometriosis care has not been systematically evaluated.
This prospective comparative study is designed to examine differences in patient-reported and physician-reported outcomes between patients who used AI tools to prepare for an endometriosis-related consultation and those who did not. The study is conducted in a gynecology outpatient clinic specializing in endometriosis care. All eligible adult women attending the clinic during the study period are invited to participate. Following informed consent, participants are categorized into two groups based on self-reported use of AI tools for preparation prior to the clinic visit.
Data collection is performed using structured questionnaires administered before and after the clinical consultation. The pre-visit questionnaire captures baseline information regarding prior use of artificial intelligence tools, including use for medical information and preparation for the current visit. Baseline demographic and clinical characteristics are also collected. The post-visit questionnaire captures patient-reported satisfaction with the consultation, intention to adhere to the physician's treatment recommendations, perceived concordance between AI-provided information and physician guidance, perceived added value of the physician beyond AI, and perceived necessity of the in-person visit.
Physicians conducting the consultations are blinded to patient AI usage status and complete a structured assessment immediately after each visit. Physician-reported measures include perceived patient trust, compliance, engagement, and prior knowledge, as well as the duration of the consultation. Pain experienced during the physical examination is recorded using a visual analog scale.
No discussion of questionnaire responses occurs between physicians and participants during the visit. All physicians involved in data collection hold valid Good Clinical Practice certification and are listed as investigators or sub-investigators. Data are collected anonymously using coded identifiers and stored securely in accordance with institutional data protection policies.
Comparisons are performed between AI users and non-users to evaluate differences in patient satisfaction, intention to adhere to treatment recommendations, physician-perceived interaction quality, pain during examination, and visit duration. This study aims to provide structured evidence regarding the influence of patient use of artificial intelligence on the clinical encounter in endometriosis care and to inform future integration of AI-informed patients into routine clinical practice.
- Conditions
- Endometriosis
- Being tested
- using Chat gpt before outpatient clinic visit
- Medical subject headings
- Endometriosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
using Chat gpt before outpatient clinic visitOther
This study involves a behavioral, non-randomized observational intervention based on patients' self-directed use of generative artificial intelligence (AI) tools prior to their clinical visit.
The intervention group consists of patients who report using AI-based large language models (e.g., ChatGPT or similar tools) to prepare for their endometriosis-related consultation. AI use may include seeking information about symptoms, diagnosis, treatment options, prognosis, or formulating questions for the physician. No specific AI platform, prompts, or duration of use is mandated, and AI engagement occurs independently and outside the clinical setting.
The control group includes patients who report no use of AI tools in preparation for the visit.
No AI tools are introduced, recommended, or used during the clinical encounter by study personnel. Physicians are blinded to patient AI use status and conduct consultations according to standard clinical practice. Aside from questionnaire administ
| Study group | Role | What they receive |
|---|---|---|
| using Chat gpt before outpatient clinic visit | using Chat gpt before outpatient clinic visit Receives: Other: using Chat gpt before outpatient clinic visit | |
| Chat -gpt non users | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
Patient Satisfaction and Treatment Plan Adherence After Consultation
Overall patient satisfaction will be measured immediately after the endometriosis consultation using a structured post-visit questionnaire and reported as a score on a 0-5 scale, where 0 indicates not satisfied at all and 5 indicates very satisfied. Intention to adhere to the physician's treatment plan will be measured immediately after the consultation as a binary outcome (yes/no) based on the patient's response to the post-visit questionnaire item asking whether she intends to follow the doctor's treatment recommendations.
Measured: Immediately after the consultation (same day)
Secondary outcomes (1)
Physician-Perceived Interaction Quality and Consultation Characteristics
Physician-perceived patient trust, compliance, and engagement will be measured immediately after the consultation using physician-completed ratings on a 0-4 ordinal scale. Physician-perceived patient prior knowledge regarding endometriosis will be recorded using a structured post-visit physician assessment.
Patient-reported concordance between information obtained from artificial intelligence tools and the physician's treatment recommendations will be measured immediately after the consultation as a binary response (yes/no) using the post-visit questionnaire. Patient-reported receipt of new or additional information from the physician beyond AI-provided content will also be measured as a binary response (yes/no). Patient perception of the necessity of an in-person visit after AI use will be recorded as a binary response (yes/no).
Pain experienced during the physical examination will be measured during the consultation using a 0-10 visual analog scale (VAS). Duration of the clinical
Measured: During and immediately after the consultation (same day)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted6 Feb 2026
- Study start1 Feb 2026 (estimated)
- Primary completion1 Jan 2027 (estimated)
- Study completion1 Jan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for EndometriosisStudies of the same condition, open and under way.
- More trials run by Hadassah Medical OrganizationThe sponsor's other registered studies.
- 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-control
- Time perspective
- Prospective
- Enrolment
- 94 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hadassah Medical Organization
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07393568
- Sponsor's protocol ID
- 0423-25-HMO
- Status last verified
- Jan 2026
- First submitted
- 17 Dec 2025
- Last updated
- 6 Feb 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 6 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Influence of Patient Use of Artificial Intelligence on Doctor-Patient Interaction and Clinical Outcomes in Endometriosis Consultations
- ClinicalTrials.gov ID
- NCT07393568
- Acronym / sponsor ID
- 0423-25-HMO
- Conditions
- Endometriosis
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 94 participants (estimated)
- Lead sponsor
- Hadassah Medical OrganizationUniversity, hospital or other
- Study start
- 1 Feb 2026 (estimated)
- Primary completion
- 1 Jan 2027 (estimated)
- Study completion
- 1 Jan 2027 (estimated)
- First posted
- 6 Feb 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.
Generative artificial intelligence (AI), including large language models such as ChatGPT, Gemini, and Copilot, is increasingly used by patients to obtain medical information and prepare for clinical encounters. Although these tools often provide guideline-consistent information, their responses may be incomplete, inaccurate, or lack personalization, potentially influencing patient expectations and clinical interactions. The impact of patient AI use on satisfaction, adherence, and physician-patient communication remains poorly understood.
This prospective comparative study will evaluate the effects of patient AI use prior to gynecologic consultations for endometriosis. Women attending a specialized endometriosis clinic will be categorized as AI users or non-users based on their preparation for the visit. Patient-reported outcomes, including satisfaction, expectations, adherence to physician recommendations, and pain during physical examination, will be assessed using validated questionnaires and visual analogue scales. Physicians, blinded to AI use, will independently assess patient engagement, trust, and compliance. Visit duration will also be recorded.
The primary objective is to determine whether AI use affects patient satisfaction and adherence to treatment recommendations. Secondary objectives include evaluating physician-perceived interaction quality and concordance between AI-generated guidance and physician recommendations. Findings from this study will provide critical evidence on how AI influences patient behavior and clinical care in endometriosis, informing best practices for integrating AI-informed patients into routine clinical encounters.
Detailed description
Generative artificial intelligence (AI), including large language models, is increasingly used by patients to obtain medical information prior to clinical encounters. These tools provide rapid access to health-related content and may influence patient knowledge, expectations, communication style, and decision-making during physician consultations. The effect of patient use of AI tools on the doctor-patient interaction and short-term clinical outcomes in the context of endometriosis care has not been systematically evaluated.
This prospective comparative study is designed to examine differences in patient-reported and physician-reported outcomes between patients who used AI tools to prepare for an endometriosis-related consultation and those who did not. The study is conducted in a gynecology outpatient clinic specializing in endometriosis care. All eligible adult women attending the clinic during the study period are invited to participate. Following informed consent, participants are categorized into two groups based on self-reported use of AI tools for preparation prior to the clinic visit.
Data collection is performed using structured questionnaires administered before and after the clinical consultation. The pre-visit questionnaire captures baseline information regarding prior use of artificial intelligence tools, including use for medical information and preparation for the current visit. Baseline demographic and clinical characteristics are also collected. The post-visit questionnaire captures patient-reported satisfaction with the consultation, intention to adhere to the physician's treatment recommendations, perceived concordance between AI-provided information and physician guidance, perceived added value of the physician beyond AI, and perceived necessity of the in-person visit.
Physicians conducting the consultations are blinded to patient AI usage status and complete a structured assessment immediately after each visit. Physician-reported measures include perceived patient trust, compliance, engagement, and prior knowledge, as well as the duration of the consultation. Pain experienced during the physical examination is recorded using a visual analog scale.
No discussion of questionnaire responses occurs between physicians and participants during the visit. All physicians involved in data collection hold valid Good Clinical Practice certification and are listed as investigators or sub-investigators. Data are collected anonymously using coded identifiers and stored securely in accordance with institutional data protection policies.
Comparisons are performed between AI users and non-users to evaluate differences in patient satisfaction, intention to adhere to treatment recommendations, physician-perceived interaction quality, pain during examination, and visit duration. This study aims to provide structured evidence regarding the influence of patient use of artificial intelligence on the clinical encounter in endometriosis care and to inform future integration of AI-informed patients into routine clinical practice.
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| using Chat gpt before outpatient clinic visit | – | Other: using Chat gpt before outpatient clinic visitusing Chat gpt before outpatient clinic visit |
| Chat -gpt non users | – | – |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population will consist of adult women (aged ≥18 years) attending a specialized gynecology outpatient clinic for evaluation or management of endometriosis-related complaints. Eligible participants must be able to provide informed consent and complete study questionnaires independently. Participants will include both new and returning patients with suspected or confirmed endometriosis. Individuals with cognitive impairment or psychiatric conditions that significantly interfere with communication or the ability to provide informed consent will be excluded. Following enrollment, participants will be categorized based on self-reported use of generative artificial intelligence (AI) tools to prepare for their clinical visit. Demographic and baseline clinical characteristics-including age, ethnicity, body mass index, smoking status, medical comorbidities, reproductive history, and prior surgical history-will be collected to characterize the study population and allow for compariso
Key inclusion criteria (3 listed)
- Women aged ≥18.
- Attending clinic for endometriosis-related complaints.
- Able to give informed consent.
Key exclusion criteria (1 listed)
- Cognitive impairment or psychiatric conditions that affect communication or the ability to provide informed consent
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 |
|---|---|---|
| using Chat gpt before outpatient clinic visitThis study involves a behavioral, non-randomized observational intervention based on patients' self-directed use of generative artificial intelligence (AI) tools prior to their clinical visit. The intervention group consists of patients who report using AI-based large language models (e.g., ChatGPT or similar tools) to prepare for their endometriosis-related consultation. AI use may include seeking information about symptoms, diagnosis, treatment options, prognosis, or formulating questions for the physician. No specific AI platform, prompts, or duration of use is mandated, and AI engagement occurs independently and outside the clinical setting. The control group includes patients who report no use of AI tools in preparation for the visit. No AI tools are introduced, recommended, or used during the clinical encounter by study personnel. Physicians are blinded to patient AI use status and conduct consultations according to standard clinical practice. Aside from questionnaire administ | Other | using Chat gpt before outpatient clinic visit |
Primary outcome
Patient Satisfaction and Treatment Plan Adherence After Consultation
Time frame: Immediately after the consultation (same day)
Overall patient satisfaction will be measured immediately after the endometriosis consultation using a structured post-visit questionnaire and reported as a score on a 0-5 scale, where 0 indicates not satisfied at all and 5 indicates very satisfied. Intention to adhere to the physician's treatment plan will be measured immediately after the consultation as a binary outcome (yes/no) based on the patient's response to the post-visit questionnaire item asking whether she intends to follow the doctor's treatment recommendations.
1 secondary outcome
Physician-Perceived Interaction Quality and Consultation Characteristics
Time frame: During and immediately after the consultation (same day)
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 6 Feb 2026.
- Individual participant dataSharing planned: Undecided
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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.
The record lists no contact. Use the official record to reach the sponsor.
Questions about this trial
What is this clinical trial studying?
An observational study of Endometriosis, run by Hadassah Medical Organization.
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 1 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: opening soon, as of the sponsor's last update on 6 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
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?
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?
Patient Satisfaction and Treatment Plan Adherence After Consultation (time frame: Immediately after the consultation (same day)). 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 6 Feb 2026.