The Influence of Patient Use of Artificial Intelligence on Doctor-Patient Interaction and Clinical Outcomes in Endometriosis Consultations

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.

• Physician-Perceived Interaction Quality and Consultation Characteristics [Срок оценки: During and immediately after the consultation (same day)]