ACCEPT-AI-BC Patients´ acceptance of artificial intelligence in breast cancer tumor boards

ACCEPT-AI-BC Patients´ acceptance of artificial intelligence in breast cancer tumor boards - ACCEPT-AI-BC

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00037991

Enrollment

840

Registered

2025-10-20

Start date

2025-12-01

Completion date

Unknown

Last updated

2026-04-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

C50

Interventions

Group 1: Tumor board without artificial intelligence support (immersive scenario) Group 2: Tumor board with artificial intelligence support (immersive scenario) Group 3: Tumor board with artificial in

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: - Minimum age =18 years - Self-reported breast cancer (current or past) - Sufficient knowledge of German to understand scenarios/items - Access to the internet and use of the GDPR-compliant tool (Unipark)

Exclusion criteria

Exclusion criteria: - 20% missing in the primary endpoint) - Non-patients (e.g., relatives, professionals) - Acute crisis/stress with indication of inability to participate (self-reported)

Design outcomes

Primary

Measure	Time frame
Acceptance of AI in the tumor board (scenario comparison) What: Acceptance of AI in the tumor board (immersive scenario comparison: without AI / AI-supported / AI-automated), overall score. When: cross-sectional, once, immediately after the assigned scenario How: Likert items according to the integrated model by Wichmann, Gesk & Leyer (2024);	—

Secondary

Measure	Time frame
1) Moderating effects of acceptance (subgroup analysis): including medical supervision/human-in-the-loop HITL, age, educational level, treatment phase (primary vs. recurrent treatment). What: Interaction scenario × moderator (HITL, age, educational level, treatment phase). When: concurrent with the primary endpoint. How: Linear models with interaction (centered moderators), Structural Equation Modeling (SEM) 2) Explanatory paths of the primary endpoint according to the integrated theoretical model by Wichmann, Gesk & Leyer (2024) What: Indirect effects of the scenario on acceptance via model mediator(s) (e.g., benefit, risk, trust, controllability). When: concurrent with the primary endpoint. How: Structual Equation Modeling SEM	—

Measure

Time frame

1) Moderating effects of acceptance (subgroup analysis): including medical supervision/human-in-the-loop HITL, age, educational level, treatment phase (primary vs. recurrent treatment). What: Interaction scenario × moderator (HITL, age, educational level, treatment phase). When: concurrent with the primary endpoint. How: Linear models with interaction (centered moderators), Structural Equation Modeling (SEM) 2) Explanatory paths of the primary endpoint according to the integrated theoretical model by Wichmann, Gesk & Leyer (2024) What: Indirect effects of the scenario on acceptance via model mediator(s) (e.g., benefit, risk, trust, controllability). When: concurrent with the primary endpoint. How: Structual Equation Modeling SEM

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Countries

Germany

Contacts

Public ContactSebastian Griewing

Institut für Digitale Medizin, Philipps-Universität Marburg

s.griewing@uni-marburg.de06421 58 67079

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: May 1, 2026