Acceptability of Artificial Intelligence in the Diagnosis of Prostate Cancer

NCT07074405 | Completed

• 1 other identifier: 2024-345
• Study Type: interventional
• Target: 51
• Locations: 1 country
• Sites: 1

Brief Summary

This study investigates the acceptability of artificial intelligence (AI) as a diagnostic support tool among patients with localized prostate cancer and healthcare providers, as well as their willingness to share health data for AI development. Background AI tools in healthcare show promising potential, especially in improving diagnosis accuracy and personalizing treatment. However, successful implementation depends not only on technical performance but also on the acceptability of AI among its users-both patients and professionals. Prior research has shown varied acceptability depending on context, disease severity, task performed by AI, and user population. Objectives Assess patients' acceptability of AI as a diagnostic support in prostate cancer. Explore patients' willingness to share health data for developing clinical AI. Assess healthcare providers' acceptability of AI in this diagnostic context. Methodology Design: A cross-sectional, mixed-method, multinational study (Belgium, Italy, Spain). Quantitative Phase: Online questionnaire, using adapted theoretical frameworks (Value Perception Model, NASSS-AI, TFA). Qualitative Phase: Will follow based on quantitative findings. Participants: Adults diagnosed with localized prostate cancer. Recruitment via hospitals, social media, and patient associations. Data Collected: Personal and health information, attitudes toward AI, willingness to share data. Ethics Approved by ethics committees in each participating country. Informed consent obtained digitally before participation. Data anonymized and GDPR-compliant.

Conditions

Prostate Cancer

Keywords

Questionnaire; Artificial Intelligence; Acceptability of AI

Outcome Measures

Primary Outcomes (4)

• Perceived Benefits of using AI in the diagnosis of prostate cancer

  They are latent measures and will be assessed in several questions: * Benefits: I believe that tools based on artificial intelligence can 'Improve the diagnosis of prostate cancer', 'Advance the prostate cancer diagnostic process', 'Provide an accurate diagnosis of prostate cancer', Reduce the costs of prostate cancer diagnosis'. Scale: "Strongly disagree", "Disagree", "Somewhat disagree", "Neither agree nor disagree", "Somewhat agree", "Agree", "Strongly agree"; 'Strongly agree' gives the highest value of benefit.

  Baseline

• Perceived Risks of using AI in the prostate cancer diagnosis

  Risks, scale "Very low", "Low", "Somewhat low", "Moderate", "Somewhat high", "High", "Very high". The questions are too long to include here but they access the percieved risks of using AI in the diagnosis and treatment of prostate cancer. The 'very high' risk is considered the worst.

  Baseline

• Intention to use AI

  Question: Would you like to use artificial intelligence-based tools to manage my prostate cancer diagnosis. Answers - yes, uncertain beacause and no; then there are concerns if they answer 'no' or 'yes because' and they evaluate these concerns on the scale from 0 to 10; 10 is the biggest concern.

  Baseline

• Willingless to share personal data

  Question: Willingless to share personal data; answers 'yes', 'no', yes with conditions; then they can describe their conditions

  Baseline

Study Arms (1)

Questionnaire

EXPERIMENTAL

This is an online questionnaire that the patients copmlete on their own or with the help of the responsable person

Other: Questionnaire and Physical Exam

Interventions

Questionnaire and Physical Exam OTHER

This is an online questionnaire that the patients fill in

Questionnaire

Eligibility Criteria

• Age: 18 Years+
• Sex: male
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• over 18 years;
• with diagnose of localized prostate cancer;
• consent to the study.

You may not qualify if:

• not speaking French;
• diagnosed with metastatic cancer from the outset;
• terminally ill;
• people suffering from mental retardation, dementia or altered state of consciousness.

Sponsors & Collaborators

• Centre Hospitalier Universitaire de Liege: lead

Study Sites (1)

CHU Liege

Liège, Belgium

Location

Related Publications (3)

• Frost EK, Bosward R, Aquino YSJ, Braunack-Mayer A, Carter SM. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. Int J Med Inform. 2024 Jun;186:105417. doi: 10.1016/j.ijmedinf.2024.105417. Epub 2024 Mar 22.

  PMID: 38564959 RESULT

• Esmaeilzadeh P. Use of AI-based tools for healthcare purposes: a survey study from consumers' perspectives. BMC Med Inform Decis Mak. 2020 Jul 22;20(1):170. doi: 10.1186/s12911-020-01191-1.

  PMID: 32698869 RESULT

• Fazakarley CA, Breen M, Thompson B, Leeson P, Williamson V. Beliefs, experiences and concerns of using artificial intelligence in healthcare: A qualitative synthesis. Digit Health. 2024 Feb 11;10:20552076241230075. doi: 10.1177/20552076241230075. eCollection 2024 Jan-Dec.

  PMID: 38347935 RESULT

Related Links

• The online questionnaire for patients

MeSH Terms

Conditions

Prostatic Neoplasms

Interventions

Surveys and Questionnaires; Restraint, Physical

Condition Hierarchy (Ancestors)

Genital Neoplasms, Male; Urogenital Neoplasms; Neoplasms by Site; Neoplasms; Genital Diseases, Male; Genital Diseases; Urogenital Diseases; Prostatic Diseases; Male Urogenital Diseases

Intervention Hierarchy (Ancestors)

Data Collection; Epidemiologic Methods; Investigative Techniques; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health; Behavior Control; Therapeutics; Immobilization

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: HEALTH SERVICES RESEARCH
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Scientifique R&D

Study Record Dates

• First Submitted: June 10, 2025
• First Posted: July 20, 2025
• Study Start: December 2, 2024
• Primary Completion: December 31, 2025
• Study Completion: December 31, 2025
• Last Updated: March 27, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

BE (1)