Trust in AI and Digitalization in Healthcare Across Generational Groups: A Comparative Study of Barriers and Facilitators Toward Equitable Adoption. (TRUST-AI)

Acceptance and Perceived Benefits of Digitalization by Medical Assistants and Other Generational Groups (ANDI-MFA-2): "Trust in AI and Digitalization in Healthcare Across Generational Groups: A Comparative Study of Barriers and Facilitators Toward Equitable Adoption"

This study aims to investigate differences in perception of barriers and facilitators of digitalization and Artificial Intelligence (AI) usage in healthcare across different generational groups (youth, working-age adults, and seniors). The results will help create practical recommendations for public health projects and consultants to support fair and inclusive use of new digital tools in healthcare. A cross-sectional online survey will be conducted among students at HAW, patients and employees in the rehabilitation center in Oldenburg, and seniors participating in the "Digital im Alter"(DIA) project.

Study Overview

• Status: Recruiting
• Conditions: Digital Health; Artificial Intelligence (AI)

Detailed Description

This study will use an online questionnaire to collect data from respondents about their attitudes toward digital technologies and artificial intelligence in healthcare, as well as their opinions about barriers and facilitators for the equal adoption of modern technologies. The survey will be conducted in November to December 2025.

The survey will use validated scales, including the eHealth Literacy Scale (eHEALS) and the Human-Computer Trust Scale (HCTS), combined with additional items assessing perceived barriers and facilitators. Open-ended questions will allow participants to express their views on barriers and facilitators in their own words and from their perspective.

• Study Type: Observational
• Enrollment (Estimated): 250

Contacts and Locations

• Study Contact: Name: Polina Vedernikova; Phone Number: +4917644507235; Email: Polina.Vedernikova@haw-hamburg.de
• Study Contact Backup: Name: Sonia Lippke, Prof. Dr.; Phone Number: 04212004730; Email: S.Lippke@jacobs-university.de

Study Locations

• Germany
  • Bremen, Germany, 28759
    • Recruiting
    • Constructor University (formerly known as Jacobs University)
    • Contact: Sonia Lippke, PhD; Phone Number: +4942120004730; Email: slippke@constructor.university
    • Principal Investigator: Sonia Lippke, PhD
  • Hamburg, Germany, 21033
    • Active, not recruiting
    • HAW Hamburg

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

The study population is chosen in a way that the cohorts can cover all three generations required for the comparative study. Therefore, the cohorts in this study are:

• Students at Hamburg University of Applied Sciences.
• Seniors participating in "Digital in Old Age" training courses.
• Patients and employees at a rehabilitation center in Oldenburg.

Description

Inclusion Criteria:

• Age 18 or older
• Belonging to one of the defined participant groups
• Consent to participate in the online survey
• Ability to participate in the survey (e.g., sufficient German or English language skills)

Exclusion Criteria:

• Individuals under 18
• Inability to give informed consent
• Illiteracy

Study Plan

How is the study designed?

Number of groups / cohorts

3

Cohorts and Interventions

Group / Cohort
Students; Students at HAW Hamburg
Rehabilitation Center Oldenburg patients and employees; Patients and employees at a rehabilitation center Oldenburg.
training course participants; Seniors participating in "Digital in Old Age" training courses.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Trust in digitalization and AI in healthcare	Measured with the adapted Human-Computer Trust Scale (HCTS). Total scores are calculated by summing ten items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree), resulting in a minimum possible score of 10 and a maximum of 50. Higher scores indicate a greater level of trust in the computer system or AI.; Comparison across generational groups (youth, working-age adults, seniors).	December 2025 - January 2026
Perceived barriers to adoption of AI and digitalization in healthcare	Measured with 5 Likert-scale items (accuracy, privacy and security, lack of human contact, ethics, lack of knowledge). Each item is rated from 1 = no concern to 5 = very strong concern.; Open-ended question: "What is your biggest concern about AI and digital technologies in healthcare and why?"; Comparison across generational groups (youths, working-age adults, seniors). Analysis of universal and generation-specific barriers.	December 2025 - January 2026
Perceived facilitators to the adoption of AI and digitalization in healthcare	Measured with 6 Likert-scale items (clear explanations, regulation, professional review, transparent data use, training, success stories). Each item is rated from 1 = not effective to 5 = very effective.; Open-ended question: "What would help you personally to trust in digital technologies and AI in healthcare?"; Comparison across generational groups (youths, working-age adults, seniors). Analysis of universal and generation-specific facilitators.	December 2025 - January 2026

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
eHealth literacy and digital skills	Measured with the eHEALS (The eHealth Literacy Scale). Total scores are calculated by summing eight items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree), resulting in a minimum possible score of 8 and a maximum of 40. Higher scores indicate better perceived eHealth literacy.; Descriptive analysis and role as a potential moderator of trust and acceptance across generational groups.	December 2025 - January 2026

Collaborators and Investigators

• Sponsor: Jacobs University Bremen gGmbH
• Collaborators: Hamburg University of Applied Sciences/Hochschule für Angewandte Wissenschaften Hamburg (HAW Hamburg)

Study record dates

Study Major Dates

• Study Start (Actual): November 24, 2025
• Primary Completion (Estimated): March 30, 2026
• Study Completion (Estimated): December 30, 2026

Study Registration Dates

• First Submitted: November 18, 2025
• First Submitted That Met QC Criteria: November 24, 2025
• First Posted (Estimated): December 4, 2025

Study Record Updates

• Last Update Posted (Actual): December 19, 2025
• Last Update Submitted That Met QC Criteria: December 12, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Barriers; Artificial Intelligence (AI); Trust; Facilitators; Digitalization; Intergenerational Comparision
• Other Study ID Numbers: ANDI-MFA2

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No