Digital HealthTRUST-AINCT07265427
Trust in AI and Digitalization in Healthcare Across Generational Groups
An observational study of Digital Health and Artificial Intelligence (AI), run by Jacobs University Bremen gGmbH at 2 sites in Germany.
Trial summary
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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Digital Health, Artificial Intelligence (AI)
- How many people
- 188 participants
- Where
- 2 sitesGermany
- Study dates
- 24 Nov 2025to 30 Jun 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
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
- All sexes
- Adult, Older adult
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.
Who may be able to join
- 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)
Who cannot join
- Individuals under 18
- Inability to give informed consent
- Illiteracy
Trial locations and contacts
2 sites in 1 country.
Germany2 sites
Constructor University (formerly known as Jacobs University)
Bremen, 28759
HAW Hamburg
Hamburg, 21033
About this study
Official title: 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.
Read the 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.
- Conditions
- Digital Health, Artificial Intelligence (AI)
- Keywords
- Artificial Intelligence (AI), Digitalization, Trust, Barriers, Facilitators, Intergenerational Comparision
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Patients in medical rehabilitation and employees in a rehabilitation center | Patients in medical rehabilitation and employees in a rehabilitation center | |
| Training course participants | Seniors participating in "Digital in Old Age" training courses | |
| Students | Students at HAW Hamburg |
What is being measured
The primary outcome is the main question the study is designed to answer.
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).
Measured: 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.
Measured: 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.
Measured: December 2025 - January 2026
Secondary outcomes (1)
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.
Measured: December 2025 - January 2026
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Dec 2025
- Study start24 Nov 2025
- Primary completion30 Mar 2026
- Study completion30 Jun 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Digital HealthStudies of the same condition, open and under way.
- 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
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 188 participants (actual)
Sponsor and investigators
- Lead sponsor
- Jacobs University Bremen gGmbH
- Sponsor type
- University, hospital or other
- Collaborators
- Hamburg University of Applied Sciences
- Responsible party
- Principal investigator, Prof. Dr. Sonia Lippke, Jacobs University Bremen gGmbH
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07265427
- Sponsor's protocol ID
- ANDI-MFA2
- Acronym
- TRUST-AI
- Status last verified
- Sep 2026
- First submitted
- 18 Nov 2025
- Last updated
- 25 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- 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"
- ClinicalTrials.gov ID
- NCT07265427
- Acronym / sponsor ID
- TRUST-AI / ANDI-MFA2
- Conditions
- Digital Health, Artificial Intelligence (AI)
- Keywords
- Artificial Intelligence (AI), Digitalization, Trust, Barriers, Facilitators, Intergenerational Comparision
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 188 participants (actual)
- Lead sponsor
- Jacobs University Bremen gGmbHUniversity, hospital or other
- Collaborators
- Hamburg University of Applied Sciences
- Study start
- 24 Nov 2025 (actual)
- Primary completion
- 30 Mar 2026 (actual)
- Study completion
- 30 Jun 2026 (actual)
- First posted
- 4 Dec 2025 (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.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Patients in medical rehabilitation and employees in a rehabilitation center | – | –Patients in medical rehabilitation and employees in a rehabilitation center |
| Training course participants | – | –Seniors participating in "Digital in Old Age" training courses |
| Students | – | –Students at HAW Hamburg |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (4 listed)
- 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)
Key exclusion criteria (3 listed)
- Individuals under 18
- Inability to give informed consent
- Illiteracy
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Trust in digitalization and AI in healthcare
Time frame: December 2025 - January 2026
* 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).
Perceived barriers to adoption of AI and digitalization in healthcare
Time frame: December 2025 - January 2026
* 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.
Perceived facilitators to the adoption of AI and digitalization in healthcare
Time frame: December 2025 - January 2026
* 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.
1 secondary outcome
eHealth literacy and digital skills
Time frame: December 2025 - January 2026
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Sep 2026.
- Individual participant dataSharing planned: No
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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. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Digital Health and Artificial Intelligence (AI), run by Jacobs University Bremen gGmbH at 2 sites in Germany.
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 4 inclusion and 3 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: finished, as of the sponsor's last update on 25 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Germany. Whether a site is taking part right now should be confirmed with that site. See every site.
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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Trust in digitalization and AI in healthcare (time frame: December 2025 - January 2026). The study lists 3 primary outcomes in all. 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 25 Sep 2026.