Artificial Intelligence (AI), Digital Health
Conditions
Keywords
Artificial Intelligence (AI), Digitalization, Trust, Barriers, Facilitators, Intergenerational Comparision
Brief 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). 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.
Interventions
None listed
Sponsors
Hamburg University of Applied Sciences/Hochschule für Angewandte Wissenschaften Hamburg (HAW Hamburg)
Jacobs University Bremen gGmbH
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Trust in digitalization and AI in healthcare | 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 | 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 | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| eHealth literacy and digital skills | December 2025 - January 2026 | * 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. |
Countries
Germany
Contacts
Primary ContactPolina Vedernikova
Backup ContactSonia Lippke, Prof. Dr.
Outcome results
None listed