MyCODEx Lay-language Molecular Tumor Board Reports for Patients

MyCODEx Lay-language Molecular Tumor Board Reports for Patients - MyCODEx

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00037795

Enrollment

372

Registered

2025-09-09

Start date

2025-09-15

Completion date

Unknown

Last updated

2026-03-30

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

Conditions

C00-C97

Interventions

Group 1: AISource&AIgen: Participants are informed that the report was generated by an AI (AI Source), and it was generated by an AI (AIgen). Group 2: AISource&MDgen: Participants are informed that th

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: Cancer patients with Stage II cancer or higher.

Exclusion criteria

Exclusion criteria: Below the minimum age of 18 No cancer diagnosis or a diagnosis of Stage I cancer

Design outcomes

Primary

Measure	Time frame
The study aims to systematically analyze the direct effects and interaction effects of communicated source and actual generation – particularly with regard to the following dimensions: • Trust and Transparency (Affective Component) • Cognitive Load/Comprehensibility (Cognitive Component) • Behavioral Intention (Behavioral Component) • Credibility The specified primary endpoints are collected using a questionnaire (via Lime Survey), which consists of validated scales. The questionnaire, including the patient protocol, is sent to members of self-help groups. First, sociodemographic data are collected, followed by the randomized assignment of the patient protocols. Immediately afterward, participants answer questions assessing the patient protocols in the specified dimensions (the complete questionnaire can be viewed under supplementary documents in the study results). Cognitive: Differential Cognitive Load Questionnaire (Kleptsch et al., 2017) Affective: Trust in Oncologist Scale (Hillen et al., 2016), Health Care Relationship Trust Scale (Bova et al., 2006), 4 Points Alliance Scale (Misdrahi et al., 2009) Behavioral: Oriented/adapted from an item by Shekar et al. (2024): “I would use the patient protocol in conversations with my relatives.” Credibility of the message (adapted from Sundar & Appemann, 2016): “How well do the following adjectives describe the content of the MTB patient protocol?” (response via slider): accurate, credible, authentic	—

Measure

Time frame

The study aims to systematically analyze the direct effects and interaction effects of communicated source and actual generation – particularly with regard to the following dimensions: • Trust and Transparency (Affective Component) • Cognitive Load/Comprehensibility (Cognitive Component) • Behavioral Intention (Behavioral Component) • Credibility The specified primary endpoints are collected using a questionnaire (via Lime Survey), which consists of validated scales. The questionnaire, including the patient protocol, is sent to members of self-help groups. First, sociodemographic data are collected, followed by the randomized assignment of the patient protocols. Immediately afterward, participants answer questions assessing the patient protocols in the specified dimensions (the complete questionnaire can be viewed under supplementary documents in the study results). Cognitive: Differential Cognitive Load Questionnaire (Kleptsch et al., 2017) Affective: Trust in Oncologist Scale (Hillen et al., 2016), Health Care Relationship Trust Scale (Bova et al., 2006), 4 Points Alliance Scale (Misdrahi et al., 2009) Behavioral: Oriented/adapted from an item by Shekar et al. (2024): “I would use the patient protocol in conversations with my relatives.” Credibility of the message (adapted from Sundar & Appemann, 2016): “How well do the following adjectives describe the content of the MTB patient protocol?” (response via slider): accurate, credible, authentic

—

Secondary

Measure	Time frame
The influence of (inter-)individual characteristics of the participants on the primary endpoints is analyzed: •Current psychological distress •General self-efficacy •Willingness to trust in automated technologies •Demographic characteristics (age, gender, education) •Cancer stage •Subjectively estimated medical knowledge as well as AI-related prior knowledge	—

Countries

Germany

Contacts

Public ContactIna Pretzell

Universitätsklinikum Essen

ina.pretzell@uk-essen.de+49 20172383210

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Apr 4, 2026