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How do medical students perform when they have to diagnose common diseases using a clinical decision support system?

How do medical students perform when they have to diagnose common diseases using a clinical decision support system?

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
DRKS
Registry ID
DRKS00039181
Enrollment
164
Registered
2026-01-30
Start date
2020-04-28
Completion date
Unknown
Last updated
2026-02-02

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

Conditions

Medical students who are asked to make the following diagnoses based on case vignettes: pulmonary embolism with stomach pain as the main symptom and bacterial tonsillitis with sore throat and gray tonsils.

Interventions

Group 1: Students receive a case vignette of the first case (common disease with typical symptoms) in the order 1. Clinical Decision Support System (CDSS), 2. Conventional diagnostic methods. After ea

Sponsors

Charité - Universitätsmedizin Berlin
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: Medical students = 18 years of age who are participating in a tutorial of their own choosing and have completed their sixth semester. This ensures that no third-party consent is required (age) and that students have the necessary knowledge of medical history and diagnosis (semester).

Exclusion criteria

Exclusion criteria: Students < 18 years of age or in their 6th semester or below.

Design outcomes

Primary

MeasureTime frame
The primary outcome is accuracy of the diagnosis arrived at with the CDSS compared to conventional methods. After each within-subjects condition (CDSS and conventional methods), participants assign a diagnosis. Each given diagnosis will be assessed on a scale from 1 (incorrect) to 5 (correct) using the organ system (lymphatic tonsillar ring and lungs) and the disease mechanism (inflammation and thromboembolism) as orientation marks. For instance, if both the organ system and the disease mechanism are correct (i.e., bacterial tonsillitis and pulmonary embolism), the diagnosis will be given 5 points; if both are incorrect (e.g., rib fracture), the diagnosis will be given 1 point; if one is correct, the other incorrect (e.g., pneumonia), the diagnosis will be scored with 3 points. The scores 2 and 4 pay heed to grey areas as common in many medical settings. Final scores for each diagnosis will be identified by using the median score from the three experts. The highest scoring diagnosis for each participant in each condition will be included in the analyses together with the corresponding trust value (no ranking of the up to three diagnoses).

Secondary

MeasureTime frame
acceptance (Van der Laan, Heino, & de Waard, 1997) perceived usefulness (Davis, Bagozzi, & Warshaw, 1989) perceived ease of use (Davis et al., 1989) technology acceptance (subscale technology commitment) (Neyer, Felber, & Gebhardt, 2012) technology competence belief (subscale technology commitment) (Neyer et al., 2012) technology control beliefs (subscale technology commitment) (Neyer et al., 2012) sociodemographic variables (age, gender, semester of study, prior medical knowledge)

Countries

Germany

Contacts

Public ContactJan Zöllick

Charité - Universitätsmedizin Berlin

jan.zoellick@charite.de+49 30 450 529055

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 7, 2026