A Digital Communication Assistance Tool (DCAT) to Obtain Medical History from Foreign-Language Patients: Development and Pilot Testing in a Primary Health Care Center for Refugees
Bibliographic record
Abstract
Background: Language barriers play a critical role in the treatment of migrant and refugee patients. In Germany, primary care interpreters are often not available especially in rural areas or if patients demand spontaneous or urgent consultations. Methods: In order to enable patients and their physicians to communicate effectively about the current illness history, we developed a digital communication assistance tool (DCAT) for 19 different languages and dialects. This paper reports the multidisciplinary process of the conceptual design and the iterative development of this cross-cultural user-centered application in an action-oriented approach. Results: We piloted our app with 36 refugee patients prior to a clinical study and used the results for further development. The acceptance and usability of the app by patients was high. Conclusion: Using digital tools for overcoming language barriers can be a feasible approach when providing health care to foreign-language patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".