The Cultural Formulation Interview since DSM-5: Prospects for training, research, and clinical practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While social science research has demonstrated the importance of culture in shaping psychiatric illness, clinical methods for assessing the cultural dimensions of illness have not been adopted as part of routine care. Reasons for limited integration include the impression that attention to culture requires specialized skills, is only relevant to a subset of patients from unfamiliar backgrounds, and takes too much time to be useful. The DSM-5 Cultural Formulation Interview (CFI), published in 2013, was developed to provide a simplified approach to collecting information needed for cultural assessment. It offers a 16-question interview protocol that has been field tested at sites around the world. However, little is known about how CFI implementation has affected training, health services, and clinical outcomes. This article offers a comprehensive narrative review that synthesizes peer-reviewed, published studies on CFI use. A total of 25 studies were identified, with sample sizes ranging from 1 to 460 participants. In all pilot CFI studies 960 unique subjects were enrolled, and in final CFI studies 739 were enrolled. Studies focused on how the CFI affects clinical practice; explored the CFI through research paradigms in medical communication, implementation science, and family psychiatry; and examined clinician training. In most studies, patients and clinicians reported that using the CFI improved clinical rapport. This evidence base offers an opportunity to consider implications for training, research, and clinical practice and to identify crucial areas for further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.005 |
| 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 it