Feasibility, acceptability and clinical utility of the Cultural Formulation Interview: Mixed-methods results from the DSM-5 international field trial
Bibliographic record
Abstract
Background There is a need for clinical tools to identify cultural issues in diagnostic assessment. Aims To assess the feasibility, acceptability and clinical utility of the DSM-5 Cultural Formulation Interview (CFI) in routine clinical practice. Method Mixed-methods evaluation of field trial data from six countries. The CFI was administered to diagnostically diverse psychiatric out-patients during a diagnostic interview. In post-evaluation sessions, patients and clinicians completed debriefing qualitative interviews and Likert-scale questionnaires. The duration of CFI administration and the full diagnostic session were monitored. Results Mixed-methods data from 318 patients and 75 clinicians found the CFI feasible, acceptable and useful. Clinician feasibility ratings were significantly lower than patient ratings and other clinician-assessed outcomes. After administering one CFI, however, clinician feasibility ratings improved significantly and subsequent interviews required less time. Conclusions The CFI was included in DSM-5 as a feasible, acceptable and useful cultural assessment tool.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.248 | 0.236 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".