Culture and Psychiatric Evaluation: Operationalizing Cultural Formulation for<i>DSM-5</i>
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
The Outline for Cultural Formulation (OCF) introduced with DSM-IV provided a framework for clinicians to organize cultural information relevant to diagnostic assessment and treatment planning. However, use of the OCF has been inconsistent, raising questions about the need for guidance on implementation, training, and application in diverse settings. To address this need, DSM-5 introduced a cultural formulation interview (CFI) that operationalizes the process of data collection for the OCF. The CFI includes patient and informant versions and 12 supplementary modules addressing specific domains of the OCF. This article summarizes the literature reviews and analyses of experience with the OCF conducted by the DSM-5 Cross-Cultural Issues Subgroup (DCCIS) that informed the development of the CFI. We review the history and contents of the DSM-IV OCF, its use in training programs, and previous attempts to render it operational through questionnaires, protocols, and semi-structured interview formats. Results of research based on the OCF are discussed. For each domain of the OCF, we summarize findings from the DCCIS that led to content revision and operationalization in the CFI. The conclusion discusses training and implementation issues essential to service delivery.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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