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Record W3001612706 · doi:10.1176/appi.focus.20190037

Update on the Cultural Formulation Interview

2020· article· en· W3001612706 on OpenAlexaboutno aff
G. Eric Jarvis, Laurence J. Kirmayer, Ana Gómez-Carrillo, Neil Krishan Aggarwal, Roberto Lewis‐Fernández

Bibliographic record

VenueFOCUS The Journal of Lifelong Learning in Psychiatry · 2020
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Perspective (graphical)PsychologyMedicineCultural diversityClinical psychologyPsychotherapistPsychiatrySociology

Abstract

fetched live from OpenAlex

. The CFI is an interview protocol designed to be used by clinicians in any setting to gather essential data to produce a cultural formulation. The CFI aims to improve culturally sensitive diagnosis and treatment by focusing clinical attention on the patient's perspective and social context. Preliminary evidence indicates that the CFI can improve clinical communication by enhancing clinician-patient rapport, allowing the clinician to obtain new, cultural data in a relatively short period, eliciting patients' perspectives on what caused their symptoms, and helping patients to become aware of their problems in more insightful ways. With practice, the CFI takes approximately 20 minutes to complete. The CFI has been evaluated internationally in the United States, Canada, Kenya, Peru, the Netherlands, India, and Mexico and generally has been found to be clinically acceptable and useful in these varied settings. Clinicians receiving as little as one hour of training on the CFI improved their ability to work with culturally diverse patients. The CFI may be more difficult to conduct with patients who have severe symptoms, including acute psychosis, suicidal behavior, aggression, and cognitive impairment. The CFI provides a simple way to begin the process of cultural assessment, and its systematic use can foster a reflective stance and promote systemic thinking in routine clinical practice about the patient's life and experience.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.291
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations87
Published2020
Admission routes1
Has abstractyes

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