MétaCan
Menu
Back to cohort
Record W3172888237 · doi:10.6061/clinics/2021/e1706

Brazilian version of Calgary-Cambridge Observation Guide 28-item version: cross-cultural adaptation and psychometric properties

2021· article· en· W3172888237 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueClinics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPatient-Provider Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsRasch modelConfirmatory factor analysisPsychologyReliability (semiconductor)EmpathyPsychometricsContext (archaeology)Adaptation (eye)Differential item functioningFacet (psychology)Applied psychologyItem analysisClinical psychologyStructural equation modelingItem response theorySocial psychologyComputer scienceDevelopmental psychologyPersonalityBig Five personality traits

Abstract

fetched live from OpenAlex

OBJECTIVES: The search for appropriate tools to assess communicational skills remains an ongoing challenge. The Calgary-Cambridge Observation Guide (CCOG) 28-item version can measure and compare performance in communication skills training. Our goal was to adapt this version of the CCOG for the Brazilian cultural context and perform a psychometric quality analysis of the instrument. METHODS: Experienced preceptors (35) assessed videos of five medical residents with a simulated patient using the translated guide. For the cultural adaptation, we followed the methodological norms on synthesis, retro-translation, committee review, and testing. We obtained validity evidence for the CCOG 28-item version using confirmatory factor analysis and the Many-Facet Rasch Model (MFRM). RESULTS: Confirmatory factor analysis indicated an adequate level of goodness-of-fit. The MFRM reliability coefficient was high in all facets, namely assessors (0.90), stations (0.99), and items (0.98). The assessors had greater difficulty with attitudinal items, such as demonstration of respect, confidence, and empathy. CONCLUSIONS: The psychometric indicators of the tool were adequate, a good potential for reproducing its Brazilian version as well as acceptable reliability for its use.

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 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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.345
GPT teacher head0.463
Teacher spread0.118 · 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