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Record W4386989281 · doi:10.1093/pch/pxad055.028

28 Lost in Translation: Canadian Paediatric Resident Education and Practice of Clinical Translation Services

2023· article· en· W4386989281 on OpenAlexaboutno aff
Sarah Peters, Matthew Carwana, Erin R. Peebles

Bibliographic record

VenuePaediatrics & Child Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsInterpreterMedicineAccreditationPsychological interventionFamily medicineLanguage barrierDescriptive statisticsMedical educationData collectionNursing

Abstract

fetched live from OpenAlex

Abstract Background Canadian paediatric residents provide care to many families with non-English or French language preferences (NEFLP). Lack of communication in a family’s preferred language is inequitable and results in inferior care. Professional medical interpreters offer a route to enhanced understanding and safety. There is no data available about Canadian paediatric residents’ use of interpreters, making it difficult to identify gaps in practice or develop targeted interventions to improve patient experience. Objectives An anonymous, 19-item survey (REDCap) was designed to evaluate: (1) interpreter services available in paediatric training centers; (2) resident perception of their ease of access, utility, and value; and (3) barriers and drivers to interpreter use. This survey represents the first collection of data from Canadian paediatric residents about translator services. Design/Methods Eligible participants included all paediatric residents enrolled in an accredited Canadian paediatric training program. The survey was distributed by email and available for a three-month period. This project was reviewed and considered within the category of quality improvement and thus exempt from formal review by the hospital ethics committee. Descriptive statistics were performed in STATA v15.1. Results 122 residents (approximately 19% of eligible participants) responded. Approximately 40% reported no previous training in interpreter use, and 60% desired more training. Interpreter services are widely available but remain underused in a variety of clinical situations: interpreters are most often used during informed consent (98% ‘mostly’ or ‘always’), family meetings (97%), and history-taking (86%), and least often during physical examinations (41%) and bedside rounds (38%). Residents are more likely to use an interpreter if access is easy (97% ‘more likely’ or ‘likely’) or if there is extra time for the encounter (78%). Most residents (85%) felt they provide better care to patients who share their primary language (English or French), compared with families who prefer other languages. Conclusion Residents are more confident in their clinical and communication skills when working with families who share their primary language compared with NEFLP families, even when an interpreter is present. Our findings suggest that residents lack the training and confidence to provide equal care to families with varying language preferences. Paediatric training programs should develop curriculum content that not only targets safe and effective interpreter use, but also reviews non-spoken aspects of cultural awareness and safety.

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 imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.079
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.182
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.079
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.004
Scholarly communication0.0050.002
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.002

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 head0.093
GPT teacher head0.478
Teacher spread0.385 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2023
Admission routes1
Has abstractyes

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