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Record W4390686103 · doi:10.1186/s12916-023-03193-y

Randomized controlled trial demonstrates novel tools to assess patient outcomes of Indigenous cultural safety training

2024· article· en· W4390686103 on OpenAlexafffundabout
Janet Smylie, Michael Rotondi, Sam Filipenko, William T. L. Cox, Diane Smylie, Cheryl Ward, Kristina Klopfer, Aïsha Lofters, Braden O’Neill, Melissa Graham, Linda Weber, Ali Damji, Patricia G. Devine, Jane Collins, Billie-Jo Hardy

Bibliographic record

VenueBMC Medicine · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsCredit Valley HospitalUniversity of TorontoNational Association of Friendship CentresWomen's College HospitalVancouver Island UniversityYork UniversitySt. Michael's Hospital
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of General Medical SciencesCanada Research ChairsNational Institutes of HealthSt. Michael's Hospital Foundation
KeywordsMedicineIndigenousRandomized controlled trialObservational studyFamily medicineMEDLINEOdds ratioOddsIntensive carePhysical therapyNursingIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Health care routinely fails Indigenous peoples and anti-Indigenous racism is common in clinical encounters. Clinical training programs aimed to enhance Indigenous cultural safety (ICS) rely on learner reported impact assessment even though clinician self-assessment is poorly correlated with observational or patient outcome reporting. We aimed to compare the clinical impacts of intensive and brief ICS training to control, and to assess the feasibility of ICS training evaluation tools, including unannounced Indigenous standardized patient (UISP) visits. METHOD: Using a prospective parallel group three-arm randomized controlled trial design and masked standardized patients, we compared the clinical impacts of the intensive interactive, professionally facilitated, 8- to10-h Sanyas ICS training; a brief 1-h anti-bias training adapted to address anti-Indigenous bias; and control continuing medical education time-attention matched to the intensive training. Participants included 58 non-Indigenous staff physicians, resident physicians and nurse practitioners from family practice clinics, and one emergency department across four teaching hospitals in Toronto, Canada. Main outcome measures were the quality of care provided during UISP visits including adjusted odds that clinician would be recommended by the UISP to a friend or family member; mean item scores on patient experience of care measure; and clinical practice guideline adherence for NSAID renewal and pain assessment. RESULTS: Clinicians in the intensive or brief ICS groups had higher adjusted odds of being highly recommended to friends and family by standardized patients (OR 6.88, 95% CI 1.17 to 40.45 and OR 7.78, 95% CI 1.05 to 58.03, respectively). Adjusted mean item patient experience scores were 46% (95% CI 12% to 80%) and 40% (95% CI 2% to 78%) higher for clinicians enrolled in the intensive and brief training programs, respectively, compared to control. Small sample size precluded detection of training impacts on clinical practice guideline adherence; 100% of UISP visits were undetected by participating clinicians. CONCLUSIONS: Patient-oriented evaluation design and tools including UISPs were demonstrated as feasible and effective. Results show potential impact of cultural safety training on patient recommendation of clinician and improved patient experience. A larger trial to further ascertain impact on clinical practice is needed. TRIAL REGISTRATION: Clinicaltrials.org NCT05890144. Retrospectively registered on June 5, 2023.

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)0.013
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.026
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.094
GPT teacher head0.387
Teacher spread0.293 · 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 designRandomized trial
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

Citations9
Published2024
Admission routes3
Has abstractyes

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