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Record W4414610441 · doi:10.1186/s12910-025-01280-8

Informed consent processes with First Nations peoples undergoing surgery or invasive procedures: a scoping review

2025· review· en· W4414610441 on OpenAlexaboutno aff
Camila Kairuz, Kate Hunter, Bianca Barnier, Bobby Porykali, Keziah Bennett‐Brook, Tamara Mackean, Edward Litton, Jacquita S. Affandi, Courtney Ryder, Siva Senthuran, Julieann Coombes

Bibliographic record

VenueBMC Medical Ethics · 2025
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy of medicineInformed consentGeneral partnershipHealth careQuality (philosophy)RacismMEDLINEDeveloping countryHuman rights

Abstract

fetched live from OpenAlex

BACKGROUND: Informed consent is a cornerstone of medical practice, however, is not always ethically obtained. For First Nations people, this can be hindered by different worldviews and health paradigms. Although best practice entails consideration of patient's cultural beliefs and needs, the extent towhich informed consent is adequately obtained from First Nations patients is unknown. We aimed to conduct a scoping review to map and analyse informed consent processes with First Nations peoples in Australia, New Zealand and North America who are undergoing surgery or an invasive medical procedure. METHODS: A systematic search was conducted using PubMed, Web of Science, Embase and Health InfoNet. Google scholar and webpages of relevant medical organisations were manually searched. Descriptions of informed consent processes were analysed against the guidelines to obtaining informed consent of the respective jurisdictions in which the research was conducted. The experiences of First Nations people undergoing informed consent processes, impact of gaps, healthcare staff views and strategies to enhance informed consent were thematically analysed. RESULTS: Nine qualitative studies were included. Processes reported failed to address all the considerations stated in the respective guidelines. Participants reported feeling coerced due to racism and power imbalances. Physicians tended to prioritise what they thought was better over patient's cultural values and protocols. Inadequate processes resulted in fear, disengagement of health services and negative impact on wellbeing. Engagement of professional interpreters, use of diagrams and workforce training that fosters reflective practice were found to enhance informed consent. CONCLUSION: Evidence suggests that consent forms are often signed by patients who are not fully informed. For First Nations people, this is aggravated by language barriers, culturally different understanding of health and racism leading to coercion. Better assessment of informed consent processes with First Nations people, training and ongoing quality improvement are required to identify and address gaps. Partnership with First Nations people is required to enhance current guidelines and to develop strategies to ensure true informed consent.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: yes · About a Canadian topic: yes
Systematic reviewlow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.196
metaresearch head score (Gemma)0.516
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.196
Threshold uncertainty score0.991

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1960.516
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0280.028
Science and technology studies0.0050.008
Scholarly communication0.0100.016
Open science0.0050.009
Research integrity0.0090.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.665
GPT teacher head0.623
Teacher spread0.042 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
DomainMethods
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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