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Record W2548539927 · doi:10.1097/pts.0000000000000293

Compelled Disclosure of Confidential Information in Patient Safety Research

2016· review· en· W2548539927 on OpenAlexafffundabout
Li Du, Blake Murdoch, Carina Chiu, Timothy Caulfield

Bibliographic record

VenueJournal of Patient Safety · 2016
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchHealth CanadaAlberta Innovates - Health Solutions
KeywordsConfidentialityInformed consentDutyInternet privacyBusinessPsychologyPublic relationsLawPolitical scienceMedicineComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

ABSTRACT: The protection of confidential research data is of key importance to clinical patient safety research. A review of selected Canadian and American case law indicates that although the relationship between researcher and participant has not been recognized as privileged, court-ordered disclosure of confidential research information seems to be a rare occurrence. In this review, we examine how confidentiality issues are presented in informed consent form templates and in relevant research ethics policies. We find an agreement among research policy documents that all information gathered should be treated as confidential, unless otherwise required by law. Confidentiality provisions in informed consent forms reflect the reality that in some cases, the law can compel disclosure of confidential data. There is, therefore, a potential tension between the law and existing research ethics policy. It has been suggested that researchers have an ethical and possibly legal duty to actively resist disclosure requests. We conclude that it is reasonable for researchers to disclose, as part of the informed consent process, how rare successful disclosure demands are and that steps will be taken to oppose such demands.

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)0.013
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.359
GPT teacher head0.580
Teacher spread0.221 · 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.

Study designOther design
Domainnot available
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

Citations0
Published2016
Admission routes3
Has abstractyes

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