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Record W4224271634 · doi:10.1177/15562646221092663

Practicalities of Impracticability: An Interim Review of Randomized Controlled Trials

2022· review· en· W4224271634 on OpenAlexaff
Roma Dhamanaskar, William B. Feldman, Jon F. Merz

Bibliographic record

VenueJournal of Empirical Research on Human Research Ethics · 2022
Typereview
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsImpactMcMaster University Medical Centre
Fundersnot available
KeywordsWaiverInformed consentInterimRandomized controlled trialMedicineClinical trialSet (abstract data type)Family medicineAlternative medicineLawPolitical scienceSurgeryInternal medicinePathologyComputer science

Abstract

fetched live from OpenAlex

Impracticability is an ethical standard for waiver of informed consent in research. We examine how well the criterion of impracticability appears to have been fulfilled in a set of 36 completed randomized controlled trials (RCTs) that secured consent from some subjects or LARs and employed waivers to enroll others. These trials were identified among 155 RCTs using waivers of consent in a convenience sample drawn from 7 systematic reviews. Recruitment data were available for 19 of the 36 trials, revealing an average of 41.6% of subjects (range 0.2-98.7%, 95% CI: 24.8-58.4%) were enrolled without consent. Six trials enrolled less than 10% of subjects without consent and an overlapping set of 9 trials sought consent from all subjects or LARs at some sites while waiving consent at other sites. We question whether these trials were practicable without waivers and identify issues for consideration by investigators and ethics review boards.

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: no · About a Canadian topic: no
Systematic reviewlow
gptMetaresearch
Domain: Methods · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.887
metaresearch head score (Gemma)0.987
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (broad), Research integrity
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8870.987
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0450.014
Bibliometrics0.0070.004
Science and technology studies0.0010.014
Scholarly communication0.0000.000
Open science0.0040.003
Research integrity0.0040.132
Insufficient payload (model declined to judge)0.0110.000

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 head0.986
GPT teacher head0.854
Teacher spread0.132 · 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 · Other design
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
Published2022
Admission routes1
Has abstractyes

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