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Record W2894910408 · doi:10.1177/1747016118798877

Examining the use of consent forms to promote dissemination of research results to participants

2018· article· en· W2894910408 on OpenAlexaffabout
Dorothyann Curran, Mike Kekewich, Thomas Foreman

Bibliographic record

VenueResearch Ethics · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsOttawa HospitalSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsInformed consentOrder (exchange)ReciprocalInformation DisseminationDisseminationPublic relationsPsychologyMedical educationIdeal (ethics)MedicinePolitical scienceBusinessAlternative medicineComputer scienceWorld Wide WebLaw

Abstract

fetched live from OpenAlex

It is becoming widely recognized that dissemination of research results to participants is an important action for the conclusion of a research study. Most research institutions have standardized consent documents or templates that they require their researchers to use. Consent forms are an ideal place to indicate that results of research will be provided to participants, and the practice of inserting statements to this effect is becoming more conventional. In order to determine the acceptance of this practice across Canada we conducted an assessment of 121 institutional consent document templates from 65 institutions (hospitals and universities) looking for language that endorsed results dissemination to participants. About half (51%) of the documents we examined had language included which stated that results should be made available. In an era where research participation in hospital settings and universities is becoming ubiquitous there should be a reciprocal expectation that results should be provided. The success of research should be measured in part by its accessibility and dissemination to all stakeholders.

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)0.683
metaresearch head score (Gemma)0.801
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.995
Threshold uncertainty score0.391

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.6830.801
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.007
Science and technology studies0.0080.011
Scholarly communication0.0080.012
Open science0.0040.006
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0060.003

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 head0.954
GPT teacher head0.713
Teacher spread0.241 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations7
Published2018
Admission routes2
Has abstractyes

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