MétaCan
Menu
Back to cohort
Record W3017180481 · doi:10.1089/bio.2019.0090

Biobanking for Genomic and Personalized Health Research: Participant Perceptions and Preferences

2020· article· en· W3017180481 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiopreservation and Biobanking · 2020
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsMcGill UniversityUniversity of VictoriaIsland Health
Fundersnot available
KeywordsBiobankHealth careFamily medicineBiorepositoryMedicineSample (material)Test (biology)PsychologyMedical educationBioinformatics

Abstract

fetched live from OpenAlex

Introduction: Biospecimens and associated data are invaluable tools in Genomics and Personalized Health (GAPH) research and can aid in the discovery of disease etiology and the development of therapeutics. Objective: To examine the experiences of patients invited to a particular GAPH study, Spectrometry in TIA Rapid Assessment (SpecTRA), and to explore broader biospecimen and data sharing preferences among a larger group of patients who had opted into a Permission to Contact for research program. Methods: An electronic survey was e-mailed to 515 participants. The survey was completed by 38% of participants, an unspecified number of whom were also SpecTRA participants. Results: Of those respondents who recalled participating in SpecTRA, 96% strongly agreed, agreed, or were neutral when asked if they received enough information to make an informed decision. Seventy-two percent agreed and 20% were neutral when asked if their study questions were addressed. Ninety-six percent of all respondents felt that SpecTRA's aim to develop a proteomic test for stroke was a worthwhile investment for health care, 98% said they were willing to provide a sample and/or information to facilitate the project's goals, and 96% to health research in general. Fifty-three percent of all participants suggested they would be comfortable sharing health information collected during SpecTRA with for-profit organizations, 87% with nonprofit organizations, and 38% said it matters to them where in the world their sample/information would be sent. Conclusions: Our results suggest that while there is room for improvement in providing adequate information to enable participants' understanding of the purpose of GAPH studies such as SpecTRA, patients are supportive of GAPH in general. Results also suggest that willingness to participate would likely be impacted by factors such as the study's commercial and national affiliations. This study indicates that further work is required to guide improvements on how the GAPH research community describes studies to potential participants, and to enable participation options that incorporate variable participant preferences.

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.

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
gemmaResearch integrity
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.917
GPT teacher head0.622
Teacher spread0.295 · 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