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Record W2779606936 · doi:10.1186/s13063-017-2333-5

Promoting deceased organ and tissue donation registration in family physician waiting rooms (RegisterNow-1 trial): study protocol for a pragmatic, stepped-wedge, cluster randomized controlled registry

2017· article· en· W2779606936 on OpenAlexafffundabout
Alvin H. Li, Amit X. Garg, V. Prakash, Jeremy Grimshaw, Monica Taljaard, Joanna Mitchell, Danny Matti, Stefanie Linklater, Kyla L. Naylor, Stephanie N. Dixon, Rachel Bevan, Leah Getchell, Greg Knoll, S. Joseph Kim, Jessica M. Sontrop, Lise M. Bjerre, Allison Tong, Justin Presseau

Bibliographic record

VenueTrials · 2017
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity Health NetworkUniversity of TorontoUniversity of OttawaTrillium Therapeutics (Canada)Western UniversityInstitute for Clinical Evaluative SciencesOttawa HospitalLawson Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineOrgan donationTissue DonationFamily medicineRandomized controlled trialDonationClinical trialIntervention (counseling)Protocol (science)Economic shortageMedical emergencyTransplantationAlternative medicineNursingSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: There is a worldwide shortage of organs available for transplant, leading to preventable mortality associated with end-stage organ disease. While most citizens in many countries with an intent-to-donate "opt-in" system support organ donation, registration rates remain low. In Canada, most Canadians support organ donation but less than 25% in most provinces have registered their desire to donate their organs when they die. The family physician office is a promising yet underused setting in which to promote organ donor registration and address known barriers and enablers to registering for deceased organ and tissue donation. We developed a protocol to evaluate an intervention to promote registration for organ and tissue donation in family physician waiting rooms. METHODS/DESIGN: This protocol describes a planned, stepped-wedge, cluster randomized registry trial in six family physician offices in Ontario, Canada to evaluate the effectiveness of reception staff providing patients with a pamphlet that addresses barriers and enablers to registration including a description of how to register for organ donation. An Internet-enabled tablet will also be provided in waiting rooms so that interested patients can register while waiting for their appointments. Family physicians and reception staff will be provided with training and/or materials to support any conversations about organ donation with their patients. Following a 2-week control period, the six offices will cross sequentially into the intervention arm in randomized sequence at 2-week intervals until all offices deliver the intervention. The primary outcome will be the proportion of patients visiting the office who are registered organ donors 7 days following their office visit. We will evaluate this outcome using routinely collected registry data from provincial administrative databases. A post-trial qualitative evaluation process will assess the experiences of reception staff and family physicians with the intervention and the stepped-wedge trial design. DISCUSSION: Promoting registration for organ donation in family physician offices is a potentially useful strategy for increasing registration for organ donation. Increased registration may ultimately help to increase the number of organs available for transplant. The results of this trial will provide important preliminary data on the effectiveness of using family physician offices to promote registration for organ donation. TRIAL REGISTRATION: ClinicalTrials.gov, ID: NCT03213171 . Registered on 11 July 2017.

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)0.012
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.392
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.081
GPT teacher head0.424
Teacher spread0.343 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations27
Published2017
Admission routes3
Has abstractyes

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