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Record W3214220875 · doi:10.1080/10790268.2021.1970898

Central Recruitment: A process for engaging and recruiting individuals with spinal cord injury/disease in research at Toronto Rehabilitation Institute

2021· article· en· W3214220875 on OpenAlexafffundabout
B. Catharine Craven, Louise Brisbois, Chelsea Pelletier, Julia Rybkina, Ann Heesters, Mary C. Verrier

Bibliographic record

VenueJournal of Spinal Cord Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsPublic Health OntarioToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersToronto Rehabilitation InstituteOntario Neurotrauma Foundation
KeywordsMedicineSpinal cord injuryRehabilitationInformed consentResearch ethicsProcess (computing)DiseaseNursingMedical emergencyFamily medicinePhysical therapySpinal cordPsychiatryAlternative medicinePathology

Abstract

fetched live from OpenAlex

CONTEXT: Insufficient recruitment is a barrier to research and limits statistical power. We describe an initiative aimed to streamline recruitment and consent processes for inpatients with spinal cord injury or disease (SCI/D) via implementation of a Central Recruitment (CR) process. The CR process adhered to ethical standards, reduced participant burden, and maximized research participation. METHODS: In this CR process, the inpatient's nurse affirmed suitability for research approach based on fluency, cognition and health stability. A patient research liaison (PRL) was the sole contact for information regarding the research process, and introduced ongoing studies, screened for eligibility, and completed the consent process(es). RESULTS: Over five and a half years, 1,561 inpatients with SCI/D were screened for eligibility upon admission, of whom 80% (1256/1561) were deemed suitable for the PRL approach. Of those suitable for the CR process, 80% (1001/1256) agreed to discuss current research opportunities, 46% (235/516) consented to participate in one or more studies, and 86% (856/1001) agreed to future research contact. CONCLUSION: This process adhered to ethical procedures and reduced the burden of having multiple researchers approach each individual inpatient regarding research participation, with high consent rates for low-risk studies. Future evaluation of the process scalability is underway.

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)0.014
metaresearch head score (Gemma)0.055
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.055
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.658
GPT teacher head0.643
Teacher spread0.015 · 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 designObservational
Domainnot available
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

Citations14
Published2021
Admission routes3
Has abstractyes

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