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Record W4200069930 · doi:10.1080/07380577.2021.2018751

The Clinical Usefulness of the Practice Resource for Driving after Stroke (PReDAS)

2021· article· en· W4200069930 on OpenAlexaff
April Vander Veen, Michael Cammarata, Sarah Renner, Liliana Alvarez

Bibliographic record

VenueOccupational Therapy In Health Care · 2021
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsLondon Health Sciences CentreGrand River HospitalWestern University
Fundersnot available
KeywordsMedicineStroke (engine)Acute strokeHealth careResource (disambiguation)Clinical PracticeAcute careMEDLINEHealth professionalsMedical emergencyPhysical therapyEmergency departmentNursing

Abstract

fetched live from OpenAlex

Occupational Therapists (OTs) have identified a critical need for organized, evidence-based resources to approach driving post-stroke. The Practice Resource for Driving After Stroke (PReDAS) is a resource to support the clinical reasoning and practice of health professionals for addressing driving in acute stroke care. The purpose of this pilot study is to evaluate the usefulness of the PReDAS to support clinician and patient decision-making about return to driving after stroke/Transient Ischemic Attack (TIA) in the acute care hospital setting. OTs, physicians, and patients diagnosed with stroke/TIA were surveyed regarding their experience with the PReDAS in acute care. Patient participants were also contacted for a follow-up questionnaire. OT, physician and patient stakeholders reported the PReDAS was useful to support decision-making for driving. The majority of patients recalled information provided in acute care and abstained from driving as advised. This study provides preliminary support for the clinical usefulness of the PReDAS.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.123
GPT teacher head0.505
Teacher spread0.381 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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