MétaCan
Menu
Back to cohort
Record W2009778816 · doi:10.1016/j.pmrj.2010.03.030

Driving and Reintegration Into the Community in Patients After Stroke

2010· article· en· W2009778816 on OpenAlexafffundabout
Hillel M. Finestone, Meiqi Guo, Paddi O’Hara, Linda S. Greene-Finestone, Shawn Marshall, Lynn Hunt, Jennifer Biggs, Anita Jessup

Bibliographic record

VenuePM&R · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsPublic Health Agency of CanadaÉlisabeth Bruyère HospitalQueen's UniversityOttawa HospitalCanadian Institutes of Health ResearchUniversity of Ottawa
FundersCanadian Institutes of Health ResearchRoyal National Lifeboat InstitutionHeart and Stroke Foundation of Canada
KeywordsMedicineStroke (engine)Physical medicine and rehabilitationPhysical therapyEngineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the relationship between driving versus not driving and community integration after stroke. Much research on patients who drive after experiencing a stroke has focused on driving assessment protocols; little attention has been given to the implications of assessment outcomes. DESIGN: Prospective study. SETTING: Six driving evaluation centers in Ontario, Canada. PARTICIPANTS: Fifty-three community-dwelling patients who were referred for a driving assessment after they experienced a stroke. METHODS: Data on demographics, living circumstances, health status, driving habits, and driving history were gathered via a semistructured interview and various questionnaires administered on 3 occasions: study entry (> or =1 month after stroke; n = 53), 3 months (n = 44), and 1 year (n = 43). MAIN OUTCOME MEASUREMENT: Reintegration into the community at 1 year, as evaluated with the Reintegration to Normal Living Index (RNLI). RESULTS: The participants had sustained a stroke an average of 12.3 months before study entry. Two subjects were driving at study entry. At 1 year, 28 (65%) of 43 subjects had passed their driving test and had resumed/continued driving. Nondrivers had a significantly lower mean RNLI score than drivers. Subjects who were not driving at study entry but had resumed driving by 1 year had a significant increase in RNLI score (P = .011). Driving was significantly associated with community integration after adjustment for concomitant health status (P < .001). Driving and health status were associated with community integration at 1 year, accounting for 32% of the variance in RNLI score. CONCLUSIONS: Driving after stroke was significantly associated with community integration in patients after adjustment for health status (P < .001). Community decision-makers may decide to use the study results when determining the transportation needs of stroke survivors who self-limit their driving because of weather, time of day, or distance concerns.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.356
Teacher spread0.335 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations51
Published2010
Admission routes3
Has abstractyes

Explore more

Same venuePM&RSame topicOlder Adults Driving StudiesFrench-language works237,207