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Record W2291213997 · doi:10.1161/str.43.suppl_1.a3123

Abstract 3123: Toolkit for Return to Work after Stroke

2012· article· en· W2291213997 on OpenAlexaffabout
Paula M. Gilmore, John Barry, Jeffrey L. Blanchard, Shannon Howson

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsParkwood InstituteLondon Health Sciences Centre
Fundersnot available
KeywordsStroke (engine)MedicineRehabilitationNursingHealth careSocial workWork (physics)Quality of life (healthcare)Stroke recoveryGerontologyPhysical therapy

Abstract

fetched live from OpenAlex

Background: The Southwestern Ontario (SWO) Stroke Network completed community engagement forums with stroke survivors, their loved ones and community service providers to determine barriers to living fully in the community after stroke. One of the priorities identified in the forums was the need for "return to work" services. Currently, 10 % of stroke survivors are people under the age of 50 and in the prime of their working life. Research indicates that return to work rates after stroke are as low as 7%. However, employment is one of the most important social roles that a person fulfills and not working has negative impacts on one’s overall quality of life, health, finances, social isolation and self-efficacy. Stroke survivors and health care professionals need to be aware of how to navigate the process of return to work after stroke. Purpose: A toolkit of resources has been developed to assist stroke survivors and health care professionals navigate the process of return to work after stroke. Methods: A working group comprised of experts in vocational rehabilitation and stroke care developed a toolkit of resources to educate and assist stroke survivors and health care professionals navigate the complex system of return to work. The resources have undergone an external review by health care professionals and stroke survivors. Results: Resources developed include a self assessment guide. It assesses five critical areas to return to work by evaluating the stroke survivor’s current abilities against the demands of the job and is designed to help focus the individual’s recovery efforts. Algorithms on how to navigate the system of return to work, including how to traverse the system of financial benefits and questions to ask employers and information on community financial supports were developed. A literature review and inventories outlining services for persons with stroke, who are preparing to re-enter the workforce, are part of the toolkit. Health care providers and stroke survivors have confirmed the face to face validity of the resources. Conclusions: Research indicates that stroke survivors should be encouraged to evaluate their potential of returning to work and should receive support from knowledgeable professionals regarding return to work as soon as possible after stroke. This toolkit is intended to support stroke survivors and their health care professionals to navigate the system for a successful return to work. Next steps include the development of a website to assist with return to work.

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)0.005
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.060
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0030.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0600.024

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 head0.019
GPT teacher head0.293
Teacher spread0.274 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2012
Admission routes2
Has abstractyes

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