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Record W1504779793 · doi:10.1161/str.46.suppl_1.ns16

Abstract NS16: What’s Important for Post-Stroke Community Re-integration? Viewpoints of Stroke Survivors and Service Providers in Ontario, Canada

2015· article· en· W1504779793 on OpenAlexaffabout
Darren Jermyn, Phyllis Montgomery, Sharolyn Mossey, Patricia Hill Bailey, Parveen Nangia, Mary Egan, Sue Verrilli

Bibliographic record

VenueStroke · 2015
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of OttawaLaurentian UniversityHealth Sciences North
Fundersnot available
KeywordsMedicineViewpointsService providerStroke (engine)Service (business)Qualitative researchNursingGerontologyFamily medicine

Abstract

fetched live from OpenAlex

Background: Stroke is a leading cause of disability worldwide. Stroke survivors living in the community require regular, ongoing, and coordinated services to prevent deterioration and maximize health outcomes. Published evidence, often conducted in large urban centres, suggests that community reintegration services are an important component of care for stroke survivors. This evidence, however, often does not address the particular challenges inherent in servicing stroke survivors who reside in smaller urban and rural contexts. Purpose: The purpose of this study was to gain an understanding of the priorities that are needed to support stroke recovery and community reintegration from the perspectives of survivors and service providers living in four geographic districts in Northeastern Ontario, Canada. Methods: Using Q methodology, 45 service providers, and 43 stroke survivors and their family caregivers ranked 30 theoretical statement cards. Each card identified a feature specific to stroke recovery, community navigation and community reintegration. These statements were generated through a review of health care literature and qualitative data collected from interviews with stroke survivors. Q analysis of the priority ranked statements involved centroid factor analysis and varimax rotation. Results: The three discrete viewpoints of survivors were Role of Skilled Navigators, Survivors as Co-navigators, and Striving for Well-being. The survivors’ consensus perspective, labelled Quality Service, identified the importance of timeliness and appropriateness of service. The three discrete viewpoints for service providers were Role of Skilled Navigators, Survivor-centered Practices, and Optimizing Survivors’ Resources. The consensus perspective of service providers was labelled Involvement of Family Carers. Findings were consistent across all 4 geographic districts. Conclusion: This research suggests that survivors’ and providers’ conceptualized role of community navigators is focused on building upon the strengths and capacity of survivors through cooperative inquiry with multiple stakeholders. A time-sensitive, appropriate, and family involved service structure supports survivor-centric community reintegration.

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)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.886

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0220.005
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.277
Teacher spread0.246 · 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 designQualitative
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

Citations0
Published2015
Admission routes2
Has abstractyes

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