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Record W4210396540 · doi:10.12968/ijtr.2006.13.5.21376

Exploring social and leisure participation among stroke survivors: Part two

2006· article· en· W4210396540 on OpenAlexaff
Farah Amarshi, Lisa Artero, Denise Reid

Bibliographic record

VenueInternational Journal of Therapy and Rehabilitation · 2006
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMeaning (existential)Qualitative researchStroke (engine)GerontologyGrounded theoryPsychologySocial engagementCommunity participationSocial supportMedicineSocial psychologySociologyPsychotherapist

Abstract

fetched live from OpenAlex

Older adults who live in the community often report decreased levels of social and leisure participation following stroke. A qualitative study using open-ended, focused interviews was conducted with a sample of 12 older adult stroke survivors. This study aimed to explore how often older adult stroke survivors participate in social and leisure activities, the meaning(s) associated with this participation and the factors felt to hinder or contribute to this participation. Background information and the methodology are described in part one. In this second part, the findings and discussion of the interviews are provided. Using a modified grounded theory approach to analysis, four main themes emerged from the data: ‘it's a completely different life’; ‘what limits me from participating’; ‘what I need to participate’; and ‘continuing on with my life’. A model was developed to describe the potential relationships between the themes generated. This study highlights the re-establishment of continuity in social and leisure participation following stroke. The findings provide implications for health-care providers, who can help in developing programmes that support social and leisure participation among stroke survivors in the community

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.081
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.331
Teacher spread0.271 · 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.

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

Citations11
Published2006
Admission routes1
Has abstractyes

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