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Record W1964335829 · doi:10.1310/tsr1805-509

An Ecological Approach to Activity After Stroke: It Takes a Community

2011· article· en· W1964335829 on OpenAlexaff
Sharon Anderson, Kyle Whitfield

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2011
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiopsychosocial modelRehabilitationInclusion (mineral)Stroke (engine)Situational ethicsActivities of daily livingPsychologyGerontologyInternational Classification of Functioning, Disability and HealthIntervention (counseling)Physical medicine and rehabilitationMedicinePhysical therapySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Biopsychosocial recovery from stroke is remarkable for some individuals, but the majority of stroke survivors have difficulty resuming activities. Even survivors with mild disability become disengaged. METHODS: Situational analysis grounded theory and ecological models were used to examine the barriers and facilitators to choice of everyday activities of stroke survivors aged 50 to 64 years. RESULTS: Resuming activities was an iterative process of scaffolding small tasks into activities through bargaining for access to practical support and inclusion into social situations. Although participants geared up to manage their condition and access activities, for the most part they were not in charge of the services and supports they required. They had little control over who was accepted to rehabilitation, for which services they qualified or disability policies. CONCLUSIONS: There are layers of interactions between individuals and multiple factors in their environments that influence participation. Low poststroke activity levels may be amenable to intervention. Further research should consider the following: (1) participation in activities through the lens of all levels of the socioecological model; (2) the impact of disability and aging-related stigma; (3) the results of ad hoc community navigation; and (4) the effects of restrictive health and disability policies on meaningful activity.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.073
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.052
GPT teacher head0.318
Teacher spread0.266 · 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

Citations31
Published2011
Admission routes1
Has abstractyes

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