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Record W2056065826 · doi:10.1177/000841740507200403

ADL Differences in Individuals with Unilateral Hemispheric Stroke

2005· article· en· W2056065826 on OpenAlexvenueno aff
Patricia Rexroth, Anne G. Fisher, Brenda Merritt, Jeff Gliner

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2005
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsActivities of daily livingOccupational therapyIntervention (counseling)Stroke (engine)Physical medicine and rehabilitationPsychologyPhysical therapyMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Literature regarding the ability of individuals who have a cerebrovascular accident (CVA) to perform activities of daily living (ADL) is inconclusive regarding the impact of gender, age or side of the lesion. PURPOSE: To determine if people with a CVA differ in their abilities to perform ADL tasks and actions as affected by their gender, age, and side of the lesion. METHOD: A descriptive comparison of 3878 people with a right or left CVA included in the Assessment of Motor and Process Skills (AMPS) database. RESULTS: People with stroke demonstrated statistically significant gender, age, and side of CVA differences in overall ADL ability. However, the gender and side of CVA differences were not clinically detectable. Increased age was associated with a gradual decline in ADL ability. CONCLUSION: Individuals with a right or left CVA have similar abilities when performing ADL tasks and actions. PRACTICE IMPLICATIONS: These findings indicate that occupation-based intervention, which focuses on the utilization of intact ADL skills to compensate for ADL skill deficits (vs. the utilization of tests of body function), may be a more efficient and effective means of planning and implementing occupational therapy intervention for individuals with a stroke.

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 score0.020
Threshold uncertainty score0.891

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)0.0010.000

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 head0.059
GPT teacher head0.323
Teacher spread0.263 · 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

Citations32
Published2005
Admission routes1
Has abstractyes

Explore more

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