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Record W2169437917 · doi:10.15453/2168-6408.1120

Home-based Constraint Induced Movement Therapy Poststroke

2014· article· en· W2169437917 on OpenAlexaff
Stephen Isbel, Christine Chapparo, David McConnell, Judy Ranka

Bibliographic record

VenueThe Open Journal of Occupational Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsConstraint-induced movement therapyOccupational therapyPhysical medicine and rehabilitationMovement (music)Constraint (computer-aided design)PsychologyPhysical therapyMedicineRehabilitationArtAesthetics

Abstract

fetched live from OpenAlex

Background: This study examined the efficacy of a home-based Constraint Induced Movement Therapy (CI Therapy) protocol with eight poststroke survivors. Method: Eight ABA, single case experiments were conducted in the homes of poststroke survivors. The intervention comprised restraint of the intact upper limb in a mitt for 21 days combined with a home-based and self-directed daily activity regime. Motor changes were measured using The Wolf Motor Function Test (WMFT) and the Motor Activity Log (MAL). Results: Grouped results showed statistically and clinically significant differences on the WMFT (WMFT [timed items]): Mean 7.28 seconds, SEM 1.41, 95% CI 4.40 – 10.18, p = 0.000; WMFT (Functional Ability): z = -4.63, p = 0.000). Seven out of the eight participants exceeded the minimal detectable change on both subscales of the MAL. Conclusion: This study offers positive preliminary data regarding the feasibility of a home-based CI Therapy protocol. This requires further study through an appropriately powered control trial.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.093
GPT teacher head0.378
Teacher spread0.286 · 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 designNon-randomized trial
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

Citations1
Published2014
Admission routes1
Has abstractyes

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