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Record W4394932878 · doi:10.3390/future2020004

Supporting Functional Goals in Spinal Muscular Atrophy: A Case Report of The Cognitive Orientation to Daily Occupational Performance (CO-OP) Approach

2024· article· en· W4394932878 on OpenAlexaboutno aff
Stephanie Taylor, Iona Novak, Michelle Jackman

Bibliographic record

VenueFuture · 2024
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsSpinal muscular atrophyOrientation (vector space)CognitionPhysical medicine and rehabilitationAtrophyPsychologyMedicinePhysical therapyNeurosciencePathology

Abstract

fetched live from OpenAlex

Children with spinal muscular atrophy (SMA) are now living longer as a result of advancements in pharmaceutical and medical interventions. There is a paucity of research regarding therapeutic interventions to support this population to be independent and participate in life activities that are most important to them. The aim of this case report is to explore the use of the Cognitive Orientation to daily Occupational Performance (CO-OP) approach to support a child with SMA type 1 to achieve their functional and participation goals. This is a retrospective case study. A 7-year-old girl with SMA type 1 received ten 1 h sessions of CO-OP, weekly in the home and community settings with a physiotherapist. Clinically meaningful improvements were found in goal performance and satisfaction on the Canadian Occupational Performance Measure (COPM) and Performance Quality Rating Scale (PQRS). Despite the progressive nature of SMA, the CO-OP approach was able to support goal attainment. Given medical advances are leading to a longer life span for children with neuromuscular conditions, further research is needed to investigate the efficacy of functional and participation-based interventions, including impact on quality of life and self-efficacy.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0060.006
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 head0.028
GPT teacher head0.358
Teacher spread0.331 · 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 designCase report
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
Published2024
Admission routes1
Has abstractyes

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