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Record W2067937226 · doi:10.1097/pep.0b013e3182750c28

The Motor Learning Strategy Instrument

2012· article· en· W2067937226 on OpenAlexaff
Danielle Levac, Cheryl Missiuna, Laurie Wishart, Carol DeMatteo, F. Virginia Wright

Bibliographic record

VenuePediatric Physical Therapy · 2012
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsCanadian Foundation for Healthcare ImprovementHolland Bloorview Kids Rehabilitation HospitalMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsInter-rater reliabilityGeneralizability theoryPsychological interventionReliability (semiconductor)PsychologyPhysical therapyIntervention (counseling)Physical medicine and rehabilitationMedicineRating scaleDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate and compare the interrater reliability of the Motor Learning Strategy Rating Instrument (MLSRI) within usual and virtual reality (VR) interventions for children with acquired brain injury. METHODS: Two intervention sessions for each of 11 children (total, 22) were videotaped; sessions were provided by 4 physical therapists. Videotapes were divided into usual and VR components and rated by 2 observers using the MLSRI. A generalizability theory approach was used to determine interrater reliability for each intervention. RESULTS: Interrater reliability for usual interventions was high for the MLSRI total score (g-coefficient, 0.81), whereas it was low for the VR total score (g-coefficient, 0.28); MLSRI category g-coefficients varied from 0.35 to 0.65 for usual and from 0.17 to 0.72 for VR interventions. CONCLUSION: Adequate reliability was achieved within ratings of usual interventions; however, challenges related to MLSRI use to rate VR-based interventions require further evaluation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.280

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 head0.027
GPT teacher head0.290
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

Citations12
Published2012
Admission routes1
Has abstractyes

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