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Record W2772013587 · doi:10.1097/pep.0000000000000458

Power Mobility Training Methods for Children: A Systematic Review

2017· review· en· W2772013587 on OpenAlexaff
Lisa K. Kenyon, Lisa Hostnik, Rachel McElroy, Courtney Peterson, John Farris

Bibliographic record

VenuePediatric Physical Therapy · 2017
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsTraining (meteorology)Power (physics)Physical medicine and rehabilitationMEDLINEPsychologyComputer scienceMedicinePolitical scienceGeography

Abstract

fetched live from OpenAlex

PURPOSE: To summarize and critically appraise the existing evidence related to power mobility training methods used in research studies conducted with children 21 years or younger. METHODS: A systematic review was conducted using 16 electronic databases to identify primary source quantitative studies published in peer-reviewed journals. Data extraction, determination of level of evidence, evaluation of methodological rigor, and assessment of the risk of bias were completed. The Evidence Alert Traffic Light Grading System (EATLS) was used. RESULTS: Twenty-seven studies were included in the review. Levels of evidence were II to V; scientific rigor scores were 2 to 7. CONCLUSIONS: An overall Yellow EATLS level of evidence was found indicating that therapists should use caution when providing power mobility training interventions and measure outcomes related to established goals in areas such as development, functional skills, or use of a power mobility device.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.622
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.003
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 head0.141
GPT teacher head0.476
Teacher spread0.335 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations42
Published2017
Admission routes1
Has abstractyes

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