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Record W2947475902 · doi:10.1093/ptj/pzz022

Validating Accelerometry as a Measure of Arm Movement for Children With Hemiplegic Cerebral Palsy

2019· article· en· W2947475902 on OpenAlexafffund
Jaclyn Dawe, Jaynie F. Yang, Darcy Fehlings, Jirapat Likitlersuang, Peter Rumney, José Zariffa, Kristin E. Musselman

Post-publication record

NatureReinstatement
ReasonDate of Article and/or Notice Unknown;Error by Journal/Publisher;Notice - Limited or No Information;Retract and Replace;Temporary Removal;
Date2/26/2019 0:00
Flagged by OpenAlex?No. Retraction Watch records this, and OpenAlex does not flag it.

Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.

Bibliographic record

VenuePhysical Therapy · 2019
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalWomen and Children’s Health Research InstituteUniversity of AlbertaToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersToronto Rehabilitation InstituteUniversity Health Network
KeywordsCerebral palsyPhysical medicine and rehabilitationMovement (music)Measure (data warehouse)Movement disordersMedicinePhysical therapyPsychologyComputer sciencePhysicsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: For children with hemiplegic cerebral palsy (HCP), rehabilitation aims to increase movement of the affected arm. However, no validated measure objectively examines this construct in pediatric practice or daily life. OBJECTIVE: The objective of this study was to evaluate the criterion and known-groups validity of accelerometry as a measure of arm movement in children and adolescents with HCP. DESIGN: This was a prospective cross-sectional study. METHODS: Twenty-seven children and adolescents with typical development (3.4-13.9 years old) and 11 children and adolescents with HCP (4.7-14.7 years old; Manual Ability Classification System rating I or II) wore accelerometers on their wrists while engaged in 20 minutes of play, which included intermittent intervals of stillness and vigorous movement of the arms. Vector magnitude (VM) values identified the presence (VM > 2.0 counts per epoch) and absence (VM ≤ 2.0 counts per epoch) of arm movement for every 2-second epoch. Video was simultaneously recorded; each 2-second interval of footage was scored as "movement" or "no movement" for each arm. RESULTS: Agreement between accelerometry and video observation was greater than or equal to 81%, and the prevalence-adjusted and bias-adjusted κ value was greater than or equal to 0.69 for both groups of participants; these results supported the criterion validity of accelerometry. The ratio of nondominant arm movement to dominant arm movement measured by accelerometry was significantly greater in participants with typical development (mean [SD] = 0.87 [0.09]) than in participants with HCP (mean = 0.78 [0.07]) on the basis of 10 age- and sex-matched pairs; these results supported known-groups validity. LIMITATIONS: The small sample size of the group with HCP prevented the stratification of data by age. Participants with HCP had high or moderately high function of the affected arm; hence, the findings do not apply to children and adolescents with more significant hemiparesis. CONCLUSIONS: Accelerometry is a valid measure of arm movement in children with HCP and children without HCP. These findings contribute to the development of innovative upper limb assessments for children with hemiparesis.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.532

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 head0.026
GPT teacher head0.291
Teacher spread0.265 · 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 designBench or experimental
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

Citations16
Published2019
Admission routes2
Has abstractyes

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