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Record W4404095721 · doi:10.1016/j.arrct.2024.100384

Psychometrics of Wearable Devices Measuring Physical Activity in Ambulant Children With Gait Abnormalities: A Systematic Review and Meta-analysis

2024· review· en· W4404095721 on OpenAlexaff
Huib van Moorsel, Barbara Engels, Jacek Buczny, Jan Willem Gorter, Kelly P. Arbour‐Nicitopoulos, Tim Takken, Raoul Engelbert, Manon Bloemen

Bibliographic record

VenueArchives of Rehabilitation Research and Clinical Translation · 2024
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of TorontoMcMaster University
FundersNationaal Regieorgaan Praktijkgericht Onderzoek SIA
KeywordsPhysical medicine and rehabilitationMeta-analysisGaitGait analysisWearable computerPsychometricsMedicinePhysical therapyPsychologyComputer scienceClinical psychologyPathology

Abstract

fetched live from OpenAlex

<h2>Abstract</h2><h3>Objective</h3> To evaluate psychometrics of wearable devices measuring physical activity (PA) in ambulant children with gait abnormalities due to neuromuscular conditions. <h3>Data Sources</h3> We searched PubMed, Embase, PsycINFO, CINAHL, and SPORTDiscus in March 2023. <h3>Study Selection</h3> We included studies if (1) participants were ambulatory children (2-19y) with gait abnormalities, (2) reliability and validity were analyzed, and (3) peer-reviewed studies in the English language and full-text were available. We excluded studies of children with primarily visual conditions, behavioral diagnoses, or primarily cognitive disability. We performed independent screening and inclusion, data extraction, assessment of the data, and grading of results with 2 researchers. <h3>Data Extraction</h3> Our report follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We assessed methodological quality with Consensus-based Standards for the selection of health measurement instruments. We extracted data on reported reliability, measurement error, and validity. We performed meta-analyses for reliability and validity coefficient values. <h3>Data Synthesis</h3> Of 6911 studies, we included 26 with 1064 participants for meta-analysis. Results showed that wearables measuring PA in children with abnormal gait have high to very high reliability (intraclass correlation coefficient [ICC]<sub>+, test-retest reliability</sub>=0.81; 95% confidence interval [CI], 0.74-0.89; <i>I</i><sup>2</sup>=88.57%; ICC<sub>+, interdevice reliability</sub>=0.99; 95% CI, 0.98-0.99; <i>I</i><sup>2</sup>=71.01%) and moderate to high validity in a standardized setting (<i>r</i><sub>+, construct validity</sub>=0.63; 95% CI, 0.36-0.89; <i>I</i><sup>2</sup>=99.97%; <i>r</i><sub>+, criterion validity</sub>=0.68; 95% CI, 0.57-0.79; <i>I</i><sup>2</sup>=98.70%; <i>r</i><sub>+, criterion validity cutoff</sub> <sub>point based</sub>=0.69; 95% CI, 0.58-0.80; <i>I</i><sup>2</sup>=87.02%). The methodological quality of all studies included in the meta-analysis was moderate. <h3>Conclusions</h3> There was high to very high reliability and moderate to high validity for wearables measuring PA in children with abnormal gait, primarily due to neurological conditions. Clinicians should be aware that several moderating factors can influence an assessment.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.765
Threshold uncertainty score0.556

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.247
GPT teacher head0.482
Teacher spread0.235 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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