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Record W6996059729

Protocol for a scoping review: The use of accelerometers on preschool aged children: a methodological review

2018· other· en· W6996059729 on OpenAlexfundno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2018
Typeother
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsAccelerometerProtocol (science)Data collectionmHealth
DOInot available

Abstract

fetched live from OpenAlex

Background:Investigation of physical activity (PA) levels in Canadian preschool aged children (6 months-6 years) is essential in order to determine whether or not they are meeting current national recommendations of 180 minutes of any type of PA per day.However, major methodological inconsistencies may be preventing proper representation of how much and what types of activities these children are actually completing on a daily basis.Although advances in wearable technology have permitted researchers to capture free -living movement in adult, adolescent and school-aged child populations, few studies have validated and calibrated the use of accelerometers in preschool aged children.Among the studies that have been completed in this population, major methodological inconsistencies exist with regards to data processing and other methodological considerations, making it impossible to compare results across studies.To improve tracking of PA in children aged 6 months-6 years, a standardized best practices protocol should be developed; therefore, a review of the current data processing technics is imperative. Methods:Intervention studies and randomized and non-randomized clinical trials describing PA tracking through use of accelerometers in children aged 6 months-6 years from the last ten years are eligible for inclusion.Eligible outcome measures include accelerometer model, accelerometer placement, sample rate, epoch length, and data processing measures including "non-wear" time definition, description of a "valid day" and cut points used for defining each intensity of PA.The search strategy will use Medline (via OvidSP), Cochrane Library, CINAHL, Web of Science and Global Health.A search of the gray literature will be conducted through Google Scholar (first 20 pages) and ProQuest conference papers and proceedings, ProQuest dissertations and Open Access Theses and Dissertations.Discussion: This review will aim to provide a summary of the current methodological techniques used to track PA in a preschool aged population found within the literature.Emphasis will be placed on the frequency of reporting for the outcome measures listed above.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.097
metaresearch head score (Gemma)0.189
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.903
Threshold uncertainty score0.516

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0970.189
Meta-epidemiology (narrow)0.0090.013
Meta-epidemiology (broad)0.0280.031
Bibliometrics0.0210.019
Science and technology studies0.0080.007
Scholarly communication0.0160.009
Open science0.0060.009
Research integrity0.0170.015
Insufficient payload (model declined to judge)0.1130.022

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 head0.234
GPT teacher head0.407
Teacher spread0.173 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Systematic review
DomainMethods
GenreProtocol

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
Published2018
Admission routes1
Has abstractno

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