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Record W2062004955 · doi:10.1249/mss.0b013e3181d58a92

Descriptive Epidemiology of Youth Pedometer-Determined Physical Activity

2010· article· en· W2062004955 on OpenAlexaff
Cora L. Craig, Christine Cameron, Joseph M Griffiths, Catrine Tudor‐Locke

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2010
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsCanadian Fitness and Lifestyle Research Institute
Fundersnot available
KeywordsPedometerDescriptive statisticsPopulationPsychological interventionPhysical activityEpidemiologyMedicineDemographyPhysical therapyGerontologyPsychologyEnvironmental healthStatisticsMathematics

Abstract

fetched live from OpenAlex

PURPOSE: Objective measurement with body worn instrumentation is a preferred and increasingly common way to gather information about young people's physical activity. Measured samples have been typically small and recruited through schools. The purpose of this article was to present the descriptive epidemiology of children and youth pedometer-determined physical activity on the basis of a large national sample. METHODS: Children and youth (19,789) were recruited through random digit dialing. Participants were asked to wear the pedometer for seven consecutive days and to log daily steps. Of the 58% of participants who returned pedometer data, 95% wore the pedometer for at least 5 d. Daily step counts below 1000 or above 30,000 steps were truncated accordingly, and all values were included in the descriptive analysis. RESULTS: Boys and girls aged 5-19 yr took 12,259 and 10,906 steps per day, respectively. Daily steps were higher among boys than girls and declined by age group in a pattern consistent with that predicted by other smaller samples internationally. Weekday steps per day were generally higher than weekend day steps per day and varied by season. CONCLUSIONS: This study demonstrates the viability of using relatively inexpensive pedometers and methods for the surveillance of young people's physical activity. The resulting descriptive data provide key information regarding the population distribution of pedometer-determined physical activity that may be useful for identifying target groups for population strategies and other interventions.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
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 head0.077
GPT teacher head0.369
Teacher spread0.292 · 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 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

Citations73
Published2010
Admission routes1
Has abstractyes

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