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Record W2145410698 · doi:10.1123/jpah.6.1.6

Participation by US Adults in Sports, Exercise, and Recreational Physical Activities

2009· article· en· W2145410698 on OpenAlexaboutno aff
Sandra A. Ham, Judy Kruger, Catrine Tudor‐Locke

Bibliographic record

VenueJournal of Physical Activity and Health · 2009
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationNational Health and Nutrition Examination SurveyPhysical activityLeisure timeGerontologyPhysical therapyQuarter (Canadian coin)MedicinePhysical exercisePsychologyEnvironmental healthPopulationGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Given the evidence that regular physical activity produces substantial health benefits, participation in sports, exercise, and recreation is widely encouraged. The objective of this study was to describe participation in sports, exercise, and recreational physical activities among US adults. METHODS: Data from 2 national surveys of respondents age 18 years and older were analyzed. Respondents to the American Time Use Survey (ATUS) from 2003 through 2005 (N=45,246) reported all activities on 1 randomly selected survey day. Respondents to the National Health and Nutrition Examination Survey (NHANES) from 1999 through 2004 (N=17,061) reported leisure-time physical activities in the 30 days before the interview. RESULTS: One-quarter of adults participated in any sport, exercise, or recreational activity on a random day, and 60.9% of adults participated in any leisure-time activity in the previous 30 days. The most common types of activities were walking, gardening and yard work, and other forms of exercise. The sports and recreational activities had typical durations of 1/2 to 3 hours per session, and the exercise activities typically lasted 1 hour or less. CONCLUSIONS: The prevalence of sports, exercise, and recreational physical activities is generally low among US adults; exercise is the most commonly reported type of activity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.035
GPT teacher head0.365
Teacher spread0.330 · 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 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

Citations147
Published2009
Admission routes1
Has abstractyes

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