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Record W2052254763 · doi:10.3200/jach.56.1.37-42

The Prevalence of Physical Activity Maintenance in a Sample of University Students: A Longitudinal Study

2007· article· en· W2052254763 on OpenAlexaff
Jennifer D. Irwin

Bibliographic record

VenueJournal of American College Health · 2007
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsWestern University
Fundersnot available
KeywordsPhysical activityPsychological interventionMedicineHealth maintenanceGerontologyLongitudinal studyCollege healthPopulationPhysical activity levelGuidelineEnvironmental healthPsychologyPhysical therapyFamily medicineHealth careNursing

Abstract

fetched live from OpenAlex

UNLABELLED: The health and financial costs of physical inactivity are staggering. Few researchers have assessed the prevalence of physical activity at the level needed to gain health benefits. OBJECTIVE: The author's purpose in this longitudinal study was to assess the prevalence of university students who maintained physical activity at the level necessary for health gains for at least 1 month. PARTICIPANTS: University students (N = 392) from 2 campuses participated in this 1-month study. METHODS: The author administered a survey to the same group of students at baseline and 1 month later to assess the prevalence of students who met and maintained the physical activity guideline for health (PAGH). RESULTS: Thirty-five percent of students maintained the PAGH for 1 month. CONCLUSION: The majority of students in this study were insufficiently physically active. Given that insufficient physical activity may lead to serious health concerns, interventions are needed to improve activity maintenance in this population.

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 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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.381
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), 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

Citations107
Published2007
Admission routes1
Has abstractyes

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