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PHYSICAL ACTIVITY LEVELS AND NUMBER AND DURATION OF UPPER RESPIRATORY INFECTIONS IN UNDERGRADUATE STUDENTS

2003· article· en· W2033213012 on OpenAlexaff
Heather McArel, Jeffery F. Vossen, Angela Thompson, Deborah P. Vossen

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2003
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsRespiratory tract infectionsCommon coldDuration (music)Upper respiratory tract infectionMedicinePhysical activityPhysical therapyRespiratory systemInternal medicineImmunology

Abstract

fetched live from OpenAlex

The common cold, also known as an upper respiratory tract infection (URTI) is the world's most prevalent illness. It has been suggested that URTIs are the world's most expensive illness caused by excessive numbers of lost workdays, physician visits, medications and complications; unfortunately researchers have not yet been successful in finding a cure. PURPOSE To examine the relationship between physical activity and the number and duration of upper respiratory tract infections. METHODS Undergraduate university students (n=200) completed the Paffenbarger Physical Activity Questionnaire, and a questionnaire which asked the number and length of URTIs within the previous year. Pearson product-moment correlation coefficients were used to examine the relationship between physical activity and URTIs. RESULTS Mean energy expenditure was 2674 ± 548 Kcal per day. Mean number and duration of URTIs was 2.9 ± 2.1 and 6.3 ± 4.4 days respectively. Physical activity level was significantly related to the number of URTIs (r= −0.153, p = 0.03) but not with the duration of URTI (r= −0.101, p = 0.11) CONCLUSION Given the results, it is prudent to recommend moderate participation in physical activity for optimal health benefits.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.458
Teacher spread0.400 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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