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Record W2981041083 · doi:10.29011/2577-2228.100024

Respiratory Health and Housing for University Undergraduate Students

2018· article· en· W2981041083 on OpenAlexaff
Shantel Mangroo, Mika Nonoyama, Otto Sánchez, Caroline Barakat

Bibliographic record

VenueJournal of Community Medicine & Public Health · 2018
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsMedical educationPsychologyMathematics educationMedicine

Abstract

fetched live from OpenAlex

Background: Diverse factors affect the overall health of undergraduate students.These factors pertain to multiple physical and social environmental exposures, individual behaviours, and genetic predispositions.Research generally recognizes that the most common illnesses experienced by this population are respiratory-related.Within the home, exposures may include indoor air pollutants including environmental tobacco smoke and other ubiquitous chemicals, mould from water damage, and allergens.Although individuals may engage in behaviours to reduce these exposures, these exposures persist and can negatively impact respiratory health.Objectives: To assess the prevalence of wheezing and whistling symptoms, dry cough, and difficulties breathing, in relation to environmental exposures from housing accommodations among the undergraduate university population; and to explore predictors on these health outcomes, as well as the role of three housing types (on-campus, off campus, with family). Methods:We developed an online health questionnaire to collect data related to the sociodemographic and respiratory health of the study population.Spirometry was also conducted to collect lung function (FVC, FEV1, PEF, and FEV1%).Results: A total sample of 213 participants completed the questionnaire, of which 180 also underwent spirometry testing.Overall, 40% of university undergraduate students reported being sick within the last 30 days with 36% reporting that their sickness was respiratory-related.Type of housing accommodation did not appear to affect wheezing and whistling symptoms or difficulties breathing, however participants who indicated living in a housing accommodation older than 11 years were 3.28 times more likely to experience dry cough at night than those living in a housing accommodation 1-10 years old.Based on spirometry, no participants had restrictive or obstructive lung disease.Conclusions: This study suggests there are no significant differences in respiratory health based on type of housing accommodation.However, this study suggests the age of the housing accommodation is a predictor of dry cough.Furthermore, the prevalence of wheezing/whistling symptoms, dry cough, and difficulties breathing does not appear to be correlated with the type of housing accommodation resided in.This implies that the type of housing accommodation does not have an impact on respiratory health symptoms for 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)0.000
metaresearch head score (Gemma)0.002
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 score0.018
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.278
GPT teacher head0.517
Teacher spread0.239 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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