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Record W2252039819 · doi:10.21149/spm.v57i5.7620

Assessing the physical activity environment in Mexican healthcare settings

2015· article· en· W2252039819 on OpenAlexaff
Karla I. Galavíz, Rebecca E. Lee, Kim Bergeron, Lucie Lévesque

Bibliographic record

VenueSalud Pública de México · 2015
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsQueen's University
FundersNational Cancer Institute
KeywordsStairsSignageHealth careQuality (philosophy)MedicineFamily medicineEnvironmental healthGerontologyNursingBusinessGeographyAdvertising

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the informational, educational and instrumental environments among Mexican healthcare settings for their potential to promote physical activity (PA). MATERIALS AND METHODS: The Environmental Physical Activity Assessment Tool for Healthcare Settings (EPATHS) was developed to assess the PA environments of 40 clinics/hospitals representing the three Mexican healthcare systems in Guadalajara. The EPATHS assessed the presence and quality of PA enhancing features in the informational (e.g. signage), educational (e.g. pamphlets), and instrumental (e.g. stairs) environments of included clinics/hospitals. RESULTS: 28 (70%) clinics/hospitals had more than one floor with stairs; 60% of these had elevators. Nearly 90% of stairs were visible, accessible and clean compared to fewer than 30% of elevators. Outdoor spaces were observed in just over half (55%) of clinics/hospitals, and most (70%) were of good quality. Only 25% clinics/hospitals had educational PA materials. CONCLUSIONS: The PA instrumental environment of Mexican healthcare settings is encouraging. The informational and educational environments could improve.

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)0.001
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 score0.720
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.087
GPT teacher head0.385
Teacher spread0.298 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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