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Record W4400655241 · doi:10.36740/merkur202403102

Aral Sea environmental disasters area population’s physical activity level assessment – the first step for targeted health promotion

2023· article· en· W4400655241 on OpenAlexaboutno aff
Akmaral Baspakova, Aigul Aldanova, Ainur Zinalieva, Aigerim A. Umbetova, Amina Makhashbay, Yeltay Rakhmanov

Bibliographic record

VenuePolski Merkuriusz Lekarski · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsRecreationPhysical activityDemographyPopulationPromotion (chess)Quarter (Canadian coin)MedicineHealth promotionEnvironmental healthGerontologyGeographyPublic healthPhysical therapyEcologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Aim: We aimed to assess the physical activity and sedentary behavior of the population living in the Aral Sea area using the Global Physical Activity Questionnaire. PATIENTS AND METHODS: Materials: Data was collected from seven out-patient settings involving 445 participants (47.6% females, 52.4% males). The age of 33.6% of respondents was over 65. RESULTS: Results: Nearly a quarter (23.5%) of the participants did not meet World Health Organization physical activity recommendations. The Median Time spent on physical activity in recreation in all dispensaries among males (Md=34.29, IQR=66.43) was signif i cantly higher (Z=-4.78, p<0.001) than females (Md=12.86, IQR=51.43). A signif i cant association was observed between transport-related physical activity and gender (χ2= 5.60, p=0.018). The average percentage that comes from recreation-related activities among males (M=43.69, SD=26.90) was more signif i cant (MD=6.27, 95% CI: 0.46, 12.07) as compared to that of females (M=37.43, SD=31.66). A signif i cant association was observed between engagement in vigorous activity and gender (χ2= 30.77, p<0.001). CONCLUSION: Conclusions: Environmental, economic, demographic, and cultural peculiarities of the Aral Sea area should be considered in elaborating specif i c health promotion programs to shift health-harming ambient into health-improving environment.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.999

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.076
GPT teacher head0.350
Teacher spread0.273 · 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.

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
Published2023
Admission routes1
Has abstractyes

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