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Record W7024716905

Risk Perception and Physical Activity During COVID-19 Among Male and Female University Students: Using an Extended Health Belief Model

2023· article· en· W7024716905 on OpenAlexaff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsQueen's University
Fundersnot available
KeywordsPerceptionPhysical activityRegression analysisHealth belief modelRisk perceptionRegression
DOInot available

Abstract

fetched live from OpenAlex

Background: Previous studies have shown that young adults are faced with physical, emotional, and psychological threats due to the COVID-19. In particular, the overall level of physical activity (PA) among college students has markedly decreased during the pandemic. It is necessary to find underlying mechanisms of PA behavior in COVID-19, as health-related behaviors formed during the college years can be maintained throughout a lifetime. Purpose: The present study aimed to examine the impact of perceptions toward COVID-19 and PA on PA participation among South Korean university students. Methods: Data were collected online from 150 South Korean undergraduate students. Gender-stratified multiple regression analysis was used to identify the relationships between perceptions and PA. We also analyzed moderate PA (MPA) and vigorous PA (VPA) separately to identify different aspects of PA participation according to the type of PA in the COVID-19 context. Results: Regression analysis revealed that both male (Coef=432.64, p

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)0.005
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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.295
Teacher spread0.276 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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