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Record W4220885215 · doi:10.1080/14927713.2022.2054459

The effects of individual-level and area-level socioeconomic status on preferences and behaviour in leisure time physical activities: a cross-sectional analysis of Chinese adults

2022· article· en· W4220885215 on OpenAlexvenueno aff
Nan Chen, KangJae Jerry Lee, Jaehyun Kim, Chiung‐Tzu Lucetta Tsai

Bibliographic record

VenueLeisure/Loisir · 2022
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusCross-sectional studyPsychologyPhysical activityLeisure timeGerontologyEnvironmental healthMedicinePhysical therapy

Abstract

fetched live from OpenAlex

This study examines the extent to which individual and area-level socioeconomic statuses (SES) correlate with the preferences and participation in physical activities during leisure time. A multistage, random clustered sample taken from the China Health and Nutrition Survey of 2015 was used. Results from multi-level analyses indicated that both individual income and area-level SES were significantly associated with participation in walking, whereas individual educational attainment was positively associated with participation in sports. Moreover, leisure preference mediated the relationship between individual SES, area-level SES, and participation in sports. Based on these findings, this article suggests that both individual and area-level influences should be taken into account when developing health policies to promote active lifestyles. In addition, mediation effect of leisure preference in LTPA should be emphasized when implementing intervention program.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.018
GPT teacher head0.287
Teacher spread0.269 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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