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Record W4306160140 · doi:10.3389/fpsyg.2022.1014967

Physical activity and subjective well-being of older adults during COVID-19 prevention and control normalization: Mediating role of outdoor exercise environment and regulating role of exercise form

2022· article· en· W4306160140 on OpenAlexaboutno aff
Qingqing Yang, Yue Tang, George Jennings, Bin Zhao, Fusheng Zhu, Xiujie Ma

Bibliographic record

VenueFrontiers in Psychology · 2022
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersSichuan Federation of Social Science Associations
KeywordsMediationPsychologyScale (ratio)Mental healthGerontologyBayesian multivariate linear regressionRegression analysisMedicineGeography

Abstract

fetched live from OpenAlex

Since the outbreak of the COVID-19 pandemic, the physical and mental health of older adults has been threatened. Promoting physical and mental health through physical activity has therefore become a strategy for healthy aging. In order to better understand the impact of the participation of older adults in physical activity, this paper selects different types of physical activity, and examines the relationship between them and subjective well-being through the analysis of the mediation effect of outdoor exercise environment and the regulating effect of exercise form. In this cross-sectional study, a questionnaire survey was conducted in mainland China. The main data come from 903 older adults in five urban areas in Chengdu, Sichuan Province. The surveys were carried out using the Physical Activity Rating Scale, Newfoundland Subjective Well-Being Scale, Exercise Environment Scale, and Exercise Form Scale. SPSS was used for statistical analysis, linear regression analysis was adopted for processing data, and AMOS was used to establish a mediation model. The mediating variable is the outdoor exercise environment, and the moderating variable is exercise form; gender, age, education level, and monthly income were used as control variables. The study results showed that different physical activities (tai chi; health qigong; walking and jogging) were significantly, positively correlated with the subjective well-being of older adults (tai chi: R = 0.351, p < 0.01; health qigong: R = 0.340, p < 0.01; walking and jogging: R = 0.245, p < 0.01); among the activities, tai chi had the strongest effect on the subjective well-being of older adults ( R = 0.351, p < 0.01). Outdoor exercise environment played a mediating role between different physical activity types and subjective well-being of older adults [tai chi: β = 0.030, 95% CI (0.005, 0.031); health qigong: β = 0.018, 95% CI (0.000, 0.021); walking and jogging: β = 0.034, 95% CI (0.008, 0.035)]. Exercise form moderated the subjective well-being of older adults in different physical activities (tai chi: 0.006, p < 0.05; health qigong: 0.006, p < 0.05; walking and jogging: 0.009, p < 0.001). The results of this study demonstrate that the outdoor exercise environment plays a mediating role between different physical activities and the subjective well-being of older adults, and the form of exercise can also moderate the impact of different physical activities on the subjective well-being of older adults. This study has enlightening significance for psychological intervention with older adults facing stress, anxiety and depression.

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)0.001
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 score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.278
Teacher spread0.272 · 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

Citations28
Published2022
Admission routes1
Has abstractyes

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