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Record W2053481959 · doi:10.1080/13548500500155941

Counteracting stress through leisure coping: A prospective health study

2006· article· en· W2053481959 on OpenAlexaffabout
Yoshitaka Iwasaki

Bibliographic record

VenuePsychology Health & Medicine · 2006
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsResearch ManitobaUniversity of Manitoba
Fundersnot available
KeywordsCoping (psychology)PsychologySocial classSocial supportDevelopmental psychologyClinical psychologyGerontologySocial psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

The purpose of this study was to examine stress-buffer or -counteracting effects of leisure coping, by taking into account several key axes of society (i.e., gender, social class, and age) that are essential to characterize the diverse nature of our society. A 1-year prospective survey of a representative sample (n = 938) from an urban Canadian city was conducted. In the total sample, long-term health protective benefits of leisure coping became evident when stress levels were higher than lower (i.e., support for buffer effects of leisure coping). However, a health-protective effect of leisure coping to counteract the impact of stress on health was found substantially stronger for people with lower social class than for those with higher social class. On the other hand, health-protective stress-buffer effects of leisure coping were evident regardless of people's gender and age. The findings underscore the importance of giving greater attention to the role of leisure as a means of coping with stress in health practices, particularly among marginalized groups such as individuals with lower social class.

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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.058
GPT teacher head0.470
Teacher spread0.412 · 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

Citations111
Published2006
Admission routes2
Has abstractyes

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