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Record W4409524940 · doi:10.1080/14927713.2025.2489348

‘Yoga really makes me feel good’: leisure as a coping resource for parent caregivers of children living with autism

2025· article· en· W4409524940 on OpenAlexaffvenueabout
Erin Laughlin, Sanghee Chun

Bibliographic record

VenueLeisure/Loisir · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyAutismCoping (psychology)Resource (disambiguation)PsychotherapistDevelopmental psychologyClinical psychologyComputer science

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the role of leisure as a coping resource for parent caregivers of children with autism. This qualitative study recruited four participants from centres for children with autism in Southern Ontario. A phenomenological reduction technique was employed to examine the parents’ lived experiences in their daily lives. The results of this study revealed that leisure was used as a stress-coping resource in four ways: (1) rejuvenation through leisure, (2) mood enhancement through leisure, (3) distance from stressors through leisure, and (4) social experiences through leisure. This study discussed the importance of advocating for leisure, especially casual forms of leisure among parent caregivers for effective coping with caregiver-related stress. This study provided practical implications to better understand the unique needs of this population.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.323
Teacher spread0.300 · 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
Published2025
Admission routes3
Has abstractyes

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