MétaCan
Menu
Back to cohort
Record W1852138939 · doi:10.1111/aphw.12022

Conflict between Women's Physically Active and Passive Leisure Pursuits: The Role of Self‐Determination and Influences on Well‐Being

2014· article· en· W1852138939 on OpenAlexaff
Tamara Williams, Eva Guérin, Michelle Fortier

Bibliographic record

VenueApplied Psychology Health and Well-Being · 2014
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLeisure timePsychologyWell-beingSocial psychologyScheduleDevelopmental psychologyPhysical activityComputer sciencePhysical therapyPsychotherapistMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Evidence in support of both physically active and passive leisure as significant contributors to well-being has surfaced around the world. However, for physically active, working mothers, fitting leisure into an already busy schedule can be challenging. The purpose of this study was to examine the influence of time resources and self-determination for active and passive leisure on conflict between these two leisure domains and the influence of this conflict on well-being. METHODS: A total of 66 working mothers completed validated questionnaires measuring satisfaction with time and motivation at baseline followed by two weeks of computerized diary capture to evaluate leisure engagement with final measures of goal conflict and well-being at the end of the two weeks. RESULTS: Results indicated that dissatisfaction with time resources is associated with increased goal conflict as are non-self-determined motivation for physically active leisure and self-determined motivation for passive leisure. Controlling for engagement in physically active and passive leisure, well-being is negatively influenced by goal conflict. CONCLUSIONS: Time resources, goal conflict, and motivation are important factors to consider in efforts to increase well-being among physically active working mothers. Further research is required to understand the influence of opposing motivational orientations on goal conflict.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.008
GPT teacher head0.307
Teacher spread0.299 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueApplied Psychology Health and Well-BeingSame topicRecreation, Leisure, Wilderness ManagementFrench-language works237,207