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The impact of passion for exercising on the perception of well-being during periods of social isolation

2024· article· en· W4401090370 on OpenAlexaff
Evandro Morais Peixoto, Carolina Rosa Campos, Karina da Silva Oliveira, Bartira Pereira Palma, Bruno Bonfá-Araújo, Geovana Mellisa Castrezana Anacleto

Bibliographic record

VenueEstudos de Psicologia (Campinas) · 2024
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsWestern University
Fundersnot available
KeywordsPassionPsychologyPerceptionIsolation (microbiology)Social isolationSocial psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Objective of this study was to, based on a theoretical model, verify the associations between the variables passion, affect, satisfaction with life, and distress, the predictive power of the different types of passion on the perception of positive and negative affect, and the effect of this relation against the evaluation of psychological well-being and distress. Method Three hundred and fifty-nine participants aged between 18 and 70 years (M = 36.60; SD = 11.90) answered a sociodemographic questionnaire, and the Passion, Positive and Negative Affect Schedule, Satisfaction with Life, and the Kessler Psychological Distress Scales. Data were analyzed using correlation coefficients and structural equation modeling. Results The adequacy of the proposed model was estimated with satisfactory fit indices and positive relations between Harmonious Passion, Positive Affect, and Satisfaction with Life. Conclusion The results suggest that Harmonious Passion contributes to coping with suffering and negative experiences, such as those experienced in the pandemic moment.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.736

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.023
GPT teacher head0.342
Teacher spread0.319 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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