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Paixão pelo exercício: predição do comportamento ativo e mindfulness durante o distanciamento físico no enfrentamento a covid-19

2024· article· pt· W4401635832 on OpenAlexaff
Amanda Rizzieri Romano, Maynara Priscila Pereira da Silva, Evandro Morais Peixoto, Karina da Silva Oliveira, Carolina Rosa Campos, Geovana Mellisa Castrezana Anacleto, Bruno Bonfá-Araújo

Bibliographic record

VenueAvances en Psicología Latinoamericana · 2024
Typearticle
Languagept
FieldComputer Science
TopicHealthcare during COVID-19 Pandemic
Canadian institutionsWestern University
Fundersnot available
KeywordsMindfulnessCoronavirus disease 2019 (COVID-19)PsychologyBiologyPsychotherapistMedicineDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Durante o período de distanciamento físico na pandemia da covid-19, a prática de exercício físico apresentou funções essenciais na manutenção da saúde. Esta pesquisa teve como objetivo avaliar o poder preditivo das dimensões da paixão (obsessiva [PO] e harmoniosa [PH]) sobre o tempo de prática durante a semana, o estado de mindfulness na realização do exercício e suas consequências sobre a satisfação com a prática. Participaram do estudo 359 praticantes regulares de exercício de ambos os sexos (67.4 % mulheres), com idades entre 18 e 70 anos (M = 36.6 ± 11.9). Foram empregadas análises de correlação de Pearson e modelagem de equações estruturais. Os resultados evidenciaram que ambas as dimensões da paixão prediziam positivamente o tempo de prática, contudo apenas a PH predizia o estado de mindfulness, o qual predizia positivamente a satisfação com a prática. Os resultados corroboram a literatura sobre o modelo dualístico da paixão ao indicar a PH como uma variável promotora do funcionamento psicológico positivo.

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)0.006
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.351
Teacher spread0.315 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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