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Record W4414758038 · doi:10.18554/reas.v15i1.7250

Treinamento em mindfulness e impactos na saúde mental em funcionários não docentes de uma universidade pública

2025· article· en· W4414758038 on OpenAlexfundno aff
Larissa Bessani Hidalgo Gimenez, Larissa Horta Esper, Mariana Fernandes, Maria Neyrian de Fátima Fernandes, Vinícius Santos de Moraes, Edilaine Cristina da Silva Gherardi‐Donato

Bibliographic record

VenueRevista de Enfermagem e Atenção à Saúde · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Burnout
Canadian institutionsnot available
FundersUniversity of AlbertaSigma Theta Tau International
KeywordsMindfulnessAnxietyIntervention (counseling)Depression (economics)Mental healthPromotion (chess)

Abstract

fetched live from OpenAlex

Objective: to evaluate the effectiveness of a Mindfulness-based Intervention in relation to levels of mindfulness, perceived stress, depression, anxiety and burnout. Methods: quasi-experimental study with a sample of 60 workers from a public university. Participants were allocated to a group that received intervention (GE: 30) and another that did not receive intervention, considered a control group (CG: 30). They were assessed at the beginning and after the intervention. Results: The EG showed an increase in the total mean Mindfulness score and in two facets of the FFMQ scale (observing and non-reactivity to inner experience). When compared to the CG, there was a reduction in the average scores of perceived stress, depression and anxiety. The same effect after intervention was not observed for burnout. Conclusion: Mindfulness training showed the sample's perceived levels of stress, depression and anxiety. The data highlight the potential of this intervention to contribute as a prevention and promotion strategy for workers' mental health. Keywords: Mindfulness; Stress, Mental health; Workplace.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.046
GPT teacher head0.412
Teacher spread0.366 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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