MétaCan
Menu
Back to cohort
Record W4404114815 · doi:10.1080/15555240.2024.2425431

The effects of mindfulness and psychological capital on reducing worker stress and promoting health

2024· article· en· W4404114815 on OpenAlexaff
Israel Sánchez‐Cardona, Lili M. Sardiñas, Eric A. Rivera-Colón, Brian A. Moore, Marizada Sánchez-Cesareo

Bibliographic record

VenueJournal of Workplace Behavioral Health · 2024
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsMindfulnessPsychologyCapital (architecture)Stress (linguistics)BurnoutClinical psychologyPsychotherapist

Abstract

fetched live from OpenAlex

This cross-sectional study aims to test the combined effect of mindfulness and psychological capital on reducing stress and burnout and improving the perception of health (physical and psychological). The sample consisted of 398 workers (94.5% female) from a public organization in Puerto Rico dedicated to providing services to families and their children in their early formative stages. The results from moderated regressions showed that the interaction between mindfulness and psychological capital was significant, indicating that individuals with high levels of mindfulness and psychological capital showed lower burnout and stress and a higher perception of psychological health. These results suggest that mindfulness provides the conditions to foster the mobilization of personal resources (i.e., psychological capital) to deal with stressful situations and take actions toward greater well-being. Future intervention strategies should consider combining various personal resources to increase their effectiveness in reducing stress and promoting well-being.

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)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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 science0.0000.001
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 head0.036
GPT teacher head0.414
Teacher spread0.378 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Workplace Behavioral HealthSame topicHealthcare Education and Workforce IssuesFrench-language works237,207