MétaCan
Menu
Back to cohort
Record W2398420244 · doi:10.1590/0104-1169.0069.2610

Association between depression and work stress in nursing professionals with technical education level

2015· article· en· W2398420244 on OpenAlexaff
Edilaine Cristina da Silva Gherardi‐Donato, Lucilene Cardoso, Carla Araújo Bastos Teixeira, Sandra de Souza Pereira, Emilene Reisdorfer

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Burnout
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDepression (economics)Logistic regressionNursingIntervention (counseling)MedicineAssociation (psychology)PopulationScale (ratio)Cross-sectional studyPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: to analize the relationship between depression and work stress in nursing professionals with technical education level of a teaching hospital in a city of the state of São Paulo. METHODS: a cross-sectional study was carried out with 310 nursing technicians and nursing assistants, randomly selected. The outcome analyzed was the report of depression and its relationship with high levels of work stress, measured using the Job Stress Scale. Descriptive statistics and logistic regression were performed. RESULTS: the prevalence of depression in this study was 20%, and it was more expressive in females, aged over 40 years, living without a partner and in smokers. The chance of depression was twice as high among professionals showing high levels of work stress, even after multiple regression adjusting. CONCLUSION: depressive symptoms were strongly associated with high stress levels among nursing assistants and nursing technicians, evidencing a problem to be considered along with the planning of specific intervention programs for this population, as well as the need for better cases management by the supervisors.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.096
GPT teacher head0.471
Teacher spread0.375 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueRevista Latino-Americana de EnfermagemSame topicOccupational Health and BurnoutFrench-language works237,207