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Duración de las licencias médicas FONASA por trastornos mentales y del comportamiento

2012· article· es· W2156264398 on OpenAlexaff
Gonzalo Miranda H, Sergio Alvarado O, Jay S. Kaufman

Bibliographic record

VenueRevista médica de Chile · 2012
Typearticle
Languagees
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsMcGill University
Fundersnot available
KeywordsSick leaveSocioeconomic statusDuration (music)DemographyMedicineMental healthPsychologyGerontologyPsychiatrySociologyPhysical therapyArtPopulation

Abstract

fetched live from OpenAlex

BACKGROUND: In Chile, the number of sick leaves due to mental health problems has systematically increased in recent years. AIM: To perform an analysis of sick leaves due to mental problems managed by the Fondo Nacional de Salud (FONASA) during 2008. MATERIAL AND METHODS: Analysis of all sick leaves awarded during 2008 for mental or behavioral problems, that were managed at FONASA. A negative binomial regression, was performed to predict the effects of different variables on the total duration of sick leaves. RESULTS: A total of 546,477 sick leaves were awarded to 198,752 individuals (2.27 per subject). The mean duration of each leave was 15.6 days. Summing all leaves, the lapse off work was 98 ± 96 days (median 65 days). Women had longer leaves than men. The type of medical leave, occupation, working for private or public institutions, economic activity and diagnosis were significantly associated with duration of time off work. CONCLUSIONS: Sick leaves for mental problems are prolonged and related to gender and socioeconomic variables.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.028
GPT teacher head0.367
Teacher spread0.339 · 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; both teacher heads agree on what is shown here.

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
Published2012
Admission routes1
Has abstractyes

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