MétaCan
Menu
Back to cohort
Record W2947510852 · doi:10.1186/s13104-019-4096-4

Satisfaction with job and family life, and association with smoking and alcohol drinking behaviors among young men in Malawi: analysis from a multiple indicator survey

2019· article· en· W2947510852 on OpenAlexaff
Sanni Yaya, Amos Buh, Ghose Bishwajit

Bibliographic record

VenueBMC Research Notes · 2019
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOddsOdds ratioMedicineLogistic regressionDemographyAlcoholLife satisfactionJob satisfactionCigarette smokingAlcohol intakeEnvironmental healthPsychologyInternal medicineSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of the present study was to investigate if satisfaction with job and family life has any connection with smoking and alcohol drinking behavior among young men in Malawi. RESULTS: Results of multivariable logistic regression analysis indicate that compared to men who were unemployed, those who were dissatisfied were 0.90 times less likely to be non-smokers [OR = 0.90; 95% CI = 0.36-2.24], 0.83 times [OR = 0.83; 95% CI = 0.63-1.08] as likely to try drinking alcohol. Among those who reported being satisfied with job, the odds of trying alcohol was relatively more [OR = 0.77; 95% CI = 0.63-0.93], however the odds of cigarette smoking were less [OR = 1.05; 95% CI = 0.48-2.31] relative to those who were unemployed. Results also showed that not being satisfied with overall life increased the odds of smoking and alcohol drinking [OR = 0.60; 95% CI = 0.24-1.46] and [OR = 0.95; 95% CI = 0.72-1.24] respectively compared to those who were satisfied with overall life.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.129
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.414
Teacher spread0.332 · 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 teacher head, 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

Citations9
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueBMC Research NotesSame topicWorkplace Health and Well-beingFrench-language works237,207