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Record W2103590277 · doi:10.2466/01.03.pr0.113x20z3

Validation of the Karasek-Job Content Questionnaire to Measure Job Strain in Vietnam

2013· article· en· W2103590277 on OpenAlexaff
Marc Corbière, Alessia Negrini, Daniel Reinharz

Bibliographic record

VenuePsychological Reports · 2013
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailUniversité LavalCentre for Disability Prevention and RehabilitationFrancophone University AssociationUniversité de Sherbrooke
Fundersnot available
KeywordsVietnamesePsychologyJob strainApplied psychologyContent validityReliability (semiconductor)Clinical psychologySocial psychologyPsychometricsPsychosocialPsychiatry

Abstract

fetched live from OpenAlex

The objective of this study was to validate the Karasek-Job Content Questionnaire in Vietnamese. A translation/back-translation of the questionnaire was performed prior to its administration to 344 health personnel in Vietnam. Several psychometric properties of the Vietnamese version of the Karasek-Job Content Questionnaire were assessed. A valid Vietnamese version of the Karasek-Job Content Questionnaire was produced, composed of five subscales based on the original theoretical model: Psychological demands, Social support at work, Decision latitude-Autonomy, Decision latitude-Authority, and Skill discretion. Internal consistency and reliability coefficients for each subscale of the questionnaire were satisfactory. The correlations with depression and work absence indicators were weak but statistically significant, as expected. The Vietnamese version of the Karasek-Job Content Questionnaire will help Vietnamese researchers and clinicians appropriately evaluate and document the job strain of workers in Vietnamese workplaces.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.417
Teacher spread0.322 · 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

Citations31
Published2013
Admission routes1
Has abstractyes

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