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Record W4319062909 · doi:10.1097/jom.0000000000002753

Measuring Presenteeism From Work Stress

2022· article· en· W4319062909 on OpenAlexaff
Cynthia Mathieu, Brad Gilbreath

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPresenteeismPsychologyConfirmatory factor analysisScale (ratio)Job satisfactionDistressHarassmentClinical psychologyBurnoutOccupational stressExploratory factor analysisAbsenteeismStructural equation modelingPsychometricsSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Presenteeism can result from a variety of causes, one of which is job stress. This study examined the factor structure and validity of the Job Stress-Related Presenteeism Scale (JSRPS). METHODS: Using three organizational samples, the study aimed to determine the factor structure of the JSRPS, its relationship to a sickness presenteeism scale, and the association between the JSRPS and associated concepts. RESULTS: Exploratory and confirmatory factor analyses supported a reliable 6-item, 2-factor model for the JSRPS. JSRPS scores were associated with higher levels of psychological distress, workplace harassment, and turnover intentions and lower levels of job satisfaction, and work engagement. The JSRPS had stronger associations with psychological distress and workplace harassment than did the Stanford Presenteeism Scale. CONCLUSIONS: Results suggest that the JSRPS provides a valid measure of presenteeism resulting from job stress.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.062
GPT teacher head0.352
Teacher spread0.289 · 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.

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

Citations17
Published2022
Admission routes1
Has abstractyes

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