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Record W2974453879

Job stress and job performance relationship in challenge-hindrance model of stress: An empirical examination in the Middle East

2016· article· en· W2974453879 on OpenAlexfundno aff
M. Arifuddin Jamal

Bibliographic record

VenueEconstor (Econstor) · 2016
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
FundersConcordia University
KeywordsStress (linguistics)Job stressMiddle EastSocial psychologyEmpirical examinationPsychologyPolitical scienceJob satisfactionBusinessActuarial scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

This study examined the nature of the relationship of overall job stress, challenge and hindrance stress with job performance and turnover motivation among nurses (N=255) employed by three hospitals in the Gulf States of the Middle East. Multiple sources of data collection were employed. A structured questionnaire was used to collect data on measures of job stress, turnover intention and social support. Job performance data were obtained from hospital files. Multiple regression, curvilinear coefficients and moderated multiple regressions were used to analyze the data. Overall job stress, challenge stress and hindrance stress were all related to job performance and turnover motivation. The nature of the relationship between the measures of job stress and performance was primarily a negative linear. Perceived social support moderated more than eighty percent relationship between the measures of job stress and two dependent variables. Overall, the results of the present study supported the convergence instead of divergence perspective in cross cultural management research. Implications of the findings are discussed for future researchers in international and cross-cultural management.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.599

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.126
GPT teacher head0.325
Teacher spread0.199 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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