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Record W2129509720 · doi:10.5267/j.msl.2013.03.018

A study on the relationship between employee mental health and agility strategic readiness: A case study of Esfahan hospitals in Iran

2013· article· en· W2129509720 on OpenAlexvenueno aff
Hassan Ghodrati, Zahra Zargarzadeh

Bibliographic record

VenueManagement Science Letters · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessMental healthOperations managementPsychologyMarketingProcess managementApplied psychologyPsychiatryEngineering

Abstract

fetched live from OpenAlex

This study investigates whether enhancing organizational agility and mental health of staff could increase strategic readiness for crises or not. In this study, descriptive statistics is used to present demographic data of the research, and P-Test is employed for analyzing the data. In addition, to examine research hypotheses, correlation coefficients and descriptive statistics are implemented. Finally, to rank the variables and indicators of the research, Friedman test and for comparison of indicators and components of the research, nonparametric Kruskal-Wallis test are used. The proposed study designs a questionnaire and The questionnaire and distributes it among some nurses in obstetrics and anesthesiology department and among supervisors. Cronbach's alpha is also employed for determining the reliability in this study. The results indicate that working conditions as well as employees' mental health are in good conditions, the employees with higher levels of mental health have higher readiness to deal with potential crises, and the relationship between agility of hospitals and their strategic readiness for dealing with crises is confirmed.

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)0.002
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 score0.197
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.072
GPT teacher head0.304
Teacher spread0.232 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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