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Record W2606963027 · doi:10.12968/bjhc.2017.23.4.176

Expatriate health professionals in the Saudi Arabia private sector

2017· article· en· W2606963027 on OpenAlexaff
Yasin M. Yasin, Areej Al‐Hamad, Charles H. Bélanger, Annie Boucher, Mohammad A AbuRubeiha

Bibliographic record

VenueBritish Journal of Healthcare Management · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsLaurentian UniversityWestern University
Fundersnot available
KeywordsExpatriateJob satisfactionSalaryJob attitudePrivate sectorJob securityStressorPsychologyNursingJob performanceDemographic economicsBusinessMedicineSocial psychologyClinical psychologyPolitical science

Abstract

fetched live from OpenAlex

This study aimed to identify the differences in job satisfaction levels among expatriate health professionals (EHPs) working in the Saudi Arabian private sector, the stressors affecting their job satisfaction, and the influence of those stressors on their turnover intention. A cross-sectional design was guided by Herzberg's Theory. A convenience sample of 204 expatriate doctors, nurses, and pharmacists in Saudi Arabia were recruited from the private sector. Data were collected from four urban hospitals in regions having 74% of the bed capacity in the private sector. A four-part instrument measured dissatisfiers, job satisfaction, turnover intention, and cultural unrest. The results showed that EHPs have moderate job satisfaction. There was a difference in job satisfaction levels in terms of profession and nationality. Stressors influencing job satisfaction support Herzberg's theory. There was a significant positive correlation between dissatisfiers and job satisfaction. Cultural unrest had a very weak positive correlation with job satisfaction. Working conditions, salary, supervision, interpersonal relationships, hospital policy and administration, and job security were significant predictors of job satisfaction. Job satisfaction and turnover intention have insignificant relationship. The private health organisations can use the findings of this study to promote job satisfaction, decrease turnover intention, and improve cultural acclimatisation

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.396
Teacher spread0.336 · 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 designOther design
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

Citations8
Published2017
Admission routes1
Has abstractyes

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