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Record W3209412034 · doi:10.1002/nop2.1117

An integrative review of nursing leadership in Saudi Arabia

2021· review· en· W3209412034 on OpenAlex
Bayan Alilyyani, Michael Kerr, Carol Wong, Dhuha Youssef Wazqar

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Open · 2021
Typereview
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsWestern University
FundersTaif University
KeywordsCINAHLLeadership stylePsycINFOScopusNursingMEDLINENursing literatureMedicinePsychologyAlternative medicinePolitical scienceSocial psychologyPsychological intervention

Abstract

fetched live from OpenAlex

AIMS: The aims of this integrative review were to describe leadership styles from the nursing literature in Saudi Arabia and to identify the current state of evidence about relationships between leadership styles and nurse, patient and organization outcomes in Saudi Arabia. DESIGN: Integrative review was used as a design for this study. METHODS: The following search terms were used with databases: 'Saudi Arabia', 'leadership theory*', 'leadership style*', 'leadership model*', 'management style' and 'nurse*'. Methodological quality was assessed using two different quality rating tools for quantitative and qualitative studies. Databases used for this review included Nursing & Allied Health Database, Cochrane Database of Systematic Reviews, PubMed, CINAHL, Embase, PsycINFO, Scopus, Web of Science and ProQuest Dissertations & Theses. RESULTS: Nine manuscripts representing eight studies were included in this review. The papers reviewed included quantitative (n = 6), qualitative (n = 2) and mixed methods studies (n = 1). Results were grouped into different themes, identified as nursing leadership styles in Saudi Arabia, leadership styles and nurses' outcomes, and demographics and leadership styles.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.343
GPT teacher head0.486
Teacher spread0.143 · 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