Testing the psychometric properties of the Authentic Leadership Questionnaire among nurses in Saudi Arabia
Bibliographic record
Abstract
PURPOSE: This paper aims to evaluate the psychometric properties of the "rater" version of the Authentic Leadership Questionnaire in nursing practice within the context of Saudi Arabia. DESIGN/METHODOLOGY/APPROACH: 's Authentic Leadership Questionnaire (2007). This version of the Authentic Leadership Questionnaire was in the English language. A convenience sampling method was used to obtain data from 215 Saudi early career nurses working at public hospitals affiliated with the Ministry of Health in Saudi Arabia. Data analysis included assessing internal consistency (Cronbach's alpha) analysis and the exploratory factor analysis using the Statistical Package for Social Sciences version. Face and content validity were evaluated using a content validity index, and Mplus was also used to assess the factor structure of the Authentic Leadership Questionnaire by conducting confirmatory factors analysis. FINDINGS: The results of psychometric testing of the Authentic Leadership Questionnaire provide initial support for the content and construct validity and internal reliability of the instrument among early career nurses in Saudi Arabia. ORIGINALITY/VALUE: The results supported that the 16 items of the rater's version of the Authentic Leadership Questionnaire measure nurses' perceptions of the authentic leadership of their leaders. The psychometric properties of the Authentic Leadership Questionnaire yield a valuable contribution to empirical research within the nursing population. The results of this study suggest that the Authentic Leadership Questionnaire will be useful for health service researchers and nursing leaders seeking to understand and capture authentic leadership qualities in Saudi Arabia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".