Validating an Instrument for Measuring Newly Graduated Nurses' Adaptation.

Area of Science:

• Psychometrics and Measurement
• Nursing Research
• Organizational Psychology

Background:

• Confirmatory Factor Analysis (CFA) is a standard method for validating measurement models of latent constructs.
• Adapting and modifying existing instruments is crucial for ensuring relevance in specific research settings.
• The NENA-q model was developed to measure key factors influencing newly employed nurses.

Purpose of the Study:

• To validate the newly developed NENA-q measurement model for newly employed nurses.
• To assess the construct validity, convergent validity, and composite reliability of the NENA-q model.
• To confirm the second-order structure with four dimensions: organizational contribution (OC), academic institution contribution (AIC), personality traits (PT), and newly employed nurses' adaptation (NENA).

Main Methods:

• Exploratory Factor Analysis (EFA) was used to identify the initial structure of the NENA-q model.
• A two-step Confirmatory Factor Analysis (CFA) procedure (individual and pooled CFA) was employed for validation.
• Data were collected from 496 newly employed nurses in Ministry of Health (MOH) hospitals.

Main Results:

• The NENA-q model demonstrated strong construct validity, meeting all fitness index thresholds.
• Convergent validity was confirmed, with Average Variance Extracted (AVE) exceeding 0.5 for all constructs.
• Composite Reliability (CR) values surpassed the threshold of 0.6, indicating high reliability.

Conclusions:

• The NENA-q measurement model is a valid and reliable instrument for assessing newly employed nurses.
• The validated NENA-q model provides a robust foundation for further research using Structural Equation Modelling (SEM).
• The findings support the use of NENA-q in understanding factors influencing nurses' adaptation and contribution.