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Validating an Instrument for Measuring Newly Graduated Nurses’ Adaptation

Author

Listed:
  • Hafidza Baharum

    (Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia)

  • Aniza Ismail

    (Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia)

  • Zainudin Awang

    (Faculty of Business and Management, Universiti Sultan Zainal Abidin, Terengganu 21300, Malaysia)

  • Lisa McKenna

    (School of Nursing and Midwifery, La Trobe University, Bundoora, VIC 3086, Australia)

  • Roszita Ibrahim

    (Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia)

  • Zainah Mohamed

    (Department of Nursing, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia)

  • Nor Haty Hassan

    (Department of Nursing, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur 56000, Malaysia)

Abstract

A long-established approach, Confirmatory Factor Analysis (CFA) is used to validate measurement models of latent constructs. Employing CFA can be useful for assessing the validity and reliability of such models. The study adapted previous instruments and modified them to suit the current setting. The new measurement model is termed NENA-q. Exploratory factor analysis (EFA) revealed the instruments of the NENA-q model formed a construct of the second order with four dimensions, namely organizational contribution (OC), academic institution contribution (AIC), personality traits (PT), and newly employed nurses’ adaptation (NENA). Researchers administered the questionnaires to a sample of 496 newly employed nurses working in hospitals under the Ministry of Health (MOH) for the confirmation of the extracted dimensions. The study performed a two-step CFA procedure to validate NENA-q since the model involves higher-order constructs. The first step was individual CFA, while the second step was pooled CFA. The validation procedure through confirmatory factor analysis (CFA) found the model achieved the threshold of construct validity through fitness index assessment. The model also achieved convergent validity when all average variance extracted (AVE) exceeded the threshold value of greater than 0.5. The assessment of the composite reliability (CR) value indicates all CR values exceeded the threshold value of 0.6, which indicates the construct achieved composite reliability. Overall, the NENA-q model consisting of the OC construct, AIC construct, PT construct, and NENA construct for CFA has met the fitness indexes and passed the measurements of the AVE, CR, and normality test. Once the measurement models have been validated through CFA procedure, the researcher can assemble these constructs into structural model and estimate the required parameter through structural equation modelling (SEM) procedure.

Suggested Citation

  • Hafidza Baharum & Aniza Ismail & Zainudin Awang & Lisa McKenna & Roszita Ibrahim & Zainah Mohamed & Nor Haty Hassan, 2023. "Validating an Instrument for Measuring Newly Graduated Nurses’ Adaptation," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:4:p:2860-:d:1059494
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    References listed on IDEAS

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    1. Radziah Mohd Dani & Noorhayati Mansor & Zainudin Awang & Asyraf Afthanorhan, 2022. "A Confirmatory Factor Analysis of the Fraud Pentagon Instruments for Measurement of Fraud in the Context of Asset Misappropriation in Malaysia," Journal of Social Economics Research, Conscientia Beam, vol. 9(2), pages 70-79.
    2. Rung‐Fen Feng & Yun‐Fang Tsai, 2012. "Socialisation of new graduate nurses to practising nurses," Journal of Clinical Nursing, John Wiley & Sons, vol. 21(13-14), pages 2064-2071, July.
    3. Kiri Hunter & Catherine Cook, 2018. "Role‐modelling and the hidden curriculum: New graduate nurses’ professional socialisation," Journal of Clinical Nursing, John Wiley & Sons, vol. 27(15-16), pages 3157-3170, August.
    4. John D Brewer, 2011. "The impact of impact," Research Evaluation, Oxford University Press, vol. 20(3), pages 255-256, September.
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