Brief Definition of Factor Analysis

Factor analysis is a statistical method used to identify underlying latent variables (factors) that explain the pattern of correlations among a set of observed variables (Upadhyaya & Malek, 2024). It reduces data complexity by grouping variables that share common variance into interpretable factors (Upadhyaya & Malek, 2024).

Assessment Instrument

            The authors Aarons et al. (2014) note that the instrument that meets the requirements of having clearly delineated and statistically supported factors is discussed in the following:

The Implementation Leadership Scale (ILS) is a psychometrically validated instrument designed to assess leadership effectiveness at the unit level in implementing evidence-based practices. It comprises of four specified subscales: proactive leadership, knowledgeable leadership, supportive leadership, and perseverant leadership, identified and confirmed through exploratory and confirmatory factor analysis. These subscales represent core dimensions of implementation leadership and demonstrate strong internal consistency and construct validity. The ILS provides a comprehensive framework for understanding how leadership behaviors influence organizational climate and the success of evidence-based practice implementation.

Thus, it serves as a reliable example of how factor analysis supports the structural integrity of an assessment tool related to leadership and its influence on outcomes such as trust in leadership, particularly in implementation contexts.

Exploratory and Confirmatory Factor Analysis

 The difference between exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) lies in their use. This includes the level of hypothesis testing, purpose, and methodological approach in understanding the structure of interrelated variables (Kenaszchuk et al., 2010). EFA is primarily used when researchers want to identify the underlying relationships among a set of observed variables without a preconceived notion of their structure while aiming to discover the number and nature of latent variables (factors) that best explain the patterns of correlations among these variables (Tekin & Polat, 2016). EFA is data-driven and is typically employed in the early stages of scale development (Çamli et al., 2021). On the other hand, CFA is used when the researcher has a specific, theory-based hypothesis about the structure and number of factors (Santos & Lima, 2017). Confirmatory factor analysis (CFA) is hypothesis-driven and tests whether the data fit a predefined model by specifying which variables load on which factors, and often follows EFA to validate the factor structure (Kenaszchuk et al., 2010). In simple terms, EFA is used to discover the underlying structure, while CFA is used to verify the structure (Salimi & Abdollahpour, 2018).

References

Aarons, G. A., Ehrhart, M. G., & Farahnak, L. R. (2014). The implementation leadership scale (ILS): Development of a brief measure of unit level implementation leadership. Implementation Science, 9(1). https://doi.org/10.1186/1748-5908-9-45

Çamli, A. Y., Virlanuta, F. O., Türker Palamutçuoğlu, B. T., Bărbuță-Mișu, N., Güler, Ş., & Züngün, D. (2021). A study on developing a communicative rational action scale. Sustainability, 13(11), 6317–6317. https://doi.org/10.3390/su13116317

Kenaszchuk, C., Reeves, S., Nicholas, D., & Zwarenstein, M. (2010). Validity and reliability of a multiple-group measurement scale for interprofessional collaboration. BMC Health Services Research, 10(1). https://doi.org/10.1186/1472-6963-10-83

Salimi, Y., & Abdollahpour, I. (2018). Developing an adherence in hypertension questionnaire short version: MUAH-16-statistical and methodological issues. The Journal of Clinical Hypertension, 20(4), 816–816. https://doi.org/10.1111/jch.13250

Santos, A. A. A. dos, & Lima, T. H. de. (2017). Exploratory and confirmatory factor analysis of the Roteiro de Avaliação da Consciência Fonológica, a phonological awareness test. Estudos de Psicologia (Campinas), 34(2), 211–218. https://doi.org/10.1590/1982-02752017000200003

Tekin, A., & Polat, E. (2016). A scale for e-content preparation skills: Development, validity and reliability. Eurasian Journal of Educational Research, 16(62). https://doi.org/10.14689/ejer.2016.62.9

Upadhyaya, D., & Malek, M. (2024). An exploratory factor analysis approach to investigate health and safety factors in construction. Construction Economics and Building, 24(1/2). https://doi.org/10.5130/ajceb.v24i1/2.8867